Personality as a predictor of Collaborative Consumption usage

Personality as a predictor of Collaborative Consumption usage.

Final version: 23/06/2017 Student: S.J. Barends 11384670

MSc. In Business Administration – Digital Business track Amsterdam Business School

Supervisor: Mr. J. L. Pletzer PhD Candidate Jacobs University Bremen, Germany Vrije Universiteit Amsterdam, The Netherlands

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Statement of Originality

Statement of originality This document is written by Samuel Jan Barends who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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TABLE OF CONTENTS Statement of Originality .......................................................................................................................... 2

Abstract ................................................................................................................................................... 4

Introduction ............................................................................................................................................. 5

CC ......................................................................................................................................................... 7

Personality ........................................................................................................................................... 9

Lack of technology efficacy ............................................................................................................... 13

Conceptual model ............................................................................................................................. 15

Method .................................................................................................................................................. 15

Results ................................................................................................................................................... 18

Discussion .............................................................................................................................................. 23

Conclusion ............................................................................................................................................. 29

Limitations and future research ............................................................................................................ 31

References ............................................................................................................................................. 32

Appendices ............................................................................................................................................ 35

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Abstract This study researches the effect of personality on attitude towards collaborative consumption (CC) and ultimate intention to participate in CC. Much research has been done in the field of both personality and CC separately but individual differences in the study of the drivers of CC have been neglected so far. One of these individual differences is personality. For this study, personality has been divided into the commonly used five dimensions (Openness to experience, Conscientiousness, Extraversion, Agreeableness and Neuroticism). Traits from all five dimensions are compared to important factors of CC, such as trust and collaboration. Data from 335 respondents was collected through a survey and then analysed. The results show that only agreeableness has a significant positive influence on attitude towards CC and intention to participate in CC. Openness to experience had a significant positive influence on attitude towards CC but not on intention to participate in CC. Furthermore, neuroticism was the only personality dimension which was significantly moderated in the relation between personality and intention to participate in CC, mediated by attitude towards CC. This study contributes to current literature because it analyses individual differences in the study of drivers of CC. Furthermore, this study also contributes to managerial implications. Knowing which personalities can predict the usage of CC, can help managers in targeted acquisition.

Keywords: Collaborative consumption, personality, Big-Five, attitude, participation intention.

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Introduction Data from Google Trends show that the term ‘Sharing Economy’ has increased

significantly in popularity over the past three years. Companies like Uber and Airbnb are

disrupting traditional industries and completely changing attitudes towards ownership (Bardhi

& Eckhardt, 2012). According to Chen (2009), possession is no longer the ultimate desire of

consumers. Instead, consumers pool or share services or goods such as cars (Uber, BlaBlaCar)

or accommodation (Airbnb). According to PricewaterhouseCoopers (Bothun & Lieberman,

2015), sharing systems comprised a global revenue of roughly US$15 billion per year in 2015,

which is believed to grow to US$335 billion by 2025 (Marchi & Parekh, 2015).

These sharing systems are part of a construct called Collaborative Consumption (CC),

meaning that people share personal goods or services with other people through a sharing

platform, often against a fee. Interestingly, much research has been done about the drivers of

sharing economy (Hawlitschek, Teubner, & Gimpel, 2016; Hamari, Sjöklint, & Ukkonen, 2015;

Tussyadiah, 2015; Owyang, 2013). People’s motivation to participate in CC could be driven by

their perception about improving sustainability and their reputation (Heinrichs, 2013;

Tussyadia, 2015). However, individual differences in the study of the drivers of participation

have been neglected so far. One of those individual drivers is Personality. To the best of my

knowledge, no articles exist about how personality can be a predictor of intention to participate

in and attitude to CC. People’s opinion and willingness to share private properties with strangers

is possibly dependent on their personality. Personality is most commonly assessed with the Big-

Five personality traits, which are Extraversion, Conscientiousness, Openness to experience,

Agreeableness and Neuroticism (Goldberg, 1993).

Many models on the acceptance of technology are based on ease of use, complexity and

trialability of the technology, which are considered important factors for users to participate in

an online platform (Chong, Ooi, & Sohal, 2009). Because CC platforms are facilitated by ICT,

Tussyadiah (2015) argues that lack of technology efficacy is the largest deterrent of consumers’

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participation intention in CC. Therefore, lack of technology efficacy could moderate the

relationship between personality and attitude towards CC.

Understanding the relationship between personality and intention to participate in CC

can pose many advantages. By knowing which people are more likely to participate in CC,

corresponding companies can specifically target certain people to increase acquisition rates.

But not only companies benefit from CC. Research has shown that CC can also greatly benefit

customers through economic, environmental and societal benefits (Hamari, Sjöklint, &

Ukkonen, 2015). By, for example, sharing a car, less emission gas, lower gasoline costs and

more interaction with others is encouraged.

This has led to the following research question:

“What is the effect of personality on attitude and participation intention to CC?”

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First, insights are given into relevant literature about CC, personality and lack of

technology efficacy. These variables will be explained and linked to each other. Second,

hypotheses will be formulated. Third, the data and research method will be explained. Fourth,

insights into the results gathered from the research will be provided. Some descriptive statistics

as well as data analysis of the hypotheses will be framed. And lastly, the discussion and

conclusion of the findings will be discussed. The discussion links literature to the results and

the conclusion will briefly summarize the complete research.

Collaborative Consumption Although the concept of CC has been around for a long time (Felson & Spaeth, 1978),

the implications and possibilities have evolved significantly over the past years. Advances in

information and communication technologies have changed traditional market behaviours by

enabling online CC which has been defined as: “The peer-to-peer-based activity of obtaining,

giving, or sharing the access to goods and services, coordinated through community-based

online services” (Hamari, Sjöklint, & Ukkonen, 2015, p. 2047). Owyang (2013) argues in a

market report that there are three market forces which drove Collaborative Economy: Societal,

Economical and Technological. Societal market forces include increasing population density,

drive for sustainability, desire for community and generational altruism. Economic drivers are

monetize excess or idle inventory, increase financial flexibility, access over ownership and

influx of venture capital funding. And lastly technology drivers include social networking,

mobile devices and platforms, and payment systems.

Many researchers believe CC will be of great impact in the future and will help to solve

environmental, economic, and social problems (Belk, 2014; Hamari, Sjöklint, & Ukkonen,

2015; Hawlitschek, Teubner, & Gimpel, 2016).

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This research will focus on the consumers. A difference can be made between providers

and consumers of CC (Hawlitschek, Teubner, & Gimpel, 2016). Providers are the people who

offer their good or service to be accessed by a consumer. The consumer is the person who gains

access to the provider’s good or service. For example with Uber, the driver is the provider of

CC and the person who requested a ride, is the consumer. However, a clear distinction has to

be made between two exchange categories of CC platforms.

By mapping 254 CC platforms, Hamari et al. (2015) identify two exchange categories:

‘access over ownership’ and ‘transfer of ownership’. Access over ownership is the most

common exchange mode and means that users of a CC platform can offer other users to share

their goods or services for a limited amount of time. An example of an access over ownership

platform is Airbnb where users can offer their accommodation to others when they are away

from home themselves. Often these services are offered against a fee. Access over ownership

is in line with theories stating that it is no longer a consumers ultimate desire to own goods but

consumers are increasingly likely to access goods for a limited amount of time instead of buying

them (Bardhi & Eckhardt, 2012). Transfer of ownership is when ownership of a product or

service is transferred between one user to the other. This can be done in different ways such as

donating, swapping or purchasing. The difference with traditional purchasing is that with CC,

purchasing is done through a peer-to-peer platform. This study will focus on access over

ownership because it is most commonly used.

Other research has looked into motivations of why people participate in CC. Hamari et

al. (2015) distinguish two categories: intrinsic and extrinsic motivations. The intrinsic

motivations they researched are sustainability and enjoyment and the extrinsic motivations are

reputation and economic benefits. Their results show that perceived sustainability has a

significant effect on predicting someone’s attitude to CC but not on intention to participate in

CC. Enjoyment has a significant effect on both prediction as well as intention. For the extrinsic

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motivations, expected increase in reputation did not have significant effects on either attitude

to CC nor on participation intention. Furthermore, expected economic benefits did not have a

significant effect on attitude but did have a significant positive effect on participation intention.

And lastly, attitude towards CC had a significant positive effect on intention to use CC. Attitude

towards CC and intention towards CC will both be researched for this study but because

expected increase in reputation and expected economic benefits did not have a significant

positive effect on participation intention, only perceived sustainability and enjoyment will be

researched further.

One of the most discussed variables is trust (Ert, Fleischer, & Magen, 2016; Tussyadiah,

2015; Hawlitschek, Teubner, & Gimpel, 2016; Hamari, Sjöklint, & Ukkonen, 2015) which can

also be seen as a barrier to CC. For example, research has shown that consumers are more likely

to book accommodation through Airbnb when the choice of listing includes a photo of the host

(Ert, Fleischer, & Magen, 2016). This is because a photo positively affects consumer’s

perceived trustworthiness even though they are not conscious of this effect themselves. Ert,

Fleischer and Magen (2016) even state that in CC platforms like Airbnb, the consumer’s

impression of the photo has a greater influence than the review scores of an accommodation.

Möhlmann (2015) even argues that CC is for a large part based on trust. Without mutual trust,

CC could not exist because people would not be willing to participate. Because trust is such an

important variable for CC, it is important to link it with the personality dimensions. Higher

levels of trust could possibly improve attitude towards CC and ultimately intention to

participate in CC. This will be discussed in further detail later.

Personality Personality is defined in the Oxford dictionary as “The combination of characteristics

or qualities that form an individual's distinctive character” (Oxford, 2017)). There is almost an

infinite amount of individual differences which make up one’s personality, yet many of these

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differences are not visible to the daily interactions between people (Goldberg, 1990). Many

psychologists have studied personality and the various traits which can be measured. Seventy

years ago, Catell (1947) identified at least twelve traits which were replicable. However, these

were reduced by many researchers to five factors, also known as the big-five (Tupes & Christal,

1961). These five factors are: 1. Extraversion, 2. Agreeableness, 3. Conscientiousness, 4.

Openness to experience, and 5. Neuroticism. Researchers claim that these five factors, in

combination or individually, explains almost all variance in personality (Tupes & Christal,

1961).

In the next section, expectation for the relationship between personality and CC will be

outlined based on previous research.

Extraversion is measured as the degree to how outgoing or reserved someone is.

Personalty traits which are often associated with extraversion are talkability, sociability,

activeness and assertiveness (Barrick & Mount, 1991). Extraverts tend to like working with

others due to their social and talkative nature, in contrast to introverts, who have a more quiet

and private nature (McCrae & John, 1992). Several studies have examined how extraversion

affects people’s willingness to collaborate (McLean & Pasupathi, 2006; Doucette, Nevins, &

McDonough, 2005; Haberyan & Barnett, 2010). The results show that someone with high

extraversion level is more likely to choose working together with someone else rather than

working alone. The reason for this is that extraverts are more willing to socialize and talk with

others, which is required when collaborating. Furthermore, it is argued that trust towards

strangers is controlled by extraversion (Hiraishi, Yamagata, Shikishima, & Ando, 2008). With

trust being such an important factor to people’s attitude towards CC, extraverts will probably

be more likely to participate.

Hypothesis 1: Extraversion has a positive influence on Attitude towards CC.

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The second dimension is known as agreeableness or likability. This dimension is

associated with personality traits such as being soft-hearted, courteous, trusting and flexible

(Barrick & Mount, 1991). Agreeableness is seen as the compassionate side of humans (Digman,

1990). Additionally, according to Mooradian et al. (2006) it is important to note the difference

of interpretation of this personality factor. Where some researchers see this factor as someone

being warm and happy other researchers regard as how compliant one is to another (Mooradian,

Renzl, & Matzler, 2006). For this research, the degree of warmness and happiness is used.

Agreeableness is often linked with sociability and work performance indicating people who

score high on this factor have higher satisfaction in life and better performances due to better

inter-personal relationships (Asendorpf & Wilpers, 1998; Hurtz & Donovan, 2000). Due to the

more trusting nature of agreeable people (Barrick & Mount, 1991) and better inter-personal

relationships with others (Asendorpf & Wilpers), it could indicate that people who score high

on agreeableness are more likely to participate in CC platforms because it requires trust in the

platform to be willing to participate (Tussyadiah, 2015). Agreeableness has also been associated

with altruistic and sympathetic natured persons who want to help others (McCrae & John,

1992).

Their more social nature results in agreeableness predicting higher successfulness in

collaborations with others (Mooradian, Renzl, & Matzler, 2006). Therefore, individuals scoring

higher on agreeableness are expected to have better attitudes towards CC.

Hypothesis 2: Agreeableness has a positive influence on attitude towards CC.

Openness to experience measures the degree of how curious or cautious one is. Traits

which are associated with this factor are, for example, curiosity, intelligence, complexity and

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creativeness (Barrick & Mount, 1991). Research by Lumsden and Mackay (2006) shows that

openness to experience has a positive effect on trust meaning that people who score higher on

openness to experience are also more trusting. Trust is seen as one of the most important drivers

of CC usage (Ert, Fleischer, & Magen, 2016; Hawlitschek, Teubner, & Gimpel, 2016) and

therefore the trusting nature of people who score higher on openness to experience has a positive

influence on their attitude towards CC. Furthermore, curiosity is one of the traits associated

with openness to new experience. Curiosity has also been linked with higher development of

learning and engagement (Arnone, Small, Chauncey, & McKenna, 2011). Since lack of

technology efficacy is the largest deterrent of CC, people who are more willing to learn, will

also be more likely to learn, or have learned, new technologies related to CC platforms.

Hypothesis 3: Openness to experience has a positive influence on Attitude towards CC.

Conscientiousness measures how dependent someone is and is linked with personality

traits such as organization, carefulness and responsibility which is contrasted with unreliability

and negligence (Barrick & Mount, 1991; Goldberg, 1993). The fourth personality factor does

not have much resemblance with CC and is therefore difficult to assess beforehand. One article

indicates that conscientiousness has a negative relationship with internet usage and therefore

people who score high on the corresponding traits use the internet less (Landers & Lounsbury,

2006). Because CC platforms require the use of internet, this could result in a negative influence

with individuals scoring high on conscientiousness. Other research shows a positive

relationship between conscientiousness and sharing due to the high self-interested nature of

conscientous people (Matzler et al., 2008). This could lead to a positive relationship with CC

because often collaborative services can save the user time and money or even make a living

from it. However, just like agreeableness, there is not enough empirical research related to both

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CC and conscientiousness to clearly assess a relationship beforehand without further emperical

research. Hence, this relationship will also be be examined exploratory.

The fifth and last factor is the dimension of Neuroticism which covers personality traits

like anxiousness, depression, embarrassment and emotionality or on the contrast emotional

stability (Barrick & Mount, 1991; Goldberg, 1993). Due to their stressfull and anxious

personality, neuroticism has a negative relationship with technology acceptance meaning that

people who score high on neuroticism are less likely to accept new technology (Devaraj et al.,

2008). This is because neurotic people find new experiences, such as a new technology,

threatening, which makes them stressed (Devaraj et al., 2008). Other research suggests

neuroticism also has a negative relationship with trust (Zhou & Lu, 2011). Since trust is such

an important factor of CC usage intention (Tussyadiah, 2015), this would indicate that

neuroticism has a negative relationship with individual’s attitude towards CC.

Hypothesis 4: Neuroticism has a negative influence on Attitude towards CC.

Lack of technology efficacy Technologies, like online platforms, are becoming an increasingly important part of

everyday life. However, new technologies are not always easy for everyone to adapt to. Models

on the acceptance of technology are often based on ease of use, complexity and trialability of

the technology (Chong, Ooi, & Sohal, 2009). Especially the perceived ease of use of technology

is often used as an important factor of accepting new technologies. This perception has been

described as the extent to how much effort a person believes is needed to using a new

technology (Venkatesh, 2000). Therefore, the better someone’s efficacy with a new technology,

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the more likely is it that he/she will accept the technology and thereby have a more positive

attitude towards the new technology.

Tussyadiah (2015) differentiates lack of trust in three different forms: lack of trust

between consumer and provider, lack of trust in technology by users and lack of trust in a

company. Tussyadiah (2015) argues the lack of trust in technology comes from a lack of

technology efficacy. This means that a consumer is not able to produce a desired result because

of technology which can be caused due to high complexity. From the results, it is concluded

that lack of technology efficacy seems to be the major barrier, followed by lack of trust and

lastly lack of economic benefits (Tussyadiah, 2015).

Therefore, making sure the CC platform is easy to use and not creating a technology

barrier is of great importance to increase the consumers’ attitude towards CC. Since technology

efficacy can be of such great impact to new technologies, or in this case CC platforms, this

study will research the moderating role of lack of technology efficacy between personality and

attitude towards CC.

Hypothesis 5: The influence of the personality dimensions on attitude towards CC will be

weakened by a lack of technology efficacy.

Hamari et al. (2015) have already studied the relation between attitude towards CC and

intention to participate in CC. Therefore, their research is followed and a positive influence of

attitude towards CC on intention to participate in CC assumed.

Hypothesis 6: Attitude towards CC has a positive influence on intention to participate in CC.

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Conceptual model

Note. H = Hypothesis; - = negative influence; + = positive influence; * = will be researched exploratory

Method The population researched in this study is anyone with the accessibility to internet,

which is a requirement to make use of CC platforms. The survey was distributed online through

Social Media and via e-mail. Since many of the platforms require a minimum age of 18, any

response of a younger respondent was removed. Due to the large possible population and

unknown sampling frame, a non-probability convenience sampling method was used. In total,

335 participants filled in the questionnaire of which 258 completed it. Because the survey was

mainly distributed through Facebook, it was very difficult to predict the response rate since it

was an open message to my connections. These connections will also be asked to share the

survey, increasing the difficulty to assess the amount of people reached.

The questionnaire starts with asking the respondents their demographics such as Sex,

Age, Educational Background and Nationality. Age and gender are used as controlling variables

to remove their effects from the equation. The other constructs will be measured with

questionnaires used in the following scientific articles:

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For all dimensions of ‘Personality’ (Extraversion, Agreeableness, Openness to

experience, Conscientiousness and Neuroticism), the Big Five Inventory was used (John &

Srivastava, 1999). All Cronbach alphas are between 0.70 and 0.87. The items range from 1

“disagree strongly” to 5 “agree strongly”. For each item, the participant has to answer the

question: ‘I see myself as someone who..’

The first dimension, extraversion, has eight items. An example of an item is: ‘Is

talkative’ and ‘Is reserved’. The second dimension, agreeableness, has nine items. An example

of an item is: ‘Tends to find fault with others’ and ‘Is helpful and unselfish with others’. The

third dimension, conscientiousness, has nine items. An example of an item is: ‘Does a thorough

job’ and ‘Can be somewhat careless’. The fourth dimension, neuroticism, has eight items. An

example of an item is: ‘Is depressed, blue’ and ‘Is relaxed, handles stress well’. And the last

dimension, openness to experience, has ten items. An example of an item is: ‘Is original, comes

up with new ideas’ and ‘Is curious about many different things’.

For both the structures ‘Attitude towards CC’ and ‘Intention to participate in CC’, the

article by Hamari, Sjöklint and Ukkonen (2015) was used. The structure ‘Attitude towards CC’

(Cronbach alpha = 0.858) contains five items. An example of an item is: ‘All things considered,

I find participating in CC to be a wise move.’ and ‘CC is a better mode of consumption than

selling and buying individually.’. The structure ‘Intention to Participate in CC’ (Cronbach alpha

= 0.863) contains four items and an example of an item is: ‘All things considered, I expect to

continue CC often in the future.’ and ‘It is likely that I will frequently participate in CC

communities in the future.’. All items for both constructs are on a 7-point Likert scale from 1

(strongly disagree) to 7 (stongly agree).

And lastly, for ‘Lack of Technology Efficacy’, the article by Barbeite and Weiss (2004)

was used. For this construct (Cronbach alpha = 0.85), the article provides seventeen items using

a 5-point scale, from 1 (strongly disagree) to 5 (strongly agree). The items were adjusted to

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‘technology’ instead of ‘computer’ because in the article by Tussyadiah (2015) it states that

Lack of Technology Efficacy is the biggest deterrence of CC usage. An example of an item is:

‘I find working with digital technology very easy.’ and ‘17. When using digital technology I

worry I might press the wrong button and damage it.’.

For the data analysis, first the correlations were measured (Appendix 1). Then some

predictives were computed (Appendix 1). Next, a reliability analysis was conducted to test the

consistency of the data which showed all Cronbach alphas are above the 0.7 mark (Appendix

1). Afterwards, two hierarchical multiple regression models were computed. One for

personality predicting intention to participate in CC (Appendix 2) and one for personality

predicting attitude towards CC (Appendix 3). A linear regression model was computed to test

the effect of attitude towards CC on intention to participate in CC (Appendix 4). The

mediating effect of attitude towards CC between all five personality factors and intention to

participate in CC was computed next (Appendix 5-9). And lastly, a moderated mediation

analysis was performed (Appendix 10).

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Results1 Personality predicting intention to participate in CC

A hierarchical multiple regression model was computed to explore to what degree the

five personality dimensions; Openness to Experience, Conscientiousness, Extraversion,

Agreeableness, and Neuroticism can predict an individual’s intention to participate in CC, after

controlling for age and gender (Appendix 1).

For the first step of the hierarchical multiple regression model, two controlling variables

were used: age and gender. From the analysis came forth that this first model was statistically

significant F (2,255) = 13,731; p < 0,001 and it explained 9,7% of variance in an individual’s

intention to participate in CC. For the second step of the model, the five personality dimensions

were added. This second model increased the explained variance in an individual’s intention to

participate in CC to 20,5%, F (7,250) = 9,200; p < 0,001. That means that by introducing

personality, an additional 10,8% of variance in attitude towards CC is explained after

controlling for age and gender (R2 change = 0.108; F (2, 250) = 6,766; p < 0,001). In the second

and final model, two out of seven predictor variables were statistically significant with

agreeableness scoring the highest Beta value (β = 0,266; p < 0,001) after age (β = -0,280; p <

0,001). This means that if an individual’s agreeableness increases by one, his/her intention to

participate in CC increases by 0.266. But on the other hand, age has a negative relation with

intention to participate in CC meaning that older people have a lower attitude towards CC. It is

important to note here that the lowest age group selected was 3 (18 – 24), indicating that the all

participants were older than 18.

1 It is important to note here that the results from SPSS differed from Process (Hayes, 2013). For the correlations and regressions, the data from SPSS was assumed. And for the mediations and moderated mediation, data from Process was assumed.

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Personality predicting attitude towards CC

Afterwards, another hierarchical multiple regression model was computed to examine

to what degree the same five personality dimensions can predict an individual’s attitude towards

CC. Just like the previous analysis, age and gender will be controlled first (Appendix 2).

From the first analysis, with age and gender as controlling variables, came forth that this

model was statistically significant F (2,255) = 6,414; p < 0,05 and it explained 4,8% of variance

in an individual’s attitude towards CC. Then the five personality dimensions were again added

for the second step of the model. This model increased the explained variance in an individual’s

attitude towards CC to 15,8%, F (7,250) = 6,681; p < 0,001. By introducing personality, an

additional 11% of variance in attitude towards CC is explained after controlling for age and

gender (R2 change = 0.11; F (2, 250) = 6,511; p < 0,001). Three out of seven predictor variables

were statistically significant with again agreeableness scoring the highest Beta value (β = 0,249;

p < 0,05) after openness to experience (β = 0,158; p < 0,05) and age (β = -0,221; p < 0,05).

Attitude towards CC predicting intention to participate in CC

A linear regression model was computed to measure the degree to which an individual’s

attitude towards CC can predict their intention to participate in CC, after again controlling for

age and gender (Appendix 3).

Age and gender were again used as controlling variables for the first step. The first

model is statistically significant F (2,255) = 13,731; p < 0,001 and it explained 9,7% of the

variance of an individual’s intention to participate in CC. The variable attitude towards CC was

added in the model and was also statistically significant F (3,254) = 176,404; p < 0,001 and

increased the explained variance of intention to participate in CC to 67,6%. Two out of three

variables in the second model are statistically significant, namely age and attitude to CC.

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Attitude towards CC had by far the highest Beta value (β = 0,779; p < 0,001) after age (β = -

0,122; p < 0,05).

Mediations

Next the mediating effect of attitude towards CC between all five personality

dimensions and intention to participate in CC was researched using ‘process’ by Hayes (2012).

However, since agreeableness was the only dimension which significantly effected both

intention to participate in CC and attitude towards CC, the other four dimensions will not be

discussed in depth regarding the mediation.

The indirect effect of agreeableness on intention to participate in CC is 0.36 which

means that when two individuals have a difference of one unit in their noted agreeableness, the

will differ 0.36 units in their intention to participate in CC due to individuals with more agreeing

nature having a more positive attitude towards CC. As indicated by a 95% BC bootstrap

confidence interval, agreeableness has a statistically different indirect effect than zero because

the interval is entirely above zero (0.1793 to 0.5619).

Interestingly, openness to experience and extraversion also had a statistically different

indirect effect than zero because their interval were also entirely above zero (0.25 to 0.73 and

0.04 to 0.42 respectively). The other two dimensions, neuroticism and conscientiousness did

not have a statistically different indirect effect than zero (-0.11 to 0.21 and -0.33 to 0.09

respectively). However, as mentioned before, these dimensions will not be analysed further.

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Moderated mediation

Lastly, a moderated mediation analysis was performed to research the moderating effect

of lack of technology efficacy on the mediating effect of attitude towards CC between the five

personality dimensions and intention to participate in CC (Appendix 10). For this analysis

‘process’ by Hayes (2012) was again used.

The results show that there is only statistical evidence of a moderated mediation taking

place between neuroticism and attitude towards CC (b=0,27; p<0,05). The other four

dimensions all had a p-value of higher than 0.05 and were therefore not researched further. In

other words, lack of technology efficacy significantly moderates the relationship between

neuroticism and attitude towards CC.

Figure 1. Significant results of conceptual model

Note. *p<0.05

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Overview of results

The results show Hypothesis 2, 3 and 6 are accepted, Hypothesis 1 and 4 are rejected and

Hypothesis 5 is only accepted for neuroticism.

Table 1. Overview of hypotheses

Number of Hypotheses Hypotheses Results Hypothesis 1 Extraversion has a positive

influence on Attitude towards CC.

Rejected

Hypothesis 2 Agreeableness has a positive influence on attitude towards CC.

Accepted

Hypothesis 3 Openness to experience has a positive influence on Attitude towards CC.

Accepted

Hypothesis 4 Neuroticism has a negative influence on Attitude towards CC.

Rejected

Hypothesis 5 The influence of the personality dimensions on attitude towards CC will be weakened by a lack of technology efficacy.

Only accepted for neuroticism

Hypothesis 6 Attitude towards CC has a positive influence on intention to participate in CC.

Accepted

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Discussion This study researched the effect of personality on attitude and participation intention to

CC. Five personality dimensions as described by Goldberg (1993) have been analysed.

Interestingly, only agreeableness and openness to experience had a significant influence on

attitude towards CC. Additionally, agreeableness was also the only dimension which had a

significant influence on intention to participate in CC. In both cases, agreeableness had the

highest standardized coefficient (Appendix 2 and 3). To answer the research question “What is

the effect of personality on attitude and participation intention to CC?”, all five dimensions

have been analysed.

Extraversion. This research shows that extraversion does not have an influence on

either attitude towards CC or intention to participate in CC. However, even though it was

insignificant, it was still positive. This is in line with several other researchers, who argue that

extraverts are more likely to collaborate with other individuals (McLean & Pasupathi, 2006;

Doucette, Nevins, & McDonough, 2005; Haberyan & Barnett, 2010). Furthermore, researchers

argue extraversion controls an individual’s trust towards a stranger (Hiraishi, Yamagata,

Shikishima, & Ando, 2008). Both collaborating and trust are important factors of CC. Therefore

the positive influence can be explained.

Agreeableness. The analysis proved agreeableness has a positive influence on an

individual’s attitude towards CC. Not only is it positive, it is also significant. This was as

expected because previous research suggests more agreeable individuals have better inter-

personal relationships (Asendorpf & Wilpers, 1998; Hurtz & Donovan, 2000). Inter-personal

relationships are an important part of the collaborative aspect of CC. Furthermore,

agreeableness has been positively linked with trust (Barrick & Mount, 1991), which is also an

important factor of CC (Tussyadiah, 2015). And lastly, higher scores of agreeableness are

positively related to altruism and sympathy (McCrae & John, 1992). These traits give agreeable

24

individuals a higher sense of helping others. All these aspects lead to a better attitude towards

CC.

Openness to experience. Just like agreeableness, the results indicate openness to

experience has a significant positive influence on attitude towards CC. Again trust plays an

important factor. Due to their curious and intelligent nature (Barrick & Mount, 1991),

individuals with a higher level of openness to experience are also more trusting (Lumsden &

Mackay, 2006). Not only trust, but also a higher development of learning and engagement

contributes to a positive influence on attitude towards CC. The concept of CC is still fairly new

and lack of technology efficacy is seen as the largest deterrent of these sharing systems

(Tussyadiah, 2015). Therefore, individuals who are higher developed in learning and

engagement of new experiences, such as CC and technology, will also have a more positive

attitude towards CC.

Conscientiousness. The fourth personality dimension, conscientiousness, does not have

much resemblance with CC. Conscientiousness has been associated with traits such as

carefulness, organization and responsibility (Barrick & Mount, 1991; Goldberg, 1993).

Arguments can be found for both a positive and negative relationship with attitude towards CC.

Research by Landers & Lounsbury (2006) argues conscientious individuals are less fond of

internet. Because CC platforms require usage of internet, this could indicate a negative

influence on attitude towards CC. However, on the other side, conscientiousness has been

positively associated with sharing (Matzler et al., 2008). The reason for this positive association

is because conscientious individuals have a high self-interest. CC has proven to be able to save

time and money by sharing services and goods (Hamari, Sjöklint, & Ukkonen, 2015).

Therefore, conscientiousness could also positively influence attitude towards CC.

The results of this research show there is a negative influence of conscientiousness on attitude

towards CC. However, this negative influence is not significant. This could indicate that the

25

negative influences, such as aversion to internet, outweighs the positive influences, such as the

benefits of CC to users’ self-interest.

Neuroticism. From the results we find that neuroticism actually had a positive influence

on attitude towards CC, though it was insignificant. This is on the contrary of what previous

research expected. Neuroticism has been negatively linked with trust (Zhou & Lu, 2011) and

acceptance of new technologies (Devaraj et al., 2008). Because trust is an important factor of

CC (Ert, Fleischer, & Magen, 2016; Hawlitschek, Teubner, & Gimpel, 2016) and it is still seen

as a relatively new market behaviour based on technological advances (Hamari, Sjöklint, &

Ukkonen, 2015), prior to this research it was expected neuroticism would have a negative

influence on CC. Also, because trust and technology acceptance are two important factors of

CC (Tussyadiah, 2015), it was expected to have a significant influence on attitude towards CC.

However, the results from Process indicate there is indeed a negative relation between

neuroticism and attitude towards CC. Therefore further research is required to analyse this

relationship because all previous research, to my knowledge, indicates a negative influence.

Attitude towards CC and intention to participate in CC. Hamari et al. (2015) had

already researched the relationship between attitude towards CC and intention to participate in

CC. They concluded there was a significant positive relationship. This is in line with the results

from this research. However, the correlation between these two variables was on the high side.

Some participants might therefore not have interpreted the two variables as different from each

other. But based on the findings of this research and the research by Hamari et al. (2015), it is

evident there is a significant positive relation between attitude towards CC and intention to

participate in CC.

Accordingly, it can be concluded that personality in total does not have a very significant

influence on attitude towards CC and ultimately intention to participate in CC. Only two out of

26

five dimension directly significantly influence intention to participate in CC and only one

dimension significantly influences attitude towards CC.

Moderated mediation effect. This study did not only research the effect of personality

on attitude towards CC and ultimately intention to participate in CC, but also the moderating

effect of lack of technology efficacy on the relationship between personality and intention to

participate in CC, mediated by attitude towards CC. According to Tussyadiah (2015), lack of

technology efficacy is the largest barrier of individuals to make use of CC platforms. Ease of

use, complexity and trialability of technology are often described as the three most important

factors of technology acceptance (Chong, Ooi, & Sohal, 2009). From the results we can see that

only one personality dimension was significantly moderated by lack of technology, namely

neuroticism. It is important to note here that, unlike in SPSS, the results in process show

neuroticism has a negative influence on attitude towards CC. Based on the negative influence

of neuroticism on attitude towards CC as in Process, the result is in line with prior research.

According to the results in Process, individuals scoring high in neuroticism will have a low

attitude towards CC which is moderated by lack of technology efficacy. This means that if an

individual is familiar with technology, his/her attitude towards CC will improve as well and

vice versa.

However, the other four personality dimensions were insignificantly moderated by lack

of technology efficacy. There could be several reasons for this. The mean age group of the

participants is 4,12 (Appendix 1). Age group 4 is between 25 and 34 years old. This means they

belong to the ‘Millennials’, who, according to Google Consumer Barometer, don’t go online

but live online (Google, 2017). They are born with the current technologies and are therefore

often experienced with it. The mean lack of technology efficacy was 2,030 (Appendix 1), which

means that on average, the participants did not think they have a technology efficacy. However,

this does not explain why only neuroticism was significantly moderated by lack of technology

27

efficacy. A possible explanation could be that neuroticism was, according to the results from

Process, the only dimension which negatively influenced attitude towards CC (Appendix 10).

Or in other words, lack of technology efficacy only moderates the personality dimensions which

themselves have a negative influence on attitude towards CC.

Theoretical implications.

Much research has been conducted on the drivers and advantages of CC (Hawlitschek,

Teubner, & Gimpel, 2016; Hamari, Sjöklint, & Ukkonen, 2015; Tussyadiah, 2015; Owyang,

2013). However, little to none research has been conducted on how personality can predict the

usage of CC platforms. This paper has researched which personalities are more likely to make

use of said platforms. The results show that agreeableness is the only personality dimension

which positively influences both attitude towards CC and intention to participate in CC.

Additionally, the moderating effect of lack of technology efficacy on the relationship

between personality and intention to participate in CC, mediated by attitude towards CC. has

been researched. This study shows that only neuroticism is the only personality dimension

which is significantly moderated by lack of technology efficacy.

Managerial implications.

Nowadays, the amount of collaborating services is increasing. It is disrupting traditional

market forces and the way consumers think about possession of goods and services. Also, due

to the benefits to sustainability, governments and companies are increasingly interested in CC

platforms. By finding an answer to how personality affects participation intention and attitude

towards CC, corresponding companies can improve their performances by adjusting their

services to fit customer needs. The results indicate that individuals who score high on

agreeableness have a significant positive influence on both attitude towards CC and intention

28

to participate in CC. Therefore, by studying how agreeable consumers behave, it is possible to

target these individuals and thereby increase acquisition rates of CC platforms. Not only can

companies benefit from this research, also consumers and many other people since researchers

believe CC can positively influence environmental, economic and social problems. A better

understanding of the topic can lead to improved economies, better sustainability and

improvements to society (Belk, 2014; Hamari, Sjöklint, & Ukkonen, 2015; Hawlitschek,

Teubner, & Gimpel, 2016).

29

Conclusion The main goal of this study was to find an answer to the question: “What is the effect of

personality on attitude and participation intention to CC?”. Personality has been divided into

five dimension (Openness to experience, conscientiousness, extraversion, agreeableness and

neuroticism). No previous studies had researched this relation before. However, personality

traits corresponding to the five dimensions were compared with factors of CC to find

resemblances such as collaboration and trust.

Previous research suggests openness to experience has a positive influence on intention

to participate in CC due to higher levels of trust (Lumsden & Mackay, 2006) and curiosity

(Barrick & Mount, 1991). Conscientiousness does not have much resemblance with CC and is

therefore further researched in this paper. Extraversion is also expected to positively influence

intention to participate in CC because extraverts tend be social and trusting towards others, both

needed when collaborating (McLean & Pasupathi, 2006; Doucette, Nevins, & McDonough,

2005; Haberyan & Barnett, 2010). Agreeableness is likewise expected to positively influence

intention to participate in CC because agreeable individuals tend to have better inter-personal

relationships with others (Asendorpf & Wilpers) and a high trusting nature (Barrick & Mount,

1991). And lastly, neuroticism is the only dimension which is expected to negatively influence

intention to participate in CC. Individuals with high scores in neuroticism are less likely to

accept new technologies (Devaraj et al., 2008), such as CC platforms. They are also distrusting

in strangers (Zhou & Lu, 2011), which does not benefit participation intention in CC.

In order to find an answer to this question and the hypotheses, a survey is used. 335

responses were recorded through social media platforms and email. The recorded data is then

analysed to find the answers.

The results show that only two dimensions had a significant influence on attitude

towards CC, namely agreeableness and openness to experience. Both dimensions had a positive

30

influence. Furthermore, only one dimension had a significant influence on intention to

participate in CC, namely agreeableness. Furthermore, only neuroticism is significantly

moderated in the relationship between personality and intention to participate in CC, mediated

by attitude towards CC.

No prior studies have researched these relations and thereby this study contributes to the

current theories. Furthermore, companies can benefit from the results of this study because it

shows agreeableness is the only personality dimension which significantly positively influences

both intention to participate in CC and attitude towards CC.

31

Limitations and future research This study has researched the effect of personality on attitude towards CC and intention

to participate in CC. However, a few limitations exist.

First, even though the five dimensions of personality are often used, a limitation of this

measurement is that the dimensions are measured through self-assessment. Individuals might

evaluate themselves differently than they really are or how others perceive them. Additionally,

as an example of CC platforms only Uber and AirBnB were named in the survey. This can

affect perceptions because these two companies are the largest examples at the moment. These

companies also entail transportation and accommodation respectively. Other sectors might find

different results. Another limitation is that because CC is still a fairly new concept, many

individuals might not exactly understand what it is (even though it was briefly explained in the

survey). Also, no distinction was made between users who have and users who do not have

experience with CC platforms. And lastly, attitude towards CC had a correlation of 0,81 with

intention to participate in CC which might show that people did not perceive the two questions

as compellingly different.

Future research should control other sectors and provide different examples than Uber

and AirBnB. Also, solely studying individuals who not have any experience with or knowledge

of CC can provide different results. Follow-up studies should also make a better differentiation

between attitude towards CC and intention to participate in CC.

32

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Appendices

Appendix 1:

Variables M SD 1 2 3 4 5 6 7 8 9 Gender 1,45 ,498 Age 4,12 1,524 -,197 Openness to Experience 3,762 ,541 ,018 -,115 (,725) Conscientiousness 3,653 ,637 ,079 ,372 ,1 (,778) Extraversion 3,710 ,675 ,029 ,009 ,269 ,154 (,816) Agreeableness 3,854 ,618 ,105 ,24 ,209 ,264 ,178 (,769) Neuroticism 2,630 ,817 ,263 -,428 -,101 -,272 -,298 -,317 (,857) Attitude Towards CC 5,421 1,104 ,071 -,217 ,252 -,069 ,145 ,213 ,035 (,931) Intention to Participate in CC 5,076 1,298 ,135 -,302 ,226 -,145 ,141 ,199 ,088 ,81 (,951) Technology Efficacy 2,030 ,722 ,193 ,089 -,174 -,053 -,034 -,111 ,202 -,186 -,14 (,932)

Note. N = 258. Age coding = (1 = under 12; 2 = 12-17; 3 = 18-24; 4 = 25-34; 5 = 35-44; 6 = 45 – 54; 7 = 55 – 64; 8 = 65 – 74; 9 = 75 years or older), Gender coding (1 = male; 2 = female). Cronbach alpha values are in brackets on the diagonal. M = Mean; SD = Standard deviation.

36

Appendix 2: Hierarchical regression model of Intention to participate in CC

R R² R² Change B SE β t

Step 1 0,312 0,097 Age -,244 ,052 -,287 -4,722 Gender ,205 ,158 ,079 1,297 Step 2 0,453 0,205 0,108 Age* -,239 ,058 -,280 -4,109 Gender ,114 ,160 ,044 ,711 Openness to Experience ,281 ,145 ,117 1,938 Conscientiousness -,239 ,129 -,117 -1,852 Extraversion ,185 ,119 ,096 1,553 Agreeableness* ,560 ,133 ,266 4,201 Neuroticism ,078 ,112 ,049 ,700

Note. These are standardized regression coefficients; *p<0.05

37

Appendix 3: Hierarchical regression model of Attitude towards CC


Step 1 0,219 0,048 Age -,153 ,045 -,211 -3,391 Gender ,064 ,138 ,029 ,462 Step 2 0,397 0,158 0,11 Age* -,16 ,051 -,221 -3,155 Gender -,03 ,14 -,013 -,212 Openness to Experience* ,323 ,127 ,158 2,544 Conscientiousness -,091 ,113 -,053 -,806 Extraversion ,136 ,104 ,083 1,298 Agreeableness* ,446 ,117 ,249 3,822 Neuroticism ,067 ,098 ,049 ,684

Note. These are standardized regression coefficients. *p<0.05

Appendix 4: Linear regression model of Intention to participate in CC


Step 1 ,312 ,097 Age -,244 ,052 -,287 -4,722 Gender ,205 ,158 ,079 1,297 Step 2 ,822 ,676 ,579 Age* -,104 ,032 -,122 -3,270 Gender ,146 ,095 ,056 1,543 Attitude towards CC* ,916 ,043 ,779 21,285

Note. These are standardized regression coefficients. *p<0.05.

38

Appendix 5: Mediation effect openness to experience

Consequent

Attitude towards CC (M)

Intention to participate in CC (Y)

Antecedent Coeff. SE p Coeff. SE p

Openness to experience (X) a1 ,515 ,123 ,000 c1' ,054 ,091 ,551

Attitude towards CC (M) --- --- --- b1 ,945 ,045 ,000

constant i1 3,484 0,468 ,000 i2 -,252 ,369 ,494

R2 = ,063 R2 = ,656

F(1,256) = 17,425; p < 0,001

F(2,255) = 243,554; p < 0,001

Effect SE p Direct effect c1' ,0543 ,091 ,551 Total effect c1 ,541 ,146 ,000

Boot SE Boot LLCI

Boot ULCI

39

Indirect effect a1b1 ,486 ,125 ,246 ,729

Appendix 6: Mediation effect conscientiousness

Consequent




Conscientiousness (X) a1 -,119 ,108 ,268 c1' -,182 ,074 ,014


constant i1 5,859 ,401 ,000 i2 ,621 ,371 ,096

R2 = ,005 R2 = ,664

F(1,256) = 1,229; p < ,268

F(2,255) = 251,834; p < 0,001

Effect SE p Direct effect c1' -,182 ,074 ,014 Total effect c1 -,296 ,126 ,019

Boot SE Boot LLCI

Boot ULCI

40

Indirect effect a1b1 -,113 ,106 -,329 ,089

Appendix 7: Mediation effect extraversion

Consequent




Extraversion (X) a1 ,237 ,101 ,020 c1' ,047 ,071 ,507


constant i1 4,543 ,381 ,000 i2 -,237 ,332 ,474

R2 = ,064 R2 = ,656

F(1,256) = 5,471; p < ,05

F(2,255) = 243,678; p < 0,001


Boot SE Boot LLCI

Boot ULCI

41


Appendix 8: Mediation effect agreeableness

Consequent




Agreeableness (X) a1 ,381 ,109 ,001 c1' ,057 ,079 ,469


constant i1 3,952 ,426 ,000 i2 -,268 ,348 ,441

R2 = ,045 R2 = ,6566

F(1,256) = 12,188; p < 0,001

F(2,255) = 243,803; p < 0,001


Boot SE Boot LLCI

Boot ULCI

42


Appendix 9: Mediation effect neuroticism

Consequent




Neuroticism (X) a1 ,048 ,084 ,573 c1' ,094 ,058 ,108


constant i1 5,295 ,232 ,000 i2 -,318 ,278 ,254

R2 = ,064 R2 = ,656

F(1,256) = ,319; p < ,573

F(2,255) = 246,824; p < 0,001


Boot SE Boot LLCI

Boot ULCI

43

Indirect effect a1b1 ,045 ,079 -,109 ,206

Appendix 10: Moderating mediation

Variable DV = Attitude towards CC DV = Intention to participate in CC Constant 7,258 -0,318 Independent variables Neuroticism -0,472 0,094 Attitude towards CC 0,949 Lack of technology efficacy -1,029 Interaction neuroticism x lack of technology efficacy 0,273 R2 0,060 0,659 F-Value 5,436 246,824

Documents

Personality as a predictor of Collaborative Consumption usage