The Impact of Personality and National Culture on The New Ways of Working Concept

The Impact of Personality and National Culture

on The New Ways of Working Concept

J. van Esch (311825)

MSc Business Information Management

Coach: prof. dr. ir. H.W.G.M. van Heck

Co-reader: dr. M.P.A. van Oosterhout

September 11th, 2012

The author declares that the text and work presented in this Master thesis is original and that no sources other

than those mentioned in the text and its references have been used in creating the Master thesis.

The copyright of the Master thesis rests with the author. The author is responsible for its contents. RSM

Erasmus University is only responsible for the educational coaching and beyond that cannot be held responsible

for the content.

The Impact of Personality and National Culture on The New Ways of Working Concept 3

Table of Contents

Acknowledgements ................................................................................................................................................. 5

Executive Summary ................................................................................................................................................. 6

1. Introduction ........................................................................................................................................................ 9

1.1. Research Question ..................................................................................................................................... 10

1.2. Research Goal............................................................................................................................................. 10

1.3. Structure of Thesis ..................................................................................................................................... 10

2. Literature Review .............................................................................................................................................. 12

2.1. Personality .................................................................................................................................................. 12

2.2. Work Design ............................................................................................................................................... 19

3. Conceptual Framework ..................................................................................................................................... 22

3.1. Work Practices ........................................................................................................................................... 23

3.2. Work Atmosphere ...................................................................................................................................... 26

3.3. Work Performance ..................................................................................................................................... 27

3.4. Work Arrangements ................................................................................................................................... 28

3.5. Personality Traits ........................................................................................................................................ 30

3.6. Control Variables ........................................................................................................................................ 30

3.7. Propositions ............................................................................................................................................... 31

4. Methodology and Measurement Instrument ................................................................................................... 33

4.1. Methodology .............................................................................................................................................. 33

4.2. Measurement Instrument .......................................................................................................................... 34

4.3. Validity and Reliability of Constructs.......................................................................................................... 41

5. Data Analysis ..................................................................................................................................................... 43

5.1. Sample and Response ................................................................................................................................ 43

5.2. Univariate Analysis ..................................................................................................................................... 43

5.3. Method of Analysis .................................................................................................................................... 46

5.4. Multivariate Analysis .................................................................................................................................. 49

5.5. Discussion of the Outcomes ....................................................................................................................... 66

6. Conclusion ......................................................................................................................................................... 77


6.1. Answering the Research Question ............................................................................................................. 77

6.2. Contributions to Theory ............................................................................................................................. 78

6.3. Contributions to Management Practice ..................................................................................................... 79

6.4. Limitations and Suggestions for Further Research ..................................................................................... 80

References ............................................................................................................................................................ 82

Appendix 1 – Culture ............................................................................................................................................. 91

A. Literature Review .......................................................................................................................................... 91

B. Conceptual Framework ............................................................................................................................... 103

C. Methodology ............................................................................................................................................... 106

Appendix 2 – ‘Big Model’ .................................................................................................................................... 108

Appendix 3A – Survey Instrument (Dutch).......................................................................................................... 109

Appendix 3B – Survey Instrument (English) ........................................................................................................ 118

Appendix 3C – Context Sheet .............................................................................................................................. 125

Appendix 4A – Invitation ..................................................................................................................................... 126

Appendix 4B – Reminder ..................................................................................................................................... 127

Appendix 5 – Factor Analysis .............................................................................................................................. 128

Appendix 6 – Reliability Analysis ......................................................................................................................... 129

Appendix 7 – ‘PTO Bedrijfskunde’ Alumni .......................................................................................................... 130

Appendix 8 – Univariate Analysis ........................................................................................................................ 133

Appendix 9 – Correlations ................................................................................................................................... 136

Appendix 10A – Hypotheses ............................................................................................................................... 137

Appendix 10B – Outcomes Personality Traits ..................................................................................................... 139

Appendix 11 – Plots ............................................................................................................................................. 140

Appendix 12 – Graphs Interaction Effects........................................................................................................... 143

Appendix 13 – Regression Output Sub-model 1 ................................................................................................. 149




Acknowledgements

By finalizing this thesis, an end has come to a very exciting period, as this thesis is the last part of the master’s

programme Business Information Management (BIM) that I attended at the Rotterdam School of Management.

I would like to thank everyone who has contributed to the great success of this programme.

Concerning this thesis, there is a number of people to whom I am particularly indebted:

First of all, I would like to thank Prof. Dr Ir Eric van Heck for his excellent and friendly way of coaching me

during the process. Many thanks for every advice you gave me, without which this thesis would not have been

what it is now. Although the focus has ultimately been shifted to personality, also thanks for all attempts to

search with me for a multinational company to validate the Culture model.

Besides, many thanks to Dr Marcel van Oosterhout. Officially you have been my co-reader since quite recently,

but from your position as project manager at Erasmus@Work, you have been closely involved from the

beginning. Thank you for critically reviewing my work and for all valuable recommendations.

Also thanks to the other members of Erasmus@Work, who shared their thoughts with me during the past year.

In particular, I want to mention the names of Drs. Nick van der Meulen and Dr Peter van Baalen for the

interesting discussions we had. Besides, thanks to Dr Jan van Dalen, Dr Ir Gert Jan Hofstede, Dr Ir Otto Koppius

and Prof. Dr Slawomir Magala for thinking along with me.

The number of ‘PTO Bedrijfskunde’ alumni who have completed my questionnaire has far exceeded my

expectations. Thanks to all participants!

My wonderful parents have been a great support to me. Regarding this thesis, you both contributed in

different ways. Dad inspired me to study Business Administration and assisted me with advice, while Mum

went through the thesis to correct my English. Thanks for everything you have done for me during my

studentship. Also thanks to my family members for their encouragements, in particular my sister Carla who

reviewed my work.

Last but not least, I want to express my gratitude to God, who strengthened and helped me during the past

year in which I worked on this thesis and in all the years before (Psalm 127:1).

Christian van Esch

Alblasserdam, September 2012

[email protected]

mailto:[email protected]


Executive Summary

The New Ways of Working (NWoW) concept is a new form to organize labour, with much autonomy for

workers to decide for themselves where, when and how work tasks are accomplished (Brummelhuis et al.,

2012). It appears that organizations highly differ regarding the adoption and use of NWoW practices – even

organizations that are operating in the same sector. Furthermore, there are major differences in terms of work

practices among divisions of the same, multinational organization.

Till now, little has been known about the impact of human related aspects such as personality and national

culture on the NWoW concept. Therefore, this thesis conducts exploratory research on this subject. Job design

literature suggests that work practices impact work performance (Grant et al., 2010). Others have argued that

work practices (and their impact on work performance) are related to both personality (e.g. Kichuk & Wiesner)

and culture (e.g. Hofstede, 2001).

Two separate models were developed for analyzing the impact of personality and national culture on the

NWoW concept, which are presented in the thesis. Moreover, the personality model has been validated. The

central research question hereby is: to what extent is the New Ways of Working concept affected by

personality?

The Personality model contains a number of building blocks that are briefly discussed below:

Personality: The model is founded on the dominant Big Five Model that distinguishes five separate dimensions

of personality, namely: Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness (John et

al., 2008).

Work Practices: A number of work practices were selected, based on the assumption that the NWoW concept

affects three different core dimensions: people, place, and technology (Andersen, 2012). Two of them were

attributed to the people dimension: reflexivity and flex-time. Reflexivity (on location, schedule, and media use)

is the extent to which workers reflect upon their functioning and modify it accordingly (Schippers et al., 2007).

Flex-time is the proportion of work that is performed outside regular working hours.

The following two work practices were attributed to the place dimension: flex-place and Task Workplace Fit.

Flex-place is the proportion of work that is performed outside the office. Task Workplace Fit (TWPF) is a newly

developed concept, which measures the “degree in which people are able to find a workplace that suit the

tasks they want to perform, either inside or outside the office”. Regarding TWPF, the focus is on four distinct

types of workplace activities: Socialize, Learn, Focus, and Collaborate (Gensler, 2008).

One work practice was attributed to the technology dimension: media use. This concept is about how people’s

communication is divided among a set of variables.

Work Arrangements, Work Atmosphere, and Work Performance: Based on the suggestion that work practices

should be facilitated by management, a couple of work arrangements were defined: policies and agreements,


workplace design, and media availability. For a better conception of the impact of human related aspects, a

block with work atmosphere elements was added, consisting of empowerment and control. Finally, three

performance indicators were included in the conceptual model: employee satisfaction, work life balance, and

productivity.

The personality model was (partly) validated by means of an online questionnaire among alumni of the Dutch

‘Parttime Opleiding Bedrijfskunde’ of the Rotterdam School of Management. Questions were derived from the

‘New Worlds of Work framework’ (developed by Erasmus@Work) and the Big Five Inventory (John et al., 2008),

or newly developed (in case no questions were available yet). The analyses were conducted by means of

hierarchical (moderated) multiple regression analyses.

Regarding the significant direct effects, it was found that there are three work practices that have a positive

effect on employee satisfaction: TWPF Focus, TWPF Socialize, and TWPF Learn. Also work life balance is

positively affected by three work practices: ‘reflection on working hours and schedule’, ‘reflection on media

use’, and TWPF Focus. Productivity is positively affected by TWPF Learn. TWPF Collaborate was the only type of

TWPF that did not have a significant effect on employee satisfaction. Besides, nor flex-time nor-flex-place

significantly influences one of the three performance indicators.

Three direct effects of personality on NWoW Work Practices were found: Openness has a significant positive

impact on ‘reflection on media use’ and flex-place; Extraversion has a significant positive impact on TWPF

Collaborate.

Regarding the moderator analysis, eleven significant interaction effects were found (although not always the

main effects were significant). Five of them are positive: higher scores on Extraversion in combination with

more TWPF Focus and TWPF Collaborate, and higher scores on Neuroticism in combination with more TWPF

Learn result in a relatively higher employee satisfaction. A higher score on Agreeableness in combination with

more ‘reflection on choice of location’ and a higher score on Neuroticism in combination with more flex-time

result in a relatively higher productivity.

On the other hand, there were some significant negative interaction effects as well. Higher scores on

Extraversion in combination with more ‘reflection on choice of location’ and flex-place, and a higher score on

Agreeableness in combination with more TWPF Focus result in a relatively lower employee satisfaction.

Besides, a higher score on Conscientiousness in combination with more flex-time and TWPF Learn, and a higher

score on Openness in combination with more TWPF Learn result in a relatively lower productivity.

Further, some analyses were conducted for the impact of work arrangements on work practices.

Workplace design: It seems that private office rooms are beneficial for TWPF Focus and TWPF Learn. Backup

spaces are supportive for TWPF Socialize, while having an own desk is negatively related to flex-place.

Policies and agreements: Freedom to choose the own working hours has a significant positive influence on

‘reflection on working hours and schedule’ and flex-time; freedom to choose the own work locations has


significant positive impact on ‘reflection on choice of location, TWPF Focus, and TWPF Socialize. Contrary to

what was expected, no significant influence of Telework facilitation on ‘reflection on media use’ was found.

The outcomes of the data analysis were formulated as hypotheses for which additional research is required.

This was also one of the recommendations at the end of the thesis.

As answer to the research question, it was formulated that personality really matters, because personality

traits affects both the degree in which NWoW practices are applied and the relations between work practices

and work performance.


1. Introduction

In 2005, a white paper was published by Microsoft CEO Bill Gates, in which he introduced ´The New World of

Work´. According to him, the world has rapidly changed: it has become interconnected and workers and

organizations are “nearing the point of information overload”, which affects both the productivity and the

health of workers. Employees are the heart of the enterprise and should be enabled to deal with issues like

information overload. In this process, software plays an important role. This white paper puts forward a new

form or organizing labor, in which collaboration, business intelligence and prioritizing scarce time and attention

are critical factors of success (Gates, 2005).

A couple of years later, not only Microsoft but also companies from completely different branches (e.g. Shell,

Philips, Rabobank, Essent) have adopted or have shown interest in the New Ways of Working (NWoW) concept.

Although each company designs its own New Way of Working, there are similarities as well (which will be

discussed in more detail later in this thesis).

The New Ways of Working concept has not gone unnoticed by scientists. Until now, research on several related

topics has been conducted. At the Rotterdam School of Management, Erasmus University, this topic is studied

by a multidisciplinary team called Erasmus@Work.

It appears that organizations highly differ regarding the degree in which they apply New Ways of Working

(NWoW) practices: organizations that are active in the same branch and that are characterized by quite similar

processes sometimes work according to extremely divergent work practices.

This phenomenon can be observed within countries, but is also present at the international level: it happens

that some divisions of the same multinational organization embrace NWoW practices, while other divisions are

not enthusiastic about the concept at all. They do not think that it would work for them.

Apart from the sector in which organizations operate, it could be that human related aspects such as

personality and national culture play an important role regarding the adoption and use of New Ways of

Working (practices).

In this thesis, a model has been developed to study the impact of personality on the NWoW concept

(Personality model), which builds on previous research by Erasmus@Work and relates to their ‘New Worlds of

Work framework’.

The model has interchangeable modules. In appendix 1, the transformations are discussed that have to be

made to use almost the same model for studying the impact of culture on the NWoW concept (Culture model)

and what the consequences are for the data analysis.

Personality and national culture are different concepts, but to some extent they are related to each other. The

first concept deals with the unique characteristics of individual persons, while the second concept is about


what a group of human beings differentiates from other groups. When culture is the “collective programming

of the mind”, personality could be regarded as the individual programming of the mind (Hofstede, 2001;

Hofstede & McCrae, 2004: p. 53).

The model that deals with the impact of personality (Personality model) will be validated in this thesis. The

Culture model was developed as a first way to explore the relationships with the New Ways of Working.

However, this model could not be validated due to a lack of commitment of companies to participate in the

study.

1.1. Research Question

The central research question of the thesis has been formulated as follows:

To what extent is the New Ways of Working concept affected by personality?

Sub-questions are:

1) To what extent does personality have an impact on the degree in which New Ways of Working aspects

are used by (knowledge) workers?

2) To what degree does personality have an influence on the relationship between New Ways of Working

aspects and outcomes of work?

3) Which New Ways of Working aspects fit to what personality aspects?

4) Which specific New Ways of Working arrangements should be strengthened to improve specific work

outcomes of people who have certain characteristics in terms of personality?

1.2. Research Goal

Because at this moment little is known about the impact of personality and national culture on the NWoW

concept, it is nearly impossible to verify statements like ‘this would not work for me’ or ‘this would not work in

our organization’. There is too little scientific theory on this topic to validate these statements.

The first goal of this thesis is to develop a model that could be used to analyze the relationship between

personality / national culture and the New Ways of Working. The second goal is to investigate the impact of

personality on this concept, by validating the Personality model.

Outcomes of this research could be useful for managers who pursue an appropriate way of working for their

organization that suits the kind of people they have employed.

Although only the Personality model is tested in this thesis, the Personality and Culture model complement

each other: they both shed light on the impact of human related aspects on the New Ways of Working.

1.3. Structure of Thesis

The next chapter gives a literature review on the two main streams of this thesis: personality and work design.

In chapter 3 the conceptual model of the Personality model is presented and discussed, and also the belonging


propositions. The fourth chapter is devoted to methodology and measurement instrument. The data analysis

finds place in the subsequent chapter, in which also the results are discussed. A conclusion is given in chapter

6; among other things, answers are formulated to the research questions here.

The first appendix presents the Culture model; it discusses how the impact of national culture on the NWoW

could be analyzed. In appendix 2 you can find the measurement tool that was used. In the subsequent

appendices, a number of graphs and (regression) tables are available.


2. Literature Review

In this chapter, the research streams on which this thesis builds are described. First of all, the focus is on

literature on personality. Secondly, the other main stream of this thesis is introduced: work design. The chapter

ends with definitions of the New Ways of Working (NWoW) concept.

2.1. Personality

2.1.1. Defining Personality and Trait Theory

Robert B. Ewen (2003: p.5) defines personality as: “important and relatively stable characteristics within a

person that account for consistent patterns of behavior. Aspects of personality may be observable or

unobservable, and conscious or unconscious”. Alternatively, personality could be described as “a person’s

general style of interacting with the world, especially with other people” (Gray, 2007: p.537).

In this thesis, the focus is on personality from a ‘trait theory’ perspective. ‘Trait’ could be defined as “a

relatively stable predisposition to behave in a certain way”; the purpose of trait theory is to identify a set of

distinct personality dimensions on which psychological differences among individuals could be summarized

(Gray, 2007: p.538, 539).

Allport and Odbert (1936) conducted a study based on an English dictionary and found almost 18,000 terms by

which human behavior could be described. They identified four major categories, namely: 1) ‘personality

traits’, 2) ‘temporary states, moods, and activities’, 3) ‘highly evaluative judgement of conduct and reputation’,

and 4) ‘physical characteristics, capacities, and talents’.

Others have made different categorisations. For example, the distinction was made among (prototypical) traits,

states, and activities. The difference between traits and states is that traits are stable and enduring, while

states are temporary and brief (John et al., 2008: p.117, 118).

To some degree, traits and states are related to each other: trait could be seen as one’s enduring likelihood “of

entering temporarily into a particular state” (Gray, 2007: p.58).

That the focus is on personality from a trait perspective, does not mean that there are no other theoretical

perspectives on personality. The purpose of trait theory is to describe schematically human psychological

differences and to reveal their impact. However, trait theory does not focus on the internal mental processes

that precede people’s behaviour; this is done by other theoretical perspectives.

Quite famous are the psychodynamic perspective, which was founded by Sigmund Freud and the humanistic

perspective of which Abraham Maslow (hierarchy of human needs) is a representative (Gray, 2007: p.558-565).

These theories are interesting as well, but with the scope on our research goal, they are less relevant here.


2.1.2. Conceptualization of Personality

2.1.2.1. Discovery of the Big Five

Nowadays, there is “initial consensus on a general taxonomy of personality traits, the ‘Big Five’ personality

dimensions” (John et al., 2008: p.116).

Two different research streams have been engaged in studying personality and were involved in the discovery

of the Big Five: the ‘lexical stream’ and the ‘questionnaire stream’. Especially the role of the lexical stream has

been crucial.

The lexical hypothesis says that all important differences between persons / characteristics have been encoded

in natural language. The work by Allport and Odbert, that was already mentioned in this chapter, is based on

this hypothesis. From their work, Cattell (1946) selected a subset of 4,500 trait terms for which he created

synonym clusters. He succeeded in reducing the 4,500 terms to 35 variables and conducted factor analyses on

them; he found 12 factors. These were the basis for his 16PF questionnaire.

Observer ratings on the 35 scales were obtained and factored by Tupes and Christal (1961). They concluded

that there are “five relatively strong and recurrent factors and nothing more of any consequence”. The five

personality factors they revealed are very much related to the present Big Five. Also Fiske (1949) concluded

that there are only five dimensions of personality.

Norman made a selection of the 20 best rating scales; this selection has been used in later research many

times. He replicated the Five Factors and also gave initial labels to them. Based on different sets of variables,

others found similar structures (Barrick & Mount, 1991; John et al., 2008: p.118, 119; McAdams, 1992: p.333;

McCrae & John, 1992: p.181-185).

Within the questionnaire stream, personality questionnaires were used that built on theories of Jung, Murray,

and Sullivan, for example. Consensus was reached on the existence of at least two factors (Neuroticism and

Extraversion) and the search for new dimensions was going on. Some proposed an Openness dimension, while

also a Constraint (Conscientiousness) dimension was opted. It could be that the questionnaire stream might

also have found five factors in the course of time.

The discovery of the Five Factors ultimately led to the merger of the lexical tradition and the questionnaire

tradition (McCrae & John, 1992: p.186).

2.1.2.2. Interpretation of the Big Five

It was Goldberg who called the five factors ‘Big Five’. This name does not refer to the importance of the five

dimensions, but expresses the broadness of each of them. The name ‘Big Five Model’ originates from the

questionnaire stream.

According to John et al. (2008: p.140), the five factors are “what the categories ‘plant’ and ‘animal’ are to the

world of biological objects”. McAdams (1992: p. 339) suggests to speak about ‘trait categories’ instead of ‘basic

traits’). Later in this chapter (section 2.1.4.4), it will be discussed how scholars have dealt with the broadness of

the factors.


Although initial consensus was reached, the discussion was going on. Because the Big Five dimensions were

discovered by multiple researchers, there was not a single Big Five (John et al., 2008: p.125). This led to

confusion about the naming and interpretation of the factors.

It has been said that the label names are not always a very accurate representation of the factors

(Conscientiousness is supposed to be too narrow and Openness too vague), but replacing these names might

be confusing as well (John et al., 2008: p.138).

In literature, Norman’s factor names and numbers are often used: I Extraversion or Surgency, II Agreeableness,

III: Conscientiousness, IV: Emotional Stability, and V: Culture. However, he did not give a theoretical

explanation for these names.

Others have used the following labels: Extraversion (E), Agreeableness (A), Conscientiousness (C), Neuroticism

(N), and Openness to Experience (O).

It has also been suggested to use only the Roman Numbers (without the names), because they are theoretically

neutral. Others opted the use of initials (EACNO = OCEAN) which are less related to a specific theory and are

easier to interpret. (McCrae & John, 1992: p.180).

In this thesis, the factor names and definitions by John et al. (2008: p.138) will be used:

Extraversion (Energy, Enthusiasm): “an energetic approach toward the social and material world”. It

includes traits like “sociability, activity, assertiveness, and positive emotionality”. In other words: it is a

tendency to be outgoing (Gray, 2007: p. 541).

Agreeableness (Altruism, Affection): “a pro-social and communal orientation towards others”;

agreeableness encompasses traits such as “altruism, tender-mindedness, trust, and modesty”. The

high pole of this dimension represents people who value and respect others’ conventions and beliefs.

Conscientiousness (Constraint, Control of impulse): “socially prescribed impulse control”. This

dimension relates to task- and goal-directed behavior, strong will, responsibility, thinking before

acting, following norms and rules, trustworthiness, planning, organizing, and prioritizing tasks.

Neuroticism (Negative Emotionality, Nervousness): “negative emotionality”. Neuroticism is

characterized by emotional instability, feeling anxious and nervous, pessimism, and low self-esteem.

Openness to Experience (Originality, Open-Mindedness): “depth, originality, and complexity of an

individual’s mental and experiential life”. Having an active imagination and preference for variety and

tending to be less conservative and traditional are associated with this dimension (Zhang, 2003:

p.1432).

2.1.3. Personality Frameworks

This chapter continues by discussing the most important instruments that have emerged to measure

personality. The majority of them are based on the Big Five.


2.1.3.1. 16 Personality Factors (16PF)

The 16PF, developed by Cattell, was already mentioned above; his instrument relates to the 12 factors he

found. Others reanalyzed the correlation matrices Cattell used, but they concluded that his factors were not

replicable across gender, age, or methods, or could not be found at all (Zuckerman et al., 1993, p.754).

To these twelve factors, four other factors were added by Cattell that he had only found by analysing

questionnaires (McCrae & John, 1992: p.187).

Despite of the current dominance of the Big Five, Cattell’s questionnaire (fifth edition) is still used quite

regularly. It requires 35 to 50 minutes to complete the 185 multiple choice items (Cattell & Cattell, 1995). An

example of the statements in the questionnaire is: “I like to go to parties”. For each statement, there are three

answer options: ‘yes’, ‘occasionally’, and ‘no’.

2.1.3.2. NEO Personality Inventory (Revised) (NEO-PI(R))

The work of Costa and McCrae (1985), who developed the NEO Personality Inventory (NEO-PI), has played an

important role for the study of personality. Based on the ‘questionnaire tradition’, their inventory initially

measured only three dimensions: Neuroticism (N), Extraversion (E), and Openness (O). At that time, the first

two dimensions were ubiquitous within the questionnaire stream, while Openness was added by Costa and

McCrae, based on cluster analysis of the 16PF.

When they realized that their work did not include two factors of the Big Five (which was discovered by the

‘lexical tradition’), they decided to add items on Agreeableness and Conscientiousness to their NEO inventory.

In 1992, they published the NEO-PI-R (revised edition of the NEO-PI), consisting of 240 items that cover all five

factors (John et al., 2008: p.124, 125). The administration time of the NEO PI-R is 35 to 45 minutes. An example

of the items is: “Our ideas of right and wrong may not be right for everyone in the world”. The statements are

rated on a 5-point Likert scale ranging from ‘strongly disagree’ to ‘strongly agree’.

2.1.3.3. NEO Five Factor Inventory (NEO-FFI)

As the NEO-PI-R was too extensive for many research purposes, Costa and McCrae came up with a shorter

measure, which was called NEO Five Factor Inventory (NEO-FFI). The items of the NEO-FFI are based on the

NEO-PI-R and also represent the Big Five. Each of the five factors is measured by a 12-item scale (John et al.,

2008: p.125); so the NEO-FFI has 60 items in total. Compared to the NEO-PI-R, NEO-FFI reduces the

administration time from 35-45 minutes to 10-15 minutes.

2.1.3.4. Big Five Inventory (BFI)

To meet the desire for a short instrument for measuring the Big Five dimensions, John and his colleagues

(1991) developed the 44-item Big Five Inventory (BFI). Their purpose was to “create a brief inventory that

would allow efficient and flexible assessment of the dimensions when there is no need for more differentiated

measurement of individual facets” (John et al., 2010: p.129). Section 2.1.4.4 elaborates on these facets. All 44

statements of the BFI start with the statement “I see myself as someone who…”. An example of these items is:

“generates a lot of enthusiasm”. People have to rate themselves on a scale ranging from 1 (disagree strongly)

to 5 (agree strongly). It takes about 5 minutes to complete the BFI questionnaire.


2.1.3.5. Goldberg’s Trait Descriptive Adjectives (TDA)

The Trait Descriptive Adjectives (TDA) instrument, developed by Goldberg, is composed out of 100 single

adjectives (unipolar markers). One of the drawbacks of TDA is that context is lacking; therefore, items from

other inventories might be easier to understand. Saucier (1994) developed a shorter version of the TDA which

has only 40 items. Completing the original TDA takes about 10-15 minutes, while the Saucier’s abbreviated

version takes approximately 5 minutes to complete. The TDA uses a spectrum with nine labels. Four of them

belong to ‘inaccurate’ (extremely to slightly), one to ‘neither’, and the other four to ‘inaccurate’ (slightly to

extremely). People have to give a rating for the degree in which they regard themselves as being ‘disorganized’,

‘rude’, or ‘temperamental’ (Goldberg, 1992, John et al., 2008).

2.1.3.6. Myers-Briggs Type Indicator (MBTI)

Each year, more than 3.5 million people fill in the 94 forced-choice items of the Myers-Briggs Type Indicator

(MBTI) (Durham University, 2012). This is the personality measuring tool that is used most often. However, this

inventory is not founded on the Big Five, but is Jungian-based and has four bipolar discontinuous scales:

Introversion-Extraversion, Sensation-Intuition, Thinking-Feeling, and Judging-Perceiving. Based on the

outcomes, respondents could be classified into sixteen different categories.

Some scholars are critical of the MBTI and say that the theory of Jung is outdated. Others are more nuanced

and have concluded that there is are some overlap between the MBTI and the Five Factor-based NEO-PI. In

fact, MBTI measures the Big Five factors, except Neuroticism (Furnham, 1996). Administration time of the MBTI

is about 30 minutes.

2.1.3.7. Two Final Remarks

Besides the instruments discussed above, there are many other tools for measuring the Big Five. John et al.

(2010: p.130) conclude that there is not a single instrument that could be considered as the ‘gold standard’.

One of the most prominent instruments for measuring the Big Five factors is the NEO-PI-R questionnaire, but

the choice for a certain tool should be determined by the research purposes. There is not a one-size-fits-all

measure (Vollrath, 2001: p.338).

In business practice, measurement tools are sometimes applied that might be lacking a scientific basis and/or

are not often used in scientific literature.

An interesting example of such a tool is ‘Management Drives’. This instrument distinguishes six drivers (colors)

that are related to colors. For example, the orange drive is the one that want to show progress, results, and

achievements (Management Drives, 2012). In this thesis, no further attention is given to this kind of

instruments.

2.1.4. Issues

Now some important instruments to measure personality have passed in review, it is time to reflect on issues

regarding personality, the Big Five, and the instruments that could be used to measure them, in order to choose

an appropriate method to map personality in this thesis.


2.1.4.1. Stability of Personality

Research has been conducted on the stability of personality over time. It has been found that personality is

quite stable, even over longer periods of time (decades). The older people get, the more stable their

personality becomes. Especially after an age of 50, personality is extremely stable, although (small) changes can

always occur (Gray, 2007: p.544).

2.1.4.2. Universality

The taxonomic studies that are related to the Big Five were in English and the researchers were American. So,

an important question is whether the Big Five model is universal across languages and cultures.

Taxonomy projects by Hofstee, de Raad and colleagues – also among Dutch people – revealed that the five

factors are replicable in other countries as well (Denissen et al., 2007: p.152).

One exception is that, compared to the English Big Five, the Dutch fifth factor puts more emphasis on

Unconventionality and Rebelliousness instead of Intellect and Imagination. The researchers could not explain

this finding (Hofstee et al., 1997: p. 30). Still, there is no research that suggests that personality dimensions are

not universal and that cultures and languages have their own subset of personality dimensions (John et al.,

2008: p.121-124).

2.1.4.3. Predictive Power

According to some scholars, the Big Five are too broad to be good predictors; narrow traits are better

predictors because they are more specific and selective (McAdams, 1992: p.338).

Research on the prediction power of the Big Five has started quite recently. Scientist aimed to identify which

particular Big Five factors have impact on fundamental domains (such as health, work, and relationships). This

research is built on the assumption that there is an interaction between personal factors (traits) and

environmental factors (e.g. job, relationship).

It has been found that people’s traits influence the way in which they experience and explain things; besides,

these traits have an influence on people’s choices concerning both social and non-social environments (e.g.

jobs, places to live, music) and also on how they can adapt their environments to meet their desires.

The interaction between traits and the environment make that they “are hypothesized to influence the

behavioural, emotional, social, and material life outcomes of the individual” (John et al., 2008: p.141, 142).

One interesting finding here might be that relationships were found between the Big Five traits (in particular

Conscientiousness and Neuroticism) and job performance and satisfaction (John et al., 2008: p.141, 142).

2.1.4.4. Facets / Bandwidth-fidelity Dilemma

In section 2.1.2.2, the name of the Big Five was already explained: this refers to the high bandwidth of the

factors. Each of the five factors could be subdivided into a much larger number of personality characteristics.

These characteristics are also called ‘facets’. The Big Five factors aggregate these facets, by which useful

information might be lost. This has been posed as a point of critique on the Big Five (Barrick & Mount, 1991: p.

3).


To overcome this bandwidth-fidelity dilemma, personality could be examined hierarchically. This is exactly

what (for instance) the NEO-PI-R does (Soto & John, 2009: p.84). The 240 items of NEO-PI-R measure six facets

per factor. Also the NEO-FFI could be used to measure facets (John et al., 2008: p. 125).

The goal of the Big Five Inventory was to provide a quick measure for cases in which there is no need for

assessing the individual facets (John et al., 2008: p. 129). But, an attempt by Soto and John (2009) to develop

facet scales based on the 44 BFI items, proved to be successful: 10 BFI facet scales were made, which converge

with a subset of the 30 NEO-PI-R facets and also with facets from other Big Five inventories.

The following facets were derived from the BFI: assertiveness (extraversion), activity (extraversion), altruism

(agreeableness), compliance (agreeableness), order (conscientiousness), self-discipline (conscientiousness),

anxiety (neuroticism), depression (neuroticism), aesthetics (openness), and ideas (openness).

2.1.4.5. Number of Factors

Over time, there has been much debate about the number of factors. Some have argued that fewer factors

should be sufficient to measure personality traits; however empirical evidence is available that all five factors

are needed. Besides, it has been suggested that more than five factors are needed. It seems impossible

however to find a sixth, replicable factor (McCrae & John, 1992: p.189-192).

Among the authors who propagandize the existence of a sixth factor are Ashton and Lee (2006), who created

the HEXACO model and claim that they have found an additional factor, based on lexical studies: Honesty-

Humility. At the meantime, other factors were recomposed. In response, McCrae and Costa (2008: p.167) argue

that, from a conceptual and empirical point of view, Honesty and Humility correspond with two facets of

Agreeableness: Straightforwardness and Modesty.

2.1.4.6. Commercial Versus Free Inventories

Most of the inventories discussed above are proprietary instruments. Requiring permission from copyright

holders and paying fees for each questionnaire used, hinders the progress within the science of personality

assessment (Zheng et al., 2008).

For this reason, Goldberg laid the foundation for an international collaboration: the International Personality

Item Pool (IPIP). Items of the IPIP are in the public domain and now has over 2500 items. It contains equivalents

(with good internal consistency) for many popular commercial inventories such as PF16 and the NEO

inventories. There are also translations available of (some) items in more than 25 languages. It also contains a

measurement that is quite similar to the BFI: The 50 Big Five Factor Markers (BFFM) (Zheng et al., 2008; IPIP,

2012).

From the instruments discussed above, the BFI and Goldberg’s TDA are freely available.


2.2. Work Design

2.2.1. Defining Work Design

The term ‘work design’ is not very clear and has been described in multiple ways. Torraco (2005: p.87) defines

it as “the systematic organization, design, and articulation of work activities at one or more levels of the

organization: system-wide, process, group, job, and task”.

Sinha & Van de Ven (2005: p.390), argue that work design and job design are separate concepts and cite Trist

(1981) who stated that “redesign of work leads beyond individual jobs to the organization of groups of workers,

and beyond that to the organization of support services”. In their article they deal with the design of work

within and between organizations. This implies that their ‘level’ of work design goes beyond individual

organizations. However, that is not what is focussed on in this thesis.

To be more specific, it might be better to use the term ‘job design’, which traditionally has been defined as “the

set of opportunities and constraints structured into assigned tasks and responsibilities that affect how an

employee accomplishes and experiences work”. Nowadays, this definition is broadened to “the process and

outcomes of how work is structured, organized, experienced, and enacted” (Grant et al., 2010: p.418).

2.2.2. Job Design Development

The history of job design traces back to the origin of organized work. By means of organized roles, the ancient

Egyptians were able to ‘run’ their society and to build great pyramids. Also in armies, that have existed for

thousands of years, specialized work roles have been of great importance (Morgenson & Humphrey, 2008).

The Industrial Revolution triggered a systematic study of work. Adam Smith (1776) suggested to break down

complex jobs into simpler jobs (division of labor), in order to improve performance. Charles Babbage (1835)

expanded on these ideas by presenting additional advantages such as cheaper labor (Parker et al., 2001).

In 1911, Frederick Taylor published his book The Principles of Scientific Management, which earned him the

title ‘father of scientific management’. According to him, increasing productivity would be beneficial to both

firm and worker, and therefore he aimed to determine scientifically (by means of observation and stopwatch)

the ‘one best way’ to perform tasks. Time, methods, and rules of work were fundamental to Taylor’s approach

(Nickels et al., 2008: p.260, 261). The introduction of the first moving assembly line by Henry Ford is strongly

related to his approach.

Research that took place at the Western Electric Company’s Hawthorne plant (1927-1933) revealed the

importance of human and psychological factors. Gradually, more researchers became concerned about the

effects of scientific management on employees’ well-being, satisfaction, and motivation, which “paved the way

for a full-blown research agenda on the design of jobs to satisfy and fulfill employees’ basic motives and

psychological needs” (Grant et al., 2010).

Over time, some prominent theories have been developed within the field of job design. For instance,

McGregor distinguished between Theory X and Theory Y. Theory X managers believe that workers are lazy and

dislike work, why Theory Y managers assume that employees are committed and like working towards a goal

(Nickels et al., 2008: p.269, 270; Grant et al., 2010: p.420).


Also Herzberg’s theory about motivators and hygiene factors has received much attention. Motivators are job

factors that make employees productive and satisfied, such as the work itself, achievement, recognition,

responsibility, and growth and advancement. Hygiene factors, on the other hand, can cause dissatisfaction if

absent, but do not motivate if present. Examples of hygiene or maintenance factors are: company policy and

administration, supervision, working conditions, interpersonal relationships, salary, status, and job security

(Nickels et al., 2008: p.265,266).

It seemed that empirical support to confirm the basic premise of the two-factor theory was lacking.

Nevertheless, it raised attention for concepts like job redesign, job enlargement, and job enrichment (Parker et

al., 2001: p.415; Grant et al., 2010: p.420).

A theory that is closely connected to job design is the Sociotechnical Systems Theory (SST) which dates back

from the 1950s and was developed by the Tavistock Institute, London. SST suggests that organizations are

composed of interacting people and a technical system that together produce services and products.

Productivity and satisfaction could be maximized by joint optimization of human and mechanical-technological

systems, which in turn could be achieved by autonomous workgroups (Grant et al., 2010: p.424; Morgeson &

Campion, 2003: p.426). Within the field of group work design, SST has received much attention as it focuses on

interrelations with other groups or units (Rousseau, 1977: p.19).

2.2.3. Job Characteristics Model

To date, the dominant model of job design is the Job Characteristics Model (JCM), developed by Hackman and

Oldham (Grant et al., 2010: p.421). This model, which was designed as an alternative for Herzberg’s two-factor

theory, distinguishes five core job characteristics: task significance, task identity, skill variety, autonomy, and

feedback.

Task significance is the impact that a job has on the lives and work of others. Task identity is the degree to

which a job allows to complete a whole, identifiable, visible piece of work from start to finish. Skill variety is the

extent to which different skills are involved in the job. Autonomy is the degree of freedom and discretion in the

scheduling of work and the determination of procedures. Feedback is the amount of clear, direct information

about performance and understanding the results of behavior (and of having internal control) (Grant et al.,

2010: p.421; Nickels et al., 2008: p.268).

The job characteristics theory suggests that the five job characteristics cause three critical psychological states

(experienced meaningfulness, responsibility, and knowledge of result) which in turn influence four outcomes:

motivation, satisfaction, performance, and withdrawal behaviors (Grant et al., 2010; Morgeson & Campion,

2003).

Over time, both extensions and challenges of the Job Characteristics Model have been proposed. A major

challenge came from the Social Information Processing Perspective. According to this view, not the structural

properties of the work itself, but rather how the work is socially constructed (cues from co-workers,

supervisors, customers, family members, and own behaviors and experiences) determine job perceptions and


attitudes. However, research points out that objective job characteristics are more significant than social cues

(Grant et al., 2010: 422, 423).

The difference between enriched tasks and enriched jobs has been a motive for some researchers to extend

the Job Characteristics Model.

More recently, new job characteristics, outcomes, mediators, and moderators were added to the model (Grant

et al., 2010: p.423). The Work Design Questionnaire, developed by Morgeson et al., distinguishes four broad

categories of job characteristics: task, physical, knowledge, and social (Morgeson & Humphrey, 2008). Other

researchers have broadened job design theories by presenting “new perspectives on the boundaries, processes

and outcomes of job design” (Grant et al., 2010: p.431). The traditional focus on motivation, satisfaction, and

withdrawal was extended by the following four categories: uncertainty, proactivity, dynamism, and creativity.

2.2.4. New Ways of Working

Three key characteristics of New Ways of Working could be distinguished. First of all, the timing of work has

become more flexible; work schedules are no longer fixed. Secondly, the place of work has become more

flexible. Thirdly, New Ways of Working are facilitated by new media technologies. Based on these

characteristics, Brummelhuis et al. (2012) define New Ways of Working as “a work design in which employees

can control the timing and place of their work, while being supported by electronic communication”.

The definition of New Ways of Working that is used by Erasmus@Work reads as follows: “a new form to

organize labour, where the employee has a high degree of autonomy to decide himself on time and place

where work will be done, while management of the work is primarily based on the employee’s output. This

enables the employee to find his balance between work and private. Hereby, he is supported by a flexible

working space and information technology, which enables him to execute his work efficient and effective,

within and outside the boundaries of the organization, alone and in collaboration with others, while it is not at

the expense of social cohesion within the organization”.


3. Conceptual Framework

The current chapter presents the conceptual framework that was developed to study the impact of personality

on the New Ways of Working concept. This model is depicted in figure 3.1. An extended version of this model,

containing all variables, can be found in appendix 2.

The ‘building blocks’ or ‘modules’ represent different concepts, while the arrows stand for propositions. Both

concepts and propositions are explained in the sections below. First of all, the focus is on the blocks that both

the Personality model and the Culture model have in common.

To what extent the Cultural model differs from the Personality model is discussed in appendix 1.

Figure 3.1. – Conceptual model (Personality)

The concepts will be discussed in the following order:

1. Work Practices

2. Work Atmosphere

3. Work Performance

4. Work Arrangements

5. Personality Traits

6. Control Variables

This model is based on the assumption that the following three core dimensions are affected by the NWoW

concept: People, Place, and Technology (Andersen, 2012).

Work Arrangements People

- Policies / agreements

Place - Workplace design

Technology

- Media availability

Control variables Gender, Age, Position, Time dependency, Location dependency

Work Atmosphere Empowerment

Control

Work Practices People

- Reflexivity - Flexibility (time)

Place - Flexibility (place) - Task Workplace Fit

Technology - Media use

Personality Traits Extraversion, Agreeableness, Conscientiousness, Neuroticism, Openness

Work Performance

People

- Employee satisfaction

- Work life balance

Profit

- Productivity P1: +

P4

P5

P3

P2


Regarding people, there is a mental shift going on because digital tools become commonplace. This

enables working and communicating in different ways.

Regarding place, workers have become more fluid in terms of physical presence. For instance, they are

increasingly working on the move.

Regarding technology, technological developments challenge the idea that the office should be the

primary work location; they enable workers to perform their tasks at any time and at any location.

Based on this assumption, a number of Work Practices and Work Performance elements were selected that

should be part of the conceptual model. The Work Performance indicators (employee satisfaction, work life

balance, and productivity) were selected based on previous research by Erasmus@Work.

3.1. Work Practices

Regarding the people dimension, the focus is on reflexivity and flex-time. Two work practices are linked to the

place dimension: flex-place and Task Workplace Fit. Media use is related to the technology dimension.

3.1.1. Reflexivity

According to Schippers et al. (2007) reflexivity is “the extent to which teams reflect upon and modify their

functioning”. The authors regard reflexivity as a group process, although they state that it could also be

operationalized at the individual level. This is the case in this thesis.

Reflexivity is an iterative process, which consists out of the following components: reflection, planning, and

action/adaption, while reflection in turn is assumed to have three levels of depth: swallow, moderate, and

deep (Schippers, 2007: p.190).

The focus of this thesis is on three kinds of reflexivity, which are related to the other new work practices:

‘reflection on choice of location’, ‘reflection on working hours and schedule’, and ‘reflection on media usage’.

3.1.2. Flexibility

Flexible work arrangements includes flexibility in the scheduling of hours (flex-time), flexibility in the amount of

hours (part-time or job sharing), and flexibility in the location of work (flex-place) (Nadler et al., 2010). This

thesis addresses the first and the last type of flexibility. Flexibility in the amount of hours is not a typical

characteristic for the NWoW concept.

Although flex-time and flex-place often coincide (e.g. Raghuram et al., 2001), here they are conceptualized as

two free-standing practices, in order to measure their separate contributions.

3.1.2.1. Flex-place (where)

People became interested in the concept of telework during the oil crisis of the 1970s (Haddon & Brynin, 2005).

Since, telework has been studied by multiple of scientific disciplines (Bailey & Kurland, 2002) and has proven to

be a very rapidly changing phenomenon (Sullivan, 2003).


Telework is often associated with working from the home environment (e.g. Baruch, 2000). One should,

however, consider that this is only one example of telework/flex-place. Alternatively, people can work from an

external office or meeting location, at the client location, or on the road.

Hill et al. (2001: p.51) define flex-place as “giving employees varying degrees over where their work is done”. It

refers to people’s freedom to decide for themselves at what place they are going to perform their tasks.

Kurland & Bailey (1999) distinguish four types of telework: home-based telecommuting, satellite offices,

neighbourhood work center, and mobile workers.

Decreases in real-estate costs and contributions to the reduction of air pollution and traffic congestion were

mentioned (among other things) as benefits of telework (Bailey & Kurland, 2002).

3.1.2.2. Flex-time (when)

Nadler et al. (2010: p.865, 866) define flexible work scheduling, in agreement with Avery and Zabel (2001), as

“non-traditional variability in work schedules, allowing for less rigid attendance requirements”. Some benefits

of work schedule flexibility are: a greater range of customer service hours, higher employee satisfaction, and

increased attractiveness to potential employees.

Contrary to other scholars, Nadler et al. (2010) do not treat schedule flexibility as a homogeneous construct.

They suggest that there are eight types of work schedule flexibility, which are varying in terms of the amount of

flexibility in ending and starting schedule times, core hours present, and the flexibility of day-to-day changes.

The first option is that there is no flexibility at all. Flexi-tour means that starting time and corresponding

quitting time (fixed to the starting time) is flexible, but predetermined. In case of modified flexi-tour, there is an

ability to change starting time when needed, if it is notified before. This notification is not needed anymore

when the flex-time plan is a Gliding schedule. Modified gliding schedule is similar to gliding schedule, except

that there is a set of core hours. Till now, people had to work eight hours a day (fixed after starting time). This

changes in case of Variable day: both starting and ending times are flexible and there is a weekly quota of

working hours, but there are still core hours. Variable week replaces the quota of weekly working hours by a

quota of weekly goals (although there are core hours). The most extreme form of schedule flexibility, Crediting

schedule, has complete flexibility. There are no core hours anymore. Hours can be credited (or debited) from

one week to another week (e.g. vacation time).

3.1.3. Task Workplace Fit (TWPF)

Besides flex-place, also the design of a workplace is decisive for the extent to which people can find a place

where they can perform a certain task. Different tasks impose different requirements with regard to the

workplace. Task Workplace Fit could be defined as: the degree in which people are able to find a workplace

that suits the task they want to perform, either inside or outside the office.

Based on projects with thousands of companies and their annual workplace survey, Gensler (2008), a “leading

design firm for business”, identified four different work modes, by which all ‘day-to-day knowledge workplace

activities’ could be categorized: Focus, Collaborate, Learn, and Socialize.


‘Focus’ is a work mode that requires concentration and attention. On average, an employee spends

59% of his/her time on focus work. Focus is about tasks like: thinking, reflecting, analysing, writing,

problem-solving, quantitative analysis, creating, imagining, reviewing, and assessing. Focus activities

require a workplace without acoustic and visual distractions.

On average, 22% of work time is spent on ‘Collaborate’. ‘Collaborate’ is working with other persons or

teams, in order to achieve a goal. It includes the following tasks: sharing knowledge and information,

discussing, listening, co-creating, showing, and brainstorming. Proximity and visual contract is

supportive for collaboration tasks.

‘Learn’ means that new knowledge or skills are acquired through education or experience. People

spend on average 4% of their time on learning. ‘Learn’ is about training, concept exploration and

development, problem-solving, memorising, discovery, teaching, reflecting, and integrating and

applying knowledge. The learning style is determinant for what type of workplace is required.

The fourth work mode, ‘Socialize’, is about creating “common bonds and values, collective identity

and productive relationships” through work interactions. ‘Socialize’ includes talking, laughing,

networking, trust building, recognition, celebrating interacting, mentoring, and enhancing

relationships. People spend on average 6% of their work time on socializing (Gensler, 2008).

Although it might be interesting to consider the proportion of time (quantity) spent on each workplace activity,

to some extent this is subject to the characteristics of the job itself. Some jobs might require relatively more of

a certain workplace activity than others. This does not have to be problematic at all.

What is really of interest here is whether workers can perform a certain task at the right place (quality).

Consequently, the purpose is to answer questions such as: to what extent do workers have access to a place

where they can Focus/Collaborate/Learn/Socialize at any time they need to?

This question implies that there can be variation at two different levels:

- The need for such (a) place(s)

- The availability of such (a) place(s)

When the availability of places for a certain workplace activity matches the desire for (a) place(s) that suits to

this activity, a Task Workplace Fit exists.

3.1.4. Media Use

Both definitions of New Ways of Working that were discussed in the previous chapter state that information

and communication technologies are an important enabler of the NWoW concept.

For quite a long time, the media richness theory has dominated scientific research on media use. According to

this theory, task performance could be improved by matching task information needs to the information

richness of a medium. However, the media richness theory did not appear to be able to deal with new media


such as computer mediated communication. For that reason, a new theory was developed, called ‘media

synchronicity theory’ (Dennis et al., 2008).

True synchronicity could be described as “a state in which individuals are working together at the same time

with a common focus”. People that are communicating synchronously do not automatically achieve

synchronicity. Therefore, Dennis et al. (2008) define ‘media synchronicity’ as “the extent to which the

capabilities of a communication medium enable individuals to achieve synchronicity”.

3.2. Work Atmosphere

The term ‘Work Atmosphere’ is used here as a collective noun for (inter)personal aspects. It deals with people’s

perceptions, behavior, and interaction with each other on work related issues.

3.2.1. Empowerment

Within scientific literature, the focus has largely been on two types of empowerment: structural empowerment

and psychological empowerment. The first one is employees’ perception of the actual empowering conditions

in the workplace, while psychological empowerment is how employees psychologically interpret or react to

these conditions (Laschinger et al., 2004). Besides, there is a third conception of empowerment, called the

process approach, which focuses on the relationship between structural antecedents and resulting

psychological states (Mathieu et al., 2006: p.97).

Although structural empowerment may empower employees, this is not necessarily the result. It makes

therefore more sense to focus on psychological empowerment, which implies a reaction of employees to the

structural empowerment conditions (Spreitzer, 1995: p.1443). Thomas & Velthouse (1990: p.668) defined

(psychological) empowerment as “intrinsic task motivation” and mention four cognitions in which the concept

manifests itself: Meaning, Competence, Self-determination, and Impact. Spreitzer (1995) elaborated on these

cognitions. Meaning is the value that a certain work goal or purpose has for someone; this judgement is based

on the individual’s own ideas or standards. Competence is someone’s belief that he or she is capable to

perform a certain task or activity ‘with skill’. This is also called ‘self-efficacy’. Self-determination is a feeling of

having choice in initiating, regulating, and continuing work behaviors and processes. Impact is the degree to

which ‘strategic, administrative, or operating outcomes at work’ can be influenced by an individual (impact is

the opposite of learned helplessness) (Spreitzer, 1995: p.1443,1444; Liden et al., 2000: p.407).

It is notable that these cognitions closely align with the critical psychological states of the Job Characteristics

Model (see section 2.2.3): Meaning is similar to meaningfulness, Impact to knowledge of results, and Self-

determination to experienced responsibility. However, the psychological empowerment approach differs from

the Job Characteristics model regarding its assumption that the psychological states “can arise from influences

over and above work characteristics, such as peer helping and supportive customer relationships” (Parker et

al., 2001: p.416, 417).

3.2.2. Control

Control has been defined as “the business process by which organizational entities impact and motivate other

entities to carry out collaborative plans to ensure that specific organizational goals are met” (Kang et al., 2011).


Within scientific literature, several forms of control have been distinguished. In the conceptual model, the

focus is on the following forms of control: Output control, Behavioral control, Social control, and Mutual

control.

The first two types of control belong to the category ‘formal control’, which deals with performance evaluation.

In case of Output control, people are rewarded for reaching desired outcomes. When Behavioral control is

applied, the focus is on whether people stick to rules and procedures (Kang et al., 2011).

Social control and Mutual control are informal modes of control, which means that they are based on social or

people strategies. The purpose of clan control is to reinforce acceptable behavior by spreading common values,

beliefs, and philosophy among the members of a group (Kirsch, 1997: p.217). Mutual control is the monitoring

of one another (Langfred, 2004: p.385).

3.3. Work Performance

A great challenge for companies is maximizing the triple bottom line ‘People, Planet, Profit’, which

encompasses social, ecological, and economic aspects. For this study, two aspects related to People and one

aspect related to Profit are selected.

Regarding People, the focus is on Employee Satisfaction and Work Life Balance, while Productivity is an aspect

that belongs to Profit.

To limit the scope of the model, only social and economic performance aspects are considered, which implies

that ecological aspects are disregarded here. Although these aspects are not unimportant, they are not often a

main motive for implementing the NWoW concept and therefore are ignored.

Together, the three selected aspects are labelled ‘Work Performance’. According to Tangen (2005),

performance could be defined as the successfulness of a company and its activities.

Now each of these aspects will be considered more closely.

3.3.1. Employee Satisfaction

Employee satisfaction or job satisfaction has been defined as “the extent of positive emotional response to the

job resulting from an employee’s appraisal of the job as fulfilling or congruent with the individual’s values”

(Morris & Venkatesh, 2010). Since the 1930s, job satisfaction has become a concept studied often. For

instance, it has been researched in relationship to concepts like productivity, employee commitment,

absenteeism, and turnover (Agho et al., 1993).

Researchers have found that employee satisfaction is an important driver of quality, customer satisfaction, and

productivity. With the rise of ‘the knowledge economy’, also the importance of employee satisfaction and

loyalty has increased: knowledge is a highly mobile resource which is stored in the heads of people who can

easily take it with them (Matzler et al., 2004). Because knowledge workers ‘own’ the production means,

companies are increasingly dependent on their employees (Drucker, 1999), which strengthens the need for

satisfying employees.


3.3.2. Work Life Balance

The term ‘work life balance’ might be a little bit confusing. First of all, there is confusion about the term

‘balance’. Used as a noun (Oxford English Dictionary), it implies “an equal distribution of weight or amount”.

This might however not be the kind of balance meant in case of work life balance.

From a physical and psychological point of view, ‘balance’ means: “stability of body and mind”. This indicates

that balance can have “both an objective and a subjective meaning and measurement”.

Used as a verb (Oxford English Dictionary), balance means: “to off-set or compare, to equal and neutralise, to

bring or come into equilibrium”. It seems that balance is good, but it is not clear whether or not imbalance can

be favourable.

Regarding ‘work’ and ‘life’ similar difficulties arise. Is work only ‘paid employment’ or does it also include

unpaid hours (traveling hours)? Regarding life, the focus is often exclusively on family life, but this is “only one

aspect of life outside work”. Distinctions have been made between free time and leisure time, and committed

time and free time. Anyway, it seems to be clear that ‘work life balance’ could be defined in many ways (Guest,

2002).

To bypass these issues, the following definition of work life balance will be used: “a personal sense of when

both the work and home environment offset each other in such a way that the individual may be successful in

both environments” (Van der Meulen, 2010).

3.3.3. Productivity

The (multidimensional) term ‘productivity’ is often used, is “rarely adequately defined or explained” (Tangen,

2005), and has a meaning that varies in accordance to the context in which it is used. Nevertheless, some

crucial elements of productivity could be distinguished: it is related to the use and availability of resources.

Besides, it is strongly connected to the creation of value. Another characteristic of productivity is that it is a

relative concept: to observe an increase or decrease, there should be deviations from a standard (e.g.

competitor, other department) or changes over time (Tangen, 2005).

A quite broad definition of productivity was given by Hill (1993), which reads as follows: “the ratio of what is

produced to what is required to produce it. Productivity measures the relationship between output such as

goods and services produced, and inputs that include labour, capital, material and other resources” (Cited in

Tangen, 2005).

Compared to productivity of manual workers, quantifying and measuring knowledge-worker productivity is

much more complicated (Drucker, 1999, p.5). For that reason, often self-reported data is used in research on

productivity of nonmanufacturing industries (which is also the case in this thesis). Although a threat exists that

this method brings along a self-serving bias, it is reasonable that this bias is consistent across respondents and

therefore this method could be applied ‘safely’ (Eaton, 2003: p.157).

3.4. Work Arrangements

It might be clarifying to start this section by explaining why ‘Work Arrangements’ were added to the conceptual

model. This is based on the assumption that there are two requisites for the use of (NWoW) work practices. In


the first place, there should be a fit with human related aspects (personality traits and/or cultural values).

Besides, the practices should be facilitated by managers; employees should be allowed to use these practices.

This second requisite is captured by ‘Work Arrangements’.

Again, the triad People-Place-Technology was used as a basis: Policies/Agreements are related to the People

dimension, Workplace Design to Place, and Media Availability to Technology.

3.4.1. Policies / Agreements

Policies / Agreements focuses on what is agreed on the place where and the time when work is done. It deals

with the question whether or not people are allowed to work in a flexible way.

In the literature, a distinction is made between two kinds of flexibility policies: formal and informal. Formal

flexibility policies are defined as “written, officially approved human resource policies that provide flexibility

based on the approval of the HR department and supervisor discretion” (Kossek et al., 2005: p. 349). When

more flexibility is permitted by supervisors than formally allowed, there is talk of informal flexibility. Because

this kind of flexibility is not formal, it is invisible to higher-level managers (Eaton, 2003: p.147).

3.4.2. Workplace Design

More attention for flexibility regarding the location of work, does not mean that the office design has become

less important. Instead, the office type should facilitate and align with the new way of working.

According to Danielsson and Bodin (2008), both architectural (spatial organization) and functional (work

organization) should be considered in the categorization of office environments. Elaborating on existing

literature, they composed a categorisation that meets these two goals.

These are the seven office types they distinguish: cell office, shared room office, small open plan office,

medium-sized open plan office, large open plan office, flex office, and combi office.

Cell office: in case of this office design, there are multiple private room offices. Each room has a

window and the small rooms are connected to each other by long corridors. The majority of amenities

needed are available in the rooms. Characteristic for this design are independence and concentration

possibilities.

Shared room office: shared room offices are ‘populated’ by 2-3 persons. Work stations are freely

arranged and colleagues share a window. Sometimes divisional elements like screens are used to

provide privacy to individuals. Amenities are mostly found outside the office, although shared room

offices for team-based work (interactive project work) often have work facilities in the room. People

are divided among the rooms, based on the type of work they do. The choice for this office

environment is often motivated by lack of space.

Open plan offices: this office design has a shared room, in which workstations are often freely

arranged in groups. For noise reduction and privacy issues, screens can be used. There are no

individual windows in the open plan office. Amenities are sometimes at the individual workstation.

Employees mainly work individually, work is routine-based and levels of interaction are low. The

choice for this office environment is motivated by the desire for being flexible to change. It enables


the implementation of changes without any need for reconstruction. There are three kinds of open

plan offices: small open plan, medium-sized open plan, and large open plan.

o Small open plan: a room is shared by 4-9 persons.

o Medium-sized open plan: a room is shared by 10-24 persons.

o Large open plan: a room is shared by more than 24 persons.

Flex office: flex office is the most flexible office type in which both employees and furniture are

flexible. There is often an open plan office (although this is not a strict requirement), and there are

‘backup spaces’ for specific tasks (e.g. concentrated work, private phone calls, and meetings). Because

of absenteeism (e.g. expected illness, work outside the office), this office is dimensioned for less than

70% of the workforce to be present at the same time. By means of information technology, people can

freely book workstations, both inside and outside the office. There are shared amenities in common

spaces.

Combi office: in this type of workplace, employees spend more than 20% of their time “at

workstations other than their ‘own’“ (Danielsson & Bodin, 2008). Individual workstations could be

located both in an individual room or in an open plan office: there is ‘no strict spatial definition’. Again,

there are backup spaces. The choice for this office environment is motivated by teamwork and sharing

of common amenities. Movement of teams in the office finds place on an as-needed basis. Work

facilities are shared.

3.4.3. Media Availability

Before a certain type of media can be used, the organization should have adopted it. Media availability is the

degree in which people are provided with media, which could be regarded as a prerequisite for Media Use. The

media categories on which this thesis focuses are based on Dennis et al. (2008) and will be discussed later (see

section 4.2.1.4).

3.5. Personality Traits

The personality traits block resembles the Big Five model. These are the Five Factors that map personality

(traits), which were discussed in the literature review (2.1.2.2) (John & Srivastava, 1999):

1. Extraversion

2. Agreeableness

3. Conscientiousness

4. Neuroticism

5. Openness

3.6. Control Variables

Finally, some control variables were added to the conceptual model, namely:

1. Gender

2. Age


3. Position

4. Time/location dependency

Gender and age are two general human characteristics. Knowing people’s position within the organisation is

helpful because it is related to their decision-power regarding the use of certain work practices.

Time and location dependency are relevant because they tell us to what extent certain work practices are

allowed by the type of work.

3.7. Propositions

Based on the conceptual model, a number of propositions were formulated. These are presented in this section.

3.7.1 Proposition 1: New Work Practices – Work Performance

In chapter 2, a review of the literature on Job Design was given. Job Design theories suppose that the way in

which work is organized, impacts the behavior and performance outcomes of employees. In line with these

theories, it is reasonable that NWoW Work Practices have an impact on Work Performance of employees.

The New Ways of Working concept was developed to meet (younger) employees’ (knowledge workers)

expectations for collaboration tools and methods that enable them to get their work done (Van Heck, 2010). If

it is true that NWoW Work Practices better fit the needs of employees than traditional practices, a positive

impact of these practices on Work Performance could be expected:

P1: NWoW Work Practices have a positive impact on Work Performance.

3.7.2. Proposition 2: Work Arrangements – Work Practices

In section 3.4, the assumption was discussed that there is a relationship between Work Arrangements and the

practices that are performed: before employees can apply NWoW Work Practices, these practices should be

facilitated to them through Work Arrangements. To verify this assumption, the following proposition was

formulated:

P2: Work Arrangements impact NWoW Work Practices.

3.7.3. Proposition 3: Personality Traits – Work Practices

Personality determines people’s preferences (John et al., 2008). The NWoW concept differs from the more

traditional ways of organizing work. Workers have much more freedom in deciding when they work, where

they work, and how they work (e.g. concerning communication means).

It could be that certain types of personalities are more likely to adopt and use (certain) NWoW practices than

others (Lamond, 2000): they are more likely to work for an organization that provides these practices and use

the opportunities offered by their organization more intensively than others: Therefore:

P3: Specific Personality Traits impact Work Practices.


3.7.4. Proposition 4: Personality Traits – Work Practices/Work Performance

The previous proposition states that the preference for and use of certain Work Practices (adoption) is affected

by Personality Traits. However, there could be not only an impact of personality on the use of NWoW practices,

but also on the effect of these practices on Work Performance (e.g. Barrick & Mount, 1991).

A conflict between Personality Traits and (one or more) NWoW Work Practices could have a different impact

on (one or more) Work Outcomes than a match between these two. This results in the following proposition:

P4: Specific Personality Traits impact the relationship between Work Practices and Work Performance.

3.7.5. Proposition 5: Personality Traits (Work Atmosphere) –Work Practices/Work

Performance

When it is true that Personality Traits impact the relationship between Work Practices and Work Performance,

it could be valuable to know whether this relationship goes via Work Atmosphere or not. This provides a

deeper understanding of the relationship.

It could be that having a certain Work Atmosphere benefits the degree in which people with certain Personality

Traits benefit (in terms of Work Performance) from Work Practices, because the Atmosphere enables them to

apply the practices. This leads to the following proposition:

P5: Specific Personality Traits impact via Work Atmosphere the relationship between Work Practices and Work

Performance.

3.7.6 Summary of Propositions

In short, these are the propositions that were formulated:



P3: Specific Personality Traits impact Work Practices.

P4: Specific Personality Traits impact the relationship between Work Practices and Work Performance.

P5: Specific Personality Traits impact via Work Atmosphere the relationship between Work Practices and Work

Performance.

Because the amount of knowledge on the relationship between personality and the New Ways of Working

concept is limited, the propositions are formulated in a quite open way. This aligns with the purpose of this

study, namely: contributing to the development of new theory on the topic of NWoW (exploratory research).


4. Methodology and Measurement Instrument

This chapter describes how the data for this thesis was collected. Based on the conceptual model that was

presented in the previous chapter, a measurement instrument was developed. An explanation is given on the

composition of this instrument.

4.1. Methodology

4.1.1. Research Design

According to Sekeran (2003), a questionnaire is an effective data collection mechanism. It is defined as “a pre-

formulated written set of questions to which respondents record their answers, usually within rather closely

defined alternatives” (Sekeran, 2003: p.236).

Within this context, a major advantage of a questionnaire is that it enables elaboration on previous work by

Erasmus@Work (the New Worlds of Work framework). Also for determining people’s personality traits,

questionnaires have proven to be very useful.

4.1.2. Level of Analysis

The level of analysis in this thesis is the individual worker. More specific, the focus is on individual alumni of the

Dutch ‘Part-Time Opleiding Bedrijfskunde’ (Rotterdam School of Management, Erasmus University).

The group of alumni is interesting for several reasons: in terms of sectors, organizations and positions, there is

quite some variation. At the same time, most of the alumni could be regarded as knowledge workers, the type

of worker for whom the New Ways of Working concept was particularly developed.

4.1.3. Context and Data Collection

As just stated, the study took place within the context of Erasmus@Work, an interdisciplinary research

program that focuses on high performance work in collaboration with several innovative firms.

The data was collected as follows: first of all, the questionnaire (presented in the remainder of this chapter)

was made up in GlobalPark, an online survey tool. Subsequently, names and email addresses of 809 alumni

were entered into the system; this data was derived from the Alumni Guide 2011.

There were also some names in the guide without contact details. Therefore, these persons had to be skipped.

When people had more than one email address, the private ones were selected. This is because private email

addresses are not subject to job changes. From the first shift, a total of 91 emails bounced. In that case, the

corporate email addresses were used (if available). From the 42 emails that were sent in the second shift, 8

emails bounced again.

Being personal was very important in this case, in order to acquire goodwill. All alumni got a personalized email

in Dutch (appendix 4a). The subject of the email was: ‘request from a fellow’. Each message contained a unique

link that referred to the questionnaire. Respondents were able to interrupt the questionnaire and continue at a


later moment. Confidentiality of the answers was promised. Respondents could indicate whether or not they

would like to receive a summary of the findings afterwards.

The survey was available from July 23 till August 9, 2012. After one workweek, a reminder was sent to people

who did not start / complete the survey yet (appendix 4b). At the end, a 218 respondent had completed the

questionnaire.

4.2. Measurement Instrument

Now a description will be given of how the survey instrument was developed. There are two major sources for

the selected questions: the New Worlds of Work framework, developed by Erasmus@Work and the Big Five

Inventory (John et al., 2008). The advantage of using these sources is that these questions were validated

previously. Also much attention is given to the constructs that were not derived from these two sources.

The final version of the survey instrument can be found in appendix 3a (Dutch). An English version is available

in appendix 3b.

As in chapter 3, the concepts will be discussed in the following order:

1. Work Practices

2. Work Atmosphere

3. Work Performance

4. Work Arrangements

5. Personality Traits

6. Control Variables

4.2.1. Work Practices

4.2.1.1. Reflexivity

Brahm & Schippers (2010) developed constructs to measure ‘reflection on choice of location’ and ‘reflection on

media usage’. These two constructs are included in the questionnaire. In terms of formulation, these constructs

are almost identical.

A construct that could be used to measure ‘reflection on working hours and schedule’ was not available yet.

The New Worlds of Work framework had a construct called Time Shifting, but this construct presupposes that

people are working from their home location. However, the NWoW concept is about people’s freedom to work

at any location.

Therefore, a new construct was developed, analogous to the two existing ones. First of all, the following

observations were made:

- ‘Reflection on choice of location’ is about the tuning of work location to certain tasks.

- ‘Reflection on media usage’ is about the tuning of a certain medium to a specific message.


- The new construct should be about the tuning of working hours to the personal situation (or the

situation of the household/family).

In line with these observations, the following items were formulated for ‘reflection on working hours and

schedule’:

1. I carefully consider which hours are best suited for work, given my personal situation or the situation

of the members of my household/family

2. When I notice that working hours don’t suit my personal situation or the situation of the members of

my household/family, I will adjust my time schedule

3. I try to match my working hours with my personal situation or with the situation of the members of

my household/family

4.2.1.2. Flexibility

Flex-place

To measure the place aspect of flexible work, a question developed by Erasmus@Work has been selected:

‘Indicate in percentages how your working time is divided across different locations’. There are five options: (1)

at the office, (2) at external office or meeting location, (3) at client location, (4) on the road, and (5) at home.

Respondents are asked to divide a total of 100% among these locations.

Flex-time

The descriptive part of the Erasmus@Work framework contained the following questions on employment:

1) Could you, please, indicate for how many hours you are currently employed?

This concerns the contractually agreed number of hours, excluding overtime.

__ hours per week.

2) How many hours per week do you spend on your work on average?

This concerns the actual total number of hours, including overtime, business travel (not commuter travel),

education, meetings, etc.

__ hours per week.

To these questions, a number of questions were added; some of them intend to measure flex-time:

3) How many hours do you work in a typical week outside regular working hours* (e.g. not from 9 to 5)? __

hour(s)

*also mention the hour(s) you worked on day(s) you are not contracted, including the weekend.

4) How many of these hours are overwork (non-contractually agreed hours)? __ hour(s)

5) How many hours do you take off during regular working hours for private matters? __ hour(s)

The focus is mainly on two aspects of schedule flexibility:

- The number of hours worked outside ‘working time’ (Q3).

- The number of hours spent on personal issues during ‘work time’ (Q5).


Both answers should give an indication of the degree in which people deviate from ‘standard’ working hours.

4.2.1.3. Task Workplace Fit (TWPF)

As no measure was available for this concept, based on Gensler (2008) a new construct was developed.

This resulted in the following items:

1. The availability of places for […] matches my desire

2. I can find a place for […] at any time I need it

3. My needs for places for […] are fully met within the current situation

After contacting the authors of Gensler (2008), they provided the questions they used themselves for their

research. From their questionnaire, the following descriptions of the work modes were derived, that replace

the […]:

1. Socialize: social interaction

2. Learn: training / learning new skills

3. Focus: focused individual work (requiring concentration)

4. Collaborate: working with another person or group

So, in total 12 items are used to measure task / work place fit.

4.2.1.4. Media Use

Dennis et al. (2008) compared the media below on their synchronicity. The table below presents their findings:

Medium Synchronicity level

Face-to-face High

Video Conference High

Telephone Conference Medium

Synchronous Instant Messaging Medium

Synchronous Electronic Conferencing Low-Medium

Asynchronous Electronic Conferencing Low

Asynchronous Electronic Mail Low

Voice Mail Low

Fax Low

Documents Low

Table 4.1. – Media synchronicity (adapted from Dennis et al. (2008))

However, these categories seem to be much too complex to use within a survey question. It is for example not

very clear at first sight (and without definitions) what the difference is between Synchronous Electronic

Conferencing and Asynchronous Electronic Conferencing.


The questions on ‘medium of contact colleagues’ and ‘medium of contact manager’ from the Erasmus@Work

framework were combined into one question in combination with an abridged and simplified list of these

media categories. This resulted in the following question:

In which way do you primarily contact your colleagues and manager(s)?

Please, divide the total contact with your colleagues and manager(s) across the following means of contact.

Please note you can only enter whole numbers in percentages: the total must equal 100%.

Face-to-face

Video Conference

Telephone / Telephone Conference

Chat / Instant Messaging

Electronic Mail

Voice Mail

Fax

Documents

Other

4.2.2. Work Atmosphere

4.2.2.1. Empowerment

In paragraph 3.2.1, four different cognitions of empowerment were described: Meaning, Competence, Self-

determination, and Impact. The corresponding instrument, developed by Spreitzer (1995), was selected to

measure these cognitions. For each cognition, Spreitzer developed a construct with three items on a 5-point

Likert scale.

Some of these statements were somewhat rewritten by the Erasmus@Work team. Statements are formulated

like: ‘I am self-assured about my capabilities to perform my work activities’ (Competence).

4.2.2.2. Control

Also for the other Work Atmosphere concept (Control), items from the Eramus@Work framework were

selected. This concerns the constructs on Outcome control, Behavioural control, Social control, and Mutual

control. The questions on Behavioural control originate to Snell (1992), while Social control is measured on an

adapted version of a construct from Langfred (2004).

The items are formulated like: ‘In my work, I am judged on the way in which I do my work, not on the outcome

of my work’ (Behavioural control).

4.2.3. Work Performance

4.2.3.1. Employee Satisfaction

The employee satisfaction construct in the Erasmus@Work framework was developed by Jun et al. (2006) and

is measured by four items on a 5-point Likert scale (ranging from ‘strongly disagree’ to ‘strongly agree’). An


example of these statements is: ‘If a friend is looking for a job, I would recommend this organization to him or

her’.

4.2.3.2. Work Life Balance

The work life balance-construct also comes from the Erasmus@Work framework and is a shortened version of

a measurement developed by Hill et al. (2001). It consists out of four items, which are measured on a 5-point

Likert scale. These items are formulated like: ‘when I am on holiday, I can disassociate myself from my work

and enjoy myself’.

4.2.3.3. Productivity

The measurement developed by Staples et al. (1999) forms the basis of this construct, which was further

developed by Erasmus@Work based on Ramirez and Nembhard (2004). Earlier research by Erasmus@Work

revealed that the first 5 items of the productivity construct were sufficient to measure the belonging concept.

Therefore, a shortened version has been selected. An example of the items is: ‘within my working group, I

believe that my own performance is among the best 25%’.

4.2.4. Work Arrangements

There are two ways to measure the Personality model (and the Culture model):

The model can be tested among people that all work for the same organization. In case of the Culture

model, the focus is on one single multinational organization which has divisions in several countries.

The model can be tested among people working for many different organizations (which is the case in

the subsequent chapters).

When the first option is chosen, it might be an option to leave the questions on Work Arrangements outside

the questionnaire and to use a Context Sheet (see appendix 3c). This is because work practices are facilitated

within an organization or are not, and therefore not much variation is expected at the individual level. From

each participation division (or department) only one person (manager) has to answer the questions of the

Context sheet.

For the second option, questions were newly developed. These will be presented now.

4.2.4.1. People (Policies/Agreements)

The following two questions were formulated to measure the degree of freedom people experience in

determining their own working hours and work location(s):

1) Please rate the amount of freedom management gives you in determining your own working hours - on a

scale from 1 (no freedom) to 10 (full freedom)

It is not necessary that you use this freedom. Please enter a whole number.

2) Please rate the amount of freedom management gives you in determining your own work location(s) - on a

scale from 1 (no freedom) to 10 (full freedom)



4.2.4.2. Place (Workplace Design)

Based on the article by Danielsson and Bodin (2008), which was discussed in section 3.4.2, the following

questions were added to the questionnaire:

1) Do you have your own work place / desk in the office of the company?

Yes, I have my own work place / desk

No, work places / desks are flexible

2) With how many other persons do you share a room within the office of the company?

I have a private room

With 1-2 other persons



With more than 23 other persons

3) Does the office have 'backup spaces' for specific tasks, such as concentrated work, private phone calls, and

meetings?

Yes

No

4.2.4.3. Technology (Media Availability)

In section 4.2.1.4, a question was formulated to measure in which ways people communicate with their

colleagues and manager. A condition for using media in the business context is that these media are provided

to people by their company. This question is added to ask whether this condition is met or not:

1) Which of the following facilities for telework (i.e. working at another location than the office of the

company) are provided to you by the company?

Laptop

Smart phone

Mobile internet

Access via internet to business applications / data

None of these facilities

4.2.4.4. General Question

Finally, a general question was added to the list of questions:

1) Overall, how do you rate the degree in which the company facilitates you for telework - on a scale from 1

(not at all) to 10 (in full)?


4.2.5. Personality Traits

It was already stated in chapter 2 that the choice for a certain measurement tool should be determined by the

type of research for which it is used.


Given the dominance of the Big Five for personality research, which is “the most established and well-validated

model of personality” the MBTI will be left out of consideration as it is based on previous theories (Denissen et

al., 2007: p.152).

The data for this thesis will be collected by means of a survey. Because there is already a large amount of

questions on New Ways of Working aspects, a brief measure of the personality dimensions is preferred, that is

reliable and undisputed at the same time. Several authors advice the use of BFI when time and space are

limited and there is no need to focus on specific facets of personality (Denissen et al., 2007: p.152, 155).

An advantage of measures such as the NEO-PI-R, NEO-FFI en 16PF (or freely available equivalents from IPIP) is

that they are hierarchical, but these inventories take relatively much time to complete, contrary to the BFI.

Given the exploratory character of this study, facets are not of utmost importance here. Moreover, to some

degree the BFI is hierarchical as well, as it could also be used to measure facets – which was explained above.

There is even a shorter version of the BFI available that only has 10 items which could be completed in only one

minute or less. Reliability and validity are largely remained compared to the BFI-44 (original), but there are

substantial losses as well and therefore the BFI-10 is recommended to use only in settings when there is no

alternative (e.g. telephone surveys) (Rammelstedt & John, 2007; Gosling et al., 2003). This is not the case here.

So, in short: the BFI was selected because it is a brief, complete and original measure of the Big Five.

Another important point was that a validated Dutch translation of the BFI was already there. Denissen et al.

(2007), who translated the BFI in Dutch, emphasised that translated items should be equivalent in terms of

meaning to the English original. Testing the Dutch BFI made clear that there was a congruence coefficient

between these two of 0.92; this implies that the overall factor structures are quite similar to the English version

(Denissen et al., 2007: p.153).

All five factors are measured by the BFI: Extraversion (8 items), Agreeableness (9 items), Conscientiousness (9

items), Neuroticism (8 items), and Openness (10 items).

4.2.6. Other questions

4.2.6.1. Control variables

Some additional questions were needed to measure the control variables: age, gender, position and

time/location dependency.

The questions on age and gender were derived from the Erasmus@Work framework. Erasmus@Work also

developed questions on time and location dependency, which are used here as well.

To question people’s (power) position within the organization, the following question was added:

Which one of the following best describes your position within the company?

- Employee (no management function)

- Top Manager


- Middle Manager

- Operational Manager

- Independent / Hired

4.2.7. General Questions

Furthermore, some questions were added about the home situation, education level, industry (based on the

classification of the Dutch Centraal Bureau voor de Statistiek), and department.

Last but not least, a general question was added, which is related to the overall NWoW concept: this is the first

question in appendix 3a/3b.

4.3. Validity and Reliability of Constructs

New constructs were developed to measure Task Workplace Fit. First of all, the assumption that the data on

these items fit a factor structure has been validated. This is done by means of a principal component factor

analysis. Appendix 5 shows that there is indeed a clear factor structure. Also the conditions for factor analysis

are met: the Barlett’s test of sphericity, which tests the presence of correlations among the correlations, has a

significant result (χ2 = 2083.355, p = 0.000) and the Kaiser-Meyer-Olkin measure (0.829) indicates that factor

analysis is appropriate here: KMO values that are higher than 0.8 are considered as good (Hair et al., 2006:

p.114-115).

Many variables in this thesis are measured by means of multiple items. Therefore, it is useful to assess the

degree in which these items are consistent. A diagnostic measure that is often used to observe the consistency

of entire scales is Cronbach’s alpha. In general, a Cronbach’s alpha of 0.70 is the lower limit, but in exploratory

research 0.60 is sufficient as well. Sometimes the possibility exists to improve Cronbach’s alpha by deleting one

or more items from the scale (Hair et al., 2006: p.137).

Appendix 6 gives for each construct the Cronbach’s alpha and the Corrected item-Total correlation. The

Corrected item-Total correlation is the correlation between each item and the sum score of the other items,

and indicates how well a certain item suit the other ones.

It appears that most of the Cronbach’s alphas meet the lower limit. Regarding the newly developed constructs,

especially Task / WorkPlace Fit (TWPF) Focus (0.951) and TWPF Learn (0.925) have very high Cronbach’s alphas

and also the other new constructs are well above the lower limit: TWPF Collaborate (0.894), TWPF Socialize

(0.860), and ‘Reflection on working hours and schedule’ (0.819).

Nevertheless, the alpha’s for the constructs that measure control are below 0.70. Mutual control (0.697) and

Output control (0.684) are not far from this value, but alphas for Behavioural control (0.378) and Social control

(0.365) are.

Deleting items is not a desirable option, as this results in a loss of information. Especially when the Cronbach’s

alphas were (almost) 0.70, removing one or more items was not considered here. This applies to Mutual


control (0.697), Agreeableness (0.684) and Conscientiousness (0.688), for which Cronbach’s alphas are slightly

below 0.70.

Relatively large increases could be gained by deleting the first item of Social control ‘The organization has not

influenced my attitude and behaviour’( from 0.365 to 0.467) and the third item of Behavioural control ‘My

actual working results are seldom compared with planned results’ (from 0.378 to 0.482). However, also in that

case, the alphas remain far below 0.70. Therefore, all items were kept with the side mark that Behavioural

control and Social control are not measured on consistent scales.


5. Data Analysis

This chapter describes the analyses that have been conducted, both at the univariate and at the multivariate

level. After that, the outcomes are discussed in accordance with the propositions that were formulated in

chapter 3.

5.1. Sample and Response

During the 2.5 weeks in which the survey was ‘available’, 218 persons completed the questionnaire. Given the

fact that for 752 persons the email did not bounce (it is assumed that this is the number of people who actually

received the invitation), the completion rate is 28.989%. Besides, 82 persons started working on the survey, but

did not finish it. Some of them explained by email why they ceased; the main reason was that they found the

questionnaire too long and/or too monotonous. In that case, it was explained in a reply why the number of

questions was quite large: this is due to the comprehensiveness of the New Ways of Working concept and

scientific requirements (for which sometimes virtually the same questions are asked multiple times). On

average, it took respondents 1324.2 seconds (approximately 22 minutes) to complete the survey.

Regarding gender, the majority of respondents was male (180, 82.569%); which implies that 38 females

(17.431%) filled in the questionnaire. This unequal distribution aligns more or less with the distribution of

gender among high educated business people in general and the distribution among PTO Bedrijfskunde alumni

in particular.

Also a question was added to trace the age of respondents. It appears that the average age was 44.147

(median: 43). The youngest respondent was 30 and the oldest was 64. One of the females was apparently

ashamed of her age and answered that she was 0 years old (a baby) – which was classified as a missing value.

The standard deviation of the age of respondents is 8.008.

Most of the respondents have a top management function (63; 28.899%), while also middle managers (58;

26.606%) and employees without a management function (49; 22.477%) are well represented. Besides, there

were respondents who are independent/hired (31; 14.220%) and operational managers (17; 7.798).

Respondents are from 16 different sectors. Well represented are ‘Financial institutions’ (18.807%),

‘Consultancy and research’ (14.678%), and ‘Industry’ (12.844%).

A table with details about the respondents and graphs are available in appendix 7.

5.2. Univariate Analysis

In this section, descriptions of single variables are given. A more detailed summary of the data (mean, standard

deviation, minimum, maximum) can be found in appendix 8.

5.2.1. Work Practices

Reflexivity: the reflexivity of the respondents is not very high. Reflection on media usage has the highest

average value (3.648), while reflection on choice of location has an average of 3.569 and reflection on working

hours and schedule has an average of 3.498. Reflexivity is measured on a Likert scale, ranging from 1 to 5.


Flex-time: on average, respondents work 10.115 hours per week outside regular working hours. Although they

are contracted for 37.083 hours, they actually spend 46.454 hours on their work each week (excluding

commuting time). On the other side, 1.849 regular working hours are taken for private issues. Commuting time

is about 7 hours per week.

It appeared that people did not always interpret the questions on flex-time as they were intended.

Respondents were asked to indicate for how many hours they work outside regular working hours (e.g. not

from 9 to 5). After that, people should answer how many of these hours are overwork. Some people mentioned

the total amount of hours spent on overwork in an average week. For that reason, the flex-time variable was

calculated differently than originally intended (see paragraph 4.2.1.2): the total amount of hours worked

outside regular working hours was divided by the total amount of hours actually spent on work (excluding

commuting time) in an average week. So, in this case ‘flex-time’ is the percentage of work that is performed

during non-regular working hours. There is one side-mark: the amount of hours spent on work is not equally

distributed over the five job functions. Employees work on average 43.776 hours, top managers 52.079 hours,

middle managers 45.310 hours, operational managers 44.824 hours, and independent / hired workers 42.290

hours. It could be that some respondents are forced to work outside regular working hours, because too many

hours are spent on work (the hours do not go in a regular workweek). In these cases, there is no real schedule

flexibility. On average, 20.914% of the work is performed outside regular working hours.

One respondent answered that he works 60 hours per week outside regular working hours. However, this

amount is higher than his total amount of working hours per week. This single answer has been deleted from

the dataset.

Flex-place: the average person who completed the questionnaire spends a majority of 53.033% of his/her

working hours at the office of the organization. 16.900% of work time is spent at the client location, 15.938% at

home, 8.861% at an external office or meeting location and 5.268% on the road. 46.967% of the work tasks are

accomplished outside the office.

According to the questionnaire, respondents had to divide a total of 100% over their work locations. However,

for 9 persons, the totals did not sum up to 100; for these respondents, the answers to this question were

removed.

Task Workplace Fit (TWPF): according to the respondents, finding a place for Collaborate is easiest (3.713). This

is followed by Socialize (3.688) and Focus (3.661). Learn lags behind with an average score of 3.303. The TWPF

constructs are measured on 5-point Likert scales.

On average, respondents spend 10.137% of their time on Socialize, 6.858% on Learn, 40.806% on Focus, and

35.701% on Collaborate.

Media use: most often, respondents communicate Face-to-face with their colleagues and manager (44.225%).

Electronic mail (27.730%) and Telephone (or telephone conference) (15.405%) are communication means that

are used quite often. 5% of the communication takes place via Documents, 2.235% via Chat or Instant

Messaging, 2.270% via Video conference, 1.890% via Voice mail and 0.065% via Fax. Modern communication

technologies seem to have replaced communication via fax. 1.180% of communication takes place via Other,


not further specified means. Again, not for each respondent (18 persons in total) the answers summed up to

100. Therefore, also here faulty answers were deleted from the dataset.

5.2.2. Work Atmosphere

Empowerment: respondents seem to value the work goal / purpose quite high: the average score on

Empowerment Meaning is 4.054. The scores on Self-determination (people’s belief that they have autonomy

and control over how to do their tasks) and Competence (people’s belief that they are able to perform their

tasks) are even higher: respectively 4.321 and 4.297. Empowerment Impact – people’s perception that they can

make a difference at work – has a slightly lower score (but still high): 3.928.

Control: on average, respondents score 2.802 on behavioral control, 3.375 on social control, 3.217 on mutual

control, and 3.494 on output control.

Both empowerment and control are measured on 5 point Likert-scales.

5.2.3. Work Performance

Of the three Work Performance indicators, average scores on work life balance are relatively low, but not bad:

3.753; respondents are reasonably able to distinguish between their professional and private lives. The score

for employee satisfaction (3.753) is slightly higher. The average value for productivity equals 3.950, which

implies that the respondents regard themselves as being highly effective and productive.

5.2.4. Work Arrangements

Policies/agreements

Ratings: on average, respondents rate the freedom management gives them in determining their working

hours – regardless whether they use this freedom with 7.583 (on a scale from 1 to 10). This score is quite high.

The freedom for choosing work locations is lower: 6.823. Overall, respondents rate the degree in which they

are facilitated for telework with 7.553.

A number of answers have been deleted, because they were not in the range 1-10. For Work Time Freedom

Rate: 2, for the Work Location Freedom Rate: 3, and for the Telework Facilitation Rate: 1.

Workplace design

Room Sharing: some variables that belong to Work Arrangements are nominal. Most of the respondents (74)

have a private room in the office of the organization (33.945%). 41 respondents (18.807%) are sharing a room

with 1-2 other persons. There are 37 respondents who share a room with 3-8 others and also 37 persons who

share a room 9-23 persons (16.972%). 13.303% or 29 respondents are sharing a room in the office with more

than 23 others.

Own Work Place: a majority of 146 respondents (66.972%) have their own work place or desk in the office of

the company. The other 72 respondents (33.028%) report that workplaces and desks are flexible.

Backup Spaces: 166 respondents (76.147%) are working in an office that has Backup Spaces for specific tasks

such as concentrated work, private phone calls, and meetings. The other 52 respondents (23.853%) do not


have these facilities. Of the 144 respondents that are sharing a room with 1 or more others, 23.611% do not

have Backup Spaces.

Media availability

Media Facilitation: in total, 135 respondents (61.927%) report that videoconferencing is facilitated by the

organization; for the other 83 (38.073%) videoconferencing is not facilitated.

Regarding the other facilities for communication, 179 (82.110%) respondents are equipped by the organization

with a laptop, 163 (74.771%) with a smartphone, 150 (68.807%) with mobile internet, and 199 (91.284%) with

online access to business applications.

5.2.5. Personality Traits

The average respondent scores (5-point Likert scale) are quite high on Extraversion (3.838), Conscientiousness

(3.779), Openness (3.746), and Agreeableness (3.657) and quite low on the Neuroticism dimension (2.179).

The differences among the five different positions (ranging from employee to independent/hired) are not very

large. However, top-managers score higher on all five dimensions except neuroticism, compared to employees.

A graph in which positions and personality traits are compared against each other, can be found in appendix

7.5.

5.2.6. Control Variables

Outcomes on gender, age, and position were already described in section 5.1. Besides, there are two other

control variables: Time Dependency and Location Dependency. Both types of constraints have relatively low

averages: the mean of Time Dependency is 2.258 and the mean of Location Dependency is 2.350, which implies

that the constraints for flexible work (in terms of time and place) are limited.

5.3. Method of Analysis

Most of the relationships in this thesis are tested by means of linear multiple regression analysis. In this section,

an explanation of this method is given and a number of issues regarding its use are discussed.

5.3.1. Linear Multiple Regression Analysis

Multiple regression analysis is a technique that could be used for analyzing the relationship between one

dependent variable and multiple independent variables. Both the dependent variable and independent

variables should be metric, although -after transformation- non-metric variables could be included as well (e.g.

by means of dummy variables). Multiple regression analysis distinguishes itself from simple regression analysis

by the number of independent variables involved (simple: 1, multiple: >1) (Hair et al., 2006: p.176-177).

There are two non-mutually exclusive applications for which multiple regression is used: prediction and

explanation. Prediction is about how well the regression variate predicts the dependent variable; explanation

focuses on the magnitude, sign and statistical relevance of each independent variables (Hair et al., 2006:

p.190).


Three types of multiple regression could be distinguished. Standard multiple regression can be used to evaluate

relationships between a set of independent variables and a dependent variable. All variables are entered at

once. Hierarchical regression enables researchers to enter one variable or a block of variables at a time. This is

useful to get more insights in what part of the variance is caused by which variables. Stepwise regression

(forward, stepwise, backward, remove) is a method by which the researcher defines a set of variables from

which variables are selectively added or deleted. This goes on until an overall criterion measure has been

achieved. Although this method is very efficient in selecting the subset of variables that maximizes the

predictive accuracy, its use is not recommended because of its high dependency on data and the relatively high

risk that falsely significant variables are selected (Hair et al., 2006: p.209; Kroonenberg & Linting, 2011: p.27).

5.3.2. Issues

5.3.1.1. Linearity

The first assumption of linear regression analysis is that the variables have a linear relationship. To check

whether this assumption has been met, one can plot the standardized residuals (ZRESID) against the

standardized predicted values (ZPRED). If the graph shows a pattern (such as a curved shape), this could

indicate that the linearity assumption is not met (Field, 2009: p.247, 248).

Besides, residual plots are a good indicator for non-linearity: when a consistent curvilinear pattern is visible, the

variables do not have a linear relation (Kroonenberg & Linting, 2011: p.30; Hair et al., 2006: p.205, 206).

5.3.1.2. Homoscedasticity

Regression analysis also assumes that “dependent variables exhibit equal levels of variance across the range of

predictor variables”. (Hair et al., 2006: p.83). In a regression analysis, the variance of a dependent variable is

explained; it is important that this variance is not concentrated to a limited range of independent values.

Alternatively, the relationship is heteroscedastic.

The graph of ZRESID plotted against ZPRED could also be used to check this assumption. Preferred is a plot in

which the dots are randomly dispersed around zero. If a graph funnels out, it could be that there is

homoscedasticity in the data (Hair et al., 2006: p.83; De Vocht, 2009: p.209; Field, 2009: p.247, 248).

5.3.1.3. Normality

Multiple regression also builds on the assumption that residuals, which are the difference between predicted

values and observed values, have a normal distribution with a mean of zero. According to some scholars, this

does not imply that the variables themselves should be normally distributed. However, when the response

(dependent) variable has a normal distribution, the residuals will often also be normally distributed. An

advantage of the F-test is that it is robust; when samples are not small (>50), the prediction will be reasonable

accurate, even when the response variable does not have a quite normal distribution.

A normal distribution of the predictor (independent) variables is no strict requirement, but a strange

distribution might affect the distribution of the residuals (Kroonenberg & Linting, 2011: p.31).


To check visually whether the normality assumption is met or not, there are two options: one can look at a

histogram of the standardized residuals and / or at a normal probability plot (P-P plot) (Hair et al., 2006: p.208;

De Vocht, 2009: p.209). Regarding the P-P plot, a straight line indicates that there is a normal distribution.

5.3.1.4. Multicollinearity

When there is a strong interdependence between explanatory variables, a multicollinearity problem could

occur. This happens when it is not possible anymore to distinguish the separate contributions of the dependent

variables from the independent variable.

There are multiple ways to detect the existence of multicollinearity. First of all, one can look at the standard

errors of the regression coefficients. Also a correlation matrix might indicate the existence of multicollinearity,

but this method is not suitable in case of more than two explanatory variables. Fortunately, there are some

other methods to deal with this deficiency: the partial correlation and the part correlation give a good

indication of the possible existence of a multicollinearity problem. In this thesis the focus is on tolerances and

VIF-values: tolerances lower than 0.2 or VIF-values higher than 5 could indicate that there might be a

multicollinearity problem, although even then this is not necessarily the case (Van Dalen & De Leede, 2009:

p.526-530).

5.3.1.5. Autocorrelation

A fifth assumption is that ‘autocorrelation’ or ‘serial correlation’ does not occur. This might especially be a risk

when there are time series data (longitudinal study): in that case, the residue for a certain period t might be

negatively or positively be correlated with a residue for an earlier period. Autocorrelation can be detected by

means of the Durbin-Watson test (Van Dalen & De Leede, 2009: p.556-557). The value should be around 2 (no

autocorrelation).

5.3.1.6. Outliers

Outliers might impact the regression analysis. Given the fact that many variables were measured by means of

constructs (with 5-point Likert scales), the existence of outliers is limited.

In the univariate analysis, it was explained why some answers were excluded from the analysis. This was done

when it was obvious that the respondent did not answer the questions in an appropriate way. In the

multivariate analysis, the existence of (possible) outliers was limited and therefore no cases were excluded.

5.3.1.7. Checking the Assumptions

For all regression analyses, residual histograms, normal P-P Plots and ZRESID/ZPRED plots were ‘inspected’ and

in some cases also the partial plots. In appendix 11 some examples of these graphs are available.

Once in a while, small deviations from the normal distribution were observed (especially in case of TWPF), but

these deviations were acceptable.

Regarding the Durbin-Watson test, no large deviations from the value of 2 were detected. This finding aligns

the expectation: the data used in this thesis was measured at only one point in time.


5.4. Multivariate Analysis

In this section, a number of sub-models that are based on the main conceptual model (discussed in Chapter 3)

are presented and validated.

First of all, there is a need for defining the variables of interest: in the multivariate analysis, the focus is mainly

on the people and place dimensions of the conceptual model. This implies that the technology dimension is not

taken into consideration. There are two reasons for this choice: first of all, for the quality of this thesis, it is

important to limit the scope. Besides, the technology aspects of the NWoW concept have already been studied

to some extent within the context of Erasmus@Work (e.g. Baas, 2010). Also the fifth propositions has been left

out of consideration; a separate thesis could be devoted to this proposition.

Initially, there were five different variables for measuring flexibility place: ‘at the office’, ‘at external office or

meeting location’, ‘at client location’, ‘on the road’, and ‘at home’. The number of variables is reduced by

merging the five variables except ‘at the office’ to one ‘flex-place’ variable. This is in line with the definition of

the NWoW: people could work anywhere and are no longer bound to the office. Nowadays, flex-place is not

only about working at home, but about working at every desired location.

In short, the focus here is on the following work practices: ‘Reflection on working hours and schedule’,

‘Reflection on choice of location’, ‘Reflection on media use’, Flex-time, Flex-place, Task work place Fit (TWPF)

Socialize, TWPF Learn, TWPF Focus, and TWPF Collaborate.

These work practices could be subdivided into three broader categories: Reflexivity, Flexibility, and Task Work

Place Fit.

Also a number of control variables are included in the analysis: gender, age, position (and time and location

dependency). Position was a nominal variable, but has been recoded into five dummies to include this variable

in the regression. For statistical reasons, one of the dummies is left out of the analyses: ‘employee (without

management function)’. This is our reference group. Time and location dependency are related to the analysis

of sub-model 3.

In case of deviations from the statistical regression model, this is indicated by the term ‘variant b’. Output for

these regression models is also available in the appendices.

After the analysis of the latest sub-model, the outcomes of this research will be discussed.

Preliminary analysis of data includes the calculation of correlations. A correlation table can be found in

appendix 9.


5.4.1. Sub-model 1: Personality – Work Practices – Work Performance

The first sub-model that has been analyzed can be depicted as follows:

This sub-model was validated by means of hierarchical multiple regression analyses. The variables are entered

into the regression model in two stages / blocks:

First stage: control variables (gender, age, and position) (regression model 1)

Second stage: work practice variables (regression model 2)

Relationship between Work Practices and Work Performance (Relation 1)

First of all, the focus is on the relationship between work practices and work performance. In the sub-model

that was presented above, this is arrow number 1:

Relation 1a: Reflexivity – Work Performance

Reflexivity was defined earlier as the extent to which workers reflect on their functioning and modify it

accordingly (Schippers et al., 2007). The conceptual model suggest that, regarding the NWoW concept, there

are three important things people might reflect on: schedule, location and media.

It could be that reflexivity results in a higher work performance: more reflection leads to better choices

regarding the optimal hours, places, and communication means, which benefits the outcomes of work.

More optimal decisions regarding work conditions (time, place, media) could increase productivity. Besides,

reflection on schedule and location could help workers to find a better balance between work and private life.

The statistical regression model is as follows:

Work performance = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 +

β3.5Position_d5) + β4Reflection on working hours and schedule + β5Reflection on choice of location + β6Reflection

on media use + ε

For each of the three performance indicators (dependent variables), a regression analysis has been conducted.

The output of these regression analyses can be found in appendix 13.1.

The regression model with only the control variables (regression model 1) is in none of the cases significant

(Employee satisfaction: F = 1.924, p = 0.078, Work life balance: F = 1.093, p = 0.368, Productivity: F = 0.795, p =

0.575).

Work Practices 1a) Reflexivity 1b) Flexibility

1c) TWPF

Work Performance - Empl. satisfaction - Work life balance

- Productivity

Work Practices Work Performance 1 2

3

Personality


It appears that there is no type of reflexivity that has a significant influence on employee satisfaction (F = 1.916,

p = 0.051). Regarding work life balance (F = 4.194, p = 0.000; R2

= 0.154; adj. R2 = 0.117), there are two types of

reflection that have a significant impact: ‘reflection on working hours and schedule’ (β4 = 0.275, p = 0.000) and

‘reflection on media use’ (β6 = 0.223, p = 0.006). Besides, ‘reflection on media use’ also has a significant positive

influence (β6 = 0.266, p = 0.000) on productivity (F = 3.538, p = 0.000; R2

= 0.133; adj. R2 = 0.096).

To explain how these results should be interpreted, the latest finding is used as an example: an increase of one

point on the 5-point Likert scale of ‘reflection on media use’, causes an increase of 0.266 on the 5-point Likert

scale of productivity.

Relation 1b: Flexibility – Work Performance

Literature on telework suggests that there is a positive relationship between telework (flex-place and flex-time)

on productivity and work life balance (e.g. Hill et al., 2001). The more flexible workers are regarding time and

place, the more productive they become.

It could be that the flex-time element of telework enables people to find a better balance between their work

and private life. Experiencing more freedom regarding work places and work schedule makes work more

flexible and varied, which may boost employee satisfaction.

The statistical regression model is as follows (and the output is available in appendix 13.2):


β3.5Position_d5) + β4Flex-place + β5Flex-time + ε

Again, three analyses have been conducted: one for each performance indicator. The same control variables

are used as in relation 1a, which implies that the first regression models (control variables) are identical to the

ones in the analyses of the previous relation.

The regression models do not become significant after adding the second block of dependent variables (flex-

time and flex-place): employee satisfaction: F = 1.572, p = 0.135, work life balance: F = 1.526, p = 0.150,

productivity: F = 0.821, p = 0.585.

Relation 1c: Task Workplace Fit – Work Performance

In general, it could be that the relationship between Task Workplace Fit (TWPF) and work performance is as

follows: when people are better able to find a workplace that suits their activities, this benefits the quality of

their activities, which in turn has a positive influence on work performance.

Being able Focus is very important for knowledge workers. Interruptions and distractions at work lead to an

inferior concentration, while the inability to concentrate is a barrier to productivity (Gensler, 2008). This

suggests that more TWPF Focus results in a higher productivity.


Sometimes Socializing is regarded as distraction from work, but – especially in case of knowledge work – could

be essential in getting the work done. Some authors emphasize the importance of social capital for

organizations (Cross & Prusak, 2002).

Also the well-being literature recognizes the importance of social support and interpersonal relationships.

When a work environment is humane, people feel more energized and passionate at work (Cartwright &

Holmes, 2006: p.200).

It therefore could be that a broader facilitation of Socializing places results in a better work performance (in

general), and more specific in a higher productivity and more employee satisfaction.

Collaborating with others is valuable, because a group of persons is more creative than an individual. It is

helpful in finding innovative ideas and solutions. More than 70% of what people know about their job, can be

attributed to interaction with colleagues (Gensler, 2008). Knowledge is needed to get the job done, and

therefore a positive influence of TWPF Collaborate on work performance is expected.

According to Peter Drucker (1999), knowledge work requires continuous Learning and teaching. Scientists

emphasise the importance of knowledge management and intellectual capital for the performance of

organizations. It therefore could be that work performance improves when there is a better fit between

Learning tasks and workplace.



β3.5Position_d5) + β4TWPF Focus + β5TWPF Collaborate + β6TWPF Learn + β7TWPF Socialize + ε

Three of these analyses were conducted, one for each of the performance indicators. The output is available in

appendix 13.3.

Regarding employee satisfaction, the first finding is that the dummy for position 2 has a significant positive

influence (β3.2 = 0.245, p = 0.039): this means that top-managers are in general 0.245 more satisfied (on a 5-

point Likert scale) than employees without a management function.

Besides, there are three types of Task Workplace Fit that have a positive impact on employee satisfaction:

TWPF Focus (β4 = 0.101, p = 0.038), TWPF Learn (β6 = 0.112, p = 0.018), and TWPF Socialize (β7 = 0.221, p =

0.001). The R2 of this regression model is 0.261 (adj. R

2 = 0.225; F = 7.271, p = 0.000).

There is one type of Task Workplace Fit that significantly influences work life balance: TWPF Focus (β4 = 0.145, p

= 0.013). (R2 = 0.122, adj. R

2 = 0.079; F = 2.858, p = 0.002). Besides, the dummy for position 2 (top-manager) is

significant (β3.2 = -0.366, p = 0.010): top-managers score 0.366 lower on work life balance (on a 5-point Likert

scale) than employees without a management function.

Also productivity is affected by one type of Task Workplace Fit: TWPF Learn (β6 = 0.087, p = 0.020). The model

(F = 2.767, p = 0.003) has an explanatory power (R2) of 0.118 (adj. R

2 = 0.076).


Relationship between Personality Traits and Work Practices (Relation 2)

The research is continued by analyzing relation 2 of sub-model 1:

Relation 2a: Personality Traits – Reflexivity

It is reasonable that certain types of people are more likely to reflect on their functioning than others. The

Conscientiousness dimension of personality is about thinking before acting. For this reason, it could be that this

dimension positively influences the three types of reflexivity.

People who score high on the Openness dimension, prefer new experiences and are more likely to break up

routines and to be creative. Therefore, also some impact of Openness on reflexivity is expected (especially in

case of ‘reflection on media use’).


Reflexivity = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 + β3.5Position_d5) +

β4Extraversion + β5Agreeableness + β6Conscientiousness + β7Neuroticism + β8Openness + ε

For each type of reflexivity, a separate analysis has been conducted. The output can be found in appendix 13.4.

Regarding ‘reflection on working hours and schedule’, the model with only control variables is already

significant (F = 4.103, p = 0.001; R2 = 0.105, adj. R

2 = 0.079) and there is a positive influence of dummy variable

gender on this type of reflection (β1 = 0.310, p = 0.027), while the impact of age is negative (β2 = -0.021, p =

0.002). This implies that women score 0.310 point higher on ‘reflection on working hours and schedule’

(measured on the 5-point Likert scale). Besides, younger people reflect more on their working hours.

Including the personality traits into the regression model does not result in a significant change of R2 (ΔR

2 =

0.012, p = 0.740); personality traits do not significantly impact ‘reflection on working hours and schedule’.

In case of ‘reflection on choice of location’, the first regression model with only the control variables is not

significant (F = 1.454, p = 0.196). After adding the personality dimensions (ΔR2 = 0.005, p = 0.960), there is still

no significant model (F = 0.871, p = 0.570).

None of the control variables are significantly influencing ‘reflection on media use’ (F = 1.086, p = 0.372). There

is one personality trait that impacts ‘reflection on media use’: Openness (β8 = 0.246, p = 0.012). The impact of

Agreeableness (β5 = 0.206, p = 0.052) is slightly above the significance level. The explanatory power (R2) of the

second regression model (including the personality dimensions) is 0.092 (adj. R2 = 0.043), which is quite low.

Personality Traits Extraversion

Agreeableness Conscientiousness

Neuroticism Openness

Work Practices 2a) Reflexivity 2b) Flexibility

2c) TWPF


Relation 2b: Personality Traits – Flexibility

Some people prefer working flexible in terms of location and time and regard this as a good alternative to

traditional ways of working. Others prefer to work at the office during business hours. It could be that

personality is a determining factor for the degree in which flexibility practices are applied.


Flexibility = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 + β3.5Position_d5)


For both concepts of flexibility (flex-time and flex-place) a separate regression analysis was conducted (output

is available in appendix 13.5).

The model with only control variables has not a significant influence on flex-time (F = 1.632, p = 0.140). Adding

the personality dimensions (ΔR2 = 0.034, p = 0.192) does not make the model significant (F = 1.582, p = 0.106).

One of the dummies, position_d5 (independent / hired), has impact (β3.5 = 23.101, p = 0.001) on flex-place in

the model with only control variables (F = 4.557, p = 0.000; R2 = 0.120, adj. R

2 = 0.093). This implies that,

compared with employees without management function (the reference group) independent people work

23.101% more often outside the office.

When the personality dimensions are added (regression model 2: F = 2.908, p = 0.001), also ‘Openness’ is

significantly influencing flex-place (β8 = 8.984, p = 0.049). However, compared to regression model 1 (control

variables) the change of R2

is not significant (ΔR2 = 0.021, p = 0.457).

When only Openness is added to the model with control variables, the change of R2

is significant (ΔR2 = 0.019, p

= 0.036). The R2

of this model is 0.139 (adj. R2

= 0.109) (variant b; F = 4.610, p = 0.000).

Relation 2c: Personality Traits – Task Workplace Fit

The degree in which people can find places where they can perform a certain type of workplace activity is

supposed to rely largely on policies / agreements regarding telework and workplace design and therefore less

impact of personality traits is expected.


TWPF = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 + β3.5Position_d5)


The output can be found in appendix 13.6. Both regression model 1 (F = 1.661, p = 0.132) and regression model

2 (F = 1.656, p = 0.086) are not significant for TWPF Focus.

In case of TWPF Socialize, both the control regression model (F = 0.793, p = 0.577) and the extended regression

model (F = 1.204, p = 0.286) are not significant either.


For the regression on TWPF Collaborate (F = 1.822, p = 0.096), the model with only control variables is not

significant, but the second model is (F = 2.243, p = 0.014; R2 = 0.107, adj. R

2 = 0.060): Extraversion significantly

influences the extent to which people can find a place to Collaborate (β4 = 0.302, p = 0.011).

Regarding TWPF Learn, both the first (F = 0.733, p = 0.580) and second (F = 1.289, p = 0.233) regression model

lack significance.

Relationship between Personality Traits and Work Performance (Relation 3)

The analysis is continued by validating the third and last relationship of sub-model 1.

To some extent, influences of personality on work performance are expected (John et al., 2008). It could be for

example that people who are higher on the Conscientiousness dimension take their work more seriously and

therefore are more productive, compared to others.


Work Performance = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 +

β3.5Position_d5) + β4Extraversion + β5Agreeableness + β6Conscientiousness + β7Neuroticism + β8Openness + ε

Separate regression analyses were conducted for each of the performance indicators. The output is available in

appendix 13.7.

For the influence of personality traits on employee satisfaction, no significant model has been found

(regression model 1: F = 1.924, p = 0.078; regression model 2: F = 1.661, p = 0.084). However, when the focus is

only on the impact of Extraversion on employee satisfaction, the beta is significant: β4 = 0.204, p = 0.025 (F =

2.404, p = 0.022; R2 = 0.075, adj. R

2 = 0.044) (variant b).

Work life balance is negatively affected by Neuroticism (β7 = -0.301, p = 0.007). Again a significant dummy for

position 2 is found; this result has already been discussed (F = 2.114, p = 0.021; R2 = 0.102, adj. R

2 = 0.054).

Conscientiousness has a significant positive influence (β6 = 0.448, p = 0.000) on productivity (F = 5.691, p =

0.000; R2 = 0.234, adj. R

2 = 0.193).

Final remark sub-model 1

There are significant relationships between work practices and work performance, personality traits and work

practices, and personality traits and work performance.

Two direct effects of personality traits on work performance were found, but these effects are not mediated by

one of the NWoW practices.

3) Work Performance Employee satisfaction

Work life balance Productivity





A more extensive discussion about the outcomes of this sub-model is given after the validation of the latest

sub-model (number 3).

5.4.2. Sub-model 2 – Moderating Effect of Personality Traits

In the previous sub-model, it was analyzed among other things to what extent personality is decisive for the

degree to which NWoW work practices are applied / used.

The second sub-model is about the influence of personality on the effects of work practices on work

performance.

The proposition here is that due to different personality traits, people experience NWoW practices in a

different way, which results in varying effects of ‘work practices’ on ‘work performance indicators’.

First of all, a graphical representation of this sub-model is given:

Hierarchical moderated regression analyses are used to validate sub-model 2. To prevent problems of

multicollinearity, the independent variables have been centered by subtracting their mean (Kroonenberg &

Linting, 2011: p. 19).

To indicate that a certain variable is centred, a ‘C’ is added to the variable name (e.g. in the appendices). By

multiplying each of the work practices with each of the (separate) personality traits, interaction terms were

computed.

The independent variables are added to the regression analysis in three stages/blocks:

First stage: control variables (gender, age, and position) (regression model 1: identical to the control

models of sub-model 1, relation 1).

Second stage: mean centered work practice variable and mean centered personality variables

(regression model 2)

Third stage: interaction terms (regression model 3)

Work Performance Employee satisfaction

Work life balance Productivity




Work Practices Reflexivity Flexibility

TWPF


Because the impact of work practices on work performance (relation 1) and the impact of personality traits on

work performance (relation 2) has already been analyzed for sub-model 1, here the emphasis is on the added

value of the interaction terms to the regression models.

The focus is especially on the R Square Change (ΔR2) and its significance (which measures the difference

between regression model 2 and regression model 3 after adding the block of interaction terms for

personality). It is important to realize that the interpretation of the parameters changes when an interaction

term is included: they now represent the number of units change in the predicted value, when a predictor

changes one unit, given that the other predictor(s) are equal to zero (Kroonenberg & Linting, p.19). Because

centered variables are used, the main effect of one independent variable is examined against the means of the

other independent variables.

The moderating impact of personality traits is also examined for relations that were not significant in the

analysis of the first sub-model (relation 1). Especially when the main effects are not significant, outcomes have

to be interpreted cautiously.

Relation 4a: Personality – Reflexivity / Work Performance

The analysis of sub-model 2 starts by focussing on the moderating impact of personality traits on the relation

between reflexivity and work performance.



β3.5Position_d5) + β4ReflexivityC + β5ExtraversionC + β6AgreeablenessC + β7ConscientiousnessC +

β8NeuroticismC + β9OpennessC + β10ReflexivityC*ExtraversionC + β11ReflexivityC*AgreeablenessC +

β12ReflexivityC*ConscientiousnessC + β13ReflexivityC*NeuroticismC + β14ReflexivityC*OpennessC + ε

This model was validated nine times in total: for each of the performance indicators (employee satisfaction,

work life balance, and productivity) and for each type of reflexivity (‘reflection on working hours and schedule’,

‘reflection on choice of location’, and ‘reflection on media use’). The output is available in appendix 14.1.

Employee satisfaction

According to the outcomes of sub-model 1, none of the three types of reflexivity has significant influence on

employee satisfaction.

In case of ‘Reflection on working hours and schedule’ the R2 change, caused by adding the interaction terms to

the regression model, is not significant (ΔR2 = 0.009, p = 0.849).

Regarding the relationship between ‘reflection on choice of location’ and employee satisfaction, regression

model 2 is not significant (F = 1.718, p = 0.065), but regression model 3 is (F = 1.833, p = 0.026; R2 = 0.135 adj.

R2 = 0.061); however, the change in R

2 is not significant (ΔR

2 = 0.044, p = 0.079).


When only ReflocC*ExtraversionC is added in the third stage to the regression model (variant b; F = 2.045, p =

0.019; R2 = 0.116 adj. R

2 = 0.059), both the change in R

2 (ΔR

2 = 0.024, p = 0.020) and the interaction term is

significant (β10 = -0.296, p = 0.020).

The main effect of ‘Reflection on choice of location’ on employee satisfaction is not significant (β4 = 0.108, p =

0.087), but the main effect of Extraversion on employee satisfaction is (β5 = 0.208, p = 0.044).

It is notable that ‘reflection on media use’, for which no significant effect was found in the analysis of relation

1a, when isolated from the other two types of reflexivity, does have a significant influence (β4 = 0.154, p =

0.045) on employee satisfaction (regression model 2: R2 = 0.100 adj. R

2 = 0.047; F = 1.885, p = 0.038). No

interaction effect of personality traits has been found for this relationship (ΔR2 = 0.014, p = 0.686).

Work life balance

The analysis of the first sub-model revealed that ‘reflection on working hours and schedule’ and ‘reflection on

media use’ have a significant impact on work life balance. These relationships are not moderated by personality

traits: adding the block with interaction terms does not add significantly to the explanatory power of the

regression model (‘reflection on working hours and schedule’: ΔR2 = 0.005, p = 0.934; ‘reflection on media use’:

ΔR2 = 0.020, p = 0.439).

‘Reflection on choice of location’ has no impact on work life balance and the R2 change due to the interaction

terms is not significant (ΔR2 = 0.014, p = 0.667).

Productivity

A significant influence of ‘reflection on media use’ on productivity was found in sub-model 1. This relationship

is not moderated by personality traits (ΔR2 = 0.011, p = 0.638).

‘Reflection on working hours and schedule’ and ‘reflection on choice of location’ did not significantly impact

productivity. After adding the interaction terms for personality, R2 do not show a significant change in case of

‘reflection on working hours and schedule’ (ΔR2 = 0.015, p = 0.549).

Regarding ‘reflection on choice of location’, the change in the explanatory power is not significant either (ΔR2 =

0.037, p = 0.078). There is, however, one interaction term that has a significant influence: when only this

variable (ReflocC*AgreeablenessC: β11 = 0.193, p = 0.049) is added in the third regression block, the R2 change

(variant b) is slightly significant (ΔR2 = 0.014, p = 0.049) (R

2 = 0.252 adj. R

2 = 0.204; F = 5.256, p = 0.000).

The main effect of ‘reflection on choice of location’ (β4 = 0.026, p = 0.929) on productivity and the main effect

of Agreeableness (β6 = -0.011, p = 0.864) on productivity are not significant.

Relation 4b: Personality – Flexibility / Work Performance

The analysis is continued by validating the moderating effect of personality on the relationship between

flexibility and work performance.




β3.5Position_d5) + β4FlexibilityC + β5ExtraversionC + β6AgreeablenessC + β7ConscientiousnessC + β8NeuroticismC

+ β9OpennessC + β10FlexibilityC*ExtraversionC + β11FlexibilityC*AgreeablenessC +

β12FlexibilityC*ConscientiousnessC + β13FlexibilityC*NeuroticismC + β14FlexibilityC*OpennessC + ε

The model has been validated six times: for each performance indicator and for each flexibility concept (output

can be found in appendix 14.2).

The analysis of relation 1b of sub-model 1 did not reveal a significant influence of flexibility (flex-time, flex-

place) on work performance (employee satisfaction, work life balance, productivity).

Regarding employee satisfaction, regression models 1 and 2 for both flex-time and flex-place are not

significant. This does not change after adding the interaction terms (regression model 3 – flex-time: F = 1.481, p

= 0.131, ΔR2 = 0.019, p = 0.511; flex-place: F = 1.421, p = 0.130, ΔR

2 = 0.029, p = 0.294).

When only Extraversion is added to the regression model in the second stage, and only Flex-

placeC*ExtraversionC is added in the third stage, regression model 2 (F = 2.152, p = 0.033; R2 = 0.080 adj. R

2 =

0.043) and regression model 3 (F = 2.414, p = 0.013; R2 = 0.099 adj. R

2 = 0.058) do appear to be significant and a

significant interaction effect is found: β10 = -0.006 (p = 0.041) (variant b).

The main effect of Extraversion on employee satisfaction is significant (β5 = 0.224, p = 0.015); the main effect of

flex-place on employee satisfaction is not significant (β4 = -0.002, p = 0.330).

No significant change of R2 took place when the interaction terms were added to the regression model in case

of work life balance (flex-time: ΔR2 = 0.014, p = 0.686; flex-place: ΔR

2 = 0.004, p = 0.971).

It turns out that flex-time has a small, significant influence on work life balance (β4 = -0.008, p = 0.039)

(regression model 2: F = 2.316, p = 0.009), but a regression model without personality traits (variant b: only

control variables and flex-time) is not significant (F = 1.701, p = 0.110).

In the analysis of sub-model 1, no significant impact of flex-time or flex-place on productivity was found.

Regarding flex-time, the moderator analyse revealed that there are two interaction terms with a significant

beta: Flex-timeC*ConscientiousnessC (β12 = -0.015, p = 0.011) and flex-timeC*NeuroticismC (β13 = 0.011, p =

0.033) (R2 = 0.301 adj. R

2 = 0.241; F = 5.005, p = 0.000).

The main effect of Conscientiousness on productivity is significant (β7 = 0.402, p = 0.000); the main effects of

Neuroticism (β8 = -0.119, p = 0.083) and flex-time on productivity (β4 = 0.003, p = 0.239) are not significant.

Regarding flex-place, adding the interaction terms to the regression model does not result in a significant

change of the explanatory power (ΔR2 = 0.016, p = 0.536).


Relation 4c: Personality – Task Workplace Fit / Work Performance

The last relation of sub-model 2 for which moderator analyses are conducted concerns the effect of personality

on the relationship between Task Workplace Fit and Work Performance.



β3.5Position_d5) + β4Task Workplace FitC + β5ExtraversionC + β6AgreeablenessC + β7ConscientiousnessC +

β8NeuroticismC + β9OpennessC + β10Task Workplace FitC*ExtraversionC + β11Task Workplace

FitC*AgreeablenessC + β12Task Workplace FitC*ConscientiousnessC + β13Task Workplace FitC*NeuroticismC +

β14Task Workplace FitC*OpennessC + ε

This model has been validated twelve times in total (three performance indicators times four types of TWPF) .

Output is available in appendix 14.3.

Employee satisfaction

The analysis of relation 1c revealed that there are three types of Task Workplace Fit that have a significant

impact on employee satisfaction: TWPF Focus, TWPF Learn, and TWPF Socialize.

The influence of TWPF Socialize on employee satisfaction is not moderated by personality traits (ΔR2 = 0.013, p

= 0.662).

FocusC*ExtraversionC (β10 = 0.213, p = 0.021) and FocusC*AgreeablenessC (β11 = -0.280, p = 0.011) have a

significant impact on the relationship between TWPF Focus and employee satisfaction (R2 = 0.225 adj. R

2 =

0.159; F = 3.401, p = 0.000).

The main effect of TWPF Focus on employee satisfaction is significant (β4 = 0.260, p = 0.000); the main effects

of Extraversion on employee satisfaction (β5 = 0.069, p = 0.488) and Agreeableness on employee satisfaction

(β6 = 0.175, p = 0.115) are not significant.

The interaction term LearnC*NeuroticismC (β13 = 0.311, p = 0.004) has a significant impact on the relationship

between TWPF Learn and employee satisfaction (R2 = 0.210 adj. R

2 = 0.142; F = 3.109, p = 0.000).

The main effect of TWPF Learn on employee satisfaction is significant (β4 = 0.237, p = 0.000); the main effect of

Neuroticism on employee satisfaction is not significant (β8 = -0.075, p = 0.451).

According to the analysis of relation 1c (sub-model 1), there was no significant impact of TWPF Collaborate on

employee satisfaction. However, in this case TWPF Collaborate is isolated from the other TWPF variables and

now it does have a significant influence on employee satisfaction (β4 = 0.260, p = 0.000) (R2 = 0.157 adj. R

2 =

0.107; F = 3.165, p = 0.000).

Adding the interaction terms for examining the moderating effect of personality traits does not result in a

significant change of R2

(ΔR2 = 0.042, p = 0.068). When only the interaction term for Extraversion is added in the


third block to the regression model (variant b), the change in R2

is significant (ΔR2 = 0.039, p = 0.002) and also

the beta for CollaborateC*ExtraversionC (β10 = 0.327, p = 0.002) (R2 = 0.196 adj. R

2 = 0.144; F = 3.803, p = 0.000)

is significant.

The main effect of TWPF Collaborate on employee satisfaction is significant (β4 = 0.265, p = 0.000); the main

effect of Extraversion on employee satisfaction is not significant (β5 = 0.104, p = 0.689).

Work life balance

In the analysis of relation 1c (sub-model 1), it was found that only TWPF Focus has a significant influence on

work life balance.

However, when the Task Workplace Fit variables are isolated from one another (regression model 2), the other

three types also have a significant impact on work life balance: TWPF Socialize (β4 = 0.181, p = 0.008) (F = 2.588,

p = 0.003; R2 = 0.132 adj. R

2 = 0.081), TWPF Learn (β4 = 0.114, p = 0.031) (F = 2.364, p = 0.007; R

2 = 0.122 adj. R

2

= 0.070), and TWPF Collaborate (β4 = 0.166, p = 0.012) (F = 2.529, p = 0.004; R2 = 0.129 adj. R

2 = 0.078).

It appears that none of the four relations are moderated by one or more interaction terms (TWPF Socialize: ΔR2

= 0.038, p = 0.110; TWPF Collaborate ΔR2 = 0.037, p = 0.126; TWPF Learn: ΔR

2 = 0.024, p = 0.353; TWPF Focus

ΔR2 = 0.038, p = 0.092).

Productivity

It was found in the analysis of relation 1c (sub-model 1) that TWPF Learn has a significant positive influence on

productivity. Adding the interaction terms to the regression model does not reveal a significant change of R2.

This implies that personality traits as a whole do not add significantly to the explanatory power of the model

(ΔR2 = 0.031, p = 0.124). But when only the interaction terms for Conscientiousness and Openness are included

in the third stage (variant b), the change of R2 is significant (ΔR

2 = 0.030, p = 0.014) and also the betas are:

LearnC*ConscientiousnessC (β12 = -0.157, p = 0.030) and LearnC*OpennessC (β14 = -0.178, p = 0.026) (F = 6.244,

p = 0.000).

The main effects of TWPF Learn (β4 = 0.114, p = 0.000) and Conscientiousness (β7 = 0.404, p = 0.000) on

productivity are significant; the main effect of Openness on productivity is not significant (β9 = 0.116, p =

0.091).

Regarding the other three types of TWPF, a similar result has been found as for work life balance. It was

concluded earlier (relation 1c, sub-model 1) that these variables do not significantly impact productivity, but

when they are isolated from each other, they do: TWPF Socialize (β4 = 0.179, p = 0.000) (F = 7.330; p = 0.000; R2

= 0.301 adj. R2 = 0.260), TWPF Focus (β4 = 0.076, p = 0.019) (F = 5.803, p = 0.000; R

2 = 0.254 adj. R

2 = 0.211), and

TWPF Collaborate (β4 = 0.092, p = 0.023) (F = 5.765, p = 0.000; R2 = 0.253 adj. R

2 = 0.209).

The personality traits do not moderate the relations between Task Workplace Fit and productivity (TWPF

Socialize: ΔR2 = 0.014, p = 0.533; TWPF Collaborate ΔR

2 = 0.002, p = 0.989; TWPF Learn: ΔR

2 = 0.031, p = 0.124;

TWPF Focus ΔR2 = 0.015, p = 0.530).


5.4.3. Sub-model 3 – Work Arrangements – Work Practices

The third sub-model deals with the impact of work arrangements on work practices. It is reasonable that

certain conditions should be met before people could apply NWoW work practices.

Also this sub-model has been validated by means of hierarchical multiple regression analyses, by using an

approach that is quite similar to the approach of sub-model 1.

First stage: control variables (gender, age, position, time dependency, and location dependency)

(regression model 1)

Second stage: work practice variables (regression model 2)

Depending on the type of relation (more related to time versus more related to location), (one of the) two

additional control variables – time dependency and location dependency – are included in the analyses of this

sub-model.

Relation 5a: Workplace Design & Freedom Work Location – Task Workplace Fit

In chapter 3, Task Workplace Fit was defined as “the degree in which people are able to find a workplace that

suit the task they are performing, either within or outside the office”. As a starting point, it is suggested that

there are two elements that define whether people are able to find a place that suit their needs. First of all, the

design of the office is very important. For instance: do people have their own room, or do they share a room

with others? Besides, also the policies and agreements on and facilitation of telework are relevant: when

workers cannot find a place in the office that suits their task, they have additional possibilities to find such a

place when they are allowed to work elsewhere.

It could be that having a private room benefits TWPF Focus and TWPF Learn, while a shared room benefits

TWPF Socialize and TWPF Collaborate. Besides, backup spaces and freedom to choose work locations could

have a positive impact on all types of TWPF.


TWPF = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 + β3.5Position_d5 +

β4Location Dependency) + β5.2Room sharing_d2 + β5.3Room sharing_d3 + β5.4Roomsharing_d4 +

β5.5Roomsharing_d5 + β6Own Workplace + β7Backup Spaces + β8Freedom Work Location + ε

Work Practices Work Arrangements

Task Workplace Fit Focus

Socialize Collaborate

Learn

Workplace design Room sharing

Own work place Backup spaces

Freedom work loc.


This model has been validated four times in total. The output can be found in appendix 15.1.

TWPF Focus

Regarding TWPF Focus, the model with only control variables is already significant (F = 2.643, p = 0.012; R2 =

0.082, adj. R2 = 0.051). There are two variables that have influence on this type of Task Workplace Fit: Age (β2 =

0.021, p = 0.015) and location dependency (β4 = -0.229, p = 0.004).

In regression model 2 (F = 4.729, p = 0.000; R2 = 0.249, adj. R

2 = 0.196), the impact of location dependency is no

longer significant (β4 = -0.135, p = 0.110).

Having a private room is indeed very beneficial for focus: all room sharing dummies have a significant negative

influence on TWPF Focus, when workers with a single room are the reference group: Room sharing_d2 (share a

room with 1-2 others: β5.2 = -0.442, p = 0.020), Room sharing_d3 (share a room with 3-8 others: β5.2 = -0.892, p

= 0.000), Room sharing_d4 (share a room with 9-23 others: β5.4 = -1.032, p = 0.000), Room sharing_d5 (share a

room with more than 23 others: β5.5 = -0.912, p = 0.000). Also the degree in which people can choose their own

work location has a positive impact on TWPF Focus (β8 = 0.074, p = 0.012).

TWPF Socialize

The model with only control variables is not significant (F = 0.670, p = 0.697), but regression model 2 is (F =

2.549, p = 0.002; R2 = 0.151, adj. R

2 = 0.092). It appears that the control variable location dependency has a

positive influence on TWPF Socialize (β4 = 0.141, p = 0.037).

The degree of freedom that people have to choose their own work location(s) (β8 = 0.059, p = 0.012) and the

availability of backup spaces (β7 = 0.351, p = 0.005) also have a significant impact on this type of Task

Workplace Fit.

TWPF Collaborate

The model with only control variables is not significant for the regression on TWPF Collaborate (F = 1.781, p =

0.093). After adding the remainder of the variables to the regression model, there is a significant model (F =

1.801, p = 0.040; R2 = 0.112, adj. R

2 = 0.050), but the betas themselves are not significant.

TWPF Learn

For TWPF Learn, the first regression model (control variables) is not significant (F = 1.692, p = 0.112), but the

second regression model appears to be significant (F = 2.153, p = 0.011; R2 = 0.131, adj. R

2 = 0.070). All

dummies on Room sharing have a negative impact on TWPF Learn; in case of two dummies, this impact is

significant: Room sharing_d2 (share a room with 1-2 others: β6.2 = -0.447, p = 0.017) and Room sharing_d4

(share a room with 9-23 others: β6.4 = -0.605, p = 0.012).

Relation 5b: Workplace Design & Freedom Work Location – Flex-place

This relationship is quite similar to relation 5a. It is expected that the design of the workplace in combination

with freedom to work outside the office, influences the amount of flex-time.



Flex-place = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 + β3.5Position_d5 +

β4Location Dependency) + β5.2Room sharing_d2 + β5.3Room sharing_d3 + β5.4Roomsharing_d4 +

β5.5Roomsharing_d5 + β6Own Workplace + β7Backup Spaces + β8Freedom Work Location + ε

Output is available in appendix 15.2. The first regression model with control variables is already significant (F =

8.082, p = 0.000; R2 = 0.222, adj. R

2 = 0.195). However, the second regression model (F = 6.074, p = 0.000; R

2 =

0.308, adj. R2 = 0.257) has a higher predictive power (ΔR

2 = 0.086, p = 0.002).

Again, it appears that especially independent / hired workers (position 5) are engaged in flex-place (β3.5 =

25.949, p = 0.000). Location dependency has a significant negative impact on flex-place (β4 = -8.634, p = 0.001).

Another significant negative influence comes from having an own work place / desk in the office of the

organization (β6 = -18.555, p = 0.000).

Relation 5c: Freedom Work Location – Reflection on Choice of Location

The next relationship validates the proposition that more freedom to choose the work location(s) leads to

more reflection on work location.


Reflection on choice of location = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 +

β3.5Position_d5 + β4Location Dependency) + β5Freedom Work Location + ε

Output is available in appendix 15.3. According to the regression model with only control variables (F = 3.812, p

= 0.001; R2 = 0.114, adj. R

2 = 0.084), location dependency has a negative effect on the degree in which people

reflect on the choice of their work location (β4 = -0.240, p = 0.000). This effect reduces (β4 = -0.142, p = 0.030) in

regression model 2, but remains significant (F = 4.783, p = 0.000; R2 = 0.157, adj. R

2 = 0.124). Also a significant

effect of freedom work location has been found, although this is a small effect (β5 = 0.072, p = 0.001).

Relation 5d: Freedom Working Hours – Flex-time

It is expected that people who receive freedom to choose their own working hours, will also use this freedom.

In this model (and the next model), the control variable ‘location constraints’ has been replaced by ‘time

constraints’.

Flex-place

Workplace design Room sharing

Own work place Backup spaces

Freedom work loc.

Reflection on choice of location

Freedom work location

Flex-time Freedom working

hours



Flex-time = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 + β3.5Position_d5 +

β4Time Dependency) + β5Freedom Working Hours + ε

Output is available in appendix 15.4. Both the first regression model (F = 3.054, p = 0.004; R2 = 0.094, adj. R

2 =

0.063) and the second regression model (F = 3.245, p = 0.002; R2 = 0.112, adj. R

2 = 0.078) is significant. The

dummies for position 2 (top manager: β3.2 = 7.800, p = 0.002) and position 3 (middle manager: β3.3 = 5.274, p =

0.043) have a significant impact on flex-time. These results were not found in the analysis or relation 2b.

Time dependency negatively influences the percentage of work that is performed during non-regular working

hours (β4 = -2.783, p = 0.039), while freedom of choosing working hours has a positive influence (β5 = 1.149, p =

0.041).

Relation 5e: Freedom Working Hours – Reflection on Working Hours and Schedule

The assumption that will be validated now is that more freedom to choose working hours results in more

reflection on working hours and schedule.


Reflection on working hours and schedule = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 +

β3.4Position_d4 + β3.5Position_d5 + β4Time Dependency) + β5Freedom Working Hours + ε

Output is available in appendix 15.5. In regression model 1, there are two control variables that have a

significant negative impact on reflection on working hours and schedule: age (β1 = -0.019, p = 0.005) and time

dependency (β4 = -0.141, p = 0.043) (F = 3.993, p = 0.000; R2 = 0.119, adj. R

2 = 0.089). Contrary to the outcomes

of relation 2a, gender does not have a significant effect here.

In regression model 2, the effect of time dependency is no longer significant (β4 = -0.002, p = 0.984). Instead,

the control variable position d_2 becomes significant (β3.2 = -0.284, p = 0.045). It appears that freedom working

hours has a significant influence on reflection on working hours and schedule (β5 = 0.128, p = 0.000) (F = 5.979,

p = 0.000; R2 = 0.188, adj. R

2 = 0.157).

Relation 5f: Telework Facilitation Rate – Reflection on Media Use

It is expected that a higher degree of telework facilitation results in more reflection on media use.


Reflection on media use = α + (β1Gender + β2Age + β3.2Position_d2 + β3.3Position_d3 + β3.4Position_d4 +

β3.5Position_d5) + β4Telework facilitation rate + ε


Output is available in appendix 15.6. I appears that both regression model 1 (F = 1.078, p = 0.377; R2 = 0.030,

adj. R2 = 0.002) and regression model 2 (F = 0.966, p = 0.457; R

2 = 0.031, adj. R

2 = -0.001) are not significant,

which means that there is no statistical support for what was expected.

5.5. Discussion of the Outcomes

In the remainder of this chapter, the findings of the research are discussed with reference to the propositions

that were formulated in chapter 3. Given the exploratory character of this study, explanations are formulated as

hypotheses. Further research is needed to validate these statements.

5.5.1. P1 - “NWoW Work Practices have a positive impact on Work Performance”


It has been found that two types of reflexivity have a significant positive influence on work life balance:

‘reflection on working hours and schedule’ and ‘reflection on media use’. Besides, ‘reflection on media use’

impacts productivity significantly as well.

Hypothesis 1A – ‘Reflection on working hours and schedule’ has a significant positive impact on work life

balance

Carefully considering which hours are best suited for work and trying to match working hours with the personal

situation (or the situation of the household / family) results in a better work life balance. Following White et al.

(2003, p.192), personal discretion over time and flexible working hours enable employees to have a more

balanced lifestyle. This argument is in line with Hill et al. (2001: p.49) who argue that more (perceived) job

flexibility makes it possible for employees to better balance their work and family life: it enables them to select

the highest quality working hours and the highest quality personal and family hours.

Hypothesis 1B – ‘Reflection on media use’ has a significant positive impact on work life balance

The relationship between ‘reflection on media use’ and work life balance could be as follows: according to

Friedman et al. (1998: p.124), telecommunication media enhance people’s flexibility regarding their work.

More concrete: these technologies enable workers to accomplish their tasks at their own time and location.

It is in line with scientific literature (Beauregard, 2009) and the previous hypothesis that more flexibility is

beneficial for a better balance between work and private life. Also Perrons (2003) concludes that new media

expand the temporal and spatial range of paid work. This results in more flexibility and time sovereignty and

enables workers “to combine interesting, enjoyable, intellectually challenging and highly satisfying work with

family life” (Perrons, 2003: p. 88).

Hypothesis 1C – ‘Reflection on media use’ has a significant positive impact on productivity

‘Reflection on media use’ does not only affect work life balance, but also has a significant influence on

productivity. Theories such as the media richness theory and the media synchronicity theory suggest that a

better match between message and medium contributes to a more efficient communication. For instance,


communicating via one single medium (e.g. face-to-face) is less effective than using a set of media. Regarding

the media synchronicity theory, Dennis et al. (2008) concluded that for conveyance processes (transmission of

new information that enables the receiver to create a mental model) media that support lower synchronicity

are required, while for convergence processes (transmission of interpreted information for reaching a common

understanding) media with a higher synchronicity result in a better communication performance (see also

section 3.1.4; Dennis et al., 2008: p.575, 588).

By tuning the medium to the type of message, communication improves, which in turn could be supportive for

employees’ productivity.

Reflection on media – employee satisfaction

The analysis of sub-model 2 suggests that there is also a (significant) positive impact of ‘reflection on media

use’ on employee satisfaction, but this effect was not found in the analysis of sub-model 1. Therefore, this

relation is not taken into consideration here.


Hypothesis 1D – Nor flex-place nor flex-time has a significant impact on one of the performance indicators

This outcome of the analysis contradicts scientific sources which claim that more flexibility results in a higher

work performance (e.g. Baltes et al., 1999; Hill et al., 2001).

First of all it could be that, contrary to what the literature suggests, there is no relationship between flexibility

and performance indicators; at least not for the group of respondents in this study.

Alternatively, the relationship between flexibility and work performance could be more sophisticated than

initially thought: more use of flexibility practices does not necessarily improve performance. Elaborating on

this, it could be that not the absolute use of flexibility practices is relevant for a better work performance, but

that the focus should be on the optimal balance between flexibility on the one hand and job characteristics,

personal situation, and preferences on the other hand: what matters is the ‘goodness of fit’ between

individuals and their jobs (and belonging work practices) (Lamond, 2000: p.70).

5.5.1.3. Task Workplace Fit

In the analysis of sub-model 1, a number of significant and positive relations were found: TWPF Focus, TWPF

Learn, and TWPF Socialize impact employee satisfaction, TWPF Focus impacts work life balance, and TWPF

Learn impacts productivity.

Surprisingly, the analysis of the second sub-model revealed that all types of TWPF impact each of the three

performance indicators. It could be that the regression analyses for sub-model 2 were more ‘sensitive’,

because the four types of TWPF were separated from each other in these analyses (they were no longer put

together into the regression models). Supportive for these findings is the existence of significant correlations

between each of the four TWPF types and each of the three performance indicators (appendix 9). Alternatively,

it could be that the four TWPF types are quite related to each other: they also have quite similar (skewed)

distributions (with a peak at value 4).


The emphasis in this discussion is particularly on the relations that were significant in both the analysis of sub-

model 1 and sub-model 2.

Hypothesis 1E – TWPF Collaborate has no significant impact on employee satisfaction, but the other three

types of TWPF have

The data indicates that all types of Task Workplace Fit significantly affect employee satisfaction, except TWPF

Collaborate (analysis sub-model 1). This could imply that workers experience these three types of Task

Workplace Fit positively.

The univariate analysis suggests that it is relatively easy to find a place that suits Collaboration activities:

compared to the other three types of TWPF, TWPF Collaborate has the highest mean score.

It could be that places for Collaboration activities are more or less expected by knowledge workers, and –

under the condition that a minimum level of Collaboration places is met – incremental amounts above this

threshold do not (significantly) impact workers’ satisfaction level anymore.

Hypothesis 1F – Task Workplace Fit Focus has a significant positive impact on work life balance

For Focus activities, a silent location with a minimum of interruptions and distractions is needed. Especially in

case of shared office rooms, the home environment better meets these requirements than the office

(Montreuil & Lippel, 2003: p.349). People who report a high TWPF Focus, can find a place for Focus activities at

any time they need it, either inside or outside the office (under the condition that there are flex-place policies).

It could be that workers who cannot find a Focus place during working hours, accomplish their Focus tasks

during their free time (at home), at the expense of their work life balance.

Alternatively, it could be that TWPF Focus relates to more flex-place (and more concrete: working at home),

which in turn result in a better work life balance, but this explanation is not (significantly) supported by the

data.

Hypothesis 1G – Task Workplace Fit Learn has a significant positive impact on productivity

The literature argues that learning new skills improve knowledge workers’ productivity. According to Drucker

(1999), especially in case of knowledge work, continuous learning is required.

It could be that TWPF Learn benefits the quality of learning activities, which in turn results in a higher

productivity. Besides, it is arguable that organizations that facilitate relatively many places for learning (e.g. at

the office), put more emphasis on Learn and therefore have higher skilled and more productive workers.

5.5.2. Proposition 2 - “Work Arrangements impact NWoW Work Practices”

5.5.2.1. Work Arrangements

Hypothesis 2A – Private office rooms have a significant positive impact on TWPF Learn and TWPF Focus

According to the literature, in shared office rooms (e.g. open plan offices) there are negative effects of acoustic

environment: workers are increasingly distracted and experience more concentration difficulties. Especially


distracting in open plan offices are noises from voice, laughter, and telephone ringing (Kaarlela-Tuomaala et al.,

2009).

Given that Learn and Focus activities require concentration, private offices better suit these workplace tasks

(although the requirements for Learn environments might differ according to people’s learning style; Gensler,

2008).

Hypothesis 2B – Own workplace / desk does not have a significant impact on Task Workplace Fit, but has a

significantly negative impact on flex-place

For Task Workplace Fit, it does not matter where exactly people find places that suit their activities. Depending

on policies and agreements that apply, they can find places both inside or outside the office; an own desk in

the office is not necessarily required.

Regarding flex-place, the situation is different. Telework has a monetary benefit for organizations: it enables

them to move to flexible offices, by which rental costs can be reduced. In these offices, the number of desks is

lower than the number of people employed. Workers can use any desk available (Martínez-Sánchez et al.,

2007: p.210).

Additionally, workers who have an own desk in the office, could feel obliged to work there, while people

without an own desk in the office might be stimulated to work elsewhere.

Furthermore, having an own workplace / desk could diminish people’s interest in working at a different

location, because the need to do so is limited.

Hypothesis 2C – Freedom to choose work location(s) has a significant positive impact on both TWPF Focus

and TWPF Socialize, but concerning TWPF Socialize, workers remain dependent on (backup spaces in) the

office

The data suggests that backup spaces for specific tasks such as concentrated work, private phone calls and

meetings only have a significant positive influence on TWPF Socialize. At the meantime, freedom to choose a

work location has a significant positive influence on both TWPF Focus and TWPF Socialize.

It could be that it is more easy for flexible workers to find a place at their own location (e.g. at home) that suits

their Focus tasks, while for Socializing activities (backup spaces in) the office or external offices and meeting

locations are preferred.

Supportive for this hypothesis is that not only the freedom to choose a work location, but also location

dependency seems to have a significant positive impact on TWPF Socialize. This result implicates that, when

people are no longer location bound (which relates to more flex-time), it is more difficult to find a place that

suit their Socializing needs.


Hypothesis 2D – Neither workplace design nor freedom to choose work location(s) has a significant impact on

TWPF Collaborate

It could be that freedom to choose the work location(s) does not matter that much, because the office is the

place par excellence for Collaboration activities. Besides, it could be that the workplace design is not very

important, because the requirements for Collaboration locations are relatively limited; this statement can be

supported by the finding of this study that the average score on TWPF Collaborate is relatively high (which is in

line with hypothesis 1E).

5.5.2.2. Policies / Agreements

Hypothesis 2E – Telework facilitation does not have a significant impact on ‘reflection on media use’, but

‘freedom to choose working hours’ has a significant positive influence on ‘reflection on working hours and

schedule’ and ‘freedom to choose work locations’ has a significant positive influence on ‘reflection on choice

of location’

The data suggests that ‘reflection on working hours and schedule’ is significantly affected by ‘freedom to

choose working hours’, while ‘reflection on choice of location’ is significantly influenced by ‘freedom to choose

work locations’. These results are quite obvious.

However, no significant impact was found of ‘telework facilitation’ on ‘reflection on media use’. An explanation

could be that media availability does not spur people to reflect on their media use. Alternatively, it could be

that ‘telework facilitation’ is too general: because it covers more aspects than media availability alone, no

significant impact was found.

Hypothesis 2F – ‘Freedom to choose working hours’ has a significant positive influence on flex-time, but

‘freedom to choose work locations’ does not have a significant influence on flex-place

According to the data analysis, flex-time is affected by the amount of freedom workers have to choose their

working hours, but flex-place is not affected by freedom to choose the own work locations. It could be that

regarding flex-place other factors play a more dominant role, such as the control variable time dependency, for

which a negative significant effect on flex-place has been found.

5.5.3. Proposition 3 - “Specific Personality Traits impact Work Practices”

Three positive effects of personality traits on work practices have been found: Openness influences both

‘reflection on media use’ and ‘flex-place’ and Extraversion impacts Task Workplace Fit Collaborate.

Hypothesis 3A – Openness has a significant positive impact on ‘reflection on media use’ and flex-place

According to Barrick et al. (2003: p.51), the Openness dimension is related to traits such as originality and

unconventionality. People who are high on this dimension are more creative, prefer new experiences, and are

more likely to break up routines (John et al., 2008).


It could be that people who score high on Openness continually consider alternative ways of doing, and

therefore also reflect more on media use. This is in line with Jacques et al. (2009) who found an impact of

Openness on the intention to use various information technologies.

A similar reasoning applies to the impact of Openness on flex-place: these people are looking for alternative

ways to accomplish their tasks, which results in a larger portion of work that is accomplished at a different

location than the office.

Hypothesis 3B – Extraversion has a significant positive impact on Task Workplace Fit Collaborate

Contrary to the expectation that Task Workplace Fit is not affected by personality (see section 5.4.1), the data

suggests a significant positive effect of Extraversion on TWPF Collaborate.

According to the literature on personality traits, extravert people are collaborators par excellence: Extraversion

predicts people’s preference for group work (Chamorro-Premuzic et al., 2005: p.252). Given that collaboration

is relatively easy for extravert people, it could be that they are more likely to mark a certain location as suitable

for working with others.

5.5.4. Proposition 4 - “Specific Personality Traits impact the relationship between Work

Practices and Work Performance”

First of all, some general remarks have to be made regarding the moderated regression analysis. It sometimes

appeared that the interaction term (predictor*moderator) was significant, but one or both main effects

was/were not significant. There is confusion among scientists about what exactly a moderator is and which

relations have to be significant (Sharma et al., 1981). Holmberg (2002) gives the following definition of

‘moderator’: “a variable that specifies conditions under which a given predictor is related to an outcome”. In

line with this definition, the focus here is on all significant interaction terms. To get a better understanding of

how the findings should be interpreted, a number of graphs were drawn (based on both significant and not

significant relations). These graphs are available in appendix 12.


The data-analysis revealed that there are two significant interaction effects regarding the relationship between

reflexivity and work performance, caused by Extraversion and Agreeableness.

Hypothesis 4A: A higher score on Extraversion in combination with more ‘reflection on choice of location’

result in a relatively lower employee satisfaction

A characteristic of extravert people is that they focus on the outer world and are energized by interaction with

others (John et al., 2008; Lamond, 2000); they highly value interpersonal interactions, such as those that occur

at work (Judge & Mount, 2002: p.531).

It could be that ‘reflection on choice of location’ does make extraverts relatively less satisfied, because they are

less willing to reflect on their location: they prefer to work with colleagues at the office and are less likely to

consider alternatives.


Hypothesis 4B: A higher score on Agreeableness in combination with more ‘reflection on choice of location’

result in a relatively higher productivity

Agreeableness is associated with being cooperative and exchanging thoughts and ideas with others (Barrick &

Mount, 1991). From this point of view, it could be that agreeable people prefer to work at the office and

therefore are less likely to reflect on the choice of their work location. However, the data does not support this

statement.

Because agreeable people are more likely to help others, it could be that others push their work towards them

(Witt et al., 2002: p.165). Reflecting on choice of location could result in a higher percentage of time that is

worked at alternative locations (not in the office). According Barrick & Mount (1991), being flexible is also a

characteristic of agreeable persons. It could be that less time from agreeable people is consumed when they

reflect more on the choice of their location and more on working somewhere else, which results in a higher

productivity.


In the previous chapter, three significant interaction effects from Extraversion, Conscientiousness, and

Neuroticism were found for the relationship between flexibility and work performance.

Hypothesis 4C: A higher score on Extraversion in combination with more flex-place result in a relatively lower

employee satisfaction

It was already discussed that extravert people are sociable; they have a preference for working with others

(hypothesis 4A).

Lamond (2000: p.68) argue that extraverts only appreciate types of telework that include high levels of intra-

and extra organizational communication. However, many types of telework (especially working at home) imply

working alone, outside the physical presence of colleagues. For this reason it could be that flex-place is less

satisfying for extravert people.

Hypothesis 4D: A higher score on Conscientiousness in combination with more flex-time result in a relatively

lower productivity

Although a positive direct effect of Conscientiousness on productivity was found (hypothesis C), the data also

suggests that in case of flex-time being conscientious is disadvantageous. According to Stumpf and Parker

Stumpf and Parker (1999: p.850), Conscientiousness is related to (healthy) perfectionism. It could be that

conscientious people spend more time on perfecting their tasks (already done), whereas others work outside

regular working hours to complete their tasks (not yet finished); this in turn could be related to conscientious

people’s tendency to self-regulate themselves too extensively (Yeo & Neal, 2004; see also hypothesis 4J).

Hypothesis 4E: A higher score on Neuroticism in combination with more flex-time result in a relatively higher

productivity

Literature suggests that there is a relationship between Neuroticism and (performance) anxiety (Wetherell et

al., 2002: p.246). Neurotic people are feeling more anxious, guilty, and depressed than others (John et al.,


2008). Besides, it is argued that people who feel extremely anxious or unsuccessful regarding social interaction,

have a preference for being alone (Long & Averill, 2003: p.31).

It could be that neurotic people feel more comfortable when they work outside the office hours, because it

gives them the feeling that they are less closely watched by their manager and colleagues. Being more happy /

feeling at ease in turn is beneficial for workers’ productivity.

5.5.4.3. Task Workplace Fit

For the relationship between Task Workplace Fit and work performance, a total of six significant interaction

terms were found.

Hypothesis 4F: A higher score on Extraversion in combination with more TWPF Focus result in a relatively

higher employee satisfaction

The literature suggests that the performance of extravert people improves in the presence of distractions

(Morgenstern et al.,1974; Campbell & Hawley, 1982). From this point of view, it is surprising that the data

suggests that extraverts are relatively more satisfied with the availability of Focus locations.

It could be that extravert people have a differing conception of Focus locations (and also consider noisier places

as suitable for Focus tasks). Alternatively or in addition to this, it could be that extraverts are relatively more

satisfied with Focus locations because of their tendency to experience more positive emotions and to have a

higher satisfaction level in general (Judge & Mount, 2002).

Hypothesis 4G: A higher score on Agreeableness in combination with more TWPF Focus result in a relatively

lower employee satisfaction

People who are high on the Agreeableness dimension grant much value to the thoughts and options of others.

Striving for a common understanding is characteristic for Agreeableness (John et al., 2008). It could be that

agreeable people are relatively less satisfied with Focus locations because they want to discuss their ideas with

others, whereas the purpose of Focus locations is to work alone (there is at least no interaction with others).

Hypothesis 4H: A higher score on Neuroticism in combination with more TWPF Learn result in a relatively

higher employee satisfaction

In line with the literature that argues that neurotic people have a preference for being alone (Long & Averill,

2003), it could be that they have an individualistic learning style (learning without others). Eysenck and

Graydon (1989: p.685) argue that anxious (neurotic) people are more “adversely affected by distractions”.

Together these two arguments could explain why neurotic people are relatively more satisfied with places that

suit their Learn activities and where they can withdraw themselves.


Hypothesis 4I: A higher score on Extraversion in combination with more TWPF Collaborate result in a

relatively higher employee satisfaction

Being high on the Extraversion dimension is related to a preference for working with others (Morgeson et al.,

2003: p.588); extravert people like to Collaborate. This could explain why especially extravert people are

satisfied when they can find sufficient places for their Collaboration tasks.

Besides, extravert people are more likely to experience more positive emotions and to be more satisfied than

others (Judge & Mount, 2002). This could be an additional (or alternative) explanation.

Hypothesis 4J: A higher score on Conscientiousness in combination with more TWPF Learn result in a

relatively lower productivity

According to the literature, Conscientiousness has a negative influence on performance in learning contexts.

This is because in these contexts, conscientious people tend to be self-deceptive; they may self-regulate

themselves excessively (Yeo & Neal, 2004: p.234). It could be that more availability of places that fit Learning

tasks is related to more leaning activities (in terms of quality and quantity), which is disadvantageous for the

productivity of conscientious people.

Hypothesis 4K: A higher score on Openness in combination with more TWPF Learn result in a relatively lower

productivity

At first sight, it is counterintuitive that Openness in relationship to TWPF Learn has a relatively negative impact

on productivity, as Openness is associated with intellectual curiosity (John et al., 2008). The literature suggests

however that Openness is positively related with a deep approach of learning, but negatively to a surface

approach (Zhang, 2003: p.1440). It could be that people who are high on the Openness dimension are learning

too extensively (digging too deep), which makes that they benefit less from TWPF Learn in terms of

productivity.

5.5.4. Other Findings

5.5.4.1. Direct Effect of Personality Traits on Work Performance

The data suggests that there are three direct effects of personality traits on work performance.

Hypothesis A: Extraversion has a significant positive impact on employee satisfaction

It was already mentioned earlier in this chapter (hypothesis 4F) that extravert people are more likely to

experience positive emotions, which in turn affects their satisfaction (Judge & Mount, 2002).

Hypothesis B: Neuroticism has a significant negative impact on work life balance

There is consensus among scientists that neuroticism negatively impacts employee satisfaction because

neurotic people are more likely to experience negative emotions (John et al, 2008: p.142; Valcour, 2007:

p.1518), but no significant effect was found in the dataset.


However, the data suggests that there is a significant negative effect of neuroticism on work life balance.

People who score high on this dimension are more affected by stress, evaluate situations more negatively, and

have a tendency to feel unhappy. It could be that neurotic people take their negative feelings home and feel

more burdened, which results in an inferior balance between work and private life.

Hypothesis C: Conscientiousness has a significant positive impact on productivity

Conscientious people are “dependable, self-disciplined, hard-working, and achievement striving” (Barrick et al.,

2003: p.50). The literature argues that the Conscientiousness dimension is positively related to performance on

almost all types of jobs, but especially to conventional jobs, which are characterized by methodological or

procedural activities (Barrick et al., 2003: p.50).

5.5.4.1. Control Variables

Hypothesis D: Top managers score higher on employee satisfaction but lower on work life balance

It could be that top-managers have more opportunities to adapt their work methods to their preferences,

which makes them more satisfied with their jobs. However, at the same time, being a top-manager is a busy

job, which is reflected by a lower work life balance.

Hypothesis E: Women and young people are more likely to reflect on working hours and schedule

The literature suggests that especially women combine their jobs with work in the household and / or raising

children (Nadler et al., 2010: p.898; Perrons, 2003).

In addition to this, in most of the cases these are younger people who have small children that require

attention and care. This could explain why especially younger workers reflect on working hours and schedule.

Alternatively, schedule flexibility is enabled by information and communication technologies (Friedman et al.,

1998: p.124); it could be that younger generations (e.g. digital natives) are more familiar with these

technologies and/or are less likely to stick to old work patterns.

Hypothesis F: Independent / hired people work relatively more outside the office (flex-place); especially top

managers and middle-managers accomplish a higher percentage of their tasks outside regular working hours

(flex-time)

Regarding independent / hired workers, flex-place seems to be a characteristic of their job function.

In case of top-managers and middle-managers, it could be that they have a more flexible working schedule.

Alternatively, this finding could be due to the higher amount of hours worked by top- and middle managers

(see paragraph 5.2.1).

5.6. Final Remarks

A table that summarizes all hypotheses mentioned on the previous pages, can be found in appendix 10a. The

data analysis supports all four propositions for which analyses have been conducted: work arrangements affect

work practices, which in turn affect work performance. Besides, personality has an impact on work practices

and on the relation between work practices and work performance. Additional research is needed to validate


the more specific hypotheses that have been formulated. These hypotheses are graphically represented in the

figures below:

Figure 5.1. – Hypotheses for proposition 1 & 3 and ‘other findings’.

Figure 5.2. – Hypotheses for proposition 2 & 4.

The green blocks represent ‘personality traits’, the blue blocks ‘work practices’, the red blocks ‘work

outcomes’, the orange blocks ‘work arrangements’, and the grey blocks ‘control variables’.

A solid line means that there is a significant relation, while a dotted line means that there is not a significant

relation. In figure 5.2, the dashed arrow stands for a main effect that is not significant. When a hypothesis

consists out of multiple arrows, lowercase letters are added to the description.


6. Conclusion

This chapter formulates answers to the research questions, describes contributions to management practice

and theory, discusses the limitations of this study, and finally gives a number of recommendations for further

research.

6.1. Answering the Research Question

At the beginning of this thesis (chapter 1), a general research question and a number of sub-questions were

formulated. Now that the data has been analysed and the outcomes have been discussed, answers can be

given to these questions, beginning with the sub-questions and ending with the overall research question.

- The first sub-question was: To what extent does personality have an impact on the degree in which New Ways

of Working aspects are used by knowledge workers?

Three effects of personality traits on work practices were found. Openness has a significant impact on the

degree in which workers reflect on the type of medium; and besides, there is a significant influence of

Openness on the amount of flex-place work.

Further, Extraversion is related to Task Workplace Fit Collaborate: people on the high end of the Extraversion

dimension are more likely to find a place that suits their Collaboration needs.

- The second sub-question was: To what degree does personality have an influence on the relationship between

New Ways of Working aspects and outcomes of work?

A total of eleven significant personality interaction terms (on the relationship between work practices and work

outcomes) were found. In five cases, the effect was positive and in six cases the effect was negative. Each of

the five personality traits moderate at least one relation.

Interaction terms were significant for six relations with employee satisfaction and five relations with

productivity. Regarding work life balance, no significant moderating effect was found, but there was a direct

negative impact of Neuroticism on work life balance.

- The third sub-question was: Which New Ways of Working aspects fit to what personality aspects?

When the focus is especially on the (positive) direct and moderating effects of personality, it appears that

‘reflection on choice of location’ especially fits to Agreeableness; TWPF Focus and TWPF Collaborate to

Extraversion; flex-time and TWPF Learn fit to Neuroticism, and ‘reflection on media use’ and flex-place fit to

Openness. On the other hand, negative interaction effects indicate that ‘reflection on choice of location’ and

flex-place fit less well to Extraversion; TWPF Focus to Agreeableness; flex-time to Conscientiousness; and TWPF

Learn to Conscientiousness and Openness.

- The fourth sub-question was: Which specific New Ways of Working arrangements should be strengthened to

improve specific work outcomes of people who have certain characteristics in terms of personality?


This really depends. The analysis suggests that in general employee satisfaction can be improved by more

TWPF Focus (especially for extravert people, but less for agreeable people), TWPF Learn (especially for neurotic

people), and TWPF Socialize.

People are better able to find a place for Focus and Learn activities when they have private office rooms (in the

office). Besides, freedom to choose work location(s) has a positive impact on TWPF Focus. The latest work

arrangement also has a positive impact on TWPF Socialize. Another option is to stimulate TWPF Socialize by

means of backup spaces.

Reflection on choice of location and flex-place have a relatively negative impact on employee satisfaction for

extravert people. This implies that freedom to choose work location(s) is relatively less important for extraverts

(although it is useful for them regarding TWPF Focus), while having an own desk at the office is relatively more

important for them.

Work life balance could be improved by more ‘reflection on working hours and schedule’, more ‘reflection on

media use’, and more TWPF Focus. For the first type of reflection, freedom to choose working hours is

important. How to support TWPF Focus was already discussed above.

For a higher productivity, ‘reflection on media use’ is beneficial and also TWPF Learn (but relatively less for

people who score high on Conscientiousness and Openness). It was already mentioned that TWPF Learn can be

stimulated by private office rooms. Agreeable people are relatively more productive due to ‘reflection on

choice of location (freedom to choose the own work location); Conscientious people are relatively less

productive in case of flex-place, while neurotic people are relatively more productive (own workplace / desk is

more important for conscientious people than for neurotic people).

Now it is time to formulate an answer to the overall research question: to what extent is the New Ways of

Working concept affected by personality?

The results of this study indicate that personality really matters. The NWoW work practices do not suit to all

workers equally. Personality impacts both the degree in which NWoW are used and the effects of work

practices on work performance. It seems that, in order to optimize work performance, it is important to get a

match between the worker and work practices.

6.2. Contributions to Theory

A major contribution of this thesis is that a model was developed for analyzing the impact of human related

aspects (personality and culture) on the New Ways of Working. This model is based on job design theory, but

also incorporates personality trait theory (and national culture theory). There were some issues regarding the

development of the model.

In the first place, organizations (or divisions of organizations) differ on the degree in which NWoW practices are

facilitated for employees. This imposed the need for a model (and belonging measurement instrument) that

applies to both organizations that facilitate these practices and to organizations that do not facilitate them.


Secondly, the model should be applicable both for assessing the degree in which a certain type of people (in

terms of personality and national culture) apply NWoW practices (do they use them more/less than others?)

and the extent to which human related aspects have impact on the effects of work practices on work

performance (do they experience them differently than others?).

For selecting the most relevant work practices, the assumption was made the NWoW concept affects the

following three dimensions: people, place and technology (Andersen, 2012).

Some new concepts (and measurement constructs) were developed in relationship with existing concepts and

based on scientific literature (Gensler, 2008; Brahm & Schippers, 2010): ‘reflection on working hours and

schedule’ and Task Workplace Fit (Socialize, Lean, Focus, and Collaborate).

This thesis has also contributed to personality trait theory. Only in the last few decades that scientists have

paid attention to the external validity and predictive value of the Big Five dimensions. They base their research

on the assumption that the personality dimensions interact with environmental factors and together produce

behavioral and experiential outcomes (John et al., 2008: p.141). The research findings of this thesis support this

assumption.

6.3. Contributions to Management Practice

According to the personality selection literature, identifying personality factors for a certain job or role enables

management to predict performance of individuals. This study is helpful for managers of organizations that

apply (or consider to apply) New Ways of Working practices and want to predict outcomes of work (to some

extent).

Personality could also be used to predict performance of teams, but this is more complex: the personality

profile should not only fit to the job requirements, but also to the team (including their personalities).

However, when organizations take the trouble to match personalities with jobs and teams, the literature

suggests that this pays off (Kichuk & Wiesner, 1997).

Managers should realize that employees differ in terms of personality and that these differences have impact

on the use and effects of work practices.

It depends on how a New Way of Working is designed, to determine what exactly the effect of personality is.

For example, one could conclude that flex-place (e.g. working at home) requires especially introvert workers

who prefer to work alone, but this is not the case when a type of flex-place is applied that includes tasks that

are mainly accomplished at the client location.

Besides – elaborating on this example – it would be wrong to conclude that the organization needs exclusively

introvert people, because this personality trait is important for other work practices (e.g. Collaboration).

Personality has especially impact on the relationships between work practices - work life balance and work

practices – productivity. Both performance indicators are important. More productivity enables businesses to


gain a higher profit; employee satisfaction is especially relevant in case of knowledge work, because the

companies’ resources are stored in the heads of their employee. Unsatisfied employees are more likely to

change jobs (Drucker, 1999).

There are roughly two ways to match personality and work practices. Changing people’s personality is not

possible and therefore managers should match work practices to the people they have employed.

Alternatively, organizations could hire people who have certain characteristics in terms of personality, which is

a much more time consuming approach.

6.4. Limitations and Suggestions for Further Research

The study was conducted among alumni from the ‘PTO Bedrijfkunde’ of the Rotterdam School of Management.

Respondents have different ages, are working in multiple industries and several job positions are represented

(varying from top-manager to independent/hired workers). These are strengths of the dataset.

Generally speaking, most knowledge workers (to whom the New Ways of Working concept applies) are well

educated. They however do not necessarily have a university degree like the respondents in this study.

Moreover, respondents all completed a quite similar (business) education program besides their job, which

might not only be an indication of their level of education, but also of their level of motivation. Related to this

is the large number of respondents with management functions and the huge amount of time that people

spend on their job.

According to Gray (2007: p.543), a problem with almost all personality questionnaires is that the items are

quite transparent. It is not difficult for someone to present himself differently. This means that the researcher

is highly dependent on the honesty of respondents and the insights they have regarding their own behavior

and attitude.

The risk for a self-serving bias was also present regarding the measurement of performance by means of self-

reported data. Within the context of this study, asking peers and/or supervisors to answer questions on

personality and performance was not feasible. It could be that there was indeed a self-serving bias, but when it

is consistent across respondents, the effects are reduced (Eaton, 2003: p.157).

In section 5.4.2, it was stated that for the moderator analysis mean-centered data was used. This method is

quite often applied with the purpose to reduce multicollinearity – and is widely recommended (Kroonenberg &

Linting, 2011).

However, some scientists argue that multicollinearity cannot be eliminated by centering variables. Although

the VIFs (see section 4.3.1.4) are lowered by mean-centering, the ‘problem’ still exists, but is masked.

Echambabi and Hess (2007) conclude that mean-centering does not hurt, but does not help either; however,

there could be good reasons to use mean-centered data for interpretation purposes (Dalal & Zickar, 2011).

When the same moderator analyses in this thesis were conducted without mean-centered data, it appeared

that the VIFs were quite high indeed. This implies that the quality of the estimations of the parameters is not

always optimal. Nevertheless, the parameters for the interaction terms are identical in both (mean-centered


and not mean-centered data) analyses (Dalal & Zickar, 2011: p.345). In most cases, collinearity problems

cannot be remedied after the data collection (Echambabi and Hess, 2007).

Regarding the impact of human related aspects on the NWoW concept, this thesis covers only the tip of the

iceberg. The following recommendations are made for further research:

In line with the explanatory character of this study, the focus was on personality traits, but not on facets. In

other words: personality was studied at the highest level. It might, however, be valuable to analyse the

relations at a deeper level. Paunonen and Ashton (2001: p.524) concluded that “both the broad factors and

narrow facets predicted substantial numbers of criteria, but the later did noticeably better in that regard”,

which is in line with findings by others (Mershon and Gorsuch, 1988). Soto and John (2009) developed 10 facet

scales based on the BFI, and therefore this type of analysis can be conducted on the existing dataset.

Alternatively, the NEO-PI-R (or an IPIP equivalent) could be used, which distinguishes no less than 30 facets.

The results of this study are based on quantitative data. It could be valuable to complement these findings by

means of interviews. Another recommendation for a more comprehensive understanding is to consider also

the relationships of the conceptual model that have not been analyzed yet. The focus was not on the effects of

media use and work atmosphere (empowerment and control).

Additionally, it could be very interesting to conduct a similar analysis within one single organization, preferably

before and after the implementation of a new way of working in order to find out whether the match between

personality and work practices improves or not.

Besides a personality model, a culture model was developed (which is described in appendix 1). The finding

that personality does matter to the use and effect of NWoW practices is supportive for the assumption that

human related aspects are relevant within this context. The first two hypotheses of the culture model have

already been validated, but the other four have not.

Last but not least, this research has yielded a number of hypotheses that are described in the previous chapter

and need to be validated as well. A table with these hypotheses can be found in appendix 10a.


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Appendix 1 – Culture

A. Literature Review

Initially, the purpose of this thesis was in particular to develop a conceptual model in order to investigate the

impact of national culture on the New Ways of Working concept. Despite several attempts, it was not possible

to gather data internationally to validate the Culture model. This appendix reviews the literature on (national)

culture, discusses the conceptual model, and describes methodological implications.

A.1. Defining Culture

In scientific literature, there is no consensus on the right definition of culture. That is why several scientists

have created their own definitions.

Sometimes, a quite old (1871) but famous definition, formulated by Tylor, is cited. According to him, culture is

“that complex whole which includes knowledge, belief, art, morals, law, custom, and any other capabilities and

habits acquired by man as a member of society” (Nakata, 2009: p.62).

Geert Hofstede defines culture as “the collective programming of the mind that distinguishes one group or

category of people from another”. Culture is collective, manifested in behaviors, and common to some (but not

to all) people (Hofstede & McCrae, 2004).

A quite broad definition of culture was given by Herskovitz. According to him, culture is the “man-made part of

the environment” (Javidan et al., 2006: p.899).

Culture could be analyzed on several levels. Hofstede (1991) enumerates the following list of levels: national,

regional, ethnic, religious, linguistic, gender, generation, social class, and organizational / corporate. The author

states that this list is not exhaustive. Other levels of culture could be added as well. National culture is about

differences among countries.

Cultural differences manifest themselves in symbols, heroes, rituals, and values. These four elements each have

their own level of depth and could be depicted as an onion.

Symbols are in the outermost and values in the innermost layer of the onion and could be described as

‘words, gestures, pictures, or objects’ with a specific meaning for people of a certain culture. They

appear and disappear quite fast and cultural groups are copying symbols from each other.

Heroes are people who serve as a model for behavior. They have characteristics that are highly valued

within a culture.

Rituals are “collective activities, technically superfluous to reaching desired ends”, but they are

“considered as socially essential” (Hofstede, 1991). Rituals can vary from greeting methods to religious

ceremonies.


Symbols, heroes and rituals, which are put together under the term ‘practices’, are visible to outside observers.

Besides, practices there are also ‘values’. These are broad and deeply rooted tendencies, based on which an

individual prefers “certain states of affairs over others”. Both practices and values are ‘components’ of culture

(Hofstede, 1991: p.6-8).

A.2. National Culture and Management

Within scientific literature, three research streams have emerged on the relationship between national culture

and management.

The first stream says management has nothing to do with national culture, because management is

about “objective practices and autonomous actors” (De Boby, 2009). This view is more or less out-

dated.

According to the emic current stream, cultures are characterized by uniqueness; quantitative

comparisons are not possible. This stream argues that in-depth qualitative descriptive and interpretive

studies are the appropriate way to study culture.

The third stream (etic current) says that national cultures are comparable, based on general

dimensions. Researchers of this stream (which derives from psychology) conduct Cross-Cultural

Studies (CSS). Frameworks are developed to make quantitative comparisons of national cultures (De

Bony, 2009: p.4).

The most dominant frameworks used by the latest stream mentioned, are discussed in the sections below.

A.3. Culture Frameworks

This paragraph describes and evaluates the most prevalent frameworks in literature to measure cultural

differences.

A.3.1. Hofstede

The framework developed by Geert Hofstede is perhaps the most influential model to classify culture (Kirkman

et al., 2006: p.285). His book, Culture’s Consequences, has become a ‘super classic’ (Nakata et al., 2009:

p.40,70) and has been cited more than 54,000 times (Tung & Verbeke, 2010: p.1239). Based on an attitude

survey research of IBM employees from international subsidiaries in 71 countries, carried out between 1967

and 1973, Hofstede defined four dimensions on which cultures can be classified (Nakata et al., 2009: p.70,72;

Barkema & Vermeulen, 1997: p.846; McSweeney, 2002: p.90, 94; Hofstede & McCae, 2004: p.61).

A fifth dimension, ‘Long-Term Orientation’ (initially called ‘Confucian dynamism’) was added later, based on

research conducted in China (Nakata et al., 2009: p.30; Barkema & Vermeulen, 1997: p.847). These surveys

were especially designed to capture dimensions of culture which are relevant in Asia (Newman & Nollen, 1996).

Quite recently (2010), a sixth dimension was added to the model: Indulgence versus Restraint. This dimension

was based on research by Michael Minkov and is related to his dimension Industry versus Indulgence

(descripted in 2.1.2.6) (Minkov, 2011: p.36; Hofstede et al., 2010: p.44, 45).


Hofstede’s approach has had much influence on management studies, especially for Information Systems

research (Baskerville, 2005: p.390); the framework is regarded as the dominant paradigm in business studies

(Nakata et al., 2009: p.3).

These are the six dimensions defined by Hofstede (Hofstede & Bond, 1984):

Power Distance (PDI): the extent to which it is accepted by less powerful members of institutions and

organizations that power is distributed unequally.

Individualism versus Collectivism (IDV): ‘Individualism’ and ‘Collectivism’ are two sides of a bipolar

continuum. Individualism means that people are only looking after themselves and their immediate

family; in collectivistic cultures, people are part of in-groups of collectivises.

Masculinity versus Femininity (MAS): ‘Masculinity’ emphasizes success, money, and things, whereas

‘femininity’ emphasizes caring for others and quality of life.

Uncertainty Avoidance (UAI): UAI deals with how comfortable people feel in case of ambiguous

situations. These are situations that are unstructured, unclear, or unpredictable. UAI also deals with

the degree in which beliefs and institutions are built to avoid these situations.

Long-Term versus Short-Term Orientation (LTO): this dimension is about the orientation of people. In

some cultures, people are oriented on the future, while people in other cultures are more focussed on

the present.

Indulgence versus Restraint (IVR): the most recent added dimension deals with the degree in which

gratification of desires related to enjoying life and having fun (and not desires in general) are allowed.

Indulgence means that this degree is high, while restraint implies a low degree (Hofstede et al., 2010).

Especially, the Individualism dimensions have received much attention, although sometimes it has been

interpreted in a different way than it was originally intended (Minkov, 2011: p.46).

A.3.2. GLOBE

GLOBE (abbreviation for Global Leadership and Organizational Behavior Effectiveness) is a research program

that investigates cultural values and practices and their impact on organizational practices and leadership in a

large number of varying countries (61 in total, House et al., 2002: p.3).

The Principal Investor of GLOBE was Robert J. House (House et al., 2002: p.3). In 1991, he wanted to do

research on leadership internationally, but he moved his scope to national and organizational cultures

(Hofstede, 2006: p.882). Over time, a research team has been composed, with almost 200 people involved.

Two of them are Co-Principal Investors, the others are Country Co-Investors. Country Co-Investors are most

often natives of the cultures for which they collect data.

The GLOBE study is highly related to Hofstede’s model. It is based on the same fundamentals (for instance, the

dimensions paradigm). The aim of GLOBE was to extend and improve Hofstede’s work (Hofstede 2006, p.883).


GLOBE uses the following nine dimensions to study culture (House et al., 2002: p. 5,6):

Uncertainty Avoidance

Power Distance

Collectivism I: Societal Collectivism

Collectivism II: In-Group Collectivism

Gender Egalitarianism

Assertiveness

Future Orientation

Performance Orientation

Humane Orientation

According to House et al. (2002), the first three cognitions reflect Hofstede’s Uncertainty Avoidance, Power

Distance and Individualism dimensions. Also the three subsequent dimensions are related to Hofstede’s

framework. While ‘Collectivism I’ is about the emphasis a society puts on individualism/collectivism,

‘Collectivism II’ is about in-group collectivism (family, organization).

Hofstede’s Masculinity dimension was split up into ‘Gender Egalitarianism’ and ‘Assertiveness’. The first one

deals with gender role differences and gender discrimination, and the second one with being assertive,

aggressive and confrontational in social relationships (House et al., 2002: p.6).

The last three dimensions are (partly) derived from several other sources. Future orientation is about

individual’s behaviors such as planning, investing in the future, and delaying gratification. Performance

Orientation is the degree to which organizations and societies are stimulating group members to improve their

performance and to become more excellent. Hofstede’s Long Term-Orientation is included in GLOBE’s

Performance Orientation.

Humane Orientation is the degree to which organizations/societies “encourage and reward individuals for

being fair, altruistic, friendly, generous, caring, and kind to others” (House et al., 2002: p.6).

Each of the nine dimensions is measured on four scales, both in ‘as is’ and ‘should be’ terms. ‘As is’ questions

are intended to measure practices, while ‘should be’ questions are intended to measure values. While Hofstede

has made a clear distinction between national culture and organizational culture (for both concepts he

developed a separate framework), GLOBE uses this single framework to analyze both levels of culture.

Measuring organizational culture is done by using largely the same questions, in which ‘society’ is replaced by

‘organization’.

Although some of the dimensions in the Hofstede and GLOBE model look similar, there are some big

differences. For instance, the Uncertainty Dimensions of both frameworks are significant negatively correlated,

which indicated that they are two entirely opposite concepts (Venaik and Brewer, 2008: p.6).


A.3.3. Schwartz

Based on literature study, Shalom H. Schwartz, an Israeli psychologist, composed a list of fifty-six values.

Initially, he focused on differences between individuals; later on, he moved the scope to countries / national

cultures. He developed a classification which distinguishes seven cultural value orientations. Together, they

form three cultural value dimensions: ‘embeddedness versus autonomy’, ‘hierarchy versus egalitarianism’, and

‘mastery versus harmony’ (Schwartz, 2008: p.9).

A.3.4. Trompenaars

The study of Fons Trompenaars, conducted in forty countries among forty-six thousand managers revealed

seven dimensions (Hampden-Turner & Trompenaars, 2000):

Universalism versus particularism

Individualism versus collectivism

Neutral versus emotional

Specific versus diffuse

Achievement versus ascription

Orientation in time

Attitudes towards the environment

Though quite often used by business consultants, these dimensions are - according to Minkov (2011: p.48) -

purely based on imagination and lack statistical evidence.

A.3.5. World Values Survey

A very comprehensive research on values, led by the political scientist Robert Inglehart from the United States,

is the World Values Study.

The study group that conducts this research has developed a survey with more than 360 items included; the

questions are about subjects such as ecology, economy, education, emotions, family, gender and sexuality,

government and politics, health, happiness, leisure and friends, morality, religion, society and nation, and work

(Hofstede, 1991: p.33).

The goal of the study is to “identify and understand changes in global attitudes” (MacIntosh, 1998: p.452).

According to the researchers, a worldwide shift is going on to a post-materialism attitude. The emphasize is

getting more on “free expression of ideas, greater democratisation, and the development of more humane

societies” instead of material well-being (Hofstede & McCrae, 2004: p.60).

Initially, no dimensions were used. Later, two of them were found, based on data analysis: ‘well-being versus

survival’ and ‘secular-rational versus traditional authority’.

A.3.6. Minkov

One of Hofstede’s followers is Michael Minkov from Bulgeria. He and Gert Jan Hofstede (Geert’s son) were co-

authors of Geert Hofstede’s third edition of Cultures and Organizations. Minkov wrote a book titled Cultural

Differences in a Globalizing World. It was recommended by Geert Hofstede as the “breakthrough in cross-

cultural research that we have been waiting for”. In this book, he presented a new framework with four


dimensions based on the World Values Survey and statistics from the United Nations and the World Health

Organization. The four dimensions he distinguishes are:

Industry versus Indulgence: the Industry pole is about prioritising hard work and thrift, while the

Indulgence pole is about prioritising leisure.

Monumentalism versus Flexumility: Monumentalism is about being proud and stable, while

Flexumility is about humility and flexibility. Identities, values, norms and beliefs are not changeable in

case of Monumentalism, but are in case of Flexumility.

Hypometropia versus Prudence: this dimension deals with time horizon differences. In cultures that

could be characterized as Hypometropia, people are more likely to act according to their ‘instincts’

(higher risks), while in prudent cultures these instincts are managed prudently (lower risks).

Exclusionism versus Universalism: in cultures characterized by Exclusionism, there are “stronger ties

between generations and within groups of relatives”. However, interests of strangers are neglected. In

Universalism-cultures the opposite holds (Minkov, 2011; Adolphus, 2011).

It appeared that Exclusionism versus Universalism had a strong correlation with Hofstede’s Collectivism versus

Individualism. This is the only indisputable equivalent in the two frameworks, although ‘Monumentalism versus

Flexumility’ correlates significantly with Short-term and Long-term orientation. To integrate Hofstede’s and

Minkov’s frameworks, Indulgence versus Restraint was added to Hofstede’s model (Adolphus, 2011; Hofstede

et al., 2010: p.45).

A.4. Conceptualization of Culture

In this paragraph, the major issues related to the use of frameworks are described. The focus is largely on the

framework developed by Hofstede, which is the dominant model in cross-cultural research. Most of the

discussion in scientific literature is about his framework. Other frameworks are criticised less; that might be

because they are applied less often and/or developed later (Venaik and Brewer, 2008: p.6).

Some of the criticism on Hofstede also holds for the other frameworks described above, as they are built on the

same paradigm. This paragraph also describes fundamental differences between the frameworks.

A.4.1. Use of Dimensions

The approach of measuring and ordering cultural differences by using a set of dimensions, was introduced by

Hofstede. According to him, the dimensions paradigm had become ‘normal science’ (Kuhn), as it had been

broadly accepted. All frameworks described in the previous paragraph are built on this paradigm (Hofstede,

2006: p883). Before Hofstede’s work, culture was treated as a single variable (Minkov & Hofstede, 2011: p.11).

One of the objections against dimensions is that qualitative methods are more suitable to measure culture

(Smith, 2006: p.915). Related to this view is the notion that surveys are not able to map differences in cultures.

Hofstede contradicts this notion, although he states that surveys should not be the only way (Hofstede, 2001:

p.73). Dimensions do not exist is reality, but they are needed to understand and deal with the complex social

world (Hofstede, 2006: p.895).


Hofstede’s work was also criticised for the way in which dimensions were determined. Moreover, the number

of dimensions was subject to discussion.

Hofstede discovered the first four dimensions by analyzing data collected at IBM for a consultancy project.

Some researchers found it problematic that his sample was limited to a single multinational cooperation

(Kirkman et al., 2006: p.286). Besides, the data was not gathered with the purpose in mind to develop a cultural

framework (Baskerville, 2005: p.390). However, later research and analyses confirmed Hofstede’s initial

findings (Minkov & Hofstede, 2011: p.14).

The GLOBE project has distinguished more dimensions than Hofstede did. According to the GLOBE researchers,

Hofstede only investigated what IBM was interested in. There might be some undiscovered dimensions, which

are not in the framework yet. They refer to the dimension Long-Term Orientation which was also added later,

based on additional research (Javidan et al., 2006: p.898)

On the contrary, Hofstede of the opinion that GLOBE’s model lacks parsimony, as it counts eighteen dimensions

in total (values and practices are measured separately for each of the nine dimensions) (Venaik and Brewer,

2008: p.7).

Hofstede is willing to add new dimensions to his framework, but they have to be “conceptually and statistically

independent” from the existing dimensions. They should also be significantly validated by “conceptually related

external measures” (Hofstede, 2001: p.73).

According to Minkov and Hofstede (2011: p.17), there is not one best way to construct cultural dimensions.

Hofstede regards both Schwartz’ classification and the World Values Survey as different ways of cutting the

same pie (Hofstede & McCrae, 2004: p60; Hofstede, 1991.: p.32, 33) and supposes that a deeper analysis of the

World Values Survey data would reveal additional dimensions that are not in their framework yet.

A.4.2. Values and Practices

In a previous section, it was stated that Hofstede distinguishes between values and practices. National cultures

are largely based on values and less on practices. For organizational cultures the opposite holds. That’s why

Hofstede developed a separate model with different dimensions to map organizational cultures (Hofstede,

1991: p.283).

Javidan et al. (2006: p.904), involved in the GLOBE program, reanalyzed Hofstede’s data and found no empirical

ground to distinguish between organizational and national cultures: “Hofstede and his colleagues (Hofstede et

al., 1990) are not supported in their claim that cultural practices are limited to the domain of organizations, and

that values have no place in organizational culture”. GLOBE does not therefore make a distinction and uses only

one framework to measure both levels of culture by using almost the same questions (‘society’ is replaced by

‘organization’).

The tool developed by Hofstede to measure national culture is called ‘Value Survey Module’. This instrument

(and similar instruments as well) has been criticized for being preoccupied with values, while other attributes of

culture are overlooked. Other aspects of culture should be considered as well (Nakata et al., 2009: p.42).


Javidan et al. (2006) discuss two assumptions which they attribute to the Hofstede approach. The first

assumption is what they call onion assumption: when the collective’s values are known, it is also known what is

actually happening in that culture (day-to-day activities). The other assumption was called ecological values

assumption: knowing the values of members within a culture is enough to know the culture itself, while other

manifestations of culture are neglected.

Hofstede contradicts that his work is built on these assumptions, by arguing that culture should be studied at

the aggregate level and by quoting his own work in which he states that culture is more than values alone and

that there are different elements of culture as well (Hofstede, 2010: p.1341). However, according to Nakata et

al. (2009: p.42), Hofstede does not practice what he preaches, because he does not measure those other

aspects.

GLOBE claims to measure both values (should be) and practices (as is), but analysis of GLOBE’s measurements

resulted in negative correlations between ‘as is’ and ‘should be’ for most of the dimensions. This is striking,

because one would expect that people tend to practice their values (Brewer & Venaik, 2010: p.1317). Javidan

et al. (2006) suggest that the relationship between values and practices might be more complex than

supposed. Maseland and Van Hoorn (2010) explain these findings by the theory of diminishing marginal utility,

while Brewer and Venaik (2010) contradict the applicability of this theory and suggest that the nature of each

culture dimension and questionnaire used may be responsible.

According to Hofstede, the major problem is that the GLOBE project members and he himself are using the

same terms, but not with a similar meaning. While Hofstede’s dimensions are based on ‘values as desired’

(what people actually desire), GLOBE’s dimensions are based on ‘values as the desirable’ (what they ought to

desire). ‘Values as desired’ are at least better related to deeds than ‘values as the desirable’.

The definition of practices is also different. Hofstede’s practices are work-related pragmatic issues, while

GLOBE’s practices are abstract aspects of societies and organizations in which respondents operate. As

described above, the meaning of ‘organizational culture’ is also distinctive (Hofstede, 2010: p.1340-1342).

Earley (2006: p.924) states that he agrees with Hofstede’s opinion that the distinction between ‘as is’ and

‘should be’ is artificial and supposes that outcomes are influenced by psychological processing.

A.4.3. Aggregation

Because a nation is not able to fill in a questionnaire, data is measured at an individual level (Earley, 2006:

p.926). For this reason it is sometimes argued that surveys are not usable to measure culture. While Hofstede

uses self-reports (statements about oneself), GLOBE asks respondents to answer questions in relation to the

environment (e.g. country or organization). A good question is however whether respondents are

knowledgeable enough to answer these questions. Therefore, the approach of GLOBE is problematic as well

(Hofstede, 2010: p.1344).


A.4.4. Culture versus Nation

When frameworks are used, there is a danger that ‘nation’ is used as a surrogate for ‘culture’. Georgas and

Berry (1995: p.122) call this the onomastic fallacy. Replacing culture by nation is an oversimplification, because

countries are not homogenous entities (Nakata et al., 2009: p.73,125,130,268; Baskerville, 2003: p.1,6).

Switzerland, for example, has a relatively small population, but there are significant differences between

German-speaking and Italian-speaking areas (Jacob, 2005: p.515).

Besides, borders of nations change over time and even if they remain unchanged, they are still permeable

because of immigration and economic zones (Nakata et al., 2009: p.251).

Contradictory to these statements are some research findings by Schwartz and Inglehart. They both compared

different subgroups within a nation (Schwartz: young-old, male-female, teachers-students; Inglehart: income,

rural/urban residence) on their own classification and found high correlations across countries (Schwartz, 2008:

p.15). However, it is doubtful what would be the results when different ethnicities from a single country would

be compared against each other.

Hofstede (2001: p.73; 2003: p.812) recognizes that nations are not the best units for studying culture. He

literally agrees that ‘nation states cannot be equated with national cultures’. The problem is that there is often

no alternative.

A.4.5. Replication

There have been some issues with the replication of Hofstede’s model (Baskerville, 2003: p.5). According to

Hofstede, differences arise because replications are not always carried out professionally. Amateurs are

entering the field of cross-cultural research and besides, there could be statistical, methodological, and

epistemological explanations for the deviant results (Hofstede, 2003: p.813).

Another possibility is that one of Hofstede’s assumptions is faulty and that it is an illusion that cultures are

“relatively stable systems in equilibrium” (Kirkman et al., 2006: p.302,312). This argument is discussed in the

next section.

A.4.6. Cultural Determinism

Hofstede argues that the outer layer of the ‘onion’ (practices) can change fast, while the inner layer (values)

changes slowly. Values are deeply rooted; they are acquired in childhood and passed from generation to

generation (Hofstede, 1991: p.12,13). Therefore, they will remain relatively stable. That is the reason why the

Hofstede scores, based on measurement of values at IBM, are still up-to-date. The four (and later five)

dimensions “are assumed to have centuries-old roots” (Hofstede, 2001: p.73).

The “increasingly fluid nature” of culture is caused by social developments like globalization, traversing of

national borders, co-mingling, hybridizing, morphing, clashing through media, migration, telecommunications,

international trade, information technology, supranational organizations, and terrorism (Nakata et al., 2009:

p.4).


Tung & Verbeke (2010: p.1263) refer to the ‘ocean metaphor’: at a given time, cultural values may ‘lie dormant’

in a country. However, they awake when they are re-ignited by external events. Examples of these events are

foreign direct investment and rapid internationalization. For example, Ralston and al. (1992) discovered that

cultural values of Chinese managers are changing quite fast.

One of the objectives of the World Values Survey was to find out whether cultural values are changing.

Researchers involved in the project, showed that this is the case (Schwartz, 2008: p.17). Based on a study

(covering a period of 36 years) in Belgium, Italy, France, the Netherlands, West-Germany, and the United

States, Inglehart concluded that cultural differences became less outspoken, although the convergence was

partial as cultural differences did not disappear (Minkov, 2011: p.42). Schwartz (2008: p.17) found that relative

positions of countries are changing very slowly.

Minkov and Hofstede (2011: p.13) endorse Inglehart’s findings; Hofstede would always have recognized the

evolution of cultures, but it is impact should not be overestimated, because they move more or less into the

same direction: “differences between them are not necessarily lost”.

Nonetheless, Hofstede was accused of cultural determinism because of his approach. To prove this, opponents

state that his theory is almost exclusively used to investigate the influence of culture as a cause (main effect or

moderating effect), but rarely as an effect (Nakata et al., 2009: p.46).

According to Schwartz (2008: p.17, 50) cultures are subject to “social conflict, tension and change”, and

therefore “one-time, static measures of the overall culture” are undesirable.

A.4.7. Two Epistemologies

Nakata et al. (2009: p.255-257) state that there are two kinds of epistemologies. On the one hand, there is an

idealized-superorganic epistemology (modernist), which considers culture as cognitive, bounded, fixed,

coherent and unified. The realist-organic epistemology (postmodernist) regards culture as changeable,

unsettled, disjunctive, and more than cognitive. Both epistemologies are valuable: they complement each

other. Together, they enrich our understanding of culture.

Social sciences both have modernist and postmodernist research method to investigate culture, while cultural

research in business studies is primarily based on modernist approaches (like the frameworks described in this

chapter).

Looking at culture from a realist-organic epistemology would have the following implications (Nakata, 2009:

p.255-257):

Culture is organic and resides on the level of individuals. There is no unifying ‘cosmic unity’ above.

Research should focus on “customs, artifacts, actions, and symbolates’ instead of ‘values, ideals, and

personality” (Nakata, 2009: p.256).

“Culture is an evolving complex of ideas, actions, and beliefs” (Nakata, 2009: p.256).

There is an influence of individuals on culture and of culture on individuals.


Is it required to go beyond Hofstede? The aim of this study is to investigate the relationship between national

culture and the NWoW concept. In previous sections, culture was described as an onion with several layers. In

the heart of this onion there are the deeply-rooted values. The outer rings represent symbols, heroes, and

rituals, collectively referred to as ‘practices’. In fact, implementing the New Ways of Working concept means

replacing existing practices by other (new) ones.

According to the theory developed by Hofstede, national culture expresses itself mainly in values, while

organizational culture manifests itself mainly in practices. Changing practices might be a hard job, but changing

values is (almost) impossible. It might be interesting to investigate how organizational cultures are related to

the NWoW concept, but this is beyond the scope of this thesis. For these reasons the focus should be especially

on values. Important to know is whether the NWoW practices clash with cultural values or not.

A.5. Choosing a Framework

The work of Hofstede is used and cited often by management scholars. International business textbooks use his

classification to explain the relevance of cultural differences. Much of the cross-cultural research is based on

Hofstede’s model and it is foreseeable that it will remain popular, although it’s also expected that some

researchers will prefer the GLOBE model (Venaik and Brewer, 2008: p.8).

The popularity of the Hofstede model does not automatically mean that this approach is the most appropriate.

A less used framework might be applicable as well. However, a major advantage of the popular frameworks

(Hofstede, GLOBE) is that new research can be related to previous research. Besides, more scientists have paid

attention to these frameworks and they are verified more often. To elect a less often applied framework, it

should be superior to the more dominant ones.

To some extent, the criticism described above could also be applied to the smaller frameworks. They are based

on the same principles, like the dimensions paradigm. This implies that there is no fundamental reason to

prefer one of these frameworks over the two ‘big’ ones.

GLOBE representatives claim that their model is an improved and extended version of Hofstede’s model.

Scientists differ in their opinions whether or not GLOBE meets this target. According to Nakata et al. (p. 4) the

five dimensions defined by Hofstede are sufficient to describe all national cultures. Earley (2006: p.928)

appreciates the GLOBE project as a leadership study, but as a values study he regards it as one of many; the

added value of GLOBE over Hofstede’s framework is questionable.

In fact, there are no convincing arguments to select another framework than the one developed by Hofstede,

which is the dominant model in cross-cultural research. However, besides the Indulgence vs. Restraint

dimension, which was based on findings by Minkov (Industry vs. Indulgence), also Monumentalism versus Self-

Effacement could be investigated. This is a Minkov-dimension that has not been incorporated into the Hofstede


conceptualization yet, although survey questions on this dimension were added to the Hofstede Survey Values

Module 2008. The choice for combining these two frameworks does not imply that culture could not be

conceptualized alternatively; there is not a one best way, but within the context of this study this is the most

appropriate method.

A.6. Organizational Culture

In the previous sections the term ‘organizational culture’ was already mentioned. Whereas GLOBE uses the

same dimensions to access both national culture and organizational culture, Hofstede developed a separate

framework to map organizational culture. According to Hofstede, national culture and organizational culture

are phenomena of different nature due to a different mix of values and practices. He regards “shared

perceptions of daily practices” as the core of organizational culture and distinguishes six cross-organizational

dimensions (Hofstede et al., 2010):

Process oriented versus results oriented: this dimension is about a concern with means versus a

concern with goals.

Employee oriented versus job oriented: this dimension is about a focus on people versus a focus on

completing the job.

Parochial versus professional: in a parochial culture, the organization is important for the identity of

employees, while in a professional culture the type of job is more relevant.

Open system versus closed system: this dimension deals with openness to newcomers and outsiders.

In an open system almost everyone fits and new people are very soon part of the group; in a closed

system the opposite is true.

Loose versus tight control: this dimension deals with the internal structuring of the organization.

Normative versus pragmatic: this dimension is about business ethics and honesty.

It seems, however, that there is less consensus regarding the dimensions of organizational culture as there is

not a dominant model (yet). Besides, it seems to be very difficult to map organizational culture by means of

survey questions.


B. Conceptual Framework

In this chapter, the Culture conceptual model is presented which focuses on the impact of cultural values instead

of personality traits. Although this model is not validated in this thesis, it is quite related to the conceptual

model that deals with personality. Both similarities and differences are discussed in this chapter.

First of all, the conceptual model that deals with Hofstede’s cultural values dimensions is presented in the

picture below (figure B.1).

Figure B.1. – Conceptual model (Culture)

Compared to the Personality Model that was presented in Chapter 3, this conceptual model has an additional

arrow: proposition 6.

It could be that Cultural Values relate to Work Arrangements, because in certain cultures specific Work

Arrangements (that facilitate NWoW) are more likely to be present than in other cultures (Cagliano et al.,

2010). Culture is something that exists mainly at the aggregate level (Hofstede, 2001); it could be that they

differ regarding which Work Arrangements are dominant.

Also, an extra control variable is added: Nationality at birth.

Work Arrangements People

- Policies / agreements

Place - Workplace design

Technology

- Media availability

Control variables Gender, Age, Nationality at birth, Position, Time dependency, Location dependency

Work Atmosphere Empowerment

Control

Work Practices People

- Reflexivity - Flexibility (time)

Place - Flexibility (place) - Task workplace fit

Technology - Media use

Cultural Values Power Distance, Individualism, Masculinity, Uncertainty Avoidance, Long-Term

Orientation, Indulgence, Monumentalism

Work Performance

People

- Employee satisfaction

- Work life balance

Profit

- Productivity P1: +

P4

P5

P3 P6

P2


B.1. Cultural Values

For cultural aspects, the conceptual model is largely based on theory developed by Geert Hofstede, whose

framework is by far the most applied conceptualization of culture in cross-cultural research. Quite recently, a

new dimension was added to this framework, based on research by Minkov: Indulgence vs. Restraint.

In this thesis, Hofstede’s framework is supplemented by a Minkov dimension that is not incorporated into the

framework (yet), although it is -by way of an experiment- included in his Values Survey Module 2008:

Monumentalism vs. Self-Effacement.

This implies that the following dimensions are included:

1. Power Distance (Hofstede)

2. Individualism vs. Collectivism (Hofstede)

3. Masculinity vs. Femininity (Hofstede)

4. Uncertainty Avoidance (Hofstede)

5. Long vs. Short-Term Orientation (Hofstede)

6. Indulgence vs. Restraint (Hofstede/Minkov)

7. Monumentalism vs. Self-Effacement (Minkov)

A description of these seven dimensions was given in sections A.3.1 and A.3.6, while the choice for them was

explained in section A.5.

B.2. Propositions Culture Model

Compared to the Personality model, there are two common propositions: P1 and P2. The other propositions are

different. The ‘new’ propositions are described in the text below.

B.1.1. P3: Cultural Values –Work Practices

An important characteristic of NWoW work practices is that they increase employees’ freedom to decide for

themselves where they work, when they work, and how they work. This implies an increase in autonomy of

employees.

The degree in which autonomy is given to and accepted by employees, is subject to cultural differences (see

literature review). This point of view could be supported by a huge amount of literature that attributes

differences in work practices to differences in cultural values (e.g. Kogut & Sing, 1988). For that reason, it is

expected that in some cultures NWoW work practices are more common than in other cultures. So:

P3: Specific Cultural Values impact Work Practices

B.1.2. P4: Cultural Values – Work Practices/Work Performance

Proposition 3 expects that the presence of certain Work Practices is influenced by Cultural Values; they are

more likely to be applied under specific cultural conditions than under others.

However, we are not only interested in how cultural values impact the presence of NWoW Work Practices, but

also in how cultural values influence the effect of Work Practices. A conflict between core Cultural Values and


(one or more) Work Practices is expected to have a different impact on (one or more) Work Outcomes than a

match between these two. This assumption is expressed in the following proposition:

P4: Specific Cultural Values impact the relationship between Work Practices and Work Performance.

B.1.2. P5: Cultural Values (Work Atmosphere) – Work Practices/Work Performance

To understand the relationship described in the previous proposition, it might be valuable to be more specific

by adding the concept of Work Atmosphere.

It was proved that the elements of Work Atmosphere (empowerment and control) are affected by Cultural

Values (Hofstede, 2001) and besides, it is reasonable that Work Atmosphere impacts the relationship between

Work Practices and Work Performance, because these elements might be supportive (or not) to the effects of

NWoW Work Practices on Work Performance. Therefore:

P5: Specific Cultural Values impact via Work Atmosphere the relationship between Work Practices and Work

Performance.

B.1.4. P6: Cultural Values – Work Arrangements

There are multiple ways to arrange work and therefore management has to make choices. Besides, scientific

literature demonstrates that ways of organizing work are culture-bound (Hofstede et al., 2010). Leaving aside

all other considerations, it could be that managers are likely to prefer Work Arrangements that match their

Cultural Values over the ones that are lacking harmony with their deeply rooted tendencies. The relationship

between Cultural Values and Work Arrangements is expressed in the following proposition:

P6(C): Specific Cultural Values impact Work Arrangements.

B.1.5. Summary of the Propositions

These are the propositions that have been formulated for the Personality model:



P3: Specific Cultural Values impact Work Practices.

P4: Specific Cultural Values impact the relationship between Work Practices and Work Performance.

P5: Specific Cultural Values impact via Work Atmosphere the relationship between Work Practices and Work

Performance.

P6: Specific Cultural Values impact Work Arrangements.


C. Methodology

This chapter describes how Hofstede’s framework could be included in the conceptual model from a

methodological point of view and discusses what the implications are for the data analysis.

C.1. Collecting Data on Culture

Researchers applying Hofstede’s framework have two options. First of all, they can use existing Hofstede

country scores. These scores are published on Hofstede’s website (geert-hofstede.com) or could be derived

from his books (e.g. Hofstede, 2001). Alternatively, researchers can measure the cultural values themselves

(from which they can compose their ‘own’ country scores). For this purpose, survey questions (and

corresponding formulas) were made available by Hofstede, which can be downloaded and used for free.

There are several reasons why the latter option is preferred for this research (measuring values instead of using

existing scores).

First of all, the focus is on a select group of people: knowledge workers who are employed (or having their own

company).

Secondly, especially when the focus is on workers who are all employed by the same multinational

organization, respondents might not be representative for the population of their country. It could be that they

are ‘infected’ by foreign values (e.g. of their organizations’ home culture) and it is likely most of them come

from the same specific areas of their countries.

Thirdly, when there is much within country variation (i.e. subcultures), using existing data might give a

distorted/incomplete image.

Fourthly, Hofstede’s view that cultural values were established in the early childhood and are quite stable, is

not undisputed. The ‘ocean metaphor’ (Tung & Verbeeke, 2010; see section A.4.6) supposes that values may

change suddenly because of external events.

Fifthly, the Hofstede scores are quite old: they are based on data from a few decades ago. Measuring cultural

values gives an extra guarantee that appropriate data is used.

Last but not least, it might be useful for the analyses when cultural values could be traced back to individuals.

C.2. Measuring Cultural Values

To measure the cultural dimensions of his framework, Hofstede developed the Values Survey Module 2008

(VSM 2008). This module is the successor of VSM 94 and is also the latest version of the VSM.

Besides the five Hofstede dimensions (Power Distance, Individualism vs. Collectivism, Masculinity vs.

Femininity, Uncertainty Avoidance, and Long vs. Short-Term Orientation), also two dimensions which were

based on research by Michael Minkov (Indulgence vs. Restraint and Monumentalism vs. Self-Effacement) could

be measured by using VSM 08. The latter two were added ‘by way of experiment’, as they might reveal ‘new’

aspects of national culture. So VSM 08 covers all Cultural Values of the conceptual model and no additional

measure is needed for cultural aspects.


VSM measures each of the seven dimensions by four questions on five-point scales. This means that VSM 08

has a total of 28 ‘content questions’. The other six questions that belong to VSM 08 are about demographics

(gender, age, education level, kind of job, present nationality, and nationality at birth).

For each separate dimension, an index formula was defined in the manual belonging to VSM 08 to aggregate

the individual answers to the country level. The Power Distance Index (PDI), for instance, can be calculated by

substituting the following formula: PDI = 35(m07 – m02) + 25(m23 – m26) + C(pd), in which m07 is the mean

score for question 07 and C(pd) a positive or negative constant. This constant can be chosen to shift the PDI

scores to values between 0 and 100; it does not affect the comparison between countries, however.

C.3. Levels of Analysis

In chapter 2, Hofstede’s definition of culture was cited: ‘the collective mental programming of the mind’.

Especially the word ‘collective’ in this definition is important. According to Hofstede, his dimensions are

exclusively suitable for country-level studies and could not be used for studying individual personalities and

organizational cultures.

Hofstede equates culture to forests and individuals to trees to show the difference between the individual and

country level. For comparing organizational cultures (of companies within the same country), Hofstede

developed a distinct framework (Hofstede, 2008).

Despite Hofstede’s arguments for using his dimensions only at the country-level, they have been applied by a

majority of researchers at individual or group/organizational levels (Kirkman et al., 2006: p.228). According to

Sivakumar & Nakata (2001: p.557), the validity of using a certain level as unit of cultural analysis is determined

by the research question in case.

Earley (2006) researched culture at the individual level, operationalizing it purely as a psychological construct.

He admits that this approach might take “the ‘culture’ out of culture”, neglecting that culture is collective by

nature, but defends his method by pointing at limitations of Hofstede’s approach. Hofstede ignores that there

is interaction among cultural values. An aggregate measure of culture is problematic as well, because it might

overwhelm variability among subgroups (p.924, 925).

In short: there is a contrast between doctrine (Hofstede) and practice: both low (individual) and high (country)

levels of analysis have been used and defended by scholars and both have their advantages and disadvantages.

It might be interesting to validate propositions of the Culture Model both at a country-level and at an

individual-level. At the country-level data is aggregated and the number of cases is identical to the number of

countries involved. If the (majority of) respondents are ‘similar’ on all criteria other than nationality, the

influence of certain national cultures could be analyzed (Hofstede, 2008).

However, when the goal of the study is to find out how cultural values are related to work practices and how

these values influence the proposed relationship between NWoW work practices and work performance, an

individual level of analysis is needed. This kind of research might help to make predictions regarding people in

other countries (based on how culture is ‘composed’ in that country).

Appendix 2 – ‘Big Model’

WORK PRACTICES

People Reflexivity

Reflection on working hours and schedule Reflection on choice of location

Reflection on media use Flexibility (time)

Flex-time

Place Flexibility (place)

At the office At external office or meeting location

At client location On the road

At home Task / work place fit

Socialize Learn Focus

Collaborate

Technology Media use

Face-to-face Video conference

Telephone (conference) Chat / instant messaging

Electronic mail Voice mail

Fax Documents

Other

WORK ATMOSPHERE Empowerment

Meaning Competence

Self determination Impact Control

Behavioural control Social control

Mutual control

WORK PERFORMANCE Employee satisfaction

Work life balance

Productivity

WORK PRACTICES

People Policies / Agreements Freedom work location Freedom working hours

Telework facilitation rate

Place Workplace design

Room sharing Own work place

Backup place

Technology Media availability

Laptop Smartphone

Mobile internet Access via internet to appl. & data

PERSONALITY TRAITS Extraversion

Agreeableness

Conscientiousness

Neuroticism

Openness


Appendix 3A – Survey Instrument (Dutch)

INTRODUCTION PAGE Hartelijk dank voor uw bereidheid om deze vragenlijst in te vullen! Mijn naam is Christian van Esch en ik hoop binnenkort af te studeren aan de Erasmus Universiteit Rotterdam. Om die reden ben ik momenteel bezig met een onderzoek naar de relatie tussen persoonlijkheid en het (al dan niet) gebruik van flexibele werkpraktijken. Uw medewerking aan dit onderzoek wordt zeer op prijs gesteld! Het invullen van de vragenlijst zal ongeveer 15 minuten in beslag nemen. De survey is in principe anoniem en antwoorden worden volledig vertrouwelijk behandeld. Wel wordt aan het einde van de vragenlijst om een e-mailadres gevraagd. Deze vraag hoeft u alleen in te vullen als u een samenvatting van de onderzoeksresultaten wilt ontvangen. Let op: er zijn geen goede of foute antwoorden! Mocht u vragen hebben, dan kunt u contact met mij opnemen door een mailtje te sturen naar: [email protected]. Klik op 'Verder' om de vragenlijst te beginnen. IDEAL JOB 1) Aan welke eigenschappen voldoet -volgens u- de ideale baan? Geef aan op onderstaand spectrum waar uw voorkeuren liggen. U kunt hierbij uw huidige baan buiten beschouwing laten.

Werknemer kiest zelf zijn/haar werklocatie(s) 1 2 3 4 5 6 7 Werkgever bepaalt werklocatie(s) Werkgever beslist hoe het werk wordt gedaan 1 2 3 4 5 6 7 Werknemer beslist hoe het werk wordt gedaan Input control (nadruk op proces) 1 2 3 4 5 6 7 Output control (nadruk op resultaat) Traditionele vormen van communicatie 1 2 3 4 5 6 7 Communicatie dmv moderne communicatietechnologieën Open kantoortuin 1 2 3 4 5 6 7 Kantoor met kleine (privé)kamertjes Werktijden staan vast 1 2 3 4 5 6 7 Werknemer kiest zelf zijn/haar werktijden Mobiel ('overal') werken 1 2 3 4 5 6 7 Werken op een vaste locatie (bijv. het kantoor)

BIG FIVE INVENTORY I De volgende vragen hebben betrekking op uw persoonlijkheid. Hierbij geldt: er zijn geen goede of foute antwoorden. 1 = Geheel mee oneens 2 = Oneens 3 = Neutraal 4 = Mee eens 5 = Geheel mee eens 2) Ik zie mijzelf als iemand die...

- ...spraakzaam is - ...geneigd is kritiek te hebben op anderen (R) - ...grondig te werk gaat - ...somber is - ...origineel is, met nieuwe ideeën komt - ...terughoudend is (R) - ...behulpzaam en onzelfzuchtig ten opzichte van anderen is - ...een beetje nonchalant kan zijn (R) - ...ontspannen is, goed met stress kan omgaan (R)


- ...benieuwd is naar veel verschillende dingen - ...vol energie is - ...snel ruzie maakt (R) - ...een werker is waar men van op aan kan - ...gespannen kan zijn - ...scherpzinnig, een denker is - ...veel enthousiasme opwekt - ...vergevingsgezind is - ...doorgaans geneigd is tot slordigheid (R) - ...zich veel zorgen maakt - ...een levendige fantasie heeft - ...doorgaans stil is (R) - ...mensen over het algemeen vertrouwt

BIG FIVE INVENTORY II 3) Ik zie mijzelf als iemand die...

- ...geneigd is lui te zijn (R) - ...emotioneel stabiel is, niet gemakkelijk overstuur raakt (R) - ...vindingrijk is - ...voor zichzelf opkomt - ...koud en afstandelijk kan zijn (R) - ...volhoudt tot de taak af is - ...humeurig kan zijn - ...waarde hecht aan kunstzinnige ervaringen - ...soms verlegen, geremd is (R) - ...attent en aardig is voor bijna iedereen - ...dingen efficiënt doet - ...kalm blijft in gespannen situaties (R) - ...een voorkeur heeft voor werk dat routine is (R) - ...hartelijk, een gezelschapsmens is - ...soms grof tegen anderen is (R) - ...plannen maakt en deze doorzet - ...gemakkelijk zenuwachtig wordt - ...graag nadenkt, met ideeën speelt - ...weinig interesse voor kunst heeft (R) - ...graag samenwerkt met anderen - ...gemakkelijk afgeleid is (R) - ...het fijne weet van kunst, muziek, of literatuur

Mocht u opmerkingen hebben met betrekking tot de voorgaande vragen, dan kunt u die hier noteren (OPTIONEEL) WORK PRACTICES I De vragen op de volgende pagina's hebben betrekking op uw huidige baan. 4) Geef aan in hoeverre u het eens bent met de volgende stellingen: <<Time dependency>>

- Het overgrote deel van mijn werkzaamheden is gebonden aan vaste tijden - De aard van mijn werk stelt mij niet in staat om op door mij gewenste tijden te werken - Ik kan mijn werk alleen op vooraf vastgestelde tijden uitvoeren

<<Location dependency>> - Het overgrote deel van mijn werkzaamheden is gebonden aan (een) vaste locatie(s) - De aard van mijn werk stelt mij niet in staat om op een locatie van mijn keuze te werken - Ik kan mijn werk alleen op vooraf vastgestelde locaties uitvoeren


5) Geef aan in procenten hoe uw werktijd verdeeld is over onderstaande locaties. <<Flex-place>> U kunt alleen gehele procentuele getallen invullen; het totaal dient gelijk te zijn aan 100%.

- Op kantoor __ - Op extern kantoor of vergaderlocatie __ - Op klantlocatie __ - Onderweg (bijvoorbeeld trein: dit betreft geen woon-werk verkeer) __ - Thuis __

6) Geef aan in hoeverre u het eens bent met de volgende stellingen: <<Reflection on choice of location>>

- Ik overweeg zorgvuldig welke werklocatie het meest geschikt is voor de taak die ik uit ga voeren - Wanneer ik merk dat een werklocatie niet geschikt is voor een bepaalde taak die ik uitvoer, kies ik een

andere werklocatie - Ik probeer mijn taken te matchen met mijn werklocatie

WORK PRACTICES II 7) Verdeel uw werkzaamheden over de volgende categorieën Geef aan hoe uw werkzaamheden verdeeld zijn over de volgende categorieën van werk-gerelateerde activiteiten. Neem een gemiddelde week als uitgangspunt. Let op: u kunt alleen hele getallen invoeren. Het totaal moet gelijk zijn aan 100% (u hoeft het %-teken niet in te voeren).

- Sociale interactie / pauzes met collega's __ - Training / nieuwe vaardigheden leren __ - Gefocust individueel werk (dat concentratie vereist) __ - Werken met iemand anders / een groep (face-to-face of dmv tele-/videoconferentie) __ - Overig (bijv. papierwerk zoals faxen, kopiëren, printen) __

8) Geef aan in hoeverre u het eens bent met de volgende stellingen: Neem alle locaties in beschouwing waar u werkt in een gemiddelde week (bijv. op kantoor, thuis etc.). De categorieën van werk-gerelateerde activiteiten komen overeen met de vorige vraag. Mocht één of meer vra(a)g(en) niet relevant zijn in uw situatie, dan kan/kunnen deze worden overgeslagen. <<TWPF Socialize>>

- De beschikbaarheid van plaatsen voor sociale interactie voldoet aan mijn wens - Ik kan op elk gewenst moment een plek vinden voor sociale interactie - Mijn behoeften aan plaatsen voor sociale interactie zijn volledig vervuld binnen de huidige situatie

<<TWPF Learn>> - De beschikbaarheid van plaatsen voor training / nieuwe vaardigheden leren voldoet aan mijn wens - Ik kan op elk gewenst moment een plek vinden voor training / nieuwe vaardigheden leren - Mijn behoeften aan plaatsen voor training / nieuwe vaardigheden leren zijn volledig vervuld binnen de

huidige situatie <<TWPF Focus>>

- De beschikbaarheid van plaatsen voor gefocust individueel werk (dat concentratie vereist) voldoet aan mijn wens

- Ik kan op elk gewenst moment een plek vinden voor gefocust individueel werk (dat concentratie vereist)

- Mijn behoeften aan plaatsen voor gefocust individueel werk (dat concentratie vereist) zijn volledig vervuld binnen de huidige situatie

<<TWPF Collaborate>> - De beschikbaarheid van plaatsen voor werken met iemand anders / een groep voldoet aan mijn wens - Ik kan op elk gewenst moment een plek vinden voor werken met iemand anders / een groep - Mijn behoeften aan plaatsen voor werken met iemand anders / een groep zijn volledig vervuld binnen

de huidige situatie WORK PRACTICES III 9) Geef aan in hoeverre u het eens bent met de volgende stellingen: <<Reflection on working hours and schedule>>


- Ik overweeg zorgvuldig welke tijden het meest geschikt zijn voor werk, gezien mijn persoonlijke situatie of de situatie van mijn huisgenoten / gezinsleden

- Wanneer ik merk dat werktijden niet aansluiten op mijn persoonlijke situatie of de situatie van mijn huisgenoten / gezinsleden, dan pas ik mijn tijdschema aan

- Ik probeer mijn werktijden te matchen met mijn persoonlijke situatie of de situatie van mijn huisgenoten / gezinsleden

10) Geef aan in hoeverre u het eens bent met de volgende stellingen: Met medium wordt het type communicatiemiddel bedoeld dat u gebruikt om te communiceren (bijvoorbeeld e-mail, chat of telefoon) <<Reflection on media use>>

- Ik overweeg zorgvuldig welk medium het meest geschikt is voor welk type bericht - Wanneer ik merk dat een bericht niet aankomt via het ene medium (bijvoorbeeld e-mail), dan stap ik

over op een meer interactief medium - Ik probeer het type bericht te matchen met het medium - Ik controleer altijd of mijn bericht is aangekomen zoals bedoeld

11) Op welke manier(en) heeft u voornamelijk contact met uw collega's en manager (of opdrachtgever)? <<Media use>> Verdeel het totale contact met uw collega's en manager over de volgende manieren van contact. U kunt alleen gehele getallen invullen (in procenten): het totaal dient gelijk te zijn aan 100% (u hoeft het %-teken niet in te voeren).

- Face-to-face __ - Video Conferentie __ - Telefoon / Telefoon Conferentie __ - Chat / Instant Messaging __ - E-mail __ - Voice Mail __ - Fax __ - Documenten __ - Anders __

Mocht u opmerkingen hebben met betrekking tot de voorgaande vragen, dan kunt u die hier noteren (OPTIONEEL) WORK ATMOSPHERE I 12) Geef aan in hoeverre u het eens bent met de volgende stellingen: <<Meaning>>

- Het werk dat ik doe, is erg belangrijk voor mij - Mijn werkactiviteiten hebben persoonlijke betekenis voor mij - Het werk dat ik doe, is betekenisvol voor mij

<<Competence>> - Ik heb vertrouwen in mijn vermogen om mijn werk te doen - Ik ben zelfverzekerd voor wat betreft mijn capaciteiten om mijn werkzaamheden te verrichten - Ik heb de vaardigheden aangeleerd die noodzakelijk zijn voor mijn werk

<<Self-determination>> - Ik heb aanzienlijke zelfstandigheid om te bepalen hoe ik mijn werk doe - Ik kan zelf beslissen hoe ik mijn werk moet aanpakken - Ik heb ruime gelegenheid voor onafhankelijkheid en vrijheid ten aanzien van de manier waarop ik mijn

werk verricht <<Impact>>

- Mijn impact op hetgeen er binnen mijn afdeling gebeurt, is groot - Ik heb veel controle over hetgeen er binnen mijn afdeling gebeurt - Ik heb een aanzienlijke invloed op hetgeen er binnen mijn afdeling gebeurt


WORK ATMOSPHERE II 13) Geef aan in hoeverre u het eens bent met de volgende stellingen: <<Outcome control>>

- Ik word beloond voor het leveren van hoogwaardige producten en diensten aan de klant - Salarisverhogingen zijn afhankelijk van hoe goed ik mijn werk verricht - Onderscheidingen op mijn afdeling zijn afhankelijk van hoe goed de medewerkers hun werk verrichten - Binnen de organisatie wordt men beoordeeld op werkresultaten (en niet op het aantal uren dat men

werkt) <<Behavioural control>>

- In mijn werk dien ik vastomlijnde en vooraf vastgestelde processen of regels te volgen - Ik word in mijn werk afgerekend op de manier waarop ik mijn werkzaamheden verricht, niet op de

uitkomsten van mijn werkzaamheden - Mijn daadwerkelijke werkresultaten worden zelden vergeleken met geplande resultaten - Ik heb regelmatig overleg met mijn manager om mijn werkzaamheden en functioneren te bespreken

<<Social control>> - De organisatie heeft geen invloed gehad op mijn houding en gedrag (R) - Sinds mijn aanstelling bij de organisatie zijn mijn persoonlijke waarden en die van de organisatie

steeds meer gelijk geworden - De managers van de organisatie hebben mij uitgelegd wat er van mij verwacht wordt in mijn functie - Ik heb de waarden geleerd die belangrijk zijn binnen de organisatie

<<Mutual control>> - Mijn collega' s controleren onderling of iedereen voldoende bijdraagt aan gezamenlijke projecten of

doelen - Mijn collega's houden in de gaten of iedereen zijn verantwoordelijkheden ten aanzien van

gezamenlijke projecten of doelen nakomt - In het geval van gezamenlijke projecten of doelen wordt zelden onderling nagegaan of iedereen de

gestelde deadlines haalt (R) - De voortgang van collega’s aangaande gezamenlijke projecten of doelen wordt door collega’s

onderling in de gaten gehouden Mocht u opmerkingen hebben met betrekking tot de voorgaande vragen, dan kunt u die hier noteren (OPTIONEEL) WORK PERFORMANCE <<Employee satisfaction>> 14) Geef aan in hoeverre u het eens bent met de volgende stellingen:

- Als een bekende op zoek is naar werk, zou ik hem of haar deze organisatie aanbevelen - Het geeft mij persoonlijk bevrediging wanneer ik mijn werk goed uitvoer - Ik vertel anderen met trots dat ik deel uitmaak van deze organisatie - Deze organisatie is voor mij de beste organisatie om voor te werken

15) Geef aan in hoeverre u het eens bent met de volgende stellingen: <<Work life balance>>

- Ik ben in staat om een goede balans te vinden tussen de eisen die mijn werk stelt en mijn gezins- en privé leven

- Ik heb buiten mijn werk voldoende tijd om een goede balans tussen mijn werk en mijn gezins- en privé leven te vinden

- Wanneer ik vakantie heb, kan ik mezelf losmaken van het werk en me goed amuseren - Ik ben erin geslaagd om een zeer goede balans te treffen tussen mijn werk en mijn gezins- en privé

leven 16) Geef aan in hoeverre u het eens bent met de volgende stellingen: <<Productivity>>


- Ik geloof dat ik een effectieve medewerker ben - Binnen mijn werkgroep behoren mijn eigen prestaties naar mijn oordeel tot de beste 25% - Ik ben tevreden over de kwaliteit van mijn werkresultaten - Ik werk zeer efficiënt - Ik ben een zeer productieve medewerker

WORK ARRANGEMENTS IN HET GEVAL DAT UW ORGANISATIE BESCHIKT OVER MEERDERE KANTOREN, BEANTWOORD DAN DE VOLGENDE DRIE VRAGEN VOOR HET KANTOOR WAAR HET VAAKST WERKT 17) Heeft u een eigen werkplek / bureau in het kantoor van uw organisatie?

Ja, ik heb een eigen werkplek / bureau

Nee, werkplekken / bureaus zijn flexibel 18) Met hoeveel andere mensen deelt u een kamer in het kantoor van de organisatie?

Ik heb een kamer alleen

Met 1-2 anderen

Met 3-8 anderen

Met 9-23 anderen

Met meer dan 23 anderen 19) Heeft het kantoor 'backup ruimtes' voor speciale taken zoals geconcentreerd werk, persoonlijke telefoongesprekken en ontmoetingen?

Ja

Nee 20) Beoordeel de mate van vrijheid die u in principe heeft om uw eigen werktijden te kiezen - op een schaal van 1 (geen vrijheid) tot 10 (volkomen vrijheid). Het is niet noodzakelijk dat u van deze vrijheid gebruik maakt. Voer een geheel getal in. __ 21) Beoordeel de mate van vrijheid die u in principe heeft om uw eigen werklocatie(s) te kiezen - op een schaal van 1 (geen vrijheid) tot 10 (volkomen vrijheid). Het is niet noodzakelijk dat u van deze vrijheid gebruik maakt. Voer een geheel getal in. __ 22) Wordt door de organisatie videoconferencing mogelijk gemaakt / gefaciliteerd?

Ja

Nee 23) Welke van de volgende faciliteiten voor telewerk (d.w.z. werken op een andere locatie dan het kantoor) worden door de organisatie aan u verstrekt?

Laptop Smartphone Mobiel internet Toegang via internet tot bedrijfsapplicaties / data Geen van deze faciliteiten

24) Het geheel overziend, hoe beoordeelt u de mate waarin de organisatie u de mogelijkheden verschaft voor telewerk - op een schaal van 1 (totaal niet) tot 10 (volkomen)? Het is niet noodzakelijk dat u van deze mogelijkheden gebruik maakt. Voer een geheel getal in. __ Mocht u opmerkingen hebben met betrekking tot de voorgaande vragen, dan kunt u die hier noteren (OPTIONEEL)


OPEN QUESTIONS 25) Kun je aangeven hoeveel uur uw huidige dienstverband bedraagt? Het betreft hier het contractueel overeengekomen aantal uren, exclusief overwerk. 26) Hoeveel uur bent u gemiddeld per week bezig met uw werk? Het betreft hier het werkelijke totaal aantal uren, inclusief overwerk, zakelijk verkeer (géén woon-werk verkeer), opleidingen, bijeenkomsten etc. __ uur/uren per week 27) Hoeveel uur besteedt u in een gemiddelde week aan woon-werk verkeer? met woon-werk verkeer wordt het reizen tussen de plaats waar u woont en de plaats waar u werkt bedoelt. __ uur/uren per week 28) Hoeveel uur werkt u in een gemiddelde week buiten reguliere werktijden* (bijv. niet van 9 tot 5)? *hierbij gaat het ook om het aantal uren dat u werkt op dagen dat u niet gecontracteerd bent, inclusief het weekend. __ uur/uren per week 29) Hoeveel van deze uren is overwerk (niet-contractueel vastgestelde uren)? __ uur/uren per week 30) Hoeveel uur neemt u vrij tijdens reguliere werktijden voor privé-aangelegenheden (in een gemiddelde werkweek)? __ uur/uren per week 31) Welk percentage van uw werktijd besteedt u aan contact met uw collega's en manager in een normale week? __ % PERSONAL INFORMATION 32) Wat is uw geslacht?

Man

Vrouw 33) Wat is uw leeftijd? __ jaar 34) Wat is de beste omschrijving van uw thuissituatie?

Alleenstaand

Partner (ook werkend) en minderjarig(e) kind(eren)

Partner (niet werkend) en minderjarig(e) kind(eren)

Partner (ook werkend)

Partner (niet werkend)

Overig (graag toelichten): __________ 35) Wat is uw opleidingsniveau?

- graag één selecteren... - Basisonderwijs - Middelbaar onderwijs - LBO - MBO - HBO - WO (drs. / MSc.) - Professionele graad (bijvoorbeeld MBA) - Gepromoveerd (PhD)

36) In welke industrie is uw organisatie voornamelijk actief?


- graag één selecteren... - Landbouw, bosbouw en visserij - Winning van delfstoffen - Industrie - Productie en distributie van en handel in elektriciteit, aardgas, stoom en gekoelde lucht - Winning en distributie van water; afval- en afvalwaterbeheer en saneringen - Bouwnijverheid - Groothandel en detailhandel; reparatie van auto’s - Vervoer en opslag - Logies-, maaltijd- en drankverstrekking - Informatie en communicatie - Financiële instellingen - Verhuur van en handel in onroerend goed - Advisering, onderzoek en overige specialistische zakelijke dienstverlening - Verhuur van roerende goederen en overige zakelijke dienstverlening - Openbaar bestuur, overheidsdiensten en verplichte sociale verzekeringen - Onderwijs - Gezondheidszorg en welzijnszorg - Cultuur, sport en recreatie - Overige dienstverlening - Huishoudens als werkgever; niet-gedifferentieerde productie van goederen en diensten door

huishoudens voor eigen gebruik - Extraterritoriale organisaties en lichamen

37) Wat is de beste omschrijving van uw positie binnen de organisatie?

Werknemer (geen management functie)

Top-manager

Midden-manager

Operationeel manager

Onafhankelijk / ingehuurd 38) Wat is de beste omschrijving van uw afdeling binnen de organisatie?

Finance/Accounting

Human Resources

Information Technologie/MIS

Administratie

Sales

Marketing

Research en/of Development

Manufacturing

Engineering

Overig (graag toelichten):__________ Mocht u opmerkingen hebben met betrekking tot de voorgaande vragen, dan kunt u die hier noteren (OPTIONEEL) EMAIL U bent gekomen aan het einde van de vragenlijst. Heel hartelijk bedankt voor uw participatie! Er bestaat een mogelijkheid om na afloop van het onderzoek een samenvatting van de onderzoeksresultaten te ontvangen. Als u hiervoor in aanmerking wilt komen, vul dan hieronder uw gegevens in. Mocht u geen belangstelling hebben, dan kunt u onderstaande vragen overslaan.


Wat is uw e-mailadres? __________ Voor welke organisatie werkt u? __________ Selecteer uw voorkeur:

JA, ik ontvang graag een samenvatting van de onderzoeksresultaten na afloop FINAL PAGE Bedankt voor het invullen van de vragenlijst! Uw bijdrage wordt enorm gewaardeerd. Alle antwoorden zijn verzonden en u kunt dit scherm nu sluiten.


Appendix 3B – Survey Instrument (English)

1) To which properties does the ideal job meet -according to you-? Please indicate on the spectrum below what are your preferences are. Hereby, you should disregard your current job. 1. (R) Employee chooses work location(s) him-/herself 1 2 3 4 5 6 7 Employer determines work location(s) 2. Employer decides how the work is done 1 2 3 4 5 6 7 Employee decides how the work is done 3. Input control (emphasis on process) 1 2 3 4 5 6 7 Output control (emphasis on result) 4. Traditional forms of communication 1 2 3 4 5 6 7 Communication through modern comm. technologies 5. (R) Open office space 1 2 3 4 5 6 7 Office with small (private) rooms 6. Working hours are solid 1 2 3 4 5 6 7 Employee chooses his/her own working hours 7. (R) Mobile working (‘everywhere) 1 2 3 4 5 6 7 Working at one solid location (e.g. the office)

BIG FIVE INVENTORY I The following questions are related to your personality. Please note: there are no right or false answers. 1 = Strongly disagree 2 = Disagree 3 = Neutral 4 = Agree 5 = Strongly agree 2) I see myself as someone who…

- ...is talkative - ...tends to find fault with others (R) - ...does a thorough job - ...is depressed, blue - …is original, comes up with new ideas - …is reserved (R) - …is helpful and unselfish with others - …can be somewhat careless (R) - …is relaxed, handles stress well (R) - …is curious about many different things - …is full of energy - …starts quarrels with others (R) - …is a reliable worker - …can be tense - …is ingenious, a deep thinker - …generates a lot of enthusiasm - …has a forgiving nature - …tends to be disorganized (R) - …worries a lot - …has an active imagination - …tends to be quiet (R) - …is generally trusting

BIG FIVE INVENTORY II 3) I see myself as someone who…

- …tends to be lazy (R) - …is emotionally stable, not easily upset (R) - …is inventive - …has an assertive personality - …can be cold and aloof (R) - …perseveres until the task is finished - …can be moody - …values artistic, aesthetic experiences - …is sometimes shy, inhibited (R)


- …is considerate and kind to almost everyone - …does things efficiently - …remains calm in tense situations (R) - …prefers work that is routine (R) - …is outgoing, sociable - …is sometimes rude to others (R) - …makes plans and follows through with them - …get nervous easily - …likes to reflect, play with ideas - …has few artistic interests (R) - …likes to cooperate with others - …is easily distracted (R) - …is sophisticated in art, music, or literature

WORK PRACTICES I The survey starts by asking a number of questions about your current job.

4) Please indicate to which extent you agree with the following statements: <<Time dependency>>

- The majority of my work has to be carried out at set times - The nature of my work does not allow me to work the hours I would prefer - I can only do my work at predetermined times

<<Location dependency>> - The majority of my work has to be carried out at (a) fixed location(s) - The nature of my work does not allow me to work at a location I prefer - I can only work at predetermined locations

5) Indicate in percentages how your working time is divided across different locations. <<Flex-place>> Note you can only enter whole numbers in percentages; the total must equal 100%. You don't have to enter the %-sign.

- At the office __ - At external office or meeting location __ - At client location __ - On the road __ - At home __

6) Please indicate to which extent you agree with the following statements: <<Reflection on choice of location>>

- I carefully consider which work location is best suited to the task I am going to perform - When I notice that a work location is not suited to a specific task that I am performing, I will select a

different work location - I try to match my tasks to my work location

WORK PRACTICES II 7) How are your work tasks divided among the following workplace activities? Please divide your tasks among the following categories of workplace activity. Please note you can only enter whole numbers in percentages: the total must equal 100% (you don’t have to enter the %-sign).

- Social interaction / breaks with colleagues __ - Training / learning new skills __ - Focused individual work (requiring concentration) __ - Working with another person or group (face-to-face or tele/video conference) __ - Other (e.g. paperwork like faxing, copying, printing) __

8) Please indicate to which extent you agree with the following statements:


You should consider all locations at which you do your job (e.g. at the office, at home, etc.). Please note that this question deals with the same workplace activities as in the previous question. You are allowed to skip questions that are not relevant in your situation. <<TWPF Socialize>>

- The availability of places for social interaction matches my desire - I can find a place for social interaction at any time I need it - My needs for places for social interaction are fully met within the current situation

<<TWPF Learn>> - The availability of places for training / learning new skills matches my desire - I can find a place for training / learning new skills at any time I need it - My needs for places for training / learning new skills are fully met within the current situation

<<TWPF Focus>> - The availability of places for focused individual work (requiring concentration) matches my desire - I can find a place for focused individual work (requiring concentration) at any time I need it - My needs for places for focused individual work (requiring concentration) are fully met within the

current situation <<TWPF Collaborate>>

- The availability of places for working with another person or group matches my desire - I can find a place for working with another person or group at any time I need it - My needs for places for working with another person or group are fully met within the current

situation WORK PRACTICES III 9) Please indicate to which extent you agree with the following statements: <<Reflection on working hours and schedule>>

- I carefully consider which hours are best suited for work, given my personal situation or the situation of the members of my household/family

- When I notice that working hours don’t suit with my personal situation or with the situation of the members of my household/family, I will adjust my time schedule

- I try to match my working hours with my personal situation or with the situation of the members of my household/family

10) Please indicate to which extent you agree with the following statements: Medium refers to the means of communication that you use to communicate (for example e-mail, chat or telephone) <<Reflection on media use>>

- I carefully consider which medium is best suited to what type of message - When I notice that a message does not come across via one medium (for example e-mail), then I will

switch to a more interactive medium - I try to match the type of message with the medium - I always check whether my message has been received as intended

11) In which way do you interact with your colleagues and manager? <<Media use>> Divide the interaction that you have with your colleagues and manager across the following means of interaction. Please note you can only enter whole numbers in percentages: the total must equal 100% (you don't have to enter the %-sign).

- Face-to-face __ - Video Conference __ - Telephone / Telephone Conference __ - Chat / Instant Messaging __ - Electronic Mail __ - Voice Mail __ - Fax __ - Documents __ - Other __


WORK ATMOSPHERE I 12) Please indicate to which extent you agree with the following statements: <<Meaning>>

- The work that I do is very important to me - My job activities are personally meaningful to me - The work I do is meaningful to me

<<Competence>> - I am confident about my ability to do my job - I am self-assured about my capabilities to perform my work activities - I have mastered the skills necessary for my job

<<Self-determination>> - I have significant autonomy in determining how I do my job - I can decide on my own how to go about doing my work - I have considerable opportunity for independence and freedom in how I do my job

<<Impact>> - My impact on what happens in my department is large - I have a great deal of control over what happens in my department - I have significant influence over what happens in my department

WORK ATMOSPHERE II 13) Please indicate to which extent you agree with the following statements: <<Outcome control>>

- I am rewarded for delivering high-quality products and services to the customer - Salary increases are dependent on how well I do my work - In my department, awards are dependent on how well the employees do their work - Within [the organisation] people are evaluated on work results (and not on the amount of hours that

they work) <<Behavioural control>>

- My work follows well-defined and predetermined processes - In my work, I am judged on the way in which I do my work, not on the outcome of my work - My actual working results are seldom compared with planned results - I have regular meetings with my manager to discuss my work and performance

<<Social control>> - The organisation has not influenced my attitude and behaviour (R) - Since my employment with the organisation my personal values and those of the organisation have

become increasingly similar - The managers of the organisation have explained to me what is expected of me in my position - I have learnt which values are important within the organisation

<<Mutual control>> - My colleagues check among themselves whether everybody contributes sufficiently towards common

projects and objectives - My colleagues check whether everybody meets their responsibilities with respect to common projects

and objectives - In case of common projects and objectives, people hardly ever check whether everybody meets the

deadlines (R) - The progress of colleagues with respect to projects and objectives is checked mutually by those

colleagues WORK PERFORMANCE <<Employee satisfaction>> 14) Please indicate to which extent you agree with the following statements:

- If a friend is looking for a job, I would recommend this organisation to him or her - It gives me personal satisfaction when I carry out my work well - I tell others with pride that I am part of this organisation - This organisation is the best organisation for me to work for

<<Work life balance>>


15) Please indicate to which extent you agree with the following statements: - I am able to find a proper balance between the demands of my work and my family and private life - I have sufficient time outside of work to find a proper balance between my work and my family and

private life - When I am on holiday, I can disassociate myself from my work and enjoy myself - I have achieved a very good balance between my work and my family and private life

16) Please indicate to which extent you agree with the following statements: <<Productivity>>

- I believe that I am an effective employee - Within my working group, I believe that my own performance is among the best 25% - I am satisfied with the quality of my working results - I work extremely efficiently - I am an extremely productive employee

WORK ARRANGEMENTS IN CASE YOUR COMPANY HAS MULTIPLE OFFICES, PLEASE ANSWER THE NEXT THREE QUESTIONS CONSIDERING THE OFFICE WHERE YOU WORK MOST OFTEN. 17) Do you have your own work place / desk in the office of the company?

Yes, I have my own work place / desk

No, work places / desks are flexible 18) With how many other persons do you share a room within the office of the company?

I have a private room




With more than 23 other persons 19) Does the office have 'backup spaces' for specific tasks, such as concentrated work, private phone calls, and meetings?

Yes

No 20) Please rate the amount of freedom management gives you in determining your own working hours - on a scale from 1 (no freedom) to 10 (full freedom) It is not necessary that you use this freedom. Please enter a whole number. __ 21) Please rate the amount of freedom management gives you in determining your own work location(s) - on a scale from 1 (no freedom) to 10 (full freedom) It is not necessary that you use this freedom. Please enter a whole number. __ 22) Is videoconferencing made possible / facilitated by the organization?

Yes

No 23) Which of the following facilities for telework (i.e. working at another location than the office of the company) are provided to you by the company?

Laptop Smart phone Mobile internet Access via internet to business applications / data None of these facilities


24) Overall, how do you rate the degree in which the company facilitates you for telework - on a scale from 1 (not at all) to 10 (in full)? It is not necessary that you use this freedom. Please enter a whole number. __

OPEN QUESTIONS 25) Could you please indicate for how many hours you are currently employed? This concerns the contractually agreed number of hours, excluding overtime. __ hours per week 26) How many hours per week do you spend on your work on average? This concerns the actual total number of hours, including overtime, business travel (not commuter travel), education, meetings, etc. __ hours per week 27) How many hours per week do you spend on commuter travel? by commuter travel we mean travel between your place of residence and place of work. __ hours per week 28) How many hours do you work in an ordinary week outside regular working hours* (e.g. not from 9 to 5)? *also mention the hour(s) you worked on day(s) you aren’t contracted, including the weekend. __ hour(s)

29) How many of these hours are overwork (non-contractually agreed hours)? __ hour(s)

30) How many hours do you take off during regular working hours for private matters? __ hour(s)

31) What percentage of your time do you spend on contact with your colleagues and manager in an ordinary week? __ %

PERSONAL INFORMATION 32) What is your gender?

Male

Female 33) What age are you? __ years old 34) What is the best description of your private situation?

Single

With partner (employed) and (a) minor child(ren)

With partner (unemployed) and (a) minor child(ren)

With partner (employed)

With partner (unemployed)

Other (please specify):__________ 35) What is your level of education? [[categorisation based on the Dutch education sysyem]] 36) In which sector is your organization mainly active? [[Dutch sector classification Centraal Bureau voor de Statistiek ]]


37) What is the best description of your position within the organization?

Employee (no management function)

Top manager

Middle manager

Operational manager

Independent / hired 38) What is the best description of your department within the organization?

Finance/Accounting

Human Resources

Information Technologie/MIS

Administration

Sales

Marketing

Research and/or Development

Manufacturing

Engineering

Other (please specify):__________


Appendix 3C – Context Sheet

The context sheet contains the following question on the three dimensions:

People (Policies/Agreements)

- Employees are trained in using work location(s) as good as possible

- Employees are trained in collaborating virtually

- Managers are trained in coaching leadership and result-driven management

- There are clear agreements on availability

- There is a 'physical minimum' defined within teams (e.g. regular meetings at the office)

- There is a reliance based management style (employees needn't account for how, where, and when

they do their work)

- There are timesheets

- Employees could choose their own working hours

- Employees could choose their own working location

- There are a governance model and KPIs to measure output of employees

Place (Workplace design)

- The office is divided in separate rooms

- The office is (half) open

- The office is divided based on activity-related working

- In the office, allocation of work places to persons is fully flexible

- Employees are facilitated to work at home

- Employees are facilitated for telework (performing tasks while commuting)

Technology (Media availability)

- All information needed by our employees in order to their work is available digitally

- Employees do have video conferencing on their personal workplace

- Employees do have instant messaging / unified communications on their personal workplace

- Employees are facilitated for using web 2.0 network services (LinkedIn, Facebook, Twitter etc.)

- Employees have mobile access via internet to business applications and data

- Employees are equipped with laptops


Appendix 4A – Invitation

Subject: Verzoek van een vakgenoot Geachte heer #u_manvrouw# #u_name#, Uw emailadres heb ik gevonden in de alumnigids van de parttime opleiding bedrijfskunde(RSM). Net als u ben ik bedrijfskundige en momenteel ben ik bezig met het schrijven van een scriptie voor de master Business Information Management. Mijn onderzoek geeft inzicht in hoe flexibele werkpraktijken op een succesvolle manier kunnen worden toegepast, iets wat in de praktijk niet vanzelfsprekend blijkt te zijn. Hierbij richt ik me met name op werkpraktijken die gerelateerd zijn aan Het Nieuwe Werken en leg ik een verbinding met persoonlijkheidskenmerken. Voor mijn onderzoek ben ik zowel geïnteresseerd in kenniswerkers die gebruik maken van flexibele werkpraktijken als in personen die dat niet / in mindere mate doen. Ik zou het heel erg op prijs stellen als u mij zou willen helpen door een online, Nederlandstalige vragenlijst in te vullen. U kunt deze vragenlijst openen door op de volgende link te klikken: #code_complete# Het invullen van de vragenlijst duurt 15 tot 20 minuten. De data wordt anoniem verwerkt. Indien u dat wilt, ontvangt u na afloop van het onderzoek een samenvatting van de resultaten. Dit kunt u aangeven aan het einde van de vragenlijst. Nogmaals: uw deelname wordt enorm gewaardeerd! Alvast heel hartelijk bedankt! Met vriendelijke groet, Christian van Esch Student Bedrijfskunde Rotterdam School of Management, Erasmus Universiteit


Appendix 4B – Reminder

Subject: Uw mening telt! Geachte #u_gender# #u_name#, Afgelopen maandag heb ik u een mailtje gestuurd, waarin ik u vroeg om uw bijdrage aan mijn afstudeeronderzoek door het invullen van een vragenlijst. Mijn scriptie gaat over de relatie tussen persoonlijkheid en flexibele werkpraktijken die gerelateerd zijn aan Het Nieuwe Werken (bijv. flex-time, flex-place en het gebruik van moderne communicatietechnologie). Ik wil graag te weten komen welk type persoonlijkheid wel/niet aansluit op deze manieren van werk. Voor mijn onderzoek ben ik zowel geïnteresseerd in kenniswerkers die gebruik maken van bovengenoemde werkpraktijken als in personen die dat niet doen. Mogelijk is dit verzoek in eerste instantie aan uw aandacht ontsnapt of heeft u nog geen geschikt moment kunnen vinden. Heel graag nodig ik u uit om alsnog deel te nemen aan mijn onderzoek, waarvan u –indien gewenst– de resultaten krijgt toegestuurd. U kunt de vragenlijst openen door op de volgende link te klikken: #code_complete# Mocht u reeds begonnen zijn met het invullen van de vragen, dan kunt u de vragenlijst hervatten op het punt waar u hem hebt onderbroken. Uw medewerking wordt enorm gewaardeerd! Bij voorbaat hartelijk dank! Met vriendelijke groet, Christian van Esch Student Bedrijfskunde Rotterdam School of Management, Erasmus Universiteit


Appendix 5 – Factor Analysis

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. ,829

Bartlett's Test of Sphericity Approx. Chi-Square 2083,355

df 66

Sig. ,000

Rotated Component Matrixa

Component

1 2 3 4

TWPF Focus 1 ,931 ,097 ,122 ,169

TWPF Focus 2 ,918 ,130 ,180 ,154

TWPF Focus 3 ,898 ,132 ,248 ,142

TWPF Learn 1 ,085 ,934 ,050 ,111

TWPF Learn 2 ,149 ,896 ,103 ,083

TWPF Learn 3 ,103 ,897 ,152 ,228

TWPF Collaborate 1 ,212 ,083 ,840 ,238



TWPF Socialize 1 ,161 ,121 ,213 ,832

TWPF Socialize 2 ,208 ,105 ,161 ,825

TWPF Socialize 3 ,085 ,219 ,300 ,828

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations.


Appendix 6 – Reliability Analysis

Construct Cronbach’s α Corrected item – Total correlation

(minimum / maximum)

Reflection on choice of location 0.732* 0.517 / 0.599

Reflection on media usage 0.759 (0.808 = 4) 0.410 / 0.671

Reflection on working hours and

schedule 0.819* 0.644 / 0.704

TWPF Socialize 0.860* 0.704 / 0.777

TWPF Learn 0.925* 0.818 / 0.864

TWPF Focus 0.951* 0.890 / 0.902

TWPF Collaborate 0.894* 0.781 / 0.805

Empw. Meaning 0.872* 0.743 / 0.786

Empw. Competence 0.828* 0.636 / 0.734

Empw. Self-determination 0.877* 0.709 / 0.799

Empw. Impact 0.879* 0.754 / 0.803

Output control 0.684* 0.405 / 0.595

Behavioural control 0.378 (0.482 = 3) 0.041 / 0.337

Social control 0.365 (0.467 = 1) 0.040 / 0.282

Mutual control 0.697 (0.828 = 3) 0.151 / 0.668

Employee satisfaction 0.811 (0.851 = 2) 0.403 / 0.759

Work life balance 0.859 (0.898 = 3) 0.524 / 0.801

Productivity 0.824* 0.574 / 0.699

Extraversion 0.791* 0.346 / 0.645

Agreeableness 0.672 (0.689 = BFI02) 0.153 / 0.410

Conscientiousness 0.688* 0.301 / 0.472

Neuroticism 0.806* 0.435 / 0.619

Openness 0.720 (0.722 = BFI35) 0.214 / 0.507

Time dependency 0.725* 0.529 / 0.588

Location dependency 0.810* 0.654 / 0.687

* Cronbach’s alpha cannot be improved by deleting items


Appendix 7 – ‘PTO Bedrijfskunde’ Alumni

Variable Frequency Percentage

Gender Male 180 82.569

Female 38 17.431

Age 30 -< 35 23 10.550

35 -< 40 48 22.018

40 -< 45 48 22.018

45 -< 50 34 15.596

50 -< 55 42 19.266

55 -< 60 13 5.963

60 -< 65 9 4.128

Missing 1 0.459

Position Employee 49 22.477

Top manager 63 28.899

Middle manager 58 26.606

Operational manager 17 7.798

Independent / hired 31 14.220

A.7.1. Gender Alumni

Male 83%

Female 17%

Gender


A.7.2. Age Alumni

A.7.3. Position Alumni

Employee 22%

Top manager 29%

Middle manager

27%

Operational manager

8%

Independent / hired 14%

Position


A.7.4. Sector Alumni

A.7.5. Personality - Position

Agriculture, forestry and fishing

1%

Mining of minerals 2%

Industry 13%

Production, distribution and trade electricity

2%

Building industry 5%

Wholesale and retail trade

1%

Transport and storage

1%

Information and communication

8%

Financial institutions 19%

Rental / trade real estate

1%

Consultancy and reserach

15%

Public administration

8%

Education 3%

Healthcare and

welfare 8%

Culture, sport, and recreation

2% Other services 11%

Sector

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Personality - Position

Employee

Top-manager

Middle-manager

Operational manager

Independent / hired


Appendix 8 – Univariate Analysis

Quantitative Variables

Variable n Mean Median Standard dev. Range

Refl. on choice of location 218 3.569 3.667 0.736 1.667 / 5

Refl. on media usage 218 3.648 3.750 0.623 1.333 / 5

Refl. on working hours and

schedule

218 3.498 3.667 0.789 1 / 5

Hours contracted 218 37.083 40.000 6.632 0 / 50

Hours work 218 46.454 45.000 10.481 9 / 75

Hours commuting 218 7.005 6.000 4.121 0 / 25

Non-regular work hours 217 10.115 10.000 7.406 0 / 30

Non-regular free hours 218 1.849 1.000 2.926 0 / 20

At the office 209 53.033 60.000 29.605 0 / 100

At ext. office or meeting

location

209 8.861 5.000 10.775 0 / 60

At client location 209 16.900 10.000 22.992 0 / 100

On the road 209 5.268 0.000 7.491 0 / 35

At home 209 15.938 10.000 14.984 0 / 100

Flex-time 217 20.914 20.000 13.495 0 / 88.889

Flex-place 209 46.967 40.000 29.605 0 / 100

TWPF Socialize 218 3.688 4.000 0.739 1 / 5

TWPF Learn 218 3.303 3.333 0.960 0 / 5

TWPF Focus 218 3.661 4.000 0.980 1 / 5

TWPF Collaborate 218 3.713 4.000 0.790 1.667 / 5

Face-to-face 200 44.225 40.000 21.224 0 / 90

Video Conference 200 2.270 0.000 4.365 0 / 30

Telephone (conf.) 200 15.405 15.000 9.822 0 / 50

Chat / Instant Messaging 200 2.235 0.000 4.154 0 / 20

Electronic Mail 200 27.730 25.000 15.341 5 / 80

Voice Mail 200 1.890 0.000 2.860 0 / 15

Fax 200 0.065 0.000 0.460 0 / 5

Documents 200 5.000 3.000 6.499 0 / 5

Other 200 1.180 0.000 6.809 0 / 85

Meaning 218 4.054 4.000 0.637 2 / 5

Competence 218 4.297 4.000 0.508 2 / 5

Self-determination 218 4.321 4.000 0.585 2 / 5


Impact 218 3.928 4.000 0.776 1.333 / 5

Output control 218 3.494 3.500 0.690 1 / 5

Behavioural control 218 2.802 2.750 0.595 1.250 / 4.500

Social control 218 3.375 3.500 0.533 1.500 / 4.750

Mutual control 218 3.217 3.250 0.675 1.250 / 5.000

Employee satisfaction 218 3.753 3.750 0.680 1.250 / 5

Work life balance 218 3.710 4.000 0.749 1.500 / 5

Productivity 218 3.950 4.000 0.493 2.200 / 5

Work Time Freedom Rate 216 7.583 8.000 1.838 1 / 10

Work Location Freedom

Rate

215 6.823 7.000 2.433 1 / 10

Telework Facilitation Rate 217 7.553 8.000 2.036 1 / 10

Extraversion 218 3.838 3.875 0.525 1.625 / 5

Agreeableness 218 3.657 3.667 0.421 2.667 / 4.889

Conscientiousness 218 3.779 3.778 0.440 2.444 / 4.889

Neuroticism 218 2.179 2.250 0.533 1 /3.750

Openness 218 3.746 3.750 0.455 2.500 / 4.900

Time dependency 218 2.258 2.000 0.753 1/4

Location dependency 218 2.350 2.333 0.864 1/5


Qualitative Variables

Variable n Answer option # %

Room Sharing 218 I have a private room 74 33.945

With 1-2 other persons 41 18.807



With more than 23 other persons 29 13.303

Own Work Place 218 Yes, I have my own work place / desk 146 66.972

No, work places / desks are flexible 72 33.028

Backup Spaces 218 Yes 166 76.147

No 52 23.853

Videoconferencing 218 Yes 135 61.927

No 83 38.073

Media Facilitation 218 Laptop 179 82.110

Smartphone 163 74.771

Mobile Internet 150 68.807

Online access to business applications

and data

199 91.284

None of these facilities 4 1.835


Appendix 9 – Correlations

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1. Extraversion

2. Agreeableness .251**

3. Conscient. .149* .164*

4. Neuroticism -.441** -.276** -.275**

5. Openness .274** .102 .025 -.214**

6. Ref choice loc. -.006 .012 -.016 .064 -.007

7. Ref w. hours -.024 .083 -.012 .043 -.046 .276**

8. Ref media use .080 .147* .076 .007 .161* .225** .229**

9. Flex-time .107 -.066 .020 .000 .137* .099 -.131 -.016

10. Flex-place .051 .040 -.036 -.028 .122 .325** .106 .183** .348**

11. Socialize .123 .057 -.034 -.074 -.076 .074 .006 .131 .090 -.156*

12. Learn .201** .050 .095 -.135* .012 .144** .156* .033 -.018 -.031 .355**

13. Focus .165* -.032 .080 -.091 .120 .044 .125 .015 .119 -.111 .385** .283**

14. Collaborate .263** .129 .037 -.206** .052 .036 .021 .101 .053 -.067 .519** .276** .422**

15. Empl. satisf. .200** .125 .023 -.143* .062 .078 .005 .154* .081 -.063 .405** .310** .334** .339**

16. Work life bal. .086 .146* .092 -.202** .024 .074 .333** .225** -.182** -.033 .190** .183** .239** .171* .194**

17. Productivity .198** .112 .436** -.271** .130 .049 .119 .335** .047 -.005 .243** .266** .187** .188** .324** .229**

* p < 0.05 ** p < 0.01


Appendix 10A – Hypotheses

P1 NWoW Work Practices have a positive impact on Work Performance

H1A ‘Reflection on working hours and schedule’ has a significant positive impact on work life balance

H1B ‘Reflection on media use’ has a significant positive impact on work life balance

H1C ‘Reflection on media use’ has a significant positive impact on productivity

H1D Neither flex-place nor flex-time has a significant impact on one of the performance indicators

H1E TWPF Collaborate has no significant impact on employee satisfaction, but the other three types of

TWPF have

H1F Task Workplace Fit Focus has a significant positive impact on work life balance

H1G Task Workplace Fit Learn has a significant positive impact on productivity

P2 Work Arrangements impact NWoW Work Practices

H2A Private office rooms have a significant positive impact on TWPF Learn and TWPF Focus

H2B Own workplace / desk does not have a significant impact on Task Workplace Fit, but has a significantly

negative impact on flex-place

H2C Freedom to choose work location(s) has a significant positive impact on both TWPF Focus and TWPF

Socialize, but concerning TWPF Socialize, workers remain dependent on (backup spaces in) the office

H2D Nor workplace design nor freedom to choose work location(s) has a significant impact on TWPF

Collaborate

H2E Telework facilitation does not have a significant impact on ‘reflection on media use’, but ‘freedom to

choose working hours’ has a sign. positive influence on ‘reflection on working hours and schedule’ and

‘freedom to choose work locations’ has a sign. positive influence on ‘reflection on choice of location’

H2F ‘Freedom to choose working hours’ has a significant positive influence on flex-time, but ‘freedom to

choose work locations’ does not have a significant influence on flex-place

P3 Specific Personality Traits impact Work Practices

H3A Openness has a significant positive impact on ‘reflection on media use’ and flex-place

H3B Extraversion has a significant positive impact on Task Workplace Fit Collaborate

P4 Specific Personality Traits impact the relationship between Work Practices and Work Performance

H4A A higher score on Extraversion in combination with more ‘reflection on choice of location’ result in a

relatively lower employee satisfaction

H4B A higher score on Agreeableness in combination with more ‘reflection on choice of location’ result in a

relatively higher productivity

H4C A higher score on Extraversion in combination with more flex-place result in a relatively lower employee

satisfaction

H4D A higher score on Conscientiousness in combination with more flex-time result in a relatively lower

productivity

H4E A higher score on Neuroticism in combination with more flex-time result in a relatively higher


productivity

H4F A higher score on Extraversion in combination with more TWPF Focus result in a relatively higher


H4G A higher score on Agreeableness in combination with more TWPF Focus result in a relatively lower


H4H A higher score on Neuroticism in combination with more TWPF Learn result in a relatively higher


H4I A higher score on Extraversion in combination with more TWPF Collaborate result in a relatively higher


H4J A higher score on Conscientiousness in combination with more TWPF Learn result in a relatively lower

productivity

H4K A higher score on Openness in combination with more TWPF Learn result in a relatively lower

productivity

Other findings / hypotheses

HA Extraversion has a significant positive impact on employee satisfaction

HB Neuroticism has a significant negative impact on work life balance

HC Conscientiousness has a significant positive impact on productivity

HD Top managers score higher on employee satisfaction but lower on work life balance

HE Women and young people are more likely to reflect on working hours and schedule

HF Independent / hired people work relatively more outside the office (flex-place); especially top managers

and middle-managers accomplish a higher percentage of their tasks outside regular working hours (flex-

time)

Table A10.1. – Summary hypotheses per proposition (based on data analysis)


Appendix 10B – Outcomes Personality Traits

Work Practices Work performance

Refl. on med. use Flex-place TWPF Collaborate Employee satisfac. Work life balance Productivity

Pe

rso

nal

ity

trai

ts

Extraversion (+) Direct effect

(+) Direct effect

(-) Mod: Reflection on

choice of location

(-) Mod: Flex-place

(+) Mod: TWPF Focus

(+) Mod: TWPF

Collaborate

Agreeableness (-) Moderating effect

TWPF Focus

(+) Mod: Reflection on

choice of location

Conscientiousness

(+) Direct effect

(-) Mod: Flex-time

(-) Mod: TWPF Learn

Neuroticism (+) Mod: TWPF Learn (+) Direct effect (+) Mod: Neuroticism

Openness (+) Direct effect (+) Direct effect (+) Mod: TWPF Learn


Appendix 11 – Plots

A11.1. Histogram Standardized Residuals

Figure A11.1 – Histogram of the Standardized Residuals for Reflexivity – Employee satisfaction (sub-model 1, relation 1a)

A11.2. Normal P-P Plot

Figure A11.2 – Normal P-P Plot for Reflexivity – Employee satisfaction (sub-model 1, relation 1a)


A11.3. ZRESID - ZPRESID

Figure A11.3 – Standardized residuals (ZRESID) vs. standardized predicted values for Reflexivity – Employee satisfaction (sub-model 1,

relation 1a)

A11.4. Residual lots


Figure A11.4 – Residual plots for Reflexivity – Employee satisfaction (sub-model 1, relation 1a)


Appendix 12 – Graphs Interaction Effects

Figure A12.1 – Graph for Reflection on choice of location (X) Employee satisfaction (Y), and Extraversion (Z)

Figure A12.2 – Graph for Reflection on location (X) Productivity (Y), and Agreeableness (Z)

Figure A12.3 – Graph for Flex-place (X) Employee satisfaction (Y), and Extraversion (Z)

Figure A12.4 – Graph for Flex-time (X) Productivity (Y), and Conscientiousness (Z)


Figure A12.5 – Graph for Flex-time (X) Productivity (Y), and Neuroticism (Z)

Figure A12.6 – Graph for TWPF Focus (X) Employee satisfaction (Y), and Extraversion (Z)

Figure A12.7 – Graph for TWPF Focus (X) Employee satisfaction (Y), and Agreeableness (Z)

Figure A12.8 – Graph for TWPF Learn (X) Employee satisfaction (Y), and Neuroticism (Z)


Figure A12.9 – Graph for TWPF Collaborate (X) Employee satisfaction (Y), and Extraversion (Z)

Figure A12.10 – Graph for TWPF Learn (X) Productivity (Y), and Conscientiousness (Z)

Figure A12.11 – Graph for TWPF Learn (X) Productivity (Y), and Openness (Z)


Output Regression Models


13.1. Reflexivity – Work Performance ............................................................................................................ 149

13.1.1. Reflexivity – Employee satisfaction ................................................................................................. 149

13.1.2. Reflexivity – Work life balance ........................................................................................................ 151

13.1.3. Reflexivity – Productivity ................................................................................................................. 153

13.2. Flexibility – Work Performance .............................................................................................................. 155

13.2.1. Flexibility – Employee satisfaction .................................................................................................. 155

13.2.2. Flexibility – Work life balance ......................................................................................................... 157

13.2.3. Flexibility – Productivity .................................................................................................................. 159

13.3. Task Workplace Fit – Work Performance ............................................................................................... 161

13.3.1. Task Workplace Fit – Employee satisfaction ................................................................................... 161

13.3.2. Task Workplace Fit – Work life balance .......................................................................................... 163

13.3.3. Task Workplace Fit – Productivity ................................................................................................... 165

13.4. Personality Traits – Reflexivity ............................................................................................................... 167

13.4.1. Personality Traits – Reflection on working hours and schedule ..................................................... 167

13.4.2. Personality Traits – Reflection on choice of location ...................................................................... 169

13.4.3. Personality Traits – Reflection on media use .................................................................................. 171

13.5. Personality Traits – Flexibility................................................................................................................. 173

13.5.1. Personality Traits – Flex-time .......................................................................................................... 173

13.5.2.A. Personality Traits – Flex-place ..................................................................................................... 175

13.5.2.B. Personality Traits – Flex-place (Variant B) ................................................................................... 177

13.6. Personality Traits – Task Workplace Fit ................................................................................................. 179

13.6.1. Personality Traits – Task Workplace Fit Focus ................................................................................ 179

13.6.2. Personality Traits – Task Workplace Fit Socialize ............................................................................ 181

13.6.3. Personality Traits – Task Workplace Fit Collaborate ....................................................................... 183

13.6.4. Personality Traits – Task Workplace Fit Learn................................................................................. 185

13.7. Personality Traits – Work Performance ................................................................................................. 187

13.7.1.A. Personality Traits – Employee satisfaction .................................................................................. 187

13.7.1.B. Personality Traits – Employee satisfaction (Variant B) ................................................................ 189


13.7.2. Personality Traits – Work life balance ............................................................................................. 191

13.7.3. Personality Traits – Productivity ..................................................................................................... 193


14.1. Personality – Reflexivity / Work Performance ....................................................................................... 195

14.1.1. Personality – Reflection on working hours and schedule / Employee satisfaction......................... 195

14.1.2.A. Personality – Reflection on choice of location / Employee satisfaction ...................................... 197

14.1.2.B. Personality – Reflection on choice of location / Employee satisfaction (Variant B) .................... 199

14.1.3. Personality – Reflection on media use / Employee satisfaction ..................................................... 201

14.1.4. Personality – Reflection on working hours and schedule / Work life balance ................................ 203

14.1.5. Personality – Reflection on choice of location / Work life balance ................................................ 205

14.1.6. Personality – Reflection on media use/ Work life balance ............................................................. 207

14.1.7. Personality – Reflection on working hours and schedule / Productivity ........................................ 209

14.1.8.A. Personality – Reflection on choice of location / Productivity ...................................................... 211

14.1.8.B. Personality – Reflection on choice of location / Productivity (Variant B) .................................... 213

14.1.9. Personality – Reflection on media use/ Productivity ...................................................................... 215

14.2. Personality – Flexibility / Work Performance......................................................................................... 217

14.2.1. Personality – Flex-time / Employee satisfaction ............................................................................. 217

14.2.2.A. Personality – Flex-place / Employee satisfaction ......................................................................... 219

14.2.2.B. Personality – Flex-place / Employee satisfaction (Variant B) ....................................................... 221

14.2.3.A. Personality – Flex-time / Work life balance ................................................................................. 223

14.2.3.B. Personality – Flex-time / Work life balance (Variant B) ............................................................... 225

14.2.4. Personality – Flex-place / Work life balance ................................................................................... 227

14.2.5. Personality – Flex-time / Productivity ............................................................................................. 229

14.2.6. Personality – Flex-place / Productivity ............................................................................................ 231

14.3. Personality – Task Workplace Fit / Work Performance ......................................................................... 233

14.3.1. Personality – TWPF Focus / Employee satisfaction ......................................................................... 233

14.3.2. Personality – TWPF Socialize / Employee satisfaction .................................................................... 235

14.3.3.A. Personality – TWPF Collaborate / Employee satisfaction ............................................................ 237

14.3.3.B. Personality – TWPF Collaborate / Employee satisfaction (Variant B) .......................................... 239

14.3.4. Personality – TWPF Learn / Employee satisfaction ......................................................................... 241


14.3.5. Personality – TWPF Focus / Work life balance ................................................................................ 243

14.3.6. Personality – TWPF Socialize / Work life balance ........................................................................... 245

14.3.7. Personality – TWPF Collaborate / Work life balance ...................................................................... 247

14.3.8. Personality – TWPF Learn / Work life balance ................................................................................ 249

14.3.9. Personality – TWPF Focus / Productivity ........................................................................................ 251

14.3.10. Personality – TWPF Socialize / Productivity .................................................................................. 253

14.3.11. Personality – TWPF Collaborate / Productivity ............................................................................. 255

14.3.12.A. Personality – TWPF Learn / Productivity ................................................................................... 257

14.3.12.B. Personality – TWPF Learn / Productivity (Variant B) ................................................................. 259


15.1. Workplace design & Freedom work location – Task Workplace Fit ....................................................... 261

15.1.1. Workplace design & Freedom work location – TWPF Focus ........................................................... 261

15.1.2. Workplace design & Freedom work location – TWPF Socialize ...................................................... 263

15.1.3. Workplace design & Freedom work location – TWPF Collaborate ................................................. 265

15.1.4. Workplace design & Freedom work location – TWPF Learn ........................................................... 267

15.2.1. Workplace design & Freedom work location – Flex-place .............................................................. 269

15.3.1. Freedom work location – Reflection on choice of location ............................................................ 271

15.4.1. Freedom working hours – Flex-time ............................................................................................... 273

15.5.1. Freedom working hours – Reflection on working hours and schedule ........................................... 275

15.6.1. Telework facilitation rate – Reflection on media use ..................................................................... 277


Appendix 13 – Regression Output Sub-model 1

13.1. Reflexivity – Work Performance

13.1.1. Reflexivity – Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate Durbin-Watson

1 ,228a ,052 ,025 ,67289

2 ,277b ,077 ,037 ,66883 2,072

ANOVA

Model Sum of Squares df Mean Square F Sig.

1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 7,712 9 ,857 1,916 ,051b

Residual 92,598 207 ,447

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Refl. media, Refl. location, Refl. time c. Dependent Variable: Employee Satisfaction


Coefficients

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) 3,713 ,280 13,280 ,000

Gender -,023 ,123 -,012 -,183 ,855 ,968 1,033

Age -,001 ,006 -,013 -,176 ,860 ,892 1,121

Position d_2 ,328 ,130 ,219 2,522 ,012 ,600 1,667

Position d_3 -,061 ,132 -,040 -,466 ,642 ,619 1,616

Position d_4 ,058 ,190 ,023 ,306 ,760 ,797 1,255

Position d_5 ,054 ,157 ,028 ,341 ,733 ,690 1,449

2 (Constant) 2,921 ,482 6,064 ,000

Gender -,040 ,125 -,022 -,318 ,751 ,927 1,079

Age ,000 ,006 ,005 ,075 ,940 ,849 1,178

Position d_2 ,323 ,131 ,216 2,466 ,014 ,583 1,715

Position d_3 -,045 ,132 -,029 -,342 ,732 ,610 1,640

Position d_4 ,070 ,190 ,028 ,369 ,712 ,795 1,258

Position d_5 ,028 ,158 ,014 ,177 ,860 ,678 1,476

Refl. location ,069 ,066 ,074 1,037 ,301 ,872 1,147

Refl. time -,009 ,064 -,010 -,134 ,893 ,816 1,225

Refl. media ,140 ,077 ,128 1,815 ,071 ,890 1,124

a. Dependent Variable: Employee Satisfaction


13.1.2. Reflexivity – Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,393b ,154 ,117 ,69996 2,251

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 18,495 9 2,055 4,194 ,000b

Residual 101,420 207 ,490

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Refl. media, Refl. location, Refl. time c. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,958 ,309 12,799 ,000

Gender ,041 ,137 ,021 ,302 ,763 ,968 1,033

Age -,003 ,007 -,032 -,440 ,661 ,892 1,121

Position d_2 -,281 ,144 -,172 -1,959 ,051 ,600 1,667

Position d_3 -,158 ,146 -,093 -1,082 ,281 ,619 1,616

Position d_4 ,094 ,211 ,034 ,445 ,657 ,797 1,255

Position d_5 -,104 ,174 -,049 -,599 ,550 ,690 1,449

2 (Constant) 2,016 ,504 3,999 ,000

Gender -,026 ,131 -,013 -,196 ,845 ,927 1,079

Age ,004 ,006 ,048 ,697 ,487 ,849 1,178

Position d_2 -,234 ,137 -,143 -1,708 ,089 ,583 1,715

Position d_3 -,072 ,138 -,043 -,523 ,601 ,610 1,640

Position d_4 ,086 ,198 ,031 ,436 ,664 ,795 1,258

Position d_5 -,175 ,165 -,082 -1,058 ,291 ,678 1,476

Refl. location -,049 ,069 -,048 -,701 ,484 ,872 1,147

Refl. time ,275 ,067 ,291 4,115 ,000 ,816 1,225

Refl. media ,223 ,081 ,186 2,751 ,006 ,890 1,124

a. Dependent Variable: Work life balance


13.1.3. Reflexivity – Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,365b ,133 ,096 ,46983 2,151

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 7,030 9 ,781 3,538 ,000b

Residual 45,693 207 ,221

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Refl. media, Refl. location, Refl. time c. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 4,087 ,206 19,850 ,000

Gender ,113 ,091 ,086 1,242 ,216 ,968 1,033

Age -,005 ,004 -,074 -1,030 ,304 ,892 1,121

Position d_2 ,098 ,096 ,090 1,023 ,307 ,600 1,667

Position d_3 ,000 ,097 ,000 -,001 ,999 ,619 1,616

Position d_4 ,153 ,140 ,084 1,093 ,276 ,797 1,255

Position d_5 ,053 ,116 ,038 ,460 ,646 ,690 1,449

2 (Constant) 3,043 ,338 8,993 ,000

Gender ,119 ,088 ,091 1,355 ,177 ,927 1,079

Age -,002 ,004 -,032 -,458 ,647 ,849 1,178

Position d_2 ,074 ,092 ,068 ,808 ,420 ,583 1,715

Position d_3 ,026 ,093 ,023 ,282 ,778 ,610 1,640

Position d_4 ,151 ,133 ,083 1,138 ,257 ,795 1,258

Position d_5 -,017 ,111 -,012 -,149 ,882 ,678 1,476

Refl. location -,036 ,046 -,053 -,770 ,442 ,872 1,147

Refl. time ,027 ,045 ,042 ,592 ,554 ,816 1,225

Refl. media ,266 ,054 ,337 4,907 ,000 ,890 1,124

a. Dependent Variable: Productivity


13.2. Flexibility – Work Performance

13.2.1. Flexibility – Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,231a ,053 ,025 ,66790

2 ,244b ,060 ,022 ,66899 2,050

ANOVA


1 Regression 5,026 6 ,838 1,878 ,086a

Residual 89,219 200 ,446

Total 94,245 206

2 Regression 5,630 8 ,704 1,572 ,135b

Residual 88,615 198 ,448

Total 94,245 206

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Flextime, Flexplace c. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,752 ,280 13,418 ,000

Gender ,044 ,126 ,024 ,346 ,730 ,960 1,041

Age -,003 ,006 -,032 -,434 ,665 ,891 1,122

Position d_2 ,369 ,131 ,248 2,813 ,005 ,608 1,644

Position d_3 ,000 ,135 ,000 ,002 ,998 ,632 1,583

Position d_4 ,065 ,189 ,026 ,342 ,733 ,796 1,256

Position d_5 ,085 ,159 ,044 ,536 ,592 ,691 1,446

2 (Constant) 3,791 ,295 12,855 ,000

Gender ,044 ,127 ,025 ,349 ,727 ,954 1,048

Age -,003 ,006 -,035 -,474 ,636 ,889 1,124

Position d_2 ,336 ,135 ,226 2,491 ,014 ,577 1,734

Position d_3 -,029 ,137 -,018 -,209 ,835 ,609 1,643

Position d_4 ,047 ,190 ,019 ,249 ,804 ,790 1,265

Position d_5 ,106 ,164 ,055 ,646 ,519 ,652 1,533

Flextime ,347 ,377 ,070 ,919 ,359 ,822 1,216

Flexplace -,002 ,002 -,079 -,999 ,319 ,764 1,309



13.2.2. Flexibility – Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,176a ,031 ,002 ,74860

2 ,241b ,058 ,020 ,74173 1,971

ANOVA


1 Regression 3,567 6 ,595 1,061 ,387a

Residual 112,082 200 ,560

Total 115,649 206

2 Regression 6,717 8 ,840 1,526 ,150b

Residual 108,932 198 ,550

Total 115,649 206

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Flextime, Flexplace c. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,995 ,313 12,745 ,000

Gender ,078 ,142 ,039 ,551 ,582 ,960 1,041

Age -,004 ,007 -,044 -,593 ,554 ,891 1,122

Position d_2 -,266 ,147 -,162 -1,812 ,072 ,608 1,644

Position d_3 -,154 ,151 -,090 -1,022 ,308 ,632 1,583

Position d_4 ,091 ,212 ,033 ,429 ,668 ,796 1,256

Position d_5 -,109 ,178 -,051 -,614 ,540 ,691 1,446

2 (Constant) 4,114 ,327 12,582 ,000

Gender ,098 ,141 ,049 ,693 ,489 ,954 1,048

Age -,004 ,007 -,043 -,585 ,559 ,889 1,124

Position d_2 -,194 ,150 -,118 -1,300 ,195 ,577 1,734

Position d_3 -,095 ,152 -,055 -,625 ,532 ,609 1,643

Position d_4 ,104 ,211 ,038 ,493 ,623 ,790 1,265

Position d_5 -,069 ,181 -,032 -,379 ,705 ,652 1,533

Flextime -,010 ,004 -,178 -2,335 ,021 ,822 1,216

Flexplace ,001 ,002 ,030 ,378 ,706 ,764 1,309



13.2.3. Flexibility – Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,171a ,029 ,000 ,48318

2 ,179b ,032 -,007 ,48493 2,082

ANOVA


1 Regression 1,413 6 ,235 1,009 ,421a

Residual 46,693 200 ,233

Total 48,106 206

2 Regression 1,545 8 ,193 ,821 ,585b

Residual 46,561 198 ,235

Total 48,106 206

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Flextime, Flexplace c. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 4,102 ,202 20,274 ,000

Gender ,138 ,091 ,108 1,513 ,132 ,960 1,041

Age -,005 ,004 -,086 -1,162 ,247 ,891 1,122

Position d_2 ,119 ,095 ,112 1,249 ,213 ,608 1,644

Position d_3 ,013 ,097 ,012 ,136 ,892 ,632 1,583

Position d_4 ,152 ,137 ,087 1,109 ,269 ,796 1,256

Position d_5 ,053 ,115 ,039 ,466 ,642 ,691 1,446

2 (Constant) 4,100 ,214 19,182 ,000

Gender ,137 ,092 ,106 1,483 ,140 ,954 1,048

Age -,005 ,004 -,087 -1,175 ,241 ,889 1,124

Position d_2 ,102 ,098 ,096 1,041 ,299 ,577 1,734

Position d_3 -,001 ,100 -,001 -,010 ,992 ,609 1,643

Position d_4 ,146 ,138 ,083 1,055 ,293 ,790 1,265

Position d_5 ,055 ,119 ,040 ,466 ,642 ,652 1,533

Flextime ,198 ,274 ,056 ,724 ,470 ,822 1,216

Flexplace -,001 ,001 -,036 -,451 ,652 ,764 1,309



13.3. Task Workplace Fit – Work Performance

13.3.1. Task Workplace Fit – Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,511b ,261 ,225 ,59992 2,026

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 26,170 10 2,617 7,271 ,000b

Residual 74,140 206 ,360

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2

b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2,

TWPF Learn, TWPF Collaborate, TWPF Focus, TWPF Socialize

c. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,713 ,280 13,280 ,000

Gender -,023 ,123 -,012 -,183 ,855 ,968 1,033

Age -,001 ,006 -,013 -,176 ,860 ,892 1,121

Position d_2 ,328 ,130 ,219 2,522 ,012 ,600 1,667

Position d_3 -,061 ,132 -,040 -,466 ,642 ,619 1,616

Position d_4 ,058 ,190 ,023 ,306 ,760 ,797 1,255

Position d_5 ,054 ,157 ,028 ,341 ,733 ,690 1,449

2 (Constant) 2,016 ,339 5,949 ,000

Gender -,008 ,110 -,005 -,077 ,939 ,963 1,039

Age -,003 ,006 -,037 -,571 ,568 ,857 1,167

Position d_2 ,245 ,118 ,164 2,073 ,039 ,575 1,741

Position d_3 -,038 ,118 -,025 -,325 ,746 ,611 1,637

Position d_4 -,078 ,171 -,031 -,457 ,648 ,786 1,272

Position d_5 ,031 ,142 ,016 ,218 ,828 ,671 1,490

TWPF Socialize ,221 ,068 ,240 3,226 ,001 ,649 1,540

TWPF Learn ,112 ,047 ,158 2,388 ,018 ,815 1,227

TWPF Focus ,101 ,049 ,146 2,088 ,038 ,739 1,354

TWPF Collaborate ,071 ,065 ,082 1,092 ,276 ,635 1,575



13.3.2. Task Workplace Fit – Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,349b ,122 ,079 ,71497 2,122

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 14,611 10 1,461 2,858 ,002b

Residual 105,303 206 ,511

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, TWPF Learn, TWPF Collaborate, TWPF Focus, TWPF Socialize c. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,958 ,309 12,799 ,000

Gender ,041 ,137 ,021 ,302 ,763 ,968 1,033

Age -,003 ,007 -,032 -,440 ,661 ,892 1,121

Position d_2 -,281 ,144 -,172 -1,959 ,051 ,600 1,667

Position d_3 -,158 ,146 -,093 -1,082 ,281 ,619 1,616

Position d_4 ,094 ,211 ,034 ,445 ,657 ,797 1,255

Position d_5 -,104 ,174 -,049 -,599 ,550 ,690 1,449

2 (Constant) 2,861 ,404 7,083 ,000

Gender ,047 ,132 ,024 ,360 ,720 ,963 1,039

Age -,005 ,007 -,057 -,814 ,417 ,857 1,167

Position d_2 -,366 ,141 -,223 -2,594 ,010 ,575 1,741

Position d_3 -,161 ,141 -,095 -1,139 ,256 ,611 1,637

Position d_4 -,013 ,204 -,005 -,065 ,948 ,786 1,272

Position d_5 -,131 ,169 -,062 -,776 ,439 ,671 1,490

TWPF Socialize ,055 ,082 ,055 ,674 ,501 ,649 1,540

TWPF Learn ,061 ,056 ,078 1,082 ,280 ,815 1,227

TWPF Focus ,145 ,058 ,191 2,513 ,013 ,739 1,354

TWPF

Collaborate

,082 ,077 ,087 1,061 ,290 ,635 1,575



13.3.3. Task Workplace Fit – Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,344b ,118 ,076 ,47501 1,966

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 6,242 10 ,624 2,767 ,003b

Residual 46,480 206 ,226

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, TWPF Learn, TWPF Collaborate, TWPF Focus, TWPF Socialize c. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 4,087 ,206 19,850 ,000

Gender ,113 ,091 ,086 1,242 ,216 ,968 1,033

Age -,005 ,004 -,074 -1,030 ,304 ,892 1,121

Position d_2 ,098 ,096 ,090 1,023 ,307 ,600 1,667

Position d_3 ,000 ,097 ,000 -,001 ,999 ,619 1,616

Position d_4 ,153 ,140 ,084 1,093 ,276 ,797 1,255

Position d_5 ,053 ,116 ,038 ,460 ,646 ,690 1,449

2 (Constant) 3,260 ,268 12,151 ,000

Gender ,114 ,087 ,087 1,308 ,192 ,963 1,039

Age -,005 ,004 -,080 -1,129 ,260 ,857 1,167

Position d_2 ,067 ,094 ,062 ,713 ,477 ,575 1,741

Position d_3 ,017 ,094 ,015 ,178 ,859 ,611 1,637

Position d_4 ,089 ,135 ,048 ,656 ,513 ,786 1,272

Position d_5 ,043 ,112 ,031 ,386 ,700 ,671 1,490

TWPF Socialize ,095 ,054 ,142 1,749 ,082 ,649 1,540

TWPF Learn ,087 ,037 ,169 2,338 ,020 ,815 1,227

TWPF Focus ,040 ,038 ,080 1,048 ,296 ,739 1,354

TWPF Collaborate ,018 ,051 ,029 ,353 ,724 ,635 1,575



13.4. Personality Traits – Reflexivity

13.4.1. Personality Traits – Reflection on working hours and schedule

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,324a ,105 ,079 ,75769

2 ,342b ,117 ,069 ,76180 1,967

Model Summary

Model

Change Statistics

R Square

Change F Change df1 df2 Sig. F Change

1 ,105a 4,103 6 210 ,001

2 ,012b ,547 5 205 ,740

ANOVA


1 Regression 14,133 6 2,355 4,103 ,001a

Residual 120,558 210 ,574

Total 134,691 216

2 Regression 15,721 11 1,429 2,463 ,007b

Residual 118,970 205 ,580

Total 134,691 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: Refl. time


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 4,529 ,315 14,385 ,000

Gender ,310 ,139 ,148 2,228 ,027 ,968 1,033

Age -,021 ,007 -,217 -3,137 ,002 ,892 1,121

Position d_2 -,277 ,146 -,160 -1,896 ,059 ,600 1,667

Position d_3 -,258 ,149 -,144 -1,738 ,084 ,619 1,616

Position d_4 ,013 ,214 ,004 ,061 ,951 ,797 1,255

Position d_5 ,040 ,177 ,018 ,228 ,820 ,690 1,449

2 (Constant) 4,229 1,018 4,155 ,000

Gender ,316 ,145 ,151 2,183 ,030 ,903 1,107

Age -,021 ,007 -,217 -3,067 ,002 ,858 1,165

Position d_2 -,257 ,155 -,148 -1,656 ,099 ,537 1,862

Position d_3 -,252 ,150 -,141 -1,685 ,094 ,615 1,625

Position d_4 ,067 ,220 ,023 ,302 ,763 ,762 1,311

Position d_5 ,029 ,183 ,013 ,159 ,874 ,652 1,533

Extraversion -,031 ,117 -,021 -,266 ,790 ,712 1,404

Agreeableness ,200 ,132 ,107 1,516 ,131 ,867 1,153

Conscient. -,076 ,128 -,043 -,599 ,550 ,848 1,179

Neuroticism ,045 ,117 ,030 ,386 ,700 ,690 1,448

Openness -,035 ,120 -,020 -,290 ,772 ,894 1,118

a. Dependent Variable: Refl. time


13.4.2. Personality Traits – Reflection on choice of location

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,200a ,040 ,012 ,73183

2 ,211b ,045 -,007 ,73886 1,947

Model Summary

Model

Change Statistics

R Square


1 ,040a 1,454 6 210 ,196

2 ,005b ,205 5 205 ,960

ANOVAc


1 Regression 4,673 6 ,779 1,454 ,196a

Residual 112,470 210 ,536

Total 117,143 216

2 Regression 5,231 11 ,476 ,871 ,570b

Residual 111,912 205 ,546

Total 117,143 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2

b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2,

Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism

c. Dependent Variable: Refl. location


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,939 ,304 12,954 ,000

Gender ,317 ,134 ,162 2,359 ,019 ,968 1,033

Age -,007 ,007 -,080 -1,113 ,267 ,892 1,121

Position d_2 -,161 ,141 -,099 -1,136 ,257 ,600 1,667

Position d_3 -,093 ,144 -,056 -,649 ,517 ,619 1,616

Position d_4 -,140 ,207 -,051 -,675 ,500 ,797 1,255

Position d_5 -,114 ,171 -,054 -,666 ,506 ,690 1,449

2 (Constant) 3,740 ,987 3,789 ,000

Gender ,331 ,140 ,170 2,362 ,019 ,903 1,107

Age -,007 ,007 -,079 -1,076 ,283 ,858 1,165

Position d_2 -,147 ,151 -,091 -,973 ,332 ,537 1,862

Position d_3 -,088 ,145 -,053 -,603 ,547 ,615 1,625

Position d_4 -,112 ,214 -,041 -,523 ,601 ,762 1,311

Position d_5 -,112 ,177 -,053 -,631 ,529 ,652 1,533

Extraversion ,024 ,113 ,017 ,215 ,830 ,712 1,404

Agreeableness ,041 ,128 ,024 ,322 ,748 ,867 1,153

Conscient. -,076 ,124 -,045 -,611 ,542 ,848 1,179

Neuroticism ,070 ,113 ,050 ,614 ,540 ,690 1,448

Openness ,021 ,117 ,013 ,177 ,860 ,894 1,118

a. Dependent Variable: Refl. location


13.4.3. Personality Traits – Reflection on media use

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,173a ,030 ,002 ,62340

2 ,303b ,092 ,043 ,61057 1,946

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,086 6 210 ,372

2 ,062b 2,784 5 205 ,019

ANOVA


1 Regression 2,532 6 ,422 1,086 ,372a

Residual 81,613 210 ,389

Total 84,145 216

2 Regression 7,722 11 ,702 1,883 ,043b

Residual 76,423 205 ,373

Total 84,145 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: Refl. media


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,994 ,259 15,418 ,000

Gender -,013 ,114 -,008 -,111 ,912 ,968 1,033

Age -,009 ,006 -,111 -1,541 ,125 ,892 1,121

Position d_2 ,094 ,120 ,069 ,784 ,434 ,600 1,667

Position d_3 -,086 ,122 -,061 -,701 ,484 ,619 1,616

Position d_4 -,014 ,176 -,006 -,077 ,939 ,797 1,255

Position d_5 ,242 ,146 ,136 1,664 ,098 ,690 1,449

2 (Constant) 1,421 ,816 1,743 ,083

Gender -,082 ,116 -,050 -,707 ,480 ,903 1,107

Age -,010 ,006 -,134 -1,860 ,064 ,858 1,165

Position d_2 ,109 ,125 ,080 ,876 ,382 ,537 1,862

Position d_3 -,076 ,120 -,054 -,635 ,526 ,615 1,625

Position d_4 ,054 ,177 ,023 ,304 ,762 ,762 1,311

Position d_5 ,271 ,147 ,152 1,847 ,066 ,652 1,533

Extraversion ,007 ,094 ,006 ,071 ,943 ,712 1,404

Agreeableness ,206 ,106 ,139 1,951 ,052 ,867 1,153

Conscient. ,150 ,102 ,106 1,471 ,143 ,848 1,179

Neuroticism ,174 ,094 ,149 1,857 ,065 ,690 1,448

Openness ,246 ,097 ,179 2,543 ,012 ,894 1,118

a. Dependent Variable: Refl. media


13.5. Personality Traits – Flexibility

13.5.1. Personality Traits – Flex-time

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,212a ,045 ,017 13,40877

2 ,280b ,079 ,029 13,32950 2,079

Model Summary

Model

Change Statistics

R Square


1 ,045a 1,632 6 209 ,140

2 ,034b 1,499 5 204 ,192

ANOVA


1 Regression 1760,200 6 293,367 1,632 ,140a

Residual 37577,156 209 179,795

Total 39337,356 215

2 Regression 3091,536 11 281,049 1,582 ,106b

Residual 36245,820 204 177,676

Total 39337,356 215

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: Flextime


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 15,908 5,584 2,849 ,005

Gender 1,620 2,463 ,045 ,658 ,511 ,966 1,035

Age ,014 ,121 ,009 ,119 ,905 ,889 1,125

Position d_2 7,077 2,589 ,238 2,733 ,007 ,601 1,664

Position d_3 4,512 2,629 ,147 1,716 ,088 ,620 1,613

Position d_4 ,608 3,795 ,012 ,160 ,873 ,797 1,254

Position d_5 5,727 3,169 ,147 1,807 ,072 ,693 1,443

2 (Constant) -2,063 17,875 -,115 ,908

Gender 1,361 2,542 ,038 ,535 ,593 ,896 1,115

Age ,007 ,122 ,004 ,055 ,956 ,857 1,167

Position d_2 6,903 2,722 ,233 2,536 ,012 ,538 1,860

Position d_3 4,565 2,622 ,149 1,741 ,083 ,616 1,623

Position d_4 ,280 3,856 ,006 ,073 ,942 ,763 1,311

Position d_5 6,253 3,230 ,160 1,936 ,054 ,659 1,517

Extraversion 2,100 2,055 ,081 1,022 ,308 ,721 1,386

Agreeableness -3,555 2,319 -,110 -1,533 ,127 ,880 1,136

Conscient. 1,218 2,249 ,039 ,542 ,589 ,851 1,175

Neuroticism 2,182 2,045 ,086 1,067 ,287 ,702 1,424

Openness 3,716 2,112 ,125 1,760 ,080 ,891 1,122

a. Dependent Variable: Flextime


13.5.2.A. Personality Traits – Flex-place

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,346a ,120 ,093 28,08366

2 ,375b ,140 ,092 28,10512 2,034

Model Summary

Model

Change Statistics

R Square


1 ,120a 4,557 6 201 ,000

2 ,021b ,939 5 196 ,457

ANOVA


1 Regression 21563,276 6 3593,879 4,557 ,000a

Residual 158527,031 201 788,692

Total 180090,308 207

2 Regression 25270,351 11 2297,305 2,908 ,001b

Residual 154819,957 196 789,898

Total 180090,308 207

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: Flexplace


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 52,873 11,733 4,506 ,000

Gender 4,836 5,307 ,061 ,911 ,363 ,962 1,039

Age -,149 ,255 -,041 -,584 ,560 ,894 1,119

Position d_2 -4,779 5,516 -,074 -,866 ,387 ,607 1,647

Position d_3 -5,246 5,662 -,077 -,927 ,355 ,631 1,585

Position d_4 -8,293 7,968 -,077 -1,041 ,299 ,796 1,257

Position d_5 23,101 6,588 ,280 3,506 ,001 ,689 1,452

2 (Constant) 30,322 38,388 ,790 ,431

Gender 5,342 5,503 ,068 ,971 ,333 ,896 1,116

Age -,168 ,260 -,046 -,647 ,518 ,861 1,162

Position d_2 -6,088 5,850 -,094 -1,041 ,299 ,541 1,850

Position d_3 -5,479 5,678 -,081 -,965 ,336 ,628 1,592

Position d_4 -9,019 8,154 -,084 -1,106 ,270 ,761 1,314

Position d_5 22,378 6,793 ,271 3,294 ,001 ,649 1,541

Extraversion ,485 4,370 ,009 ,111 ,912 ,712 1,404

Agreeableness -,493 4,962 -,007 -,099 ,921 ,869 1,150

Conscient. -2,521 4,796 -,038 -,526 ,600 ,848 1,180

Neuroticism -,114 4,361 -,002 -,026 ,979 ,690 1,450

Openness 8,984 4,528 ,138 1,984 ,049 ,902 1,109

a. Dependent Variable: Flexplace


13.5.2.B. Personality Traits – Flex-place (Variant B)

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,346a ,120 ,093 28,08366

2 ,373b ,139 ,109 27,84495 2,041

Model Summary

Model

Change Statistics

R Square


1 ,120a 4,557 6 201 ,000

2 ,019b 4,461 1 200 ,036

ANOVA


1 Regression 21563,276 6 3593,879 4,557 ,000a

Residual 158527,031 201 788,692

Total 180090,308 207

2 Regression 25022,006 7 3574,572 4,610 ,000b

Residual 155068,302 200 775,342

Total 180090,308 207

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness c. Dependent Variable: Flexplace


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 52,873 11,733 4,506 ,000

Gender 4,836 5,307 ,061 ,911 ,363 ,962 1,039

Age -,149 ,255 -,041 -,584 ,560 ,894 1,119

Position d_2 -4,779 5,516 -,074 -,866 ,387 ,607 1,647

Position d_3 -5,246 5,662 -,077 -,927 ,355 ,631 1,585

Position d_4 -8,293 7,968 -,077 -1,041 ,299 ,796 1,257

Position d_5 23,101 6,588 ,280 3,506 ,001 ,689 1,452

2 (Constant) 20,691 19,170 1,079 ,282

Gender 4,590 5,263 ,058 ,872 ,384 ,962 1,040

Age -,178 ,253 -,049 -,705 ,482 ,891 1,122

Position d_2 -5,981 5,499 -,092 -1,088 ,278 ,601 1,665

Position d_3 -5,463 5,615 -,080 -,973 ,332 ,631 1,586

Position d_4 -8,925 7,906 -,083 -1,129 ,260 ,795 1,258

Position d_5 22,713 6,535 ,275 3,476 ,001 ,688 1,453

Openness 9,089 4,303 ,140 2,112 ,036 ,980 1,020



13.6. Personality Traits – Task Workplace Fit

13.6.1. Personality Traits – Task Workplace Fit Focus

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,213a ,045 ,018 ,96922

2 ,286b ,082 ,032 ,96214 1,854

Model Summary

Model

Change Statistics

R Square


1 ,045a 1,661 6 210 ,132

2 ,036b 1,620 5 205 ,156

ANOVA


1 Regression 9,361 6 1,560 1,661 ,132a

Residual 197,273 210 ,939

Total 206,634 216

2 Regression 16,861 11 1,533 1,656 ,086b

Residual 189,773 205 ,926

Total 206,634 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: TWPF Focus


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 2,800 ,403 6,953 ,000

Gender -,001 ,178 ,000 -,005 ,996 ,968 1,033

Age ,017 ,009 ,135 1,897 ,059 ,892 1,121

Position d_2 ,299 ,187 ,139 1,598 ,111 ,600 1,667

Position d_3 ,042 ,190 ,019 ,224 ,823 ,619 1,616

Position d_4 ,376 ,274 ,103 1,369 ,172 ,797 1,255

Position d_5 -,025 ,226 -,009 -,113 ,911 ,690 1,449

2 (Constant) 1,366 1,285 1,063 ,289

Gender -,043 ,183 -,016 -,233 ,816 ,903 1,107

Age ,019 ,009 ,152 2,108 ,036 ,858 1,165

Position d_2 ,177 ,196 ,082 ,900 ,369 ,537 1,862

Position d_3 ,024 ,189 ,011 ,125 ,901 ,615 1,625

Position d_4 ,295 ,278 ,081 1,061 ,290 ,762 1,311

Position d_5 -,067 ,231 -,024 -,289 ,773 ,652 1,533

Extraversion ,305 ,148 ,164 2,068 ,040 ,712 1,404

Agreeableness -,202 ,167 -,087 -1,214 ,226 ,867 1,153

Conscient. ,141 ,161 ,063 ,873 ,384 ,848 1,179

Neuroticism ,006 ,148 ,003 ,041 ,967 ,690 1,448

Openness ,114 ,152 ,053 ,749 ,455 ,894 1,118

a. Dependent Variable: TWPF Focus


13.6.2. Personality Traits – Task Workplace Fit Socialize

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,74273

2 ,246b ,061 ,010 ,73678 1,860

Model Summary

Model

Change Statistics

R Square


1 ,022a ,793 6 210 ,577

2 ,039b 1,681 5 205 ,141

ANOVA


1 Regression 2,624 6 ,437 ,793 ,577a

Residual 115,845 210 ,552

Total 118,469 216

2 Regression 7,187 11 ,653 1,204 ,286b

Residual 111,282 205 ,543

Total 118,469 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: TWPF Socialize


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,409 ,309 11,044 ,000

Gender -,083 ,136 -,042 -,608 ,544 ,968 1,033

Age ,006 ,007 ,070 ,962 ,337 ,892 1,121

Position d_2 ,079 ,143 ,049 ,552 ,581 ,600 1,667

Position d_3 -,094 ,146 -,056 -,648 ,518 ,619 1,616

Position d_4 ,212 ,210 ,077 1,007 ,315 ,797 1,255

Position d_5 -,044 ,173 -,021 -,254 ,800 ,690 1,449

2 (Constant) 3,640 ,984 3,699 ,000

Gender -,060 ,140 -,030 -,428 ,669 ,903 1,107

Age ,010 ,007 ,108 1,484 ,139 ,858 1,165

Position d_2 -,005 ,150 -,003 -,031 ,975 ,537 1,862

Position d_3 -,107 ,145 -,064 -,741 ,460 ,615 1,625

Position d_4 ,196 ,213 ,071 ,920 ,359 ,762 1,311

Position d_5 -,131 ,177 -,062 -,740 ,460 ,652 1,533

Extraversion ,216 ,113 ,154 1,915 ,057 ,712 1,404

Agreeableness ,079 ,128 ,045 ,616 ,539 ,867 1,153

Conscient. -,124 ,123 -,074 -1,004 ,317 ,848 1,179

Neuroticism -,053 ,113 -,038 -,468 ,640 ,690 1,448

Openness -,237 ,116 -,146 -2,038 ,043 ,894 1,118

a. Dependent Variable: TWPF Socialize


13.6.3. Personality Traits – Task Workplace Fit Collaborate

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,222a ,049 ,022 ,78114

2 ,328b ,107 ,060 ,76613 2,020

Model Summary

Model

Change Statistics

R Square


1 ,049a 1,822 6 210 ,096

2 ,058b 2,663 5 205 ,023

ANOVA


1 Regression 6,670 6 1,112 1,822 ,096a

Residual 128,139 210 ,610

Total 134,809 216

2 Regression 14,484 11 1,317 2,243 ,014b

Residual 120,325 205 ,587

Total 134,809 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: TWPF Collaborate


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,319 ,325 10,224 ,000

Gender -,086 ,143 -,041 -,598 ,551 ,968 1,033

Age ,004 ,007 ,043 ,608 ,544 ,892 1,121

Position d_2 ,413 ,151 ,238 2,738 ,007 ,600 1,667

Position d_3 ,125 ,153 ,070 ,816 ,415 ,619 1,616

Position d_4 ,294 ,221 ,100 1,329 ,185 ,797 1,255

Position d_5 ,332 ,182 ,147 1,818 ,071 ,690 1,449

2 (Constant) 2,318 1,023 2,264 ,025

Gender -,099 ,146 -,047 -,679 ,498 ,903 1,107

Age ,008 ,007 ,082 1,150 ,252 ,858 1,165

Position d_2 ,245 ,156 ,141 1,570 ,118 ,537 1,862

Position d_3 ,096 ,151 ,053 ,636 ,526 ,615 1,625

Position d_4 ,236 ,222 ,080 1,064 ,288 ,762 1,311

Position d_5 ,201 ,184 ,089 1,095 ,275 ,652 1,533

Extraversion ,302 ,118 ,201 2,567 ,011 ,712 1,404

Agreeableness ,111 ,133 ,059 ,834 ,405 ,867 1,153

Conscient. -,033 ,128 -,019 -,259 ,796 ,848 1,179

Neuroticism -,115 ,117 -,078 -,976 ,330 ,690 1,448

Openness -,073 ,121 -,042 -,603 ,547 ,894 1,118

a. Dependent Variable: TWPF Collaborate


13.6.4. Personality Traits – Task Workplace Fit Learn

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,148a ,022 -,006 ,96438

2 ,254b ,065 ,014 ,95455 1,982

Model Summary

Model

Change Statistics

R Square


1 ,022a ,788 6 210 ,580

2 ,043b 1,870 5 205 ,101

ANOVA


1 Regression 4,398 6 ,733 ,788 ,580a

Residual 195,306 210 ,930

Total 199,704 216

2 Regression 12,917 11 1,174 1,289 ,233b

Residual 186,787 205 ,911

Total 199,704 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: TWPF Learn


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,794 ,401 9,468 ,000

Gender ,092 ,177 ,036 ,519 ,604 ,968 1,033

Age -,012 ,009 -,098 -1,357 ,176 ,892 1,121

Position d_2 ,046 ,186 ,022 ,247 ,805 ,600 1,667

Position d_3 -,136 ,189 -,063 -,721 ,472 ,619 1,616

Position d_4 ,275 ,273 ,077 1,009 ,314 ,797 1,255

Position d_5 ,103 ,225 ,037 ,456 ,649 ,690 1,449

2 (Constant) 2,549 1,275 1,999 ,047

Gender ,046 ,181 ,018 ,256 ,798 ,903 1,107

Age -,008 ,009 -,066 -,908 ,365 ,858 1,165

Position d_2 -,119 ,195 -,056 -,611 ,542 ,537 1,862

Position d_3 -,164 ,188 -,075 -,875 ,383 ,615 1,625

Position d_4 ,200 ,276 ,056 ,723 ,470 ,762 1,311

Position d_5 ,002 ,229 ,001 ,007 ,994 ,652 1,533

Extraversion ,340 ,146 ,186 2,324 ,021 ,712 1,404

Agreeableness -,014 ,165 -,006 -,086 ,931 ,867 1,153

Conscient. ,113 ,160 ,052 ,706 ,481 ,848 1,179

Neuroticism -,088 ,146 -,049 -,600 ,549 ,690 1,448

Openness -,088 ,151 -,042 -,582 ,561 ,894 1,118

a. Dependent Variable: TWPF Learn


13.7. Personality Traits – Work Performance

13.7.1.A. Personality Traits – Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,286b ,082 ,033 ,67028 2,070

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,030b 1,327 5 205 ,254

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 8,208 11 ,746 1,661 ,084b

Residual 92,102 205 ,449

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,713 ,280 13,280 ,000

Gender -,023 ,123 -,012 -,183 ,855 ,968 1,033

Age -,001 ,006 -,013 -,176 ,860 ,892 1,121

Position d_2 ,328 ,130 ,219 2,522 ,012 ,600 1,667

Position d_3 -,061 ,132 -,040 -,466 ,642 ,619 1,616

Position d_4 ,058 ,190 ,023 ,306 ,760 ,797 1,255

Position d_5 ,054 ,157 ,028 ,341 ,733 ,690 1,449

2 (Constant) 2,829 ,895 3,159 ,002

Gender -,032 ,127 -,018 -,253 ,801 ,903 1,107

Age ,001 ,006 ,011 ,154 ,878 ,858 1,165

Position d_2 ,234 ,137 ,156 1,708 ,089 ,537 1,862

Position d_3 -,077 ,132 -,050 -,583 ,561 ,615 1,625

Position d_4 ,042 ,194 ,016 ,214 ,831 ,762 1,311

Position d_5 -,024 ,161 -,013 -,152 ,879 ,652 1,533

Extraversion ,169 ,103 ,131 1,648 ,101 ,712 1,404

Agreeableness ,129 ,116 ,080 1,110 ,268 ,867 1,153

Conscient. -,035 ,112 -,023 -,311 ,756 ,848 1,179

Neuroticism -,043 ,103 -,034 -,421 ,674 ,690 1,448

Openness -,015 ,106 -,010 -,140 ,889 ,894 1,118



13.7.1.B. Personality Traits – Employee satisfaction (Variant B)

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,273b ,075 ,044 ,66647 2,077

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,022b 5,062 1 209 ,025

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 7,475 7 1,068 2,404 ,022b

Residual 92,835 209 ,444

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Extraversion c. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,713 ,280 13,280 ,000

Gender -,023 ,123 -,012 -,183 ,855 ,968 1,033

Age -,001 ,006 -,013 -,176 ,860 ,892 1,121

Position d_2 ,328 ,130 ,219 2,522 ,012 ,600 1,667

Position d_3 -,061 ,132 -,040 -,466 ,642 ,619 1,616

Position d_4 ,058 ,190 ,023 ,306 ,760 ,797 1,255

Position d_5 ,054 ,157 ,028 ,341 ,733 ,690 1,449

2 (Constant) 2,881 ,462 6,232 ,000

Gender -,034 ,122 -,019 -,276 ,783 ,967 1,035

Age ,001 ,006 ,011 ,150 ,881 ,873 1,145

Position d_2 ,245 ,134 ,163 1,826 ,069 ,554 1,805

Position d_3 -,074 ,131 -,048 -,562 ,575 ,618 1,619

Position d_4 ,031 ,189 ,012 ,165 ,869 ,794 1,260

Position d_5 ,000 ,157 ,000 ,001 ,999 ,674 1,483

Extraversion ,204 ,091 ,158 2,250 ,025 ,903 1,107



13.7.2. Personality Traits – Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,319b ,102 ,054 ,72482 2,127

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,093 6 210 ,368

2 ,072b 3,268 5 205 ,007

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 12,214 11 1,110 2,114 ,021b

Residual 107,700 205 ,525

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,958 ,309 12,799 ,000

Gender ,041 ,137 ,021 ,302 ,763 ,968 1,033

Age -,003 ,007 -,032 -,440 ,661 ,892 1,121

Position d_2 -,281 ,144 -,172 -1,959 ,051 ,600 1,667

Position d_3 -,158 ,146 -,093 -1,082 ,281 ,619 1,616

Position d_4 ,094 ,211 ,034 ,445 ,657 ,797 1,255

Position d_5 -,104 ,174 -,049 -,599 ,550 ,690 1,449

2 (Constant) 3,853 ,968 3,979 ,000

Gender ,022 ,138 ,011 ,163 ,871 ,903 1,107

Age -,001 ,007 -,011 -,159 ,874 ,858 1,165

Position d_2 -,430 ,148 -,262 -2,905 ,004 ,537 1,862

Position d_3 -,194 ,143 -,115 -1,358 ,176 ,615 1,625

Position d_4 ,011 ,210 ,004 ,054 ,957 ,762 1,311

Position d_5 -,231 ,174 -,109 -1,325 ,187 ,652 1,533

Extraversion ,048 ,111 ,034 ,434 ,665 ,712 1,404

Agreeableness ,180 ,126 ,102 1,434 ,153 ,867 1,153

Conscient. ,022 ,121 ,013 ,185 ,854 ,848 1,179

Neuroticism -,301 ,111 -,216 -2,707 ,007 ,690 1,448

Openness -,046 ,115 -,028 -,402 ,688 ,894 1,118



13.7.3. Personality Traits – Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,484b ,234 ,193 ,44387 2,111

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscient., Extraversion, Neuroticism c. Dependent Variable: Productivity

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,212b 11,332 5 205 ,000

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 12,334 11 1,121 5,691 ,000b

Residual 40,389 205 ,197

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Openness, Agreeableness, Conscientiousness, Extraversion, Neuroticism c. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 4,087 ,206 19,850 ,000

Gender ,113 ,091 ,086 1,242 ,216 ,968 1,033

Age -,005 ,004 -,074 -1,030 ,304 ,892 1,121

Position d_2 ,098 ,096 ,090 1,023 ,307 ,600 1,667

Position d_3 ,000 ,097 ,000 -,001 ,999 ,619 1,616

Position d_4 ,153 ,140 ,084 1,093 ,276 ,797 1,255

Position d_5 ,053 ,116 ,038 ,460 ,646 ,690 1,449

2 (Constant) 2,124 ,593 3,582 ,000

Gender -,016 ,084 -,012 -,194 ,847 ,903 1,107

Age -,005 ,004 -,080 -1,205 ,230 ,858 1,165

Position d_2 ,013 ,091 ,012 ,143 ,886 ,537 1,862

Position d_3 -,019 ,087 -,017 -,213 ,832 ,615 1,625

Position d_4 ,090 ,128 ,049 ,702 ,484 ,762 1,311

Position d_5 ,047 ,107 ,033 ,437 ,663 ,652 1,533

Extraversion ,050 ,068 ,053 ,738 ,462 ,712 1,404

Agreeableness -,001 ,077 -,001 -,013 ,989 ,867 1,153

Conscient. ,448 ,074 ,400 6,023 ,000 ,848 1,179

Neuroticism -,099 ,068 -,107 -1,459 ,146 ,690 1,448

Openness ,099 ,070 ,091 1,405 ,161 ,894 1,118




14.1. Personality – Reflexivity / Work Performance

14.1.1. Personality – Reflection on working hours and schedule / Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,288b ,083 ,029 ,67156

3 ,303c ,092 ,014 ,67656 2,050

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,031b 1,139 6 204 ,341

3 ,009c ,399 5 199 ,849

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 8,309 12 ,692 1,535 ,114b

Residual 92,001 204 ,451

Total 100,310 216

3 Regression 9,222 17 ,542 1,185 ,279c

Residual 91,088 199 ,458

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, RefTimeC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, RefTimeC, bfieC, bfinC, RefTimeC_bfiaC, RefTimeC_bfioC, RefTimeC_bfieC, RefTimeC_bficC, RefTimeC_bfinC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,640 ,289 12,578 ,000

Gender -,041 ,129 -,023 -,321 ,749 ,883 1,133

Age ,002 ,006 ,018 ,250 ,803 ,820 1,219

Position d_2 ,241 ,138 ,161 1,748 ,082 ,530 1,887

Position d_3 -,069 ,133 -,045 -,522 ,602 ,607 1,648

Position d_4 ,040 ,194 ,016 ,204 ,839 ,762 1,312

Position d_5 -,025 ,161 -,013 -,157 ,875 ,652 1,533

bfieC ,170 ,103 ,131 1,653 ,100 ,712 1,405

bfiaC ,123 ,117 ,076 1,052 ,294 ,858 1,166

bficC -,033 ,113 -,021 -,290 ,772 ,847 1,181

bfinC -,045 ,103 -,035 -,433 ,665 ,690 1,450

bfioC -,014 ,106 -,009 -,130 ,897 ,894 1,119

RefTimeC ,029 ,062 ,034 ,473 ,637 ,883 1,132

3 (Constant) 3,615 ,293 12,333 ,000

Gender -,045 ,131 -,025 -,346 ,730 ,868 1,153

Age ,002 ,006 ,023 ,309 ,758 ,815 1,227

Position d_2 ,247 ,140 ,165 1,763 ,080 ,521 1,918

Position d_3 -,073 ,135 -,048 -,545 ,586 ,601 1,665

Position d_4 ,069 ,198 ,027 ,349 ,727 ,744 1,344

Position d_5 -,027 ,164 -,014 -,166 ,869 ,642 1,557

bfieC ,161 ,105 ,125 1,533 ,127 ,692 1,445

bfiaC ,127 ,120 ,079 1,055 ,293 ,824 1,214

bficC -,031 ,114 -,020 -,269 ,788 ,832 1,202

bfinC -,037 ,106 -,029 -,347 ,729 ,667 1,499

bfioC -,002 ,109 -,001 -,021 ,984 ,857 1,167

RefTimeC ,032 ,066 ,037 ,486 ,627 ,773 1,293

RefTimeC_bfieC ,044 ,122 ,028 ,360 ,719 ,780 1,281

RefTimeC_bfiaC ,123 ,141 ,068 ,870 ,385 ,748 1,337

RefTimeC_bficC ,090 ,144 ,047 ,625 ,533 ,808 1,238

RefTimeC_bfinC ,079 ,127 ,051 ,620 ,536 ,668 1,497

RefTimeC_bfioC -,070 ,135 -,038 -,517 ,606 ,861 1,162



14.1.2.A. Personality – Reflection on choice of location / Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,303b ,092 ,038 ,66827

3 ,368c ,135 ,061 ,66018 2,070

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,040b 1,485 6 204 ,185

3 ,044c 2,006 5 199 ,079

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 9,206 12 ,767 1,718 ,065b

Residual 91,104 204 ,447

Total 100,310 216

3 Regression 13,578 17 ,799 1,833 ,026c

Residual 86,732 199 ,436

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC, RefLocC_bfiaC, RefLocC_bficC, RefLocC_bfioC, RefLocC_bfinC, RefLocC_bfieC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,635 ,282 12,894 ,000

Gender -,063 ,129 -,035 -,493 ,622 ,879 1,137

Age ,002 ,006 ,019 ,266 ,790 ,853 1,172

Position d_2 ,248 ,137 ,165 1,811 ,072 ,535 1,870

Position d_3 -,069 ,132 -,044 -,521 ,603 ,614 1,628

Position d_4 ,052 ,193 ,021 ,269 ,788 ,761 1,313

Position d_5 -,014 ,161 -,007 -,087 ,931 ,651 1,536

bfieC ,167 ,103 ,129 1,630 ,105 ,712 1,405

bfiaC ,125 ,116 ,077 1,080 ,282 ,867 1,154

bficC -,028 ,112 -,018 -,248 ,804 ,847 1,181

bfinC -,050 ,103 -,039 -,486 ,627 ,689 1,451

bfioC -,017 ,106 -,011 -,159 ,874 ,894 1,119

RefLocC ,094 ,063 ,102 1,495 ,136 ,955 1,047

3 (Constant) 3,617 ,282 12,823 ,000

Gender -,038 ,128 -,021 -,294 ,769 ,861 1,162

Age ,002 ,006 ,021 ,292 ,771 ,842 1,187

Position d_2 ,276 ,136 ,184 2,034 ,043 ,528 1,892

Position d_3 -,051 ,132 -,033 -,385 ,701 ,599 1,669

Position d_4 ,001 ,194 ,000 ,003 ,998 ,736 1,358

Position d_5 ,000 ,160 ,000 ,001 ,999 ,639 1,565

bfieC ,227 ,103 ,175 2,194 ,029 ,683 1,464

bfiaC ,119 ,115 ,074 1,036 ,301 ,856 1,168

bficC -,013 ,111 -,008 -,114 ,910 ,840 1,191

bfinC -,025 ,103 -,020 -,247 ,805 ,673 1,486

bfioC ,022 ,106 ,015 ,210 ,834 ,874 1,144

RefLocC ,075 ,065 ,081 1,149 ,252 ,868 1,152

RefLocC_bfieC -,494 ,168 -,273 -2,939 ,004 ,505 1,980

RefLocC_bfiaC ,139 ,172 ,065 ,810 ,419 ,680 1,470

RefLocC_bficC -,119 ,165 -,052 -,720 ,472 ,845 1,184

RefLocC_bfinC -,255 ,149 -,157 -1,707 ,089 ,512 1,953

RefLocC_bfioC -,007 ,143 -,003 -,047 ,963 ,796 1,256



14.1.2.B. Personality – Reflection on choice of location / Employee satisfaction (Variant B)

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,303b ,092 ,038 ,66827

3 ,340c ,116 ,059 ,66101 2,031

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,040b 1,485 6 204 ,185

3 ,024c 5,510 1 203 ,020

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 9,206 12 ,767 1,718 ,065b

Residual 91,104 204 ,447

Total 100,310 216

3 Regression 11,613 13 ,893 2,045 ,019c

Residual 88,697 203 ,437

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC, RefLocC_bfieC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,635 ,282 12,894 ,000

Gender -,063 ,129 -,035 -,493 ,622 ,879 1,137

Age ,002 ,006 ,019 ,266 ,790 ,853 1,172

Position d_2 ,248 ,137 ,165 1,811 ,072 ,535 1,870

Position d_3 -,069 ,132 -,044 -,521 ,603 ,614 1,628

Position d_4 ,052 ,193 ,021 ,269 ,788 ,761 1,313

Position d_5 -,014 ,161 -,007 -,087 ,931 ,651 1,536

bfieC ,167 ,103 ,129 1,630 ,105 ,712 1,405

bfiaC ,125 ,116 ,077 1,080 ,282 ,867 1,154

bficC -,028 ,112 -,018 -,248 ,804 ,847 1,181

bfinC -,050 ,103 -,039 -,486 ,627 ,689 1,451

bfioC -,017 ,106 -,011 -,159 ,874 ,894 1,119

RefLocC ,094 ,063 ,102 1,495 ,136 ,955 1,047

3 (Constant) 3,570 ,280 12,737 ,000

Gender -,033 ,128 -,018 -,257 ,797 ,870 1,149

Age ,003 ,006 ,030 ,418 ,676 ,850 1,177

Position d_2 ,276 ,136 ,184 2,033 ,043 ,530 1,885

Position d_3 -,036 ,131 -,023 -,273 ,785 ,607 1,647

Position d_4 ,050 ,191 ,020 ,262 ,793 ,761 1,313

Position d_5 ,002 ,159 ,001 ,015 ,988 ,650 1,539

bfieC ,208 ,103 ,160 2,022 ,044 ,692 1,446

bfiaC ,139 ,115 ,086 1,214 ,226 ,864 1,157

bficC -,018 ,111 -,011 -,159 ,874 ,845 1,183

bfinC -,026 ,102 -,021 -,259 ,796 ,683 1,465

bfioC ,007 ,105 ,005 ,067 ,946 ,886 1,129

RefLocC ,108 ,063 ,117 1,719 ,087 ,947 1,056

RefLocC_bfieC -,296 ,126 -,163 -2,347 ,020 ,898 1,114



14.1.3. Personality – Reflection on media use / Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,316b ,100 ,047 ,66532

3 ,337c ,114 ,038 ,66845 2,049

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,048b 1,801 6 204 ,100

3 ,014c ,619 5 199 ,686

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 10,010 12 ,834 1,885 ,038b

Residual 90,299 204 ,443

Total 100,310 216

3 Regression 11,392 17 ,670 1,500 ,097c

Residual 88,917 199 ,447

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, RefMedC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, RefMedC, bficC, bfieC, bfinC, RefMedC_bfieC, RefMedC_bfiaC, RefMedC_bficC, RefMedC_bfioC, RefMedC_bfinC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,605 ,282 12,799 ,000

Gender -,020 ,127 -,011 -,155 ,877 ,901 1,110

Age ,003 ,006 ,030 ,414 ,679 ,844 1,185

Position d_2 ,217 ,136 ,145 1,595 ,112 ,535 1,869

Position d_3 -,065 ,131 -,042 -,497 ,620 ,614 1,629

Position d_4 ,033 ,193 ,013 ,173 ,863 ,762 1,312

Position d_5 -,066 ,161 -,034 -,410 ,682 ,642 1,558

bfieC ,168 ,102 ,130 1,650 ,100 ,712 1,404

bfiaC ,097 ,116 ,060 ,836 ,404 ,851 1,175

bficC -,058 ,112 -,038 -,518 ,605 ,839 1,192

bfinC -,070 ,103 -,055 -,680 ,497 ,679 1,473

bfioC -,053 ,107 -,035 -,492 ,624 ,867 1,154

RefMedC ,154 ,076 ,141 2,018 ,045 ,908 1,101

3 (Constant) 3,634 ,284 12,776 ,000

Gender -,012 ,128 -,007 -,093 ,926 ,890 1,123

Age ,001 ,006 ,017 ,231 ,818 ,830 1,204

Position d_2 ,234 ,137 ,156 1,702 ,090 ,530 1,885

Position d_3 -,056 ,133 -,036 -,422 ,674 ,602 1,662

Position d_4 ,065 ,195 ,026 ,332 ,740 ,751 1,331

Position d_5 -,047 ,166 -,024 -,286 ,775 ,613 1,632

bfieC ,173 ,105 ,133 1,648 ,101 ,682 1,465

bfiaC ,130 ,120 ,080 1,085 ,279 ,811 1,233

bficC -,078 ,115 -,051 -,679 ,498 ,800 1,250

bfinC -,065 ,107 -,051 -,606 ,545 ,632 1,583

bfioC -,074 ,109 -,049 -,679 ,498 ,843 1,187

RefMedC ,170 ,080 ,156 2,118 ,035 ,826 1,211

RefMedC_bfieC -,192 ,187 -,094 -1,026 ,306 ,532 1,880

RefMedC_bfiaC ,031 ,164 ,013 ,188 ,851 ,870 1,150

RefMedC_bficC ,225 ,190 ,088 1,184 ,238 ,812 1,232

RefMedC_bfinC ,060 ,151 ,034 ,399 ,690 ,606 1,651

RefMedC_bfioC ,108 ,174 ,048 ,617 ,538 ,725 1,379



14.1.4. Personality – Reflection on working hours and schedule / Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,441b ,194 ,147 ,68830

3 ,446c ,199 ,131 ,69463 2,105

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,093 6 210 ,368

2 ,164b 6,909 6 204 ,000

3 ,005c ,260 5 199 ,934

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 23,269 12 1,939 4,093 ,000b

Residual 96,646 204 ,474

Total 119,914 216

3 Regression 23,896 17 1,406 2,913 ,000c

Residual 96,018 199 ,483

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, RefTimeC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, RefTimeC, bfieC, bfinC, RefTimeC_bfiaC, RefTimeC_bfioC, RefTimeC_bfieC, RefTimeC_bficC, RefTimeC_bfinC d. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,642 ,297 12,282 ,000

Gender -,074 ,132 -,037 -,559 ,577 ,883 1,133

Age ,005 ,006 ,059 ,849 ,397 ,820 1,219

Position d_2 -,351 ,141 -,214 -2,484 ,014 ,530 1,887

Position d_3 -,117 ,136 -,069 -,856 ,393 ,607 1,648

Position d_4 -,009 ,199 -,003 -,045 ,965 ,762 1,312

Position d_5 -,240 ,165 -,113 -1,449 ,149 ,652 1,533

bfieC ,058 ,106 ,041 ,547 ,585 ,712 1,405

bfiaC ,119 ,120 ,067 ,993 ,322 ,858 1,166

bficC ,046 ,115 ,027 ,396 ,692 ,847 1,181

bfinC -,315 ,106 -,226 -2,980 ,003 ,690 1,450

bfioC -,035 ,109 -,022 -,326 ,745 ,894 1,119

RefTimeC ,305 ,063 ,323 4,830 ,000 ,883 1,132

3 (Constant) 3,626 ,301 12,050 ,000

Gender -,065 ,135 -,033 -,485 ,629 ,868 1,153

Age ,006 ,007 ,060 ,855 ,394 ,815 1,227

Position d_2 -,335 ,144 -,204 -2,326 ,021 ,521 1,918

Position d_3 -,109 ,138 -,065 -,791 ,430 ,601 1,665

Position d_4 ,009 ,203 ,003 ,045 ,964 ,744 1,344

Position d_5 -,246 ,168 -,116 -1,463 ,145 ,642 1,557

bfieC ,046 ,108 ,032 ,422 ,673 ,692 1,445

bfiaC ,134 ,124 ,076 1,083 ,280 ,824 1,214

bficC ,044 ,117 ,026 ,379 ,705 ,832 1,202

bfinC -,305 ,108 -,219 -2,818 ,005 ,667 1,499

bfioC -,020 ,112 -,012 -,177 ,859 ,857 1,167

RefTimeC ,318 ,068 ,337 4,665 ,000 ,773 1,293

RefTimeC_bfieC ,066 ,125 ,038 ,529 ,597 ,780 1,281

RefTimeC_bfiaC ,030 ,145 ,015 ,206 ,837 ,748 1,337

RefTimeC_bficC -,019 ,148 -,009 -,130 ,897 ,808 1,238

RefTimeC_bfinC ,140 ,131 ,083 1,072 ,285 ,668 1,497

RefTimeC_bfioC ,010 ,139 ,005 ,070 ,944 ,861 1,162



14.1.5. Personality – Reflection on choice of location / Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,327b ,107 ,055 ,72448

3 ,348c ,121 ,046 ,72768 2,068

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,093 6 210 ,368

2 ,077b 2,924 6 204 ,009

3 ,014c ,643 5 199 ,667

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 12,840 12 1,070 2,039 ,023b

Residual 107,074 204 ,525

Total 119,914 216

3 Regression 14,541 17 ,855 1,615 ,063c

Residual 105,373 199 ,530

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC, RefLocC_bfiaC, RefLocC_bficC, RefLocC_bfioC, RefLocC_bfinC, RefLocC_bfieC d. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,927 ,306 12,847 ,000

Gender -,002 ,139 -,001 -,017 ,986 ,879 1,137

Age -,001 ,007 -,005 -,076 ,939 ,853 1,172

Position d_2 -,419 ,148 -,256 -2,826 ,005 ,535 1,870

Position d_3 -,187 ,143 -,111 -1,311 ,191 ,614 1,628

Position d_4 ,020 ,210 ,007 ,094 ,925 ,761 1,313

Position d_5 -,222 ,174 -,105 -1,277 ,203 ,651 1,536

bfieC ,046 ,111 ,033 ,418 ,676 ,712 1,405

bfiaC ,177 ,126 ,100 1,410 ,160 ,867 1,154

bficC ,028 ,121 ,017 ,231 ,817 ,847 1,181

bfinC -,306 ,111 -,219 -2,753 ,006 ,689 1,451

bfioC -,048 ,115 -,029 -,416 ,678 ,894 1,119

RefLocC ,075 ,068 ,074 1,092 ,276 ,955 1,047

3 (Constant) 3,918 ,311 12,602 ,000

Gender ,012 ,142 ,006 ,086 ,932 ,861 1,162

Age -,001 ,007 -,006 -,078 ,938 ,842 1,187

Position d_2 -,399 ,150 -,244 -2,668 ,008 ,528 1,892

Position d_3 -,170 ,145 -,101 -1,174 ,242 ,599 1,669

Position d_4 -,016 ,214 -,006 -,075 ,940 ,736 1,358

Position d_5 -,217 ,177 -,102 -1,230 ,220 ,639 1,565

bfieC ,076 ,114 ,054 ,667 ,505 ,683 1,464

bfiaC ,180 ,127 ,102 1,414 ,159 ,856 1,168

bficC ,035 ,122 ,021 ,284 ,777 ,840 1,191

bfinC -,299 ,113 -,215 -2,649 ,009 ,673 1,486

bfioC -,036 ,116 -,022 -,306 ,760 ,874 1,144

RefLocC ,077 ,072 ,076 1,062 ,290 ,868 1,152

RefLocC_bfieC -,245 ,185 -,124 -1,323 ,187 ,505 1,980

RefLocC_bfiaC ,000 ,190 ,000 ,001 ,999 ,680 1,470

RefLocC_bficC -,178 ,182 -,071 -,981 ,328 ,845 1,184

RefLocC_bfinC -,111 ,165 -,062 -,673 ,502 ,512 1,953

RefLocC_bfioC ,083 ,157 ,039 ,528 ,598 ,796 1,256



14.1.6. Personality – Reflection on media use/ Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,398b ,158 ,109 ,70336

3 ,422c ,178 ,108 ,70364 2,204

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,093 6 210 ,368

2 ,128b 5,176 6 204 ,000

3 ,020c ,968 5 199 ,439

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 18,993 12 1,583 3,199 ,000b

Residual 100,921 204 ,495

Total 119,914 216

3 Regression 21,389 17 1,258 2,541 ,001c

Residual 98,525 199 ,495

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, RefMedC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, RefMedC, bficC, bfieC, bfinC, RefMedC_bfieC, RefMedC_bfiaC, RefMedC_bficC, RefMedC_bfioC, RefMedC_bfinC d. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,828 ,298 12,859 ,000

Gender ,047 ,134 ,024 ,350 ,727 ,901 1,110

Age ,002 ,007 ,022 ,315 ,753 ,844 1,185

Position d_2 -,462 ,144 -,282 -3,214 ,002 ,535 1,869

Position d_3 -,171 ,138 -,101 -1,234 ,219 ,614 1,629

Position d_4 -,005 ,204 -,002 -,022 ,982 ,762 1,312

Position d_5 -,311 ,170 -,147 -1,828 ,069 ,642 1,558

bfieC ,046 ,108 ,033 ,429 ,668 ,712 1,404

bfiaC ,119 ,123 ,067 ,964 ,336 ,851 1,175

bficC -,022 ,118 -,013 -,189 ,850 ,839 1,192

bfinC -,353 ,109 -,253 -3,243 ,001 ,679 1,473

bfioC -,119 ,113 -,073 -1,055 ,293 ,867 1,154

RefMedC ,298 ,080 ,249 3,702 ,000 ,908 1,101

3 (Constant) 3,823 ,299 12,767 ,000

Gender ,054 ,135 ,027 ,403 ,687 ,890 1,123

Age ,002 ,007 ,018 ,261 ,794 ,830 1,204

Position d_2 -,466 ,144 -,285 -3,225 ,001 ,530 1,885

Position d_3 -,174 ,140 -,103 -1,244 ,215 ,602 1,662

Position d_4 -,004 ,205 -,002 -,020 ,984 ,751 1,331

Position d_5 -,313 ,174 -,147 -1,794 ,074 ,613 1,632

bfieC ,012 ,110 ,008 ,108 ,914 ,682 1,465

bfiaC ,138 ,126 ,078 1,093 ,276 ,811 1,233

bficC -,054 ,121 -,032 -,444 ,658 ,800 1,250

bfinC -,377 ,113 -,270 -3,345 ,001 ,632 1,583

bfioC -,144 ,115 -,088 -1,261 ,209 ,843 1,187

RefMedC ,317 ,084 ,265 3,752 ,000 ,826 1,211

RefMedC_bfieC ,216 ,197 ,096 1,095 ,275 ,532 1,880

RefMedC_bfiaC ,090 ,173 ,036 ,518 ,605 ,870 1,150

RefMedC_bficC ,137 ,200 ,049 ,686 ,494 ,812 1,232

RefMedC_bfinC ,159 ,159 ,083 1,001 ,318 ,606 1,651

RefMedC_bfioC ,196 ,183 ,081 1,068 ,287 ,725 1,379



14.1.7. Personality – Reflection on working hours and schedule / Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,499b ,249 ,205 ,44058

3 ,514c ,264 ,201 ,44164 2,075

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,227b 10,263 6 204 ,000

3 ,015c ,803 5 199 ,549

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 13,124 12 1,094 5,634 ,000b

Residual 39,598 204 ,194

Total 52,722 216

3 Regression 13,908 17 ,818 4,194 ,000c

Residual 38,815 199 ,195

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, RefTimeC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, RefTimeC, bfieC, bfinC, RefTimeC_bfiaC, RefTimeC_bfioC, RefTimeC_bfieC, RefTimeC_bficC, RefTimeC_bfinC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,074 ,190 21,463 ,000

Gender -,042 ,085 -,032 -,497 ,620 ,883 1,133

Age -,003 ,004 -,051 -,764 ,446 ,820 1,219

Position d_2 ,034 ,091 ,031 ,375 ,708 ,530 1,887

Position d_3 ,002 ,087 ,002 ,023 ,981 ,607 1,648

Position d_4 ,085 ,127 ,046 ,664 ,507 ,762 1,312

Position d_5 ,044 ,106 ,031 ,418 ,676 ,652 1,533

bfieC ,053 ,068 ,056 ,781 ,436 ,712 1,405

bfiaC -,017 ,077 -,015 -,226 ,821 ,858 1,166

bficC ,454 ,074 ,405 6,148 ,000 ,847 1,181

bfinC -,103 ,068 -,111 -1,524 ,129 ,690 1,450

bfioC ,101 ,070 ,093 1,456 ,147 ,894 1,119

RefTimeC ,082 ,040 ,130 2,018 ,045 ,883 1,132

3 (Constant) 4,062 ,191 21,232 ,000

Gender -,032 ,086 -,025 -,379 ,705 ,868 1,153

Age -,003 ,004 -,048 -,711 ,478 ,815 1,227

Position d_2 ,029 ,091 ,026 ,315 ,753 ,521 1,918

Position d_3 -,002 ,088 -,002 -,026 ,979 ,601 1,665

Position d_4 ,087 ,129 ,048 ,674 ,501 ,744 1,344

Position d_5 ,058 ,107 ,041 ,544 ,587 ,642 1,557

bfieC ,050 ,069 ,053 ,731 ,465 ,692 1,445

bfiaC -,028 ,079 -,023 -,350 ,727 ,824 1,214

bficC ,457 ,075 ,408 6,119 ,000 ,832 1,202

bfinC -,088 ,069 -,095 -1,272 ,205 ,667 1,499

bfioC ,090 ,071 ,082 1,255 ,211 ,857 1,167

RefTimeC ,070 ,043 ,111 1,610 ,109 ,773 1,293

RefTimeC_bfieC ,027 ,079 ,024 ,343 ,732 ,780 1,281

RefTimeC_bfiaC ,125 ,092 ,095 1,356 ,177 ,748 1,337

RefTimeC_bficC ,044 ,094 ,031 ,462 ,644 ,808 1,238

RefTimeC_bfinC ,018 ,083 ,016 ,218 ,828 ,668 1,497

RefTimeC_bfioC ,084 ,088 ,063 ,957 ,340 ,861 1,162



14.1.8.A. Personality – Reflection on choice of location / Productivity

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,215b 9,593 6 204 ,000

3 ,037c 2,015 5 199 ,078

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,487b ,237 ,193 ,44395

3 ,524c ,274 ,212 ,43853 2,107

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 12,515 12 1,043 5,292 ,000b

Residual 40,207 204 ,197

Total 52,722 216

3 Regression 14,453 17 ,850 4,421 ,000c

Residual 38,269 199 ,192

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC, RefLocC_bfiaC, RefLocC_bficC, RefLocC_bfioC, RefLocC_bfinC, RefLocC_bfieC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,143 ,187 22,119 ,000

Gender -,030 ,085 -,023 -,347 ,729 ,879 1,137

Age -,005 ,004 -,075 -1,129 ,260 ,853 1,172

Position d_2 ,019 ,091 ,017 ,208 ,835 ,535 1,870

Position d_3 -,015 ,087 -,013 -,172 ,864 ,614 1,628

Position d_4 ,095 ,129 ,052 ,736 ,462 ,761 1,313

Position d_5 ,051 ,107 ,036 ,479 ,633 ,651 1,536

bfieC ,049 ,068 ,052 ,723 ,470 ,712 1,405

bfiaC -,003 ,077 -,002 -,035 ,972 ,867 1,154

bficC ,451 ,074 ,403 6,058 ,000 ,847 1,181

bfinC -,102 ,068 -,110 -1,499 ,135 ,689 1,451

bfioC ,098 ,070 ,090 1,393 ,165 ,894 1,119

RefLocC ,040 ,042 ,060 ,960 ,338 ,955 1,047

3 (Constant) 4,117 ,187 21,974 ,000

Gender -,024 ,085 -,018 -,279 ,781 ,861 1,162

Age -,004 ,004 -,066 -1,008 ,314 ,842 1,187

Position d_2 ,019 ,090 ,018 ,215 ,830 ,528 1,892

Position d_3 -,014 ,087 -,013 -,163 ,871 ,599 1,669

Position d_4 ,115 ,129 ,063 ,893 ,373 ,736 1,358

Position d_5 ,047 ,106 ,033 ,438 ,662 ,639 1,565

bfieC ,058 ,069 ,062 ,849 ,397 ,683 1,464

bfiaC -,011 ,077 -,010 -,146 ,884 ,856 1,168

bficC ,458 ,074 ,409 6,209 ,000 ,840 1,191

bfinC -,081 ,068 -,087 -1,182 ,238 ,673 1,486

bfioC ,122 ,070 ,112 1,736 ,084 ,874 1,144

RefLocC ,022 ,043 ,033 ,507 ,613 ,868 1,152

RefLocC_bfieC -,093 ,112 -,071 -,837 ,404 ,505 1,980

RefLocC_bfiaC ,258 ,114 ,165 2,257 ,025 ,680 1,470

RefLocC_bficC ,156 ,109 ,093 1,420 ,157 ,845 1,184

RefLocC_bfinC ,000 ,099 ,000 ,004 ,997 ,512 1,953

RefLocC_bfioC -,144 ,095 -,103 -1,520 ,130 ,796 1,256



14.1.8.B. Personality – Reflection on choice of location / Productivity (Variant B)

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,487b ,237 ,193 ,44395

3 ,502c ,252 ,204 ,44081 2,108

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,215b 9,593 6 204 ,000

3 ,014c 3,921 1 203 ,049

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 12,515 12 1,043 5,292 ,000b

Residual 40,207 204 ,197

Total 52,722 216

3 Regression 13,277 13 1,021 5,256 ,000c

Residual 39,445 203 ,194

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, RefLocC, bfiaC, bficC, bfieC, bfinC, RefLocC_bfiaC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,143 ,187 22,119 ,000

Gender -,030 ,085 -,023 -,347 ,729 ,879 1,137

Age -,005 ,004 -,075 -1,129 ,260 ,853 1,172

Position d_2 ,019 ,091 ,017 ,208 ,835 ,535 1,870

Position d_3 -,015 ,087 -,013 -,172 ,864 ,614 1,628

Position d_4 ,095 ,129 ,052 ,736 ,462 ,761 1,313

Position d_5 ,051 ,107 ,036 ,479 ,633 ,651 1,536

bfieC ,049 ,068 ,052 ,723 ,470 ,712 1,405

bfiaC -,003 ,077 -,002 -,035 ,972 ,867 1,154

bficC ,451 ,074 ,403 6,058 ,000 ,847 1,181

bfinC -,102 ,068 -,110 -1,499 ,135 ,689 1,451

bfioC ,098 ,070 ,090 1,393 ,165 ,894 1,119

RefLocC ,040 ,042 ,060 ,960 ,338 ,955 1,047

3 (Constant) 4,150 ,186 22,312 ,000

Gender -,038 ,085 -,029 -,445 ,657 ,877 1,140

Age -,005 ,004 -,076 -1,151 ,251 ,853 1,172

Position d_2 ,012 ,090 ,011 ,137 ,891 ,534 1,873

Position d_3 -,017 ,087 -,016 -,201 ,841 ,614 1,629

Position d_4 ,094 ,128 ,051 ,737 ,462 ,761 1,313

Position d_5 ,039 ,106 ,028 ,370 ,712 ,649 1,541

bfieC ,041 ,068 ,043 ,603 ,547 ,709 1,410

bfiaC -,011 ,077 -,009 -,144 ,886 ,864 1,157

bficC ,455 ,074 ,407 6,159 ,000 ,846 1,182

bfinC -,096 ,068 -,104 -1,425 ,156 ,688 1,454

bfioC ,104 ,070 ,096 1,493 ,137 ,892 1,121

RefLocC ,026 ,042 ,039 ,626 ,532 ,929 1,076

RefLocC_bfiaC ,193 ,097 ,124 1,980 ,049 ,945 1,058



14.1.9. Personality – Reflection on media use/ Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,564b ,318 ,278 ,41981

3 ,574c ,330 ,272 ,42146 2,250

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,296b 14,752 6 204 ,000

3 ,011c ,681 5 199 ,638

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 16,770 12 1,397 7,929 ,000b

Residual 35,953 204 ,176

Total 52,722 216

3 Regression 17,375 17 1,022 5,754 ,000c

Residual 35,347 199 ,178

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, RefMedC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, RefMedC, bficC, bfieC, bfinC, RefMedC_bfieC, RefMedC_bfiaC, RefMedC_bficC, RefMedC_bfioC, RefMedC_bfinC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,056 ,178 22,826 ,000

Gender ,003 ,080 ,003 ,043 ,966 ,901 1,110

Age -,002 ,004 -,039 -,617 ,538 ,844 1,185

Position d_2 -,013 ,086 -,012 -,155 ,877 ,535 1,869

Position d_3 ,000 ,083 ,000 -,002 ,998 ,614 1,629

Position d_4 ,077 ,121 ,042 ,635 ,526 ,762 1,312

Position d_5 -,019 ,102 -,013 -,184 ,854 ,642 1,558

bfieC ,049 ,064 ,052 ,755 ,451 ,712 1,404

bfiaC -,051 ,073 -,043 -,691 ,490 ,851 1,175

bficC ,411 ,071 ,367 5,823 ,000 ,839 1,192

bfinC -,141 ,065 -,153 -2,175 ,031 ,679 1,473

bfioC ,039 ,067 ,036 ,586 ,559 ,867 1,154

RefMedC ,241 ,048 ,304 5,017 ,000 ,908 1,101

3 (Constant) 4,068 ,179 22,681 ,000

Gender ,013 ,081 ,010 ,157 ,875 ,890 1,123

Age -,003 ,004 -,047 -,730 ,466 ,830 1,204

Position d_2 -,015 ,087 -,014 -,176 ,861 ,530 1,885

Position d_3 -,007 ,084 -,006 -,085 ,932 ,602 1,662

Position d_4 ,078 ,123 ,043 ,635 ,526 ,751 1,331

Position d_5 -,019 ,104 -,013 -,179 ,858 ,613 1,632

bfieC ,038 ,066 ,040 ,575 ,566 ,682 1,465

bfiaC -,041 ,076 -,035 -,543 ,588 ,811 1,233

bficC ,404 ,073 ,361 5,557 ,000 ,800 1,250

bfinC -,142 ,068 -,153 -2,098 ,037 ,632 1,583

bfioC ,028 ,069 ,026 ,412 ,681 ,843 1,187

RefMedC ,243 ,051 ,307 4,800 ,000 ,826 1,211

RefMedC_bfieC ,057 ,118 ,038 ,482 ,630 ,532 1,880

RefMedC_bfiaC ,095 ,104 ,057 ,921 ,358 ,870 1,150

RefMedC_bficC ,115 ,120 ,062 ,963 ,337 ,812 1,232

RefMedC_bfinC ,019 ,095 ,015 ,203 ,839 ,606 1,651

RefMedC_bfioC ,057 ,110 ,036 ,523 ,601 ,725 1,379



14.2. Personality – Flexibility / Work Performance

14.2.1. Personality – Flex-time / Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67366

2 ,299b ,089 ,035 ,67001

3 ,329c ,109 ,032 ,67119 2,092

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,912 6 209 ,080

2 ,037b 1,381 6 203 ,224

3 ,019c ,857 5 198 ,511

ANOVA


1 Regression 5,206 6 ,868 1,912 ,080a

Residual 94,849 209 ,454

Total 100,055 215

2 Regression 8,925 12 ,744 1,657 ,079b

Residual 91,130 203 ,449

Total 100,055 215

3 Regression 10,856 17 ,639 1,418 ,131c

Residual 89,199 198 ,450

Total 100,055 215

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, FlextimeC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, FlextimeC, bficC, bfieC, bfinC, FlextC_bfieC, FlextC_bfioC, FlextC_bficC, FlextC_bfiaC, FlextC_bfinC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,704 ,283 13,098 ,000

Gender -,050 ,128 -,028 -,393 ,694 ,895 1,117

Age ,001 ,006 ,007 ,095 ,925 ,857 1,167

Position d_2 ,207 ,139 ,138 1,490 ,138 ,521 1,919

Position d_3 -,093 ,133 -,060 -,703 ,483 ,607 1,647

Position d_4 ,039 ,194 ,016 ,203 ,839 ,763 1,311

Position d_5 -,018 ,164 -,009 -,107 ,915 ,647 1,545

bfieC ,175 ,104 ,134 1,693 ,092 ,718 1,393

bfiaC ,151 ,117 ,093 1,290 ,198 ,870 1,150

bficC -,022 ,113 -,014 -,193 ,847 ,850 1,177

bfinC -,054 ,103 -,042 -,523 ,602 ,698 1,432

bfioC -,034 ,107 -,023 -,317 ,751 ,878 1,139

FlextimeC ,003 ,004 ,060 ,860 ,391 ,921 1,085

3 (Constant) 3,749 ,285 13,153 ,000

Gender -,057 ,129 -,031 -,440 ,661 ,879 1,137

Age ,000 ,006 -,005 -,073 ,942 ,846 1,182

Position d_2 ,204 ,139 ,136 1,463 ,145 ,519 1,926

Position d_3 -,110 ,134 -,072 -,825 ,410 ,599 1,670

Position d_4 ,023 ,197 ,009 ,117 ,907 ,741 1,349

Position d_5 -,063 ,166 -,032 -,382 ,703 ,635 1,576

bfieC ,155 ,106 ,119 1,462 ,145 ,685 1,460

bfiaC ,116 ,124 ,071 ,936 ,350 ,776 1,289

bficC ,051 ,122 ,033 ,421 ,674 ,731 1,368

bfinC -,011 ,106 -,009 -,103 ,918 ,661 1,514

bfioC ,011 ,113 ,008 ,101 ,920 ,786 1,272

FlextimeC ,003 ,004 ,063 ,858 ,392 ,844 1,185

FlextC_bfieC -,001 ,007 -,013 -,156 ,876 ,637 1,571

FlextC_bfiaC -,018 ,009 -,150 -1,974 ,050 ,776 1,289

FlextC_bficC ,004 ,009 ,031 ,399 ,690 ,757 1,321

FlextC_bfinC ,004 ,008 ,045 ,522 ,602 ,599 1,669

FlextC_bfioC ,009 ,009 ,073 ,964 ,336 ,795 1,258



14.2.2.A. Personality – Flex-place / Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,232a ,054 ,025 ,66707

2 ,290b ,084 ,028 ,66632

3 ,336c ,113 ,033 ,66431 2,060

Model Summary

Model

Change Statistics

R Square


1 ,054a 1,899 6 201 ,083

2 ,030b 1,076 6 195 ,378

3 ,029c 1,236 5 190 ,294

ANOVA


1 Regression 5,070 6 ,845 1,899 ,083a

Residual 89,442 201 ,445

Total 94,512 207

2 Regression 7,936 12 ,661 1,490 ,131b

Residual 86,576 195 ,444

Total 94,512 207

3 Regression 10,663 17 ,627 1,421 ,130c

Residual 83,848 190 ,441

Total 94,512 207

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, FlexplaceC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, FlexplaceC, bfieC, bfinC, FlexplC_bfinC, FlexplC_bfioC, FlexplC_bfiaC, FlexplC_bficC, FlexplC_bfieC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,686 ,282 13,078 ,000

Gender ,055 ,131 ,030 ,417 ,677 ,892 1,121

Age ,000 ,006 -,001 -,020 ,984 ,859 1,164

Position d_2 ,262 ,139 ,176 1,886 ,061 ,538 1,860

Position d_3 -,017 ,135 -,011 -,125 ,900 ,625 1,599

Position d_4 ,026 ,194 ,011 ,134 ,894 ,756 1,322

Position d_5 ,019 ,165 ,010 ,114 ,909 ,615 1,626

bfieC ,187 ,104 ,147 1,806 ,072 ,712 1,404

bfiaC ,073 ,118 ,046 ,625 ,533 ,869 1,150

bficC -,059 ,114 -,038 -,516 ,606 ,847 1,181

bfinC -,052 ,103 -,041 -,502 ,616 ,690 1,450

bfioC -,033 ,108 -,022 -,301 ,764 ,884 1,131

FlexplaceC -,001 ,002 -,058 -,787 ,432 ,860 1,163

3 (Constant) 3,655 ,288 12,676 ,000

Gender ,074 ,131 ,041 ,565 ,573 ,885 1,130

Age 2,786E-5 ,006 ,000 ,004 ,996 ,826 1,211

Position d_2 ,288 ,139 ,194 2,069 ,040 ,534 1,874

Position d_3 ,001 ,136 ,000 ,005 ,996 ,612 1,634

Position d_4 ,102 ,197 ,041 ,517 ,606 ,726 1,377

Position d_5 ,060 ,166 ,032 ,361 ,719 ,608 1,646

bfieC ,185 ,105 ,145 1,763 ,080 ,691 1,447

bfiaC ,072 ,118 ,045 ,609 ,543 ,853 1,172

bficC -,051 ,115 -,034 -,445 ,657 ,820 1,219

bfinC -,054 ,104 -,043 -,521 ,603 ,683 1,464

bfioC -,014 ,111 -,009 -,123 ,902 ,840 1,191

FlexplaceC -,002 ,002 -,075 -1,015 ,312 ,852 1,174

FlexplC_bfieC -,007 ,003 -,171 -2,161 ,032 ,744 1,344

FlexplC_bfiaC ,004 ,004 ,078 1,073 ,285 ,879 1,138

FlexplC_bficC ,002 ,004 ,048 ,664 ,508 ,881 1,135

FlexplC_bfinC -,001 ,003 -,022 -,274 ,785 ,717 1,396

FlexplC_bfioC ,000 ,004 ,007 ,098 ,922 ,888 1,126



14.2.2.B. Personality – Flex-place / Employee satisfaction (Variant B)

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,232a ,054 ,025 ,66707

2 ,282b ,080 ,043 ,66114

3 ,314c ,099 ,058 ,65584 2,043

Model Summary

Model

Change Statistics

R Square


1 ,054a 1,899 6 201 ,083

2 ,026b 2,810 2 199 ,063

3 ,019c 4,232 1 198 ,041

ANOVA


1 Regression 5,070 6 ,845 1,899 ,083a

Residual 89,442 201 ,445

Total 94,512 207

2 Regression 7,526 8 ,941 2,152 ,033b

Residual 86,985 199 ,437

Total 94,512 207

3 Regression 9,347 9 1,039 2,414 ,013c

Residual 85,165 198 ,430

Total 94,512 207

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfieC, FlexplaceC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfieC, FlexplaceC, FlexplaceC_bfieC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,739 ,279 13,417 ,000

Gender ,049 ,126 ,027 ,385 ,701 ,962 1,039

Age -,002 ,006 -,028 -,388 ,698 ,894 1,119

Position d_2 ,368 ,131 ,248 2,811 ,005 ,607 1,647

Position d_3 ,001 ,134 ,001 ,010 ,992 ,631 1,585

Position d_4 ,065 ,189 ,026 ,341 ,733 ,796 1,257

Position d_5 ,068 ,156 ,036 ,433 ,666 ,689 1,452

2 (Constant) 3,693 ,277 13,312 ,000

Gender ,046 ,125 ,025 ,364 ,716 ,957 1,045

Age ,000 ,006 -,006 -,076 ,939 ,872 1,147

Position d_2 ,276 ,136 ,186 2,037 ,043 ,557 1,796

Position d_3 -,012 ,134 -,007 -,086 ,931 ,628 1,593

Position d_4 ,027 ,188 ,011 ,141 ,888 ,788 1,269

Position d_5 ,046 ,161 ,024 ,283 ,778 ,637 1,571

bfieC ,207 ,092 ,162 2,253 ,025 ,894 1,119

FlexplaceC -,001 ,002 -,060 -,826 ,410 ,879 1,138

3 (Constant) 3,676 ,275 13,354 ,000

Gender ,064 ,125 ,035 ,510 ,611 ,952 1,050

Age ,000 ,006 -,006 -,078 ,938 ,872 1,147

Position d_2 ,294 ,135 ,197 2,178 ,031 ,555 1,803

Position d_3 ,009 ,133 ,006 ,066 ,948 ,624 1,601

Position d_4 ,087 ,189 ,035 ,459 ,647 ,769 1,300

Position d_5 ,066 ,160 ,035 ,413 ,680 ,634 1,577

bfieC ,224 ,091 ,176 2,454 ,015 ,886 1,129

FlexplaceC -,002 ,002 -,070 -,977 ,330 ,874 1,144

FlexplaceC_bfieC -,006 ,003 -,142 -2,057 ,041 ,952 1,050



14.2.3.A. Personality – Flex-time / Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,002 ,74568

2 ,347b ,120 ,068 ,72054

3 ,366c ,134 ,060 ,72395 2,058

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,084 6 209 ,373

2 ,090b 3,472 6 203 ,003

3 ,014c ,619 5 198 ,686

ANOVA


1 Regression 3,615 6 ,603 1,084 ,373a

Residual 116,211 209 ,556

Total 119,826 215

2 Regression 14,432 12 1,203 2,316 ,009b

Residual 105,394 203 ,519

Total 119,826 215

3 Regression 16,054 17 ,944 1,802 ,030c

Residual 103,772 198 ,524

Total 119,826 215

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, FlextimeC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, FlextimeC, bficC, bfieC, bfinC, FlextC_bfieC, FlextC_bfioC, FlextC_bficC, FlextC_bfiaC, FlextC_bfinC d. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,924 ,304 12,903 ,000

Gender ,029 ,138 ,014 ,208 ,835 ,895 1,117

Age -,001 ,007 -,012 -,168 ,867 ,857 1,167

Position d_2 -,377 ,149 -,230 -2,524 ,012 ,521 1,919

Position d_3 -,159 ,143 -,094 -1,110 ,268 ,607 1,647

Position d_4 ,013 ,208 ,005 ,063 ,949 ,763 1,311

Position d_5 -,173 ,176 -,080 -,983 ,327 ,647 1,545

bfieC ,069 ,111 ,048 ,617 ,538 ,718 1,393

bfiaC ,156 ,126 ,087 1,236 ,218 ,870 1,150

bficC ,037 ,122 ,022 ,307 ,759 ,850 1,177

bfinC -,285 ,111 -,202 -2,571 ,011 ,698 1,432

bfioC -,019 ,115 -,012 -,168 ,866 ,878 1,139

FlextimeC -,008 ,004 -,142 -2,078 ,039 ,921 1,085

3 (Constant) 3,960 ,307 12,879 ,000

Gender ,033 ,139 ,017 ,236 ,814 ,879 1,137

Age -,002 ,007 -,023 -,314 ,754 ,846 1,182

Position d_2 -,373 ,150 -,228 -2,481 ,014 ,519 1,926

Position d_3 -,172 ,144 -,102 -1,191 ,235 ,599 1,670

Position d_4 -,039 ,212 -,014 -,186 ,853 ,741 1,349

Position d_5 -,199 ,179 -,092 -1,111 ,268 ,635 1,576

bfieC ,029 ,115 ,020 ,255 ,799 ,685 1,460

bfiaC ,112 ,134 ,063 ,836 ,404 ,776 1,289

bficC ,073 ,132 ,043 ,554 ,580 ,731 1,368

bfinC -,272 ,115 -,193 -2,377 ,018 ,661 1,514

bfioC ,031 ,122 ,019 ,255 ,799 ,786 1,272

FlextimeC -,009 ,004 -,156 -2,173 ,031 ,844 1,185

FlextC_bfieC ,008 ,008 ,085 1,020 ,309 ,637 1,571

FlextC_bfiaC -,009 ,010 -,070 -,926 ,355 ,776 1,289

FlextC_bficC ,012 ,010 ,093 1,228 ,221 ,757 1,321

FlextC_bfinC ,007 ,008 ,070 ,814 ,417 ,599 1,669

FlextC_bfioC ,007 ,010 ,050 ,672 ,502 ,795 1,258



14.2.3.B. Personality – Flex-time / Work life balance (Variant B)

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,002 ,74568

2 ,233b ,054 ,022 ,73817 2,110

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,084 6 209 ,373

2 ,024b 5,273 1 208 ,023

ANOVA


1 Regression 3,615 6 ,603 1,084 ,373a

Residual 116,211 209 ,556

Total 119,826 215

2 Regression 6,488 7 ,927 1,701 ,110b

Residual 113,338 208 ,545

Total 119,826 215

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Flextime c. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,950 ,311 12,720 ,000

Gender ,044 ,137 ,022 ,319 ,750 ,966 1,035

Age -,003 ,007 -,030 -,414 ,679 ,889 1,125

Position d_2 -,282 ,144 -,172 -1,958 ,052 ,601 1,664

Position d_3 -,157 ,146 -,093 -1,076 ,283 ,620 1,613

Position d_4 ,094 ,211 ,034 ,444 ,657 ,797 1,254

Position d_5 -,114 ,176 -,053 -,647 ,519 ,693 1,443

2 (Constant) 4,089 ,313 13,051 ,000

Gender ,058 ,136 ,029 ,427 ,670 ,964 1,037

Age -,003 ,007 -,029 -,399 ,690 ,889 1,125

Position d_2 -,220 ,145 -,134 -1,517 ,131 ,580 1,724

Position d_3 -,118 ,146 -,070 -,809 ,420 ,611 1,636

Position d_4 ,099 ,209 ,036 ,474 ,636 ,797 1,255

Position d_5 -,064 ,176 -,030 -,363 ,717 ,682 1,466

Flextime -,009 ,004 -,158 -2,296 ,023 ,955 1,047



14.2.4. Personality – Flex-place / Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,176a ,031 ,002 ,74698

2 ,328b ,108 ,053 ,72769

3 ,335c ,112 ,032 ,73550 1,991

Model Summary

Model

Change Statistics

R Square


1 ,031a 1,070 6 201 ,382

2 ,077b 2,800 6 195 ,012

3 ,004c ,176 5 190 ,971

ANOVA


1 Regression 3,581 6 ,597 1,070 ,382a

Residual 112,155 201 ,558

Total 115,736 207

2 Regression 12,477 12 1,040 1,963 ,029b

Residual 103,259 195 ,530

Total 115,736 207

3 Regression 12,952 17 ,762 1,408 ,136c

Residual 102,783 190 ,541

Total 115,736 207

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, FlexplaceC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, FlexplaceC, bfieC, bfinC, FlexplC_bfinC, FlexplC_bfioC, FlexplC_bfiaC, FlexplC_bficC, FlexplC_bfieC d. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,001 ,308 12,998 ,000

Gender ,036 ,143 ,018 ,254 ,800 ,892 1,121

Age -,002 ,007 -,025 -,339 ,735 ,859 1,164

Position d_2 -,424 ,152 -,257 -2,791 ,006 ,538 1,860

Position d_3 -,191 ,147 -,111 -1,295 ,197 ,625 1,599

Position d_4 ,007 ,212 ,003 ,033 ,973 ,756 1,322

Position d_5 -,201 ,181 -,096 -1,111 ,268 ,615 1,626

bfieC ,050 ,113 ,036 ,444 ,657 ,712 1,404

bfiaC ,199 ,128 ,112 1,549 ,123 ,869 1,150

bficC ,061 ,124 ,036 ,494 ,622 ,847 1,181

bfinC -,290 ,113 -,209 -2,567 ,011 ,690 1,450

bfioC -,053 ,118 -,032 -,449 ,654 ,884 1,131

FlexplaceC -,001 ,002 -,037 -,507 ,613 ,860 1,163

3 (Constant) 3,986 ,319 12,487 ,000

Gender ,044 ,145 ,022 ,302 ,763 ,885 1,130

Age -,002 ,007 -,021 -,281 ,779 ,826 1,211

Position d_2 -,419 ,154 -,255 -2,720 ,007 ,534 1,874

Position d_3 -,195 ,151 -,113 -1,294 ,197 ,612 1,634

Position d_4 ,026 ,218 ,009 ,118 ,906 ,726 1,377

Position d_5 -,200 ,184 -,095 -1,087 ,278 ,608 1,646

bfieC ,059 ,116 ,042 ,507 ,613 ,691 1,447

bfiaC ,208 ,131 ,117 1,584 ,115 ,853 1,172

bficC ,045 ,128 ,027 ,353 ,724 ,820 1,219

bfinC -,290 ,115 -,209 -2,532 ,012 ,683 1,464

bfioC -,073 ,123 -,044 -,595 ,552 ,840 1,191

FlexplaceC -,001 ,002 -,039 -,524 ,601 ,852 1,174

FlexplC_bfieC ,000 ,004 -,005 -,059 ,953 ,744 1,344

FlexplC_bfiaC ,002 ,004 ,038 ,524 ,601 ,879 1,138

FlexplC_bficC -,001 ,004 -,016 -,220 ,826 ,881 1,135

FlexplC_bfinC -,001 ,004 -,014 -,171 ,864 ,717 1,396

FlexplC_bfioC -,003 ,004 -,051 -,709 ,479 ,888 1,126



14.2.5. Personality – Flex-time / Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49664

2 ,491b ,241 ,196 ,44397

3 ,548c ,301 ,241 ,43155 2,066

Model Summary

Model

Change Statistics

R Square


1 ,022a ,791 6 209 ,578

2 ,219b 9,754 6 203 ,000

3 ,060c 3,372 5 198 ,006

ANOVA


1 Regression 1,171 6 ,195 ,791 ,578a

Residual 51,549 209 ,247

Total 52,720 215

2 Regression 12,706 12 1,059 5,372 ,000b

Residual 40,014 203 ,197

Total 52,720 215

3 Regression 15,846 17 ,932 5,005 ,000c

Residual 36,874 198 ,186

Total 52,720 215

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, FlextimeC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, FlextimeC, bficC, bfieC, bfinC, FlextC_bfieC, FlextC_bfioC, FlextC_bficC, FlextC_bfiaC, FlextC_bfinC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,177 ,187 22,294 ,000

Gender -,028 ,085 -,021 -,329 ,742 ,895 1,117

Age -,005 ,004 -,084 -1,266 ,207 ,857 1,167

Position d_2 ,002 ,092 ,002 ,019 ,985 ,521 1,919

Position d_3 -,025 ,088 -,022 -,286 ,775 ,607 1,647

Position d_4 ,089 ,128 ,048 ,692 ,489 ,763 1,311

Position d_5 ,059 ,109 ,041 ,543 ,588 ,647 1,545

bfieC ,057 ,069 ,060 ,830 ,407 ,718 1,393

bfiaC ,011 ,078 ,009 ,140 ,889 ,870 1,150

bficC ,459 ,075 ,406 6,117 ,000 ,850 1,177

bfinC -,104 ,068 -,112 -1,529 ,128 ,698 1,432

bfioC ,089 ,071 ,082 1,258 ,210 ,878 1,139

FlextimeC ,001 ,002 ,028 ,437 ,662 ,921 1,085

3 (Constant) 4,189 ,183 22,857 ,000

Gender -,010 ,083 -,008 -,119 ,905 ,879 1,137

Age -,005 ,004 -,088 -1,357 ,176 ,846 1,182

Position d_2 ,007 ,090 ,006 ,078 ,938 ,519 1,926

Position d_3 -,030 ,086 -,027 -,352 ,725 ,599 1,670

Position d_4 ,113 ,127 ,061 ,890 ,374 ,741 1,349

Position d_5 ,060 ,107 ,042 ,563 ,574 ,635 1,576

bfieC ,096 ,068 ,101 1,407 ,161 ,685 1,460

bfiaC ,021 ,080 ,018 ,264 ,792 ,776 1,289

bficC ,402 ,079 ,356 5,120 ,000 ,731 1,368

bfinC -,119 ,068 -,127 -1,741 ,083 ,661 1,514

bfioC ,031 ,073 ,028 ,420 ,675 ,786 1,272

FlextimeC ,003 ,002 ,076 1,181 ,239 ,844 1,185

FlextC_bfieC ,005 ,005 ,074 ,999 ,319 ,637 1,571

FlextC_bfiaC ,001 ,006 ,016 ,241 ,810 ,776 1,289

FlextC_bficC -,015 ,006 -,175 -2,565 ,011 ,757 1,321

FlextC_bfinC ,011 ,005 ,165 2,143 ,033 ,599 1,669

FlextC_bfioC -,009 ,006 -,101 -1,512 ,132 ,795 1,258



14.2.6. Personality – Flex-place / Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,171a ,029 ,000 ,48199

2 ,472b ,222 ,175 ,43797

3 ,489c ,239 ,171 ,43898 2,075

Model Summary

Model

Change Statistics

R Square


1 ,029a 1,013 6 201 ,418

2 ,193b 8,072 6 195 ,000

3 ,016c ,821 5 190 ,536

ANOVA


1 Regression 1,412 6 ,235 1,013 ,418a

Residual 46,695 201 ,232

Total 48,108 207

2 Regression 10,703 12 ,892 4,650 ,000b

Residual 37,405 195 ,192

Total 48,108 207

3 Regression 11,494 17 ,676 3,509 ,000c

Residual 36,613 190 ,193

Total 48,108 207

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, FlexplaceC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, bficC, FlexplaceC, bfieC, bfinC, FlexplC_bfinC, FlexplC_bfioC, FlexplC_bfiaC, FlexplC_bficC, FlexplC_bfieC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,164 ,185 22,478 ,000

Gender ,023 ,086 ,018 ,273 ,785 ,892 1,121

Age -,005 ,004 -,090 -1,314 ,190 ,859 1,164

Position d_2 ,032 ,091 ,030 ,348 ,728 ,538 1,860

Position d_3 ,001 ,089 ,001 ,016 ,987 ,625 1,599

Position d_4 ,081 ,127 ,046 ,635 ,526 ,756 1,322

Position d_5 ,057 ,109 ,042 ,526 ,599 ,615 1,626

bfieC ,050 ,068 ,054 ,728 ,467 ,712 1,404

bfiaC -,044 ,077 -,039 -,575 ,566 ,869 1,150

bficC ,413 ,075 ,379 5,518 ,000 ,847 1,181

bfinC -,111 ,068 -,125 -1,640 ,103 ,690 1,450

bfioC ,083 ,071 ,078 1,166 ,245 ,884 1,131

FlexplaceC ,000 ,001 -,017 -,252 ,802 ,860 1,163

3 (Constant) 4,148 ,191 21,772 ,000

Gender ,029 ,086 ,023 ,336 ,737 ,885 1,130

Age -,005 ,004 -,084 -1,201 ,231 ,826 1,211

Position d_2 ,035 ,092 ,033 ,376 ,707 ,534 1,874

Position d_3 ,008 ,090 ,007 ,088 ,930 ,612 1,634

Position d_4 ,110 ,130 ,062 ,840 ,402 ,726 1,377

Position d_5 ,051 ,110 ,038 ,466 ,642 ,608 1,646

bfieC ,073 ,069 ,081 1,059 ,291 ,691 1,447

bfiaC -,027 ,078 -,024 -,349 ,727 ,853 1,172

bficC ,411 ,076 ,377 5,392 ,000 ,820 1,219

bfinC -,106 ,068 -,119 -1,552 ,122 ,683 1,464

bfioC ,061 ,073 ,058 ,837 ,404 ,840 1,191

FlexplaceC ,000 ,001 -,018 -,262 ,793 ,852 1,174

FlexplC_bfieC -,001 ,002 -,037 -,508 ,612 ,744 1,344

FlexplC_bfiaC -,001 ,003 -,015 -,224 ,823 ,879 1,138

FlexplC_bficC -,003 ,002 -,092 -1,359 ,176 ,881 1,135

FlexplC_bfinC -,001 ,002 -,023 -,302 ,763 ,717 1,396

FlexplC_bfioC -,003 ,002 -,082 -1,224 ,223 ,888 1,126



14.3. Personality – Task Workplace Fit / Work Performance

14.3.1. Personality – TWPF Focus / Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,414b ,171 ,122 ,63845

3 ,474c ,225 ,159 ,62497 1,963

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,119b 4,877 6 204 ,000

3 ,054c 2,779 5 199 ,019

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 17,155 12 1,430 3,507 ,000b

Residual 83,155 204 ,408

Total 100,310 216

3 Regression 22,582 17 1,328 3,401 ,000c

Residual 77,728 199 ,391

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFFocC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFFocC, bficC, bfieC, bfinC, FocC_bficC, FocC_bfioC, FocC_bfiaC, FocC_bfieC, FocC_bfinC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,863 ,272 14,220 ,000

Gender -,023 ,121 -,013 -,189 ,850 ,903 1,107

Age -,003 ,006 -,036 -,522 ,602 ,840 1,191

Position d_2 ,195 ,131 ,130 1,496 ,136 ,535 1,869

Position d_3 -,082 ,126 -,053 -,653 ,515 ,615 1,626

Position d_4 -,023 ,185 -,009 -,122 ,903 ,758 1,319

Position d_5 -,010 ,153 -,005 -,065 ,948 ,652 1,533

bfieC ,103 ,099 ,080 1,043 ,298 ,698 1,434

bfiaC ,173 ,111 ,107 1,557 ,121 ,861 1,161

bficC -,065 ,107 -,042 -,611 ,542 ,845 1,183

bfinC -,045 ,098 -,035 -,456 ,649 ,690 1,448

bfioC -,040 ,101 -,026 -,391 ,696 ,892 1,121

TWPFFocC ,217 ,046 ,312 4,685 ,000 ,918 1,089

3 (Constant) 3,908 ,268 14,598 ,000

Gender ,060 ,121 ,033 ,494 ,622 ,863 1,159

Age -,005 ,006 -,059 -,858 ,392 ,827 1,209

Position d_2 ,210 ,129 ,140 1,636 ,103 ,528 1,892

Position d_3 -,050 ,123 -,032 -,403 ,687 ,610 1,640

Position d_4 -,005 ,182 -,002 -,030 ,976 ,750 1,333

Position d_5 -,039 ,153 -,020 -,255 ,799 ,625 1,599

bfieC ,069 ,099 ,053 ,694 ,488 ,665 1,503

bfiaC ,175 ,111 ,108 1,582 ,115 ,828 1,208

bficC -,138 ,107 -,089 -1,289 ,199 ,814 1,229

bfinC -,109 ,098 -,085 -1,114 ,266 ,663 1,507

bfioC -,079 ,102 -,053 -,775 ,439 ,846 1,182

TWPFFocC ,260 ,047 ,373 5,509 ,000 ,850 1,177

FocC_bfieC ,213 ,092 ,174 2,322 ,021 ,691 1,448

FocC_bfiaC -,280 ,109 -,184 -2,567 ,011 ,758 1,318

FocC_bficC ,055 ,105 ,035 ,523 ,602 ,846 1,182

FocC_bfinC ,184 ,109 ,136 1,693 ,092 ,602 1,660

FocC_bfioC ,009 ,101 ,006 ,088 ,930 ,923 1,084



14.3.2. Personality – TWPF Socialize / Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,469b ,220 ,174 ,61937

3 ,482c ,232 ,167 ,62204 2,116

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,168b 7,310 6 204 ,000

3 ,013c ,650 5 199 ,662

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 22,052 12 1,838 4,790 ,000b

Residual 78,258 204 ,384

Total 100,310 216

3 Regression 23,309 17 1,371 3,544 ,000c

Residual 77,000 199 ,387

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFSocC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFSocC, bfiaC, bficC, bfieC, bfinC, SocC_bficC, SocC_bfioC, SocC_bfieC, SocC_bfiaC, SocC_bfinC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,811 ,262 14,572 ,000

Gender -,011 ,118 -,006 -,094 ,925 ,902 1,108

Age -,003 ,006 -,030 -,453 ,651 ,849 1,178

Position d_2 ,235 ,126 ,157 1,862 ,064 ,537 1,862

Position d_3 -,039 ,122 -,025 -,319 ,750 ,614 1,630

Position d_4 -,028 ,180 -,011 -,154 ,878 ,759 1,317

Position d_5 ,022 ,149 ,011 ,146 ,884 ,651 1,537

bfieC ,093 ,096 ,072 ,971 ,333 ,700 1,429

bfiaC ,101 ,107 ,063 ,942 ,347 ,866 1,155

bficC ,009 ,104 ,006 ,084 ,933 ,844 1,185

bfinC -,025 ,095 -,019 -,259 ,796 ,690 1,450

bfioC ,069 ,099 ,046 ,697 ,487 ,876 1,141

TWPFSocC ,353 ,059 ,383 6,007 ,000 ,939 1,065

3 (Constant) 3,815 ,265 14,385 ,000

Gender ,010 ,120 ,005 ,079 ,937 ,869 1,151

Age -,003 ,006 -,031 -,452 ,652 ,843 1,186

Position d_2 ,232 ,129 ,155 1,796 ,074 ,517 1,936

Position d_3 -,028 ,123 -,018 -,227 ,821 ,605 1,653

Position d_4 -,024 ,184 -,010 -,133 ,894 ,733 1,364

Position d_5 ,020 ,151 ,011 ,136 ,892 ,640 1,562

bfieC ,092 ,100 ,071 ,914 ,362 ,643 1,555

bfiaC ,113 ,111 ,070 1,016 ,311 ,821 1,218

bficC -,004 ,105 -,002 -,034 ,973 ,828 1,208

bfinC -,039 ,098 -,031 -,404 ,687 ,658 1,519

bfioC ,063 ,100 ,042 ,632 ,528 ,863 1,159

TWPFSocC ,352 ,060 ,382 5,842 ,000 ,900 1,111

SocC_bfieC ,014 ,129 ,008 ,111 ,912 ,761 1,314

SocC_bfiaC -,160 ,135 -,088 -1,191 ,235 ,712 1,405

SocC_bficC ,152 ,151 ,071 1,010 ,314 ,776 1,289

SocC_bfinC ,089 ,120 ,058 ,746 ,456 ,638 1,567

SocC_bfioC ,105 ,131 ,056 ,801 ,424 ,788 1,269



14.3.3.A. Personality – TWPF Collaborate / Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,396b ,157 ,107 ,64385

3 ,446c ,199 ,131 ,63542 2,048

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,105b 4,229 6 204 ,000

3 ,042c 2,089 5 199 ,068

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 15,744 12 1,312 3,165 ,000b

Residual 84,566 204 ,415

Total 100,310 216

3 Regression 19,961 17 1,174 2,908 ,000c

Residual 80,349 199 ,404

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFColC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFColC, bficC, bfieC, bfinC, ColC_bficC, ColC_bfioC, ColC_bfieC, ColC_bfiaC, ColC_bfinC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,790 ,272 13,921 ,000

Gender -,007 ,122 -,004 -,061 ,952 ,901 1,110

Age -,001 ,006 -,013 -,181 ,856 ,853 1,173

Position d_2 ,172 ,132 ,115 1,303 ,194 ,531 1,884

Position d_3 -,101 ,127 -,065 -,795 ,427 ,614 1,629

Position d_4 -,018 ,187 -,007 -,094 ,925 ,758 1,319

Position d_5 -,075 ,155 -,039 -,483 ,630 ,649 1,542

bfieC ,094 ,100 ,072 ,936 ,350 ,690 1,449

bfiaC ,101 ,112 ,063 ,906 ,366 ,864 1,157

bficC -,027 ,108 -,017 -,247 ,805 ,848 1,179

bfinC -,015 ,099 -,011 -,148 ,883 ,687 1,455

bfioC ,003 ,102 ,002 ,034 ,973 ,893 1,120

TWPFColC ,250 ,059 ,290 4,264 ,000 ,893 1,120

3 (Constant) 3,730 ,272 13,731 ,000

Gender -,013 ,123 -,007 -,109 ,913 ,876 1,141

Age -,001 ,006 -,007 -,105 ,916 ,843 1,186

Position d_2 ,183 ,131 ,122 1,397 ,164 ,526 1,900

Position d_3 -,078 ,126 -,050 -,619 ,537 ,609 1,642

Position d_4 ,008 ,186 ,003 ,043 ,966 ,741 1,349

Position d_5 -,090 ,153 -,046 -,586 ,559 ,647 1,545

bfieC ,099 ,101 ,077 ,977 ,330 ,657 1,522

bfiaC ,046 ,117 ,029 ,397 ,692 ,769 1,300

bficC -,035 ,109 -,023 -,324 ,747 ,806 1,240

bfinC -,035 ,101 -,027 -,346 ,730 ,642 1,559

bfioC -,018 ,104 -,012 -,175 ,862 ,834 1,199

TWPFColC ,260 ,059 ,302 4,392 ,000 ,853 1,172

ColC_bfieC ,364 ,119 ,224 3,054 ,003 ,747 1,339

ColC_bfiaC ,036 ,135 ,020 ,265 ,791 ,680 1,472

ColC_bficC -,062 ,135 -,032 -,457 ,648 ,823 1,215

ColC_bfinC ,095 ,145 ,052 ,655 ,513 ,632 1,582

ColC_bfioC -,011 ,125 -,006 -,088 ,930 ,838 1,194



14.3.3.B. Personality – TWPF Collaborate / Employee satisfaction (Variant B)

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,396b ,157 ,107 ,64385

3 ,443c ,196 ,144 ,63037 2,024

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,105b 4,229 6 204 ,000

3 ,039c 9,816 1 203 ,002

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 15,744 12 1,312 3,165 ,000b

Residual 84,566 204 ,415

Total 100,310 216

3 Regression 19,645 13 1,511 3,803 ,000c

Residual 80,665 203 ,397

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFColC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFColC, bficC, bfieC, bfinC, TWPFColC_bfieC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,790 ,272 13,921 ,000

Gender -,007 ,122 -,004 -,061 ,952 ,901 1,110

Age -,001 ,006 -,013 -,181 ,856 ,853 1,173

Position d_2 ,172 ,132 ,115 1,303 ,194 ,531 1,884

Position d_3 -,101 ,127 -,065 -,795 ,427 ,614 1,629

Position d_4 -,018 ,187 -,007 -,094 ,925 ,758 1,319

Position d_5 -,075 ,155 -,039 -,483 ,630 ,649 1,542

bfieC ,094 ,100 ,072 ,936 ,350 ,690 1,449

bfiaC ,101 ,112 ,063 ,906 ,366 ,864 1,157

bficC -,027 ,108 -,017 -,247 ,805 ,848 1,179

bfinC -,015 ,099 -,011 -,148 ,883 ,687 1,455

bfioC ,003 ,102 ,002 ,034 ,973 ,893 1,120

TWPFColC ,250 ,059 ,290 4,264 ,000 ,893 1,120

3 (Constant) 3,711 ,268 13,861 ,000

Gender -,016 ,120 -,009 -,130 ,897 ,901 1,110

Age ,000 ,006 -,003 -,041 ,967 ,851 1,175

Position d_2 ,181 ,129 ,121 1,396 ,164 ,531 1,885

Position d_3 -,079 ,124 -,051 -,637 ,525 ,612 1,634

Position d_4 ,008 ,183 ,003 ,046 ,963 ,757 1,321

Position d_5 -,089 ,152 -,046 -,588 ,557 ,648 1,543

bfieC ,104 ,098 ,080 1,060 ,290 ,689 1,451

bfiaC ,050 ,111 ,031 ,452 ,651 ,845 1,183

bficC -,031 ,106 -,020 -,294 ,769 ,848 1,180

bfinC -,021 ,097 -,017 -,219 ,827 ,687 1,456

bfioC -,016 ,100 -,011 -,161 ,872 ,889 1,125

TWPFColC ,265 ,058 ,307 4,590 ,000 ,887 1,127

TWPFColC_bfieC ,327 ,104 ,202 3,133 ,002 ,955 1,047



14.3.4. Personality – TWPF Learn / Employee satisfaction

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,228a ,052 ,025 ,67289

2 ,403b ,162 ,113 ,64177

3 ,458c ,210 ,142 ,63110 1,992

Model Summary

Model

Change Statistics

R Square


1 ,052a 1,924 6 210 ,078

2 ,110b 4,477 6 204 ,000

3 ,047c 2,391 5 199 ,039

ANOVA


1 Regression 5,227 6 ,871 1,924 ,078a

Residual 95,083 210 ,453

Total 100,310 216

2 Regression 16,290 12 1,357 3,296 ,000b

Residual 84,020 204 ,412

Total 100,310 216

3 Regression 21,052 17 1,238 3,109 ,000c

Residual 79,258 199 ,398

Total 100,310 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFLrnC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFLrnC, bfiaC, bficC, bfieC, bfinC, LrnC_bfiaC, LrnC_bfioC, LrnC_bficC, LrnC_bfieC, LrnC_bfinC d. Dependent Variable: Employee Satisfaction


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,585 ,271 13,250 ,000

Gender -,042 ,122 -,023 -,343 ,732 ,903 1,107

Age ,003 ,006 ,031 ,441 ,659 ,855 1,170

Position d_2 ,258 ,131 ,173 1,971 ,050 ,536 1,865

Position d_3 -,043 ,126 -,028 -,337 ,736 ,613 1,632

Position d_4 -1,891E-5 ,186 ,000 ,000 1,000 ,761 1,315

Position d_5 -,025 ,154 -,013 -,161 ,872 ,652 1,533

bfieC ,099 ,100 ,076 ,989 ,324 ,694 1,441

bfiaC ,132 ,111 ,082 1,186 ,237 ,867 1,153

bficC -,058 ,108 -,038 -,543 ,588 ,846 1,182

bfinC -,025 ,098 -,020 -,254 ,799 ,689 1,451

bfioC ,003 ,102 ,002 ,034 ,973 ,893 1,120

TWPFLrnC ,208 ,047 ,294 4,430 ,000 ,935 1,069

3 (Constant) 3,425 ,271 12,629 ,000

Gender ,024 ,122 ,013 ,195 ,846 ,870 1,149

Age ,006 ,006 ,066 ,954 ,341 ,823 1,215

Position d_2 ,250 ,132 ,167 1,894 ,060 ,511 1,958

Position d_3 ,015 ,126 ,010 ,122 ,903 ,594 1,684

Position d_4 ,091 ,186 ,036 ,488 ,626 ,737 1,357

Position d_5 -,085 ,154 -,044 -,550 ,583 ,633 1,581

bfieC ,040 ,100 ,031 ,399 ,691 ,666 1,503

bfiaC ,150 ,111 ,093 1,351 ,178 ,844 1,185

bficC -,123 ,110 -,080 -1,123 ,263 ,787 1,271

bfinC -,075 ,099 -,059 -,755 ,451 ,659 1,518

bfioC ,032 ,102 ,021 ,317 ,752 ,863 1,158

TWPFLrnC ,237 ,049 ,334 4,825 ,000 ,828 1,208

LrnC_bfieC ,179 ,105 ,137 1,703 ,090 ,613 1,632

LrnC_bfiaC -,006 ,123 -,004 -,050 ,960 ,759 1,317

LrnC_bficC ,180 ,119 ,113 1,520 ,130 ,714 1,400

LrnC_bfinC ,311 ,106 ,244 2,923 ,004 ,571 1,752

LrnC_bfioC -,128 ,128 -,072 -1,005 ,316 ,767 1,304



14.3.5. Personality – TWPF Focus / Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,409b ,168 ,119 ,69953

3 ,454c ,206 ,138 ,69176 2,100

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,093 6 210 ,368

2 ,137b 5,606 6 204 ,000

3 ,038c 1,921 5 199 ,092

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 20,090 12 1,674 3,421 ,000b

Residual 99,825 204 ,489

Total 119,914 216

3 Regression 24,686 17 1,452 3,035 ,000c

Residual 95,228 199 ,479

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFFocC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFFocC, bficC, bfieC, bfinC, FocC_bficC, FocC_bfioC, FocC_bfiaC, FocC_bfieC, FocC_bfinC d. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,135 ,298 13,894 ,000

Gender ,031 ,133 ,016 ,234 ,816 ,903 1,107

Age -,005 ,006 -,052 -,747 ,456 ,840 1,191

Position d_2 -,466 ,143 -,284 -3,256 ,001 ,535 1,869

Position d_3 -,198 ,138 -,117 -1,442 ,151 ,615 1,626

Position d_4 -,049 ,203 -,018 -,240 ,810 ,758 1,319

Position d_5 -,217 ,168 -,102 -1,292 ,198 ,652 1,533

bfieC -,014 ,108 -,010 -,128 ,898 ,698 1,434

bfiaC ,221 ,122 ,125 1,819 ,070 ,861 1,161

bficC -,006 ,117 -,004 -,053 ,958 ,845 1,183

bfinC -,302 ,107 -,217 -2,817 ,005 ,690 1,448

bfioC -,069 ,111 -,042 -,626 ,532 ,892 1,121

TWPFFocC ,204 ,051 ,267 4,012 ,000 ,918 1,089

3 (Constant) 4,101 ,296 13,842 ,000

Gender ,102 ,134 ,052 ,761 ,448 ,863 1,159

Age -,005 ,006 -,052 -,754 ,452 ,827 1,209

Position d_2 -,453 ,142 -,276 -3,181 ,002 ,528 1,892

Position d_3 -,188 ,137 -,111 -1,378 ,170 ,610 1,640

Position d_4 -,033 ,202 -,012 -,163 ,871 ,750 1,333

Position d_5 -,255 ,170 -,120 -1,500 ,135 ,625 1,599

bfieC -,066 ,110 -,047 -,603 ,547 ,665 1,503

bfiaC ,258 ,123 ,146 2,099 ,037 ,828 1,208

bficC -,064 ,118 -,038 -,542 ,588 ,814 1,229

bfinC -,353 ,108 -,253 -3,259 ,001 ,663 1,507

bfioC -,117 ,112 -,071 -1,036 ,301 ,846 1,182

TWPFFocC ,225 ,052 ,295 4,309 ,000 ,850 1,177

FocC_bfieC ,196 ,102 ,147 1,932 ,055 ,691 1,448

FocC_bfiaC -,053 ,121 -,032 -,441 ,660 ,758 1,318

FocC_bficC ,198 ,116 ,117 1,711 ,089 ,846 1,182

FocC_bfinC ,209 ,120 ,142 1,740 ,083 ,602 1,660

FocC_bfioC ,128 ,111 ,076 1,148 ,252 ,923 1,084



14.3.6. Personality – TWPF Socialize / Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,363b ,132 ,081 ,71424

3 ,412c ,170 ,099 ,70715 2,108

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,093 6 210 ,368

2 ,102b 3,990 6 204 ,001

3 ,038c 1,822 5 199 ,110

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 15,844 12 1,320 2,588 ,003b

Residual 104,070 204 ,510

Total 119,914 216

3 Regression 20,401 17 1,200 2,400 ,002c

Residual 99,513 199 ,500

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFSocC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFSocC, bfiaC, bficC, bfieC, bfinC, SocC_bficC, SocC_bfioC, SocC_bfieC, SocC_bfiaC, SocC_bfinC d. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,026 ,302 13,350 ,000

Gender ,033 ,136 ,017 ,245 ,807 ,902 1,108

Age -,003 ,007 -,031 -,435 ,664 ,849 1,178

Position d_2 -,429 ,146 -,262 -2,942 ,004 ,537 1,862

Position d_3 -,174 ,141 -,103 -1,238 ,217 ,614 1,630

Position d_4 -,024 ,207 -,009 -,116 ,908 ,759 1,317

Position d_5 -,207 ,172 -,097 -1,205 ,229 ,651 1,537

bfieC ,009 ,111 ,006 ,083 ,934 ,700 1,429

bfiaC ,166 ,124 ,094 1,339 ,182 ,866 1,155

bficC ,045 ,120 ,027 ,373 ,709 ,844 1,185

bfinC -,291 ,110 -,209 -2,659 ,008 ,690 1,450

bfioC -,003 ,114 -,002 -,028 ,978 ,876 1,141

TWPFSocC ,181 ,068 ,180 2,668 ,008 ,939 1,065

3 (Constant) 4,021 ,302 13,336 ,000

Gender ,000 ,137 ,000 -,003 ,997 ,869 1,151

Age -,003 ,007 -,027 -,383 ,702 ,843 1,186

Position d_2 -,418 ,147 -,255 -2,840 ,005 ,517 1,936

Position d_3 -,200 ,140 -,118 -1,425 ,156 ,605 1,653

Position d_4 -,004 ,209 -,001 -,018 ,986 ,733 1,364

Position d_5 -,193 ,171 -,091 -1,123 ,263 ,640 1,562

bfieC -,056 ,114 -,040 -,493 ,622 ,643 1,555

bfiaC ,198 ,126 ,112 1,568 ,118 ,821 1,218

bficC ,053 ,120 ,032 ,444 ,658 ,828 1,208

bfinC -,293 ,111 -,210 -2,641 ,009 ,658 1,519

bfioC ,029 ,114 ,018 ,258 ,797 ,863 1,159

TWPFSocC ,167 ,068 ,166 2,434 ,016 ,900 1,111

SocC_bfieC ,041 ,147 ,021 ,280 ,780 ,761 1,314

SocC_bfiaC ,263 ,153 ,131 1,716 ,088 ,712 1,405

SocC_bficC ,278 ,171 ,119 1,622 ,106 ,776 1,289

SocC_bfinC ,173 ,136 ,103 1,269 ,206 ,638 1,567

SocC_bfioC ,111 ,149 ,054 ,741 ,460 ,788 1,269



14.3.7. Personality – TWPF Collaborate / Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,360b ,129 ,078 ,71533

3 ,408c ,166 ,095 ,70887 2,088

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,093 6 210 ,368

2 ,099b 3,875 6 204 ,001

3 ,037c 1,747 5 199 ,126

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 15,529 12 1,294 2,529 ,004b

Residual 104,386 204 ,512

Total 119,914 216

3 Regression 19,917 17 1,172 2,332 ,003c

Residual 99,997 199 ,502

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFColC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFColC, bficC, bfieC, bfinC, ColC_bficC, ColC_bfioC, ColC_bfieC, ColC_bfiaC, ColC_bfinC d. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,034 ,302 13,336 ,000

Gender ,039 ,136 ,020 ,285 ,776 ,901 1,110

Age -,002 ,007 -,026 -,364 ,716 ,853 1,173

Position d_2 -,470 ,147 -,287 -3,204 ,002 ,531 1,884

Position d_3 -,209 ,141 -,124 -1,487 ,138 ,614 1,629

Position d_4 -,028 ,208 -,010 -,134 ,894 ,758 1,319

Position d_5 -,264 ,172 -,124 -1,533 ,127 ,649 1,542

bfieC -,002 ,111 -,001 -,016 ,987 ,690 1,449

bfiaC ,162 ,124 ,092 1,302 ,194 ,864 1,157

bficC ,028 ,120 ,017 ,233 ,816 ,848 1,179

bfinC -,282 ,110 -,202 -2,564 ,011 ,687 1,455

bfioC -,034 ,113 -,021 -,300 ,765 ,893 1,120

TWPFColC ,166 ,065 ,176 2,545 ,012 ,893 1,120

3 (Constant) 4,058 ,303 13,392 ,000

Gender ,033 ,137 ,017 ,244 ,808 ,876 1,141

Age -,003 ,007 -,034 -,476 ,635 ,843 1,186

Position d_2 -,468 ,146 -,286 -3,201 ,002 ,526 1,900

Position d_3 -,199 ,140 -,118 -1,422 ,156 ,609 1,642

Position d_4 -,019 ,208 -,007 -,093 ,926 ,741 1,349

Position d_5 -,285 ,171 -,134 -1,664 ,098 ,647 1,545

bfieC -,051 ,113 -,036 -,447 ,655 ,657 1,522

bfiaC ,221 ,130 ,125 1,692 ,092 ,769 1,300

bficC ,040 ,122 ,024 ,329 ,742 ,806 1,240

bfinC -,322 ,113 -,231 -2,853 ,005 ,642 1,559

bfioC -,052 ,116 -,032 -,446 ,656 ,834 1,199

TWPFColC ,151 ,066 ,160 2,283 ,024 ,853 1,172

ColC_bfieC ,151 ,133 ,085 1,134 ,258 ,747 1,339

ColC_bfiaC ,207 ,151 ,108 1,373 ,171 ,680 1,472

ColC_bficC ,102 ,150 ,049 ,681 ,497 ,823 1,215

ColC_bfinC ,275 ,162 ,138 1,695 ,092 ,632 1,582

ColC_bfioC ,205 ,139 ,104 1,470 ,143 ,838 1,194



14.3.8. Personality – TWPF Learn / Work life balance

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,174a ,030 ,003 ,74413

2 ,349b ,122 ,070 ,71836

3 ,382c ,146 ,073 ,71734 2,046

Model Summary

Model

Change Statistics

Durbin-Watson

R Square


1 ,030a 1,093 6 210 ,368

2 ,092b 3,556 6 204 ,002

3 ,024c 1,116 5 199 ,353 2,046

ANOVA


1 Regression 3,630 6 ,605 1,093 ,368a

Residual 116,284 210 ,554

Total 119,914 216

2 Regression 14,642 12 1,220 2,364 ,007b

Residual 105,272 204 ,516

Total 119,914 216

3 Regression 17,514 17 1,030 2,002 ,013c

Residual 102,400 199 ,515

Total 119,914 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFLrnC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFLrnC, bfiaC, bficC, bfieC, bfinC, LrnC_bfiaC, LrnC_bfioC, LrnC_bficC, LrnC_bfieC, LrnC_bfinC d. Dependent Variable: Work life balance


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 3,908 ,303 12,902 ,000

Gender ,017 ,136 ,009 ,125 ,901 ,903 1,107

Age ,000 ,007 -,002 -,022 ,982 ,855 1,170

Position d_2 -,416 ,147 -,254 -2,836 ,005 ,536 1,865

Position d_3 -,175 ,142 -,104 -1,235 ,218 ,613 1,632

Position d_4 -,011 ,208 -,004 -,055 ,957 ,761 1,315

Position d_5 -,231 ,173 -,109 -1,338 ,182 ,652 1,533

bfieC ,010 ,112 ,007 ,085 ,932 ,694 1,441

bfiaC ,182 ,125 ,103 1,460 ,146 ,867 1,153

bficC ,010 ,120 ,006 ,079 ,937 ,846 1,182

bfinC -,291 ,110 -,208 -2,638 ,009 ,689 1,451

bfioC -,036 ,114 -,022 -,317 ,751 ,893 1,120

TWPFLrnC ,114 ,053 ,147 2,169 ,031 ,935 1,069

3 (Constant) 3,778 ,308 12,252 ,000

Gender ,034 ,139 ,017 ,245 ,806 ,870 1,149

Age ,003 ,007 ,029 ,400 ,689 ,823 1,215

Position d_2 -,449 ,150 -,274 -2,993 ,003 ,511 1,958

Position d_3 -,153 ,144 -,091 -1,066 ,288 ,594 1,684

Position d_4 ,020 ,211 ,007 ,094 ,925 ,737 1,357

Position d_5 -,247 ,175 -,116 -1,413 ,159 ,633 1,581

bfieC -,028 ,114 -,020 -,244 ,807 ,666 1,503

bfiaC ,179 ,126 ,101 1,420 ,157 ,844 1,185

bficC -,001 ,125 ,000 -,006 ,995 ,787 1,271

bfinC -,320 ,113 -,230 -2,844 ,005 ,659 1,518

bfioC ,002 ,115 ,001 ,018 ,986 ,863 1,158

TWPFLrnC ,124 ,056 ,160 2,216 ,028 ,828 1,208

LrnC_bfieC ,048 ,120 ,034 ,402 ,688 ,613 1,632

LrnC_bfiaC ,073 ,140 ,039 ,522 ,602 ,759 1,317

LrnC_bficC ,248 ,135 ,143 1,843 ,067 ,714 1,400

LrnC_bfinC ,145 ,121 ,104 1,202 ,231 ,571 1,752

LrnC_bfioC -,093 ,145 -,048 -,641 ,522 ,767 1,304



14.3.9. Personality – TWPF Focus / Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,504b ,254 ,211 ,43895

3 ,519c ,270 ,207 ,43986 2,065

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,232b 10,593 6 204 ,000

3 ,015c ,830 5 199 ,530

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 13,417 12 1,118 5,803 ,000b

Residual 39,305 204 ,193

Total 52,722 216

3 Regression 14,220 17 ,836 4,323 ,000c

Residual 38,502 199 ,193

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFFocC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFFocC, bficC, bfieC, bfinC, FocC_bficC, FocC_bfioC, FocC_bfiaC, FocC_bfieC, FocC_bfinC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,225 ,187 22,621 ,000

Gender -,013 ,083 -,010 -,157 ,875 ,903 1,107

Age -,006 ,004 -,102 -1,551 ,123 ,840 1,191

Position d_2 ,000 ,090 ,000 -,004 ,997 ,535 1,869

Position d_3 -,020 ,086 -,018 -,236 ,814 ,615 1,626

Position d_4 ,068 ,127 ,037 ,532 ,595 ,758 1,319

Position d_5 ,052 ,105 ,037 ,490 ,625 ,652 1,533

bfieC ,027 ,068 ,029 ,399 ,690 ,698 1,434

bfiaC ,014 ,076 ,012 ,187 ,852 ,861 1,161

bficC ,437 ,074 ,390 5,935 ,000 ,845 1,183

bfinC -,100 ,067 -,108 -1,483 ,140 ,690 1,448

bfioC ,090 ,069 ,083 1,295 ,197 ,892 1,121

TWPFFocC ,076 ,032 ,150 2,371 ,019 ,918 1,089

3 (Constant) 4,259 ,188 22,608 ,000

Gender ,007 ,085 ,005 ,079 ,937 ,863 1,159

Age -,007 ,004 -,118 -1,769 ,078 ,827 1,209

Position d_2 ,007 ,090 ,007 ,082 ,935 ,528 1,892

Position d_3 -,005 ,087 -,004 -,057 ,954 ,610 1,640

Position d_4 ,069 ,128 ,038 ,538 ,591 ,750 1,333

Position d_5 ,041 ,108 ,029 ,376 ,707 ,625 1,599

bfieC ,024 ,070 ,025 ,339 ,735 ,665 1,503

bfiaC ,009 ,078 ,007 ,112 ,911 ,828 1,208

bficC ,419 ,075 ,375 5,580 ,000 ,814 1,229

bfinC -,116 ,069 -,125 -1,682 ,094 ,663 1,507

bfioC ,089 ,072 ,082 1,238 ,217 ,846 1,182

TWPFFocC ,089 ,033 ,175 2,668 ,008 ,850 1,177

FocC_bfieC ,025 ,065 ,028 ,379 ,705 ,691 1,448

FocC_bfiaC -,122 ,077 -,110 -1,584 ,115 ,758 1,318

FocC_bficC -,007 ,074 -,006 -,098 ,922 ,846 1,182

FocC_bfinC ,040 ,077 ,041 ,521 ,603 ,602 1,660

FocC_bfioC -,038 ,071 -,034 -,543 ,588 ,923 1,084



14.3.10. Personality – TWPF Socialize / Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,549b ,301 ,260 ,42495

3 ,562c ,315 ,257 ,42586 2,130

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,279b 13,579 6 204 ,000

3 ,014c ,825 5 199 ,533

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 15,884 12 1,324 7,330 ,000b

Residual 36,839 204 ,181

Total 52,722 216

3 Regression 16,631 17 ,978 5,394 ,000c

Residual 36,091 199 ,181

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFSocC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFSocC, bfiaC, bficC, bfieC, bfinC, SocC_bficC, SocC_bfioC, SocC_bfieC, SocC_bfiaC, SocC_bfinC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,229 ,179 23,570 ,000

Gender -,006 ,081 -,004 -,070 ,944 ,902 1,108

Age -,007 ,004 -,109 -1,709 ,089 ,849 1,178

Position d_2 ,014 ,087 ,013 ,159 ,874 ,537 1,862

Position d_3 ,001 ,084 ,001 ,007 ,994 ,614 1,630

Position d_4 ,055 ,123 ,030 ,447 ,655 ,759 1,317

Position d_5 ,070 ,102 ,050 ,685 ,494 ,651 1,537

bfieC ,012 ,066 ,012 ,176 ,860 ,700 1,429

bfiaC -,015 ,074 -,013 -,205 ,838 ,866 1,155

bficC ,470 ,071 ,420 6,586 ,000 ,844 1,185

bfinC -,090 ,065 -,097 -1,379 ,169 ,690 1,450

bfioC ,141 ,068 ,130 2,078 ,039 ,876 1,141

TWPFSocC ,179 ,040 ,268 4,434 ,000 ,939 1,065

3 (Constant) 4,235 ,182 23,323 ,000

Gender ,003 ,082 ,002 ,039 ,969 ,869 1,151

Age -,007 ,004 -,108 -1,697 ,091 ,843 1,186

Position d_2 -,006 ,089 -,006 -,072 ,943 ,517 1,936

Position d_3 ,014 ,084 ,012 ,164 ,870 ,605 1,653

Position d_4 ,025 ,126 ,013 ,197 ,844 ,733 1,364

Position d_5 ,065 ,103 ,046 ,626 ,532 ,640 1,562

bfieC ,044 ,069 ,047 ,643 ,521 ,643 1,555

bfiaC -,027 ,076 -,023 -,350 ,727 ,821 1,218

bficC ,469 ,072 ,419 6,500 ,000 ,828 1,208

bfinC -,100 ,067 -,108 -1,495 ,136 ,658 1,519

bfioC ,132 ,069 ,121 1,919 ,056 ,863 1,159

TWPFSocC ,174 ,041 ,261 4,224 ,000 ,900 1,111

SocC_bfieC -,054 ,089 -,041 -,607 ,545 ,761 1,314

SocC_bfiaC -,158 ,092 -,119 -1,715 ,088 ,712 1,405

SocC_bficC -,009 ,103 -,006 -,085 ,933 ,776 1,289

SocC_bfinC -,116 ,082 -,104 -1,419 ,157 ,638 1,567

SocC_bfioC ,007 ,090 ,005 ,082 ,935 ,788 1,269



14.3.11. Personality – TWPF Collaborate / Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,503b ,253 ,209 ,43931

3 ,505c ,255 ,192 ,44416 2,096

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,231b 10,519 6 204 ,000

3 ,002c ,115 5 199 ,989

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 13,351 12 1,113 5,765 ,000b

Residual 39,371 204 ,193

Total 52,722 216

3 Regression 13,465 17 ,792 4,015 ,000c

Residual 39,258 199 ,197

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFColC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, bfiaC, TWPFColC, bficC, bfieC, bfinC, ColC_bficC, ColC_bfioC, ColC_bfieC, ColC_bfiaC, ColC_bfinC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,202 ,186 22,621 ,000

Gender -,007 ,084 -,006 -,087 ,931 ,901 1,110

Age -,006 ,004 -,092 -1,397 ,164 ,853 1,173

Position d_2 -,010 ,090 -,009 -,106 ,915 ,531 1,884

Position d_3 -,027 ,086 -,024 -,316 ,752 ,614 1,629

Position d_4 ,068 ,127 ,037 ,537 ,592 ,758 1,319

Position d_5 ,028 ,106 ,020 ,265 ,791 ,649 1,542

bfieC ,022 ,068 ,024 ,328 ,743 ,690 1,449

bfiaC -,011 ,076 -,010 -,147 ,883 ,864 1,157

bficC ,451 ,074 ,403 6,126 ,000 ,848 1,179

bfinC -,089 ,068 -,096 -1,315 ,190 ,687 1,455

bfioC ,105 ,070 ,097 1,515 ,131 ,893 1,120

TWPFColC ,092 ,040 ,147 2,296 ,023 ,893 1,120

3 (Constant) 4,205 ,190 22,148 ,000

Gender -,006 ,086 -,005 -,074 ,941 ,876 1,141

Age -,006 ,004 -,092 -1,379 ,169 ,843 1,186

Position d_2 -,012 ,092 -,011 -,131 ,896 ,526 1,900

Position d_3 -,027 ,088 -,024 -,307 ,759 ,609 1,642

Position d_4 ,068 ,130 ,037 ,520 ,603 ,741 1,349

Position d_5 ,030 ,107 ,021 ,280 ,779 ,647 1,545

bfieC ,029 ,071 ,031 ,407 ,684 ,657 1,522

bfiaC -,019 ,082 -,016 -,227 ,820 ,769 1,300

bficC ,445 ,076 ,397 5,834 ,000 ,806 1,240

bfinC -,090 ,071 -,097 -1,268 ,206 ,642 1,559

bfioC ,103 ,073 ,095 1,413 ,159 ,834 1,199

TWPFColC ,093 ,041 ,149 2,243 ,026 ,853 1,172

ColC_bfieC -,016 ,083 -,013 -,189 ,850 ,747 1,339

ColC_bfiaC -,031 ,094 -,024 -,329 ,742 ,680 1,472

ColC_bficC -,045 ,094 -,032 -,478 ,633 ,823 1,215

ColC_bfinC -,015 ,102 -,011 -,148 ,882 ,632 1,582

ColC_bfioC -,005 ,087 -,004 -,062 ,951 ,838 1,194



14.3.12.A. Personality – TWPF Learn / Productivity

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,522b ,272 ,229 ,43373

3 ,550c ,303 ,243 ,42978 2,087

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,250b 11,672 6 204 ,000

3 ,031c 1,754 5 199 ,124

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 14,345 12 1,195 6,355 ,000b

Residual 38,377 204 ,188

Total 52,722 216

3 Regression 15,965 17 ,939 5,084 ,000c

Residual 36,757 199 ,185

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFLrnC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFLrnC, bfiaC, bficC, bfieC, bfinC, LrnC_bfiaC, LrnC_bfioC, LrnC_bficC, LrnC_bfieC, LrnC_bfinC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



2 (Constant) 4,116 ,183 22,507 ,000

Gender -,021 ,082 -,016 -,257 ,798 ,903 1,107

Age -,004 ,004 -,066 -1,024 ,307 ,855 1,170

Position d_2 ,025 ,089 ,023 ,286 ,775 ,536 1,865

Position d_3 -,002 ,085 -,001 -,018 ,986 ,613 1,632

Position d_4 ,069 ,126 ,038 ,552 ,581 ,761 1,315

Position d_5 ,046 ,104 ,033 ,446 ,656 ,652 1,533

bfieC ,015 ,067 ,016 ,221 ,825 ,694 1,441

bfiaC ,000 ,075 ,000 ,006 ,995 ,867 1,153

bficC ,436 ,073 ,389 5,996 ,000 ,846 1,182

bfinC -,090 ,067 -,098 -1,355 ,177 ,689 1,451

bfioC ,108 ,069 ,099 1,570 ,118 ,893 1,120

TWPFLrnC ,104 ,032 ,202 3,270 ,001 ,935 1,069

3 (Constant) 4,141 ,185 22,416 ,000

Gender -,006 ,083 -,005 -,077 ,939 ,870 1,149

Age -,005 ,004 -,083 -1,265 ,207 ,823 1,215

Position d_2 ,077 ,090 ,071 ,861 ,390 ,511 1,958

Position d_3 ,009 ,086 ,008 ,101 ,920 ,594 1,684

Position d_4 ,108 ,126 ,059 ,853 ,395 ,737 1,357

Position d_5 ,054 ,105 ,039 ,519 ,604 ,633 1,581

bfieC ,027 ,068 ,029 ,399 ,690 ,666 1,503

bfiaC -,005 ,076 -,004 -,066 ,947 ,844 1,185

bficC ,399 ,075 ,357 5,344 ,000 ,787 1,271

bfinC -,078 ,067 -,084 -1,153 ,250 ,659 1,518

bfioC ,114 ,069 ,105 1,647 ,101 ,863 1,158

TWPFLrnC ,118 ,033 ,230 3,538 ,001 ,828 1,208

LrnC_bfieC ,026 ,072 ,027 ,361 ,719 ,613 1,632

LrnC_bfiaC -,012 ,084 -,010 -,142 ,887 ,759 1,317

LrnC_bficC -,166 ,081 -,144 -2,050 ,042 ,714 1,400

LrnC_bfinC -,008 ,072 -,008 -,104 ,917 ,571 1,752

LrnC_bfioC -,189 ,087 -,147 -2,180 ,030 ,767 1,304



14.3.12.B. Personality – TWPF Learn / Productivity (Variant B)

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,006 ,49546

2 ,522b ,272 ,229 ,43373

3 ,550c ,302 ,254 ,42681 2,080

Model Summary

Model

Change Statistics

R Square


1 ,022a ,795 6 210 ,575

2 ,250b 11,672 6 204 ,000

3 ,030c 4,336 2 202 ,014

ANOVA


1 Regression 1,171 6 ,195 ,795 ,575a

Residual 51,551 210 ,245

Total 52,722 216

2 Regression 14,345 12 1,195 6,355 ,000b

Residual 38,377 204 ,188

Total 52,722 216

3 Regression 15,925 14 1,137 6,244 ,000c

Residual 36,797 202 ,182

Total 52,722 216

a. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFLrnC, bfiaC, bficC, bfieC, bfinC c. Predictors: (Constant), Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, bfioC, TWPFLrnC, bfiaC, bficC, bfieC, bfinC, LrnC_bfioC, LrnC_bficC d. Dependent Variable: Productivity


Coefficients

Model


Standardized

Coefficients

t Sig.



3 (Constant) 4,141 ,181 22,832 ,000

Gender -,006 ,081 -,005 -,077 ,939 ,899 1,112

Age -,005 ,004 -,081 -1,263 ,208 ,840 1,191

Position d_2 ,078 ,089 ,072 ,872 ,384 ,513 1,949

Position d_3 ,004 ,084 ,004 ,048 ,962 ,611 1,636

Position d_4 ,105 ,124 ,057 ,841 ,402 ,752 1,330

Position d_5 ,052 ,103 ,037 ,510 ,610 ,650 1,539

bfieC ,027 ,066 ,029 ,404 ,687 ,690 1,448

bfiaC -,002 ,074 -,002 -,032 ,974 ,865 1,156

bficC ,404 ,072 ,361 5,576 ,000 ,826 1,210

bfinC -,074 ,066 -,080 -1,123 ,263 ,682 1,466

bfioC ,116 ,068 ,107 1,698 ,091 ,871 1,149

TWPFLrnC ,114 ,032 ,222 3,607 ,000 ,913 1,095

LrnC_bficC -,157 ,072 -,136 -2,186 ,030 ,891 1,122

LrnC_bfioC -,178 ,079 -,139 -2,242 ,026 ,905 1,105




15.1. Workplace design & Freedom work location – Task Workplace

Fit

15.1.1. Workplace design & Freedom work location – TWPF Focus

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,286a ,082 ,051 ,95279

2 ,499b ,249 ,196 ,87694 1,865

Model Summary

Model

Change Statistics

R Square


1 ,082a 2,643 7 207 ,012

2 ,167b 6,337 7 200 ,000

ANOVA


1 Regression 16,797 7 2,400 2,643 ,012a

Residual 187,918 207 ,908

Total 204,715 214

2 Regression 50,912 14 3,637 4,729 ,000b

Residual 153,803 200 ,769

Total 204,715 214

a. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Room Sharing d_3, Room Sharing d_5, Backup Place, Room Sharing d_2, Own Work Place, Freedom work location, Room Sharing d_4 c. Dependent Variable: TWPF Focus


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,086 ,413 7,468 ,000

Gender -,064 ,177 -,025 -,361 ,719 ,946 1,057

Age ,021 ,009 ,175 2,458 ,015 ,873 1,145

Position d_2 ,366 ,187 ,171 1,954 ,052 ,582 1,719

Position d_3 ,118 ,190 ,054 ,624 ,533 ,602 1,662

Position d_4 ,330 ,277 ,089 1,191 ,235 ,800 1,250

Position d_5 ,000 ,224 ,000 -,001 ,999 ,683 1,465

Location dependency -,229 ,079 -,199 -2,877 ,004 ,926 1,080

2 (Constant) 3,241 ,548 5,910 ,000

Gender -,042 ,169 -,016 -,249 ,804 ,884 1,132

Age ,018 ,008 ,148 2,230 ,027 ,858 1,165

Position d_2 -,076 ,196 -,036 -,389 ,698 ,449 2,230

Position d_3 -,089 ,187 -,040 -,475 ,635 ,527 1,898

Position d_4 ,203 ,265 ,054 ,766 ,445 ,741 1,349

Position d_5 -,132 ,213 -,047 -,617 ,538 ,638 1,568


Room Sharing d_2 -,442 ,188 -,178 -2,345 ,020 ,653 1,531

Room Sharing d_3 -,892 ,192 -,341 -4,656 ,000 ,699 1,431

Room Sharing d_4 -1,032 ,227 -,399 -4,548 ,000 ,487 2,052

Room Sharing d_5 -,912 ,233 -,319 -3,916 ,000 ,565 1,771

Backup Place ,196 ,155 ,085 1,267 ,207 ,825 1,212

Own Work Place -,210 ,163 -,101 -1,286 ,200 ,603 1,658

Freedom work

location

,074 ,029 ,186 2,546 ,012 ,702 1,425

a. Dependent Variable: TWPF Focus


15.1.2. Workplace design & Freedom work location – TWPF Socialize

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,149a ,022 -,011 ,74227

2 ,389b ,151 ,092 ,70346 1,930

Model Summary

Model

Change Statistics

R Square


1 ,022a ,670 7 207 ,697

2 ,129b 4,353 7 200 ,000

ANOVA


1 Regression 2,585 7 ,369 ,670 ,697a

Residual 114,048 207 ,551

Total 116,634 214

2 Regression 17,663 14 1,262 2,549 ,002b

Residual 98,971 200 ,495

Total 116,634 214

a. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Room Sharing d_3, Room Sharing d_5, Backup Place, Room Sharing d_2, Own Work Place, Freedom work location, Room Sharing d_4 c. Dependent Variable: TWPF Socialize


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,309 ,322 10,279 ,000

Gender -,055 ,138 -,028 -,402 ,688 ,946 1,057

Age ,006 ,007 ,070 ,946 ,345 ,873 1,145

Position d_2 ,069 ,146 ,042 ,471 ,638 ,582 1,719

Position d_3 -,101 ,148 -,061 -,686 ,494 ,602 1,662

Position d_4 ,136 ,216 ,048 ,629 ,530 ,800 1,250

Position d_5 -,050 ,174 -,024 -,287 ,774 ,683 1,465

Location dependency ,043 ,062 ,049 ,690 ,491 ,926 1,080

2 (Constant) 2,265 ,440 5,149 ,000

Gender -,097 ,135 -,049 -,714 ,476 ,884 1,132

Age ,008 ,006 ,081 1,157 ,249 ,858 1,165

Position d_2 ,002 ,157 ,001 ,012 ,990 ,449 2,230

Position d_3 -,063 ,150 -,038 -,424 ,672 ,527 1,898

Position d_4 ,167 ,212 ,060 ,789 ,431 ,741 1,349

Position d_5 ,012 ,171 ,006 ,070 ,944 ,638 1,568

Location dependency ,141 ,067 ,163 2,100 ,037 ,706 1,416

Room Sharing d_2 -,211 ,151 -,113 -1,398 ,164 ,653 1,531

Room Sharing d_3 -,187 ,154 -,095 -1,214 ,226 ,699 1,431

Room Sharing d_4 ,209 ,182 ,107 1,149 ,252 ,487 2,052

Room Sharing d_5 -,013 ,187 -,006 -,071 ,943 ,565 1,771

Backup Place ,351 ,124 ,202 2,824 ,005 ,825 1,212

Own Work Place ,206 ,131 ,132 1,571 ,118 ,603 1,658

Freedom work

location

,059 ,023 ,196 2,526 ,012 ,702 1,425

a. Dependent Variable: TWPF Socialize


15.1.3. Workplace design & Freedom work location – TWPF Collaborate

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,238a ,057 ,025 ,77487

2 ,335b ,112 ,050 ,76491 2,011

Model Summary

Model

Change Statistics

R Square


1 ,057a 1,781 7 207 ,093

2 ,055b 1,775 7 200 ,094

ANOVA


1 Regression 7,485 7 1,069 1,781 ,093a

Residual 124,289 207 ,600

Total 131,775 214

2 Regression 14,756 14 1,054 1,801 ,040b

Residual 117,018 200 ,585

Total 131,775 214

a. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Room Sharing d_3, Room Sharing d_5, Backup Place, Room Sharing d_2, Own Work Place, Freedom work location, Room Sharing d_4 c. Dependent Variable: TWPF Collaborate


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,447 ,336 10,258 ,000

Gender -,124 ,144 -,060 -,861 ,390 ,946 1,057

Age ,007 ,007 ,071 ,978 ,329 ,873 1,145

Position d_2 ,410 ,152 ,238 2,692 ,008 ,582 1,719

Position d_3 ,129 ,154 ,073 ,836 ,404 ,602 1,662

Position d_4 ,266 ,225 ,089 1,181 ,239 ,800 1,250

Position d_5 ,312 ,182 ,140 1,713 ,088 ,683 1,465

Location

dependency

-,098 ,065 -,106 -1,513 ,132 ,926 1,080

2 (Constant) 3,076 ,478 6,431 ,000

Gender -,111 ,147 -,054 -,757 ,450 ,884 1,132

Age ,006 ,007 ,064 ,894 ,372 ,858 1,165

Position d_2 ,222 ,171 ,129 1,295 ,197 ,449 2,230

Position d_3 ,058 ,163 ,032 ,354 ,724 ,527 1,898

Position d_4 ,195 ,231 ,065 ,844 ,400 ,741 1,349

Position d_5 ,285 ,186 ,128 1,532 ,127 ,638 1,568

Location

dependency

-,041 ,073 -,044 -,556 ,579 ,706 1,416

Room Sharing d_2 -,255 ,164 -,128 -1,552 ,122 ,653 1,531

Room Sharing d_3 -,227 ,167 -,108 -1,358 ,176 ,699 1,431

Room Sharing d_4 -,244 ,198 -,118 -1,233 ,219 ,487 2,052

Room Sharing d_5 -,071 ,203 -,031 -,349 ,727 ,565 1,771

Backup Place ,234 ,135 ,127 1,731 ,085 ,825 1,212

Own Work Place ,109 ,142 ,066 ,765 ,445 ,603 1,658

Freedom work

location

,034 ,026 ,107 1,341 ,181 ,702 1,425

a. Dependent Variable: TWPF Collaborate


15.1.4. Workplace design & Freedom work location – TWPF Learn

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,233a ,054 ,022 ,94425

2 ,362b ,131 ,070 ,92079 2,035

Model Summary

Model

Change Statistics

R Square


1 ,054a 1,692 7 207 ,112

2 ,077b 2,526 7 200 ,016

ANOVA


1 Regression 10,562 7 1,509 1,692 ,112a

Residual 184,564 207 ,892

Total 195,127 214

2 Regression 25,555 14 1,825 2,153 ,011b

Residual 169,572 200 ,848

Total 195,127 214

a. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Room Sharing d_3, Room Sharing d_5, Backup Place, Room Sharing d_2, Own Work Place, Freedom work location, Room Sharing d_4 c. Dependent Variable: TWPF Learn


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 4,073 ,410 9,946 ,000

Gender ,025 ,175 ,010 ,140 ,889 ,946 1,057

Age -,006 ,009 -,053 -,739 ,461 ,873 1,145

Position d_2 ,091 ,185 ,043 ,490 ,625 ,582 1,719

Position d_3 -,079 ,188 -,037 -,420 ,675 ,602 1,662

Position d_4 ,209 ,274 ,058 ,761 ,447 ,800 1,250

Position d_5 ,107 ,222 ,039 ,482 ,630 ,683 1,465


2 (Constant) 3,907 ,576 6,785 ,000

Gender ,035 ,177 ,014 ,196 ,845 ,884 1,132

Age -,009 ,008 -,073 -1,033 ,303 ,858 1,165

Position d_2 -,178 ,206 -,085 -,865 ,388 ,449 2,230

Position d_3 -,167 ,196 -,077 -,852 ,395 ,527 1,898

Position d_4 ,158 ,278 ,044 ,569 ,570 ,741 1,349

Position d_5 ,034 ,224 ,013 ,154 ,878 ,638 1,568


Room Sharing d_2 -,477 ,198 -,197 -2,411 ,017 ,653 1,531

Room Sharing d_3 -,339 ,201 -,133 -1,687 ,093 ,699 1,431

Room Sharing d_4 -,605 ,238 -,240 -2,537 ,012 ,487 2,052

Room Sharing d_5 -,307 ,245 -,110 -1,254 ,211 ,565 1,771

Backup Place ,241 ,163 ,108 1,484 ,139 ,825 1,212

Own Work Place -,143 ,171 -,071 -,834 ,405 ,603 1,658

Freedom work

location

,053 ,031 ,136 1,730 ,085 ,702 1,425

a. Dependent Variable: TWPF Learn


15.2.1. Workplace design & Freedom work location – Flex-place

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,471a ,222 ,195 26,48324

2 ,555b ,308 ,257 25,43303 2,001

Model Summary

Model

Change Statistics

R Square


1 ,222a 8,082 7 198 ,000

2 ,086b 3,384 7 191 ,002

ANOVA


1 Regression 39676,896 7 5668,128 8,082 ,000a

Residual 138869,652 198 701,362

Total 178546,549 205

2 Regression 55000,331 14 3928,595 6,074 ,000b

Residual 123546,217 191 646,839

Total 178546,549 205

a. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Room Sharing d_3, Room Sharing d_5, Backup Place, Room Sharing d_2, Own Work Place, Freedom work location, Room Sharing d_4 c. Dependent Variable: Flexplace


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 69,784 11,521 6,057 ,000

Gender ,384 5,077 ,005 ,076 ,940 ,937 1,068

Age ,044 ,245 ,012 ,178 ,859 ,871 1,148

Position d_2 -,862 5,299 -,013 -,163 ,871 ,587 1,703

Position d_3 -1,763 5,416 -,026 -,325 ,745 ,615 1,626

Position d_4 -4,403 7,715 -,040 -,571 ,569 ,798 1,252

Position d_5 24,959 6,255 ,303 3,990 ,000 ,681 1,469

Location dependency -11,613 2,255 -,337 -5,150 ,000 ,917 1,091

2 (Constant) 65,554 16,021 4,092 ,000

Gender -2,158 5,039 -,028 -,428 ,669 ,877 1,141

Age ,007 ,237 ,002 ,029 ,977 ,855 1,170

Position d_2 4,144 5,780 ,064 ,717 ,474 ,455 2,197

Position d_3 2,270 5,513 ,033 ,412 ,681 ,548 1,826

Position d_4 1,967 7,709 ,018 ,255 ,799 ,737 1,356

Position d_5 25,949 6,214 ,315 4,176 ,000 ,636 1,572

Location dependency -8,634 2,460 -,251 -3,509 ,001 ,710 1,408

Room Sharing d_2 3,113 5,668 ,041 ,549 ,584 ,663 1,508

Room Sharing d_3 5,904 5,606 ,076 1,053 ,294 ,693 1,443

Room Sharing d_4 -1,623 6,664 -,021 -,243 ,808 ,480 2,084

Room Sharing d_5 -10,982 6,982 -,126 -1,573 ,117 ,566 1,768

Backup Place -2,187 4,556 -,031 -,480 ,632 ,846 1,182

Own Work Place -18,555 4,818 -,299 -3,851 ,000 ,603 1,659

Freedom work

location

1,500 ,853 ,126 1,759 ,080 ,711 1,406



15.3.1. Freedom work location – Reflection on choice of location

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,338a ,114 ,084 ,70121

2 ,396b ,157 ,124 ,68586 1,783

Model Summary

Model

Change Statistics

R Square


1 ,114a 3,812 7 207 ,001

2 ,042b 10,367 1 206 ,001

ANOVA


1 Regression 13,122 7 1,875 3,812 ,001a

Residual 101,781 207 ,492

Total 114,902 214

2 Regression 17,998 8 2,250 4,783 ,000b

Residual 96,904 206 ,470

Total 114,902 214

a. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2 b. Predictors: (Constant), Location dependency, Position d_5, Position d_4, Gender, Age , Position d_3, Position d_2, Freedom work location c. Dependent Variable: Refl. location


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 4,238 ,304 13,935 ,000

Gender ,256 ,130 ,132 1,965 ,051 ,946 1,057

Age -,003 ,006 -,028 -,398 ,691 ,873 1,145

Position d_2 -,074 ,138 -,046 -,536 ,592 ,582 1,719

Position d_3 ,001 ,140 ,001 ,010 ,992 ,602 1,662

Position d_4 -,180 ,204 -,065 -,885 ,377 ,800 1,250

Position d_5 -,071 ,165 -,034 -,433 ,666 ,683 1,465


2 (Constant) 3,533 ,369 9,565 ,000

Gender ,201 ,129 ,104 1,561 ,120 ,929 1,077

Age -,002 ,006 -,022 -,321 ,749 ,872 1,146

Position d_2 -,125 ,136 -,078 -,923 ,357 ,574 1,743

Position d_3 -,025 ,137 -,015 -,186 ,853 ,600 1,668

Position d_4 -,194 ,199 -,070 -,975 ,331 ,800 1,250

Position d_5 -,100 ,161 -,048 -,618 ,537 ,681 1,469


Freedom work

location

,072 ,022 ,239 3,220 ,001 ,744 1,344

a. Dependent Variable: Refl. location


15.4.1. Freedom working hours – Flex-time

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,307a ,094 ,063 13,14619

2 ,335b ,112 ,078 13,04384 2,124

Model Summary

Model

Change Statistics

R Square


1 ,094a 3,054 7 206 ,004

2 ,018b 4,245 1 205 ,041

ANOVA


1 Regression 3694,620 7 527,803 3,054 ,004a

Residual 35601,376 206 172,822

Total 39295,996 213

2 Regression 4416,921 8 552,115 3,245 ,002b

Residual 34879,075 205 170,142

Total 39295,996 213

a. Predictors: (Constant), Time dependency, Position d_3, Gender, Position d_4, Age , Position d_5, Position d_2 b. Predictors: (Constant), Time dependency, Position d_3, Gender, Position d_4, Age , Position d_5, Position d_2, Freedom working hours c. Dependent Variable: Flextime


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 23,884 6,015 3,971 ,000

Gender ,793 2,432 ,022 ,326 ,745 ,955 1,047

Age ,031 ,120 ,018 ,261 ,794 ,880 1,136

Position d_2 7,838 2,562 ,264 3,060 ,003 ,592 1,688

Position d_3 5,169 2,607 ,168 1,983 ,049 ,615 1,626

Position d_4 ,160 3,734 ,003 ,043 ,966 ,792 1,263

Position d_5 5,712 3,122 ,146 1,829 ,069 ,687 1,455

Time dependency -3,991 1,217 -,221 -3,279 ,001 ,965 1,037

2 (Constant) 12,240 8,219 1,489 ,138

Gender ,236 2,428 ,007 ,097 ,923 ,943 1,060

Age ,036 ,119 ,021 ,306 ,760 ,880 1,137

Position d_2 7,800 2,542 ,262 3,069 ,002 ,592 1,688

Position d_3 5,274 2,587 ,171 2,038 ,043 ,615 1,626

Position d_4 ,485 3,708 ,010 ,131 ,896 ,791 1,265

Position d_5 5,778 3,098 ,148 1,865 ,064 ,687 1,455

Time dependency -2,783 1,343 -,154 -2,073 ,039 ,780 1,281

Freedom working

hours

1,149 ,558 ,153 2,060 ,041 ,787 1,270

a. Dependent Variable: Flextime


15.5.1. Freedom working hours – Reflection on working hours and schedule

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,345a ,119 ,089 ,75134

2 ,434b ,188 ,157 ,72286 1,971

Model Summary

Model

Change Statistics

R Square


1 ,119a 3,993 7 207 ,000

2 ,069b 17,632 1 206 ,000

ANOVA


1 Regression 15,780 7 2,254 3,993 ,000a

Residual 116,853 207 ,565

Total 132,633 214

2 Regression 24,993 8 3,124 5,979 ,000b

Residual 107,640 206 ,523

Total 132,633 214

a. Predictors: (Constant), Time dependency, Position d_3, Gender, Position d_4, Age , Position d_5, Position d_2 b. Predictors: (Constant), Time dependency, Position d_3, Gender, Position d_4, Age , Position d_5, Position d_2, Freedom working hours c. Dependent Variable: Refl. time


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 4,782 ,344 13,912 ,000

Gender ,268 ,139 ,129 1,931 ,055 ,955 1,047

Age -,019 ,007 -,199 -2,860 ,005 ,884 1,132

Position d_2 -,280 ,146 -,162 -1,912 ,057 ,591 1,691

Position d_3 -,243 ,149 -,136 -1,630 ,105 ,614 1,628

Position d_4 -,023 ,213 -,008 -,110 ,913 ,792 1,263

Position d_5 ,017 ,176 ,007 ,095 ,924 ,685 1,460

Time dependency -,141 ,069 -,135 -2,040 ,043 ,966 1,035

2 (Constant) 3,492 ,451 7,739 ,000

Gender ,202 ,135 ,097 1,504 ,134 ,942 1,061

Age -,019 ,007 -,196 -2,941 ,004 ,884 1,132

Position d_2 -,284 ,141 -,164 -2,015 ,045 ,591 1,691

Position d_3 -,233 ,143 -,130 -1,624 ,106 ,614 1,629

Position d_4 ,014 ,206 ,005 ,067 ,947 ,790 1,265

Position d_5 ,044 ,170 ,020 ,262 ,794 ,684 1,462

Time dependency -,002 ,074 -,001 -,020 ,984 ,773 1,293

Freedom working

hours

,128 ,030 ,299 4,199 ,000 ,779 1,284

a. Dependent Variable: Refl. time


15.6.1. Telework facilitation rate – Reflection on media use

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the


1 ,173a ,030 ,002 ,62488

2 ,177b ,031 -,001 ,62591 1,968

Model Summary

Model

Change Statistics

R Square


1 ,030a 1,078 6 209 ,377

2 ,001b ,316 1 208 ,575

ANOVA


1 Regression 2,525 6 ,421 1,078 ,377a

Residual 81,610 209 ,390

Total 84,134 215

2 Regression 2,648 7 ,378 ,966 ,457b

Residual 81,486 208 ,392

Total 84,134 215

a. Predictors: (Constant), Position d_5, Position d_4, Age , Gender, Position d_3, Position d_2 b. Predictors: (Constant), Position d_5, Position d_4, Age , Gender, Position d_3, Position d_2, Telework facilitation c. Dependent Variable: Refl. media


Coefficients

Model


Standardized

Coefficients

t Sig.



1 (Constant) 3,992 ,260 15,329 ,000

Gender -,012 ,115 -,007 -,106 ,916 ,966 1,035

Age -,009 ,006 -,110 -1,526 ,129 ,895 1,118

Position d_2 ,094 ,121 ,069 ,781 ,435 ,601 1,664

Position d_3 -,086 ,123 -,060 -,698 ,486 ,620 1,614

Position d_4 -,017 ,181 -,007 -,094 ,925 ,805 1,242

Position d_5 ,242 ,146 ,136 1,658 ,099 ,691 1,448

2 (Constant) 3,885 ,323 12,044 ,000

Gender -,018 ,115 -,011 -,156 ,876 ,959 1,043

Age -,008 ,006 -,106 -1,457 ,147 ,885 1,130

Position d_2 ,094 ,121 ,069 ,781 ,436 ,601 1,664

Position d_3 -,082 ,123 -,058 -,670 ,503 ,618 1,617

Position d_4 -,022 ,181 -,009 -,119 ,906 ,804 1,244

Position d_5 ,243 ,146 ,136 1,660 ,098 ,691 1,448

Telework

facilitation

,012 ,022 ,039 ,562 ,575 ,975 1,026

a. Dependent Variable: Refl. media