Final Version IPA Paper Reference 38

8/10/2019 Final Version IPA Paper Reference 38

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THE LEVERS OF CONTROL FRAMEWORK IN SHIPPING COMPANIES: A

MIXED METHODS APPROACH

Androniki Triantafylli

Manchester Business School

The University of Manchester


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INVESTIGATION OF THE LEVER OF CONTROL FRAMEWORK IN

SERVICES ORGANIZATIONS

Abstract

The paper explores the relationship among control systems, their antecedents and their

outcomes. By employing Simons levers of control (1995), the paper tries to

investigate the contextual variables that underlie the dynamic nature of control

systems in the context of the maritime industry. The paper tries to reply to repeated

calls for validating empirical research by combining qualitative and quantitative

methods and thus it is using data from semi-structured interviews and responses to a

survey questionnaire. The findings indicate the importance of a number of factors

perceptions of competition, cyclicality of industry, cost consciousness, managementpractices, market pressures- that impact on the validity of the LOC framework in the

context of shipping companies. The results from this study offer an elaboration of the

efficient use of the LOC framework into the specific maritime context.

Key Words: Mixed methods approach, Levers of Control Framework, shipping

industry, contextual variables


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1.

Introduction

IntroductionIn recent years the LOC framework has been extensively examined with the majority

of studies incorporating qualitative approaches (Mundy, 2010; Henri, 2006;)

However, a number of calls for a complementary approach relying on method

triangulation combining quantitative and qualitative methods has been made (Modell,

2005; Brewer and Hunter, 1989; Lindsay, 1995)Simons framework is a useful analytical tool to explore the concepts of the dynamic

tension and balance concerned with different uses of MCS (Mundy, 2010). Simons

research programme (1987a, 1987b, 1990, 1991, 1994) gradually extended and

refined theoretical explanations of senior managers uses of control systems (Modell,

2005).

Many researchers have explored the validity of Simons arguments under different

contexts (Tuomela, 2005; Henri, 2006; Merchant & Otley, 2006; Marginson, 2002;

Kloot, 1997), however most of the studies assume a qualitative research method and

as a result they are difficult generalizable or focus on particular constructs of the LOC

framework instead of adopting a more holistic approach (Mundy, 2010; Henri, 2006

etc). Simons LOC framework was not subjected to survey based tests until the work

of Widener (2007). Widener (2007) has provided a systematic attempt to follow up

Simons stream of research. Her work is the first attempt to generalize the use of the

holistic levers of control framework in a sample of 122 U.S firms by using an

extensive survey instrument. Her work extends Simons framework by emphasizingthe complimentarity of the interrelations among the different levers of control and by

mentioning the costs and benefits associated with the use of the LOC framework in

the companies under study.

The aims of this paper are to explore how the holistic levers of control framework as

presented by Simons (1994) and applied by Widener (2007) is implemented into the

context of a specific service industry- shipping- and how this implementation is

affected by the contextual variables underlying this industry. The paper tries to

respond to repeated calls in the literature for the need of a mixed method approach tothe investigation of the LOC framework by encompassing a combined replication and

theory extension logic (Eisenhardt, 1989; Tsang & Kwan, 1999; Modell, 2005). As a

result, the current study incorporates a survey instrument based on S. Wideners

(2007) pretested questionnaire coupled with a series of interviews from senior

managers in the industry


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although scientific knowledge of reality is never infallible, it is possible to acquire

such knowledge through creative construction and critical testing of theories i.e.

replication (Tsang & Kwan, 1999). This fallibility of social sciences research makesreplication even more desirable (Tsang & Kwan, 1999).

The remainder of the paper is structured as follows. The next part presents the

literature review and the development of the hypotheses tested, followed by the

discussion of the research design and the methods employed for this study. Part 4

announces the results whereas part 5 discusses the main findings of the research.

Finally, part 6 includes the conclusions, limitations and extensions of this study.

2. Literature Review and Hypothesis Development

The Levers of Control Framework

Simons (1994, 2000) stated that control of business strategy is achieved by

integrating the four levers of beliefs systems, boundary systems, diagnostic controlsystems, and interactive control systems. The power of these levers in implementing

strategy does not lie in how each one is used alone but rather in how they

complement each other when used together. The interplay of positive and negative

forces creates a dynamic tension between opportunistic innovation and predictable

goal achievement that is necessary to stimulate and control profitable growth. Two of

the control systems- beliefs systems and interactive control systems motivate

organizational participants to search creatively and expand opportunity space. These

systems enhance intrinsic motivation by creating a positive informationalenvironment that encourages information sharing and learning. The other two

systems- boundary systems and diagnostic control systems- are used to constrain

search behaviour and allocate scarce attention. These systems rely on extrinsic

motivation by providing explicit goals, formula- based rewards, and clear limits to

opportunity seeking. The LOC framework also asserts that strategic uncertainty and

risk drive the choice and use of control systems, which in turn impact the

organization through organizational learning and the efficient use of management

attention (Simons, 2000).

The Relationship between Risks and Uncertainties and the LOC framework

Management control systems are designed according to the environmental risks and


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Empirical evidence suggests that both beliefs and boundary systems are beneficial in

managing both strategic risks and uncertainties. Simons (1994) claims that for

organizations facing strategic change the beliefs system is important for

communicating the vision and core values while the boundary system shows the

appropriate areas for pursuing opportunities. Merchant (1990) finds that boundary and

beliefs systems are intended to counteract undesirable behaviour in periods of

strategic uncertainty.

Organizations use diagnostic control systems to manage both strategic uncertainty and

risk (Galbraith, 1973; Simons, 2000; Widener, 2007). Performance measurementsystems embedded in a diagnostic control system help assure that employees

behaviours are aligned with organizational goals. Moreover, information is spread

throughout the organization by the provision of exception reporting (Widener, 2000).

In order to use a performance measurement system diagnostically it must be possibly

to set a goal, measure outputs and compute variance (Galbraith, 1973). Shipping

companies may decide to use performance measures according to factors such as

safety and quality in a diagnostic way in order to look for exceptions and gather

feedback information.

On the other hand, measures of new technology, freight levels and market trends have

greater variation and contain more noise. These measures are not that stable and

routine in order to be used diagnostically. Top management decides to use them in an

interactive way in order to facilitate discussion and emergence of new ideas

throughout the company. Empirical evidence suggests that interactive systems are

effective in companies facing high degrees of innovation risk and uncertainty (Bisbe

& Otley, 2004) or uncertainties related to product introductions, and market

competitions (Simons, 1991).

As a result, the previous discussion leads to the formulation of the first group of

hypotheses tested in this paper:

Hypotheses Group A:

HA1: The extent to which firms face strategic risks and uncertainties is positively

associated with the emphasis they place on a belief system


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levers work as negative forces to constraint undesirable behavior, to ensure

compliance with organizational objectives and to limit the explorations of the

employees. Boundary systems are necessary for the organizations survival and are

implied especially for the shipping companies by the International Maritime

Organizations regulations and the national law. For instance, the company should

establish procedures to ensure that new personnel and personnel transferred to

assignments related to safety and protection of the environment are given proper

familiarization with their duties. Also boundary systems are legally required by both

stock exchanges and the enactment of Sarbanes-Oxley Act; and called for byshareholder and stakeholder groups (Paine et al., 2005) As a result, since shipping

companies are obliged legally to implement a boundary system, they need to rely on a

diagnostic system as well in order to maintain the necessary balance needed for the

control structure.

Interactive controls provide managers with a mechanism to learn of new strategic

opportunities. As a result, objectives and critical success factors need to be redefined

and conveyed throughout the organization by using diagnostic control systems.

Simons (2000) proposes that the diagnostic system is used to communicate the

strategy that emerges through an interactive system. Within the LOC framework, the

suggestion is that the interactive use of performance measures influences the

diagnostic use of performance measures since the latter provides the necessary

structure that enables the interactive system to be effective.

A recent stream of literature has yielded valuable insights into the concept of dynamic

tension, including how it arises from the inherent conflict between controlling and

enabling uses (Marginson, 2002; Simons, 1995; Mundy, 2010); how it influences

unique organizational capabilities and performance (Henri, 2006b; Widener, 2007);

and how organizations deal with challenges associated with its development and

management (Floe, Marginson & Ogden, 2005; Marginson, 2002). Dynamic tensions

arising from the interrelations between the levers of control facilitate the developmentof organizational capabilities such as innovativeness, organizational learning,

entrepreneurship, and market orientation that together contribute to organizational

performance (Henri, 2006b; Mundy, 2010). The tension is dynamic because there are

continual and varied strategic forces acting both internally and externally that disturb

h l i h i f h diff l (B i l 2004 H i 2006b) Th


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Hypotheses Group B:

Hypothesis B1: The emphasis shipping companies place on the beliefs system ispositively associated with the emphasis they place on a boundary system.

Hypothesis B2: The emphasis shipping companies place on the beliefs system is

positively associated with the emphasis they place on the use of performance

measures in a diagnostic control system.

Hypothesis B3: The emphasis shipping companies place on the beliefs system is

positively associated with the emphasis they place on the use of performancemeasures in an interactive control system.

Hypothesis B4: The emphasis firms place on the boundary system is positively

associated with the emphasis they place on the diagnostic control system.

Hypothesis B5: The emphasis shipping companies place on the use of performance

measures in an interactive control system is positively associated with the emphasis

they place on the use of performance measures in a diagnostic control system.

Cost and Benefits from the Use of the LOC framework

The inter-dependence of the four control systems has some costs and benefits for the

companies; costs in terms of management attention and benefits in terms of

organizational learning (Simons, 1994; Widener, 2007).Simons (1994) found that after undertaking a strategic turn around, managers issue

new mission and vision statements to communicate ideas and information to

employees. The firm develops the new routines (i.e. boundary systems) based on its

experience. Marginson (2002) concluded that beliefs systems lead to new ideas

whereas boundary systems lead to a search for innovation through the prescribed

acceptable domain. Widener (2007) found that firms emphasizing beliefs systems and

diagnostic systems are more amenable to learning. Diagnostic controls communicate

agendas and translate strategy into actions by communicating critical success factors

(Simons, 1994). Interactive systems are intended to engage managers in scanning and

seeking behavior that may result in emergent strategy (i.e. new behaviors and

experiences) As a consequence interactive systems help managers handle situations


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Hypotheses Group C

Hypothesis C1: The emphasis shipping companies place on a beliefs system, ispositively associated with an organizations orientation to learning.

Hypothesis C2: The emphasis shipping companies place on a on a boundary system,

is positively associated with an organizations orientation to learning.

Hypothesis C3: The emphasis shipping companies place on the use of performance

measures in a diagnostic control system, is positively associated with an

organizations orientation to learning.

Hypothesis C4: The emphasis shipping companies place on the use of performance

measures in an interactive control system, is positively associated with an

organizations orientation to learning.

Management attention constitutes a significant but limited resource in an

organization. Monitoring multiple control systems can require tremendous managerial

attention, thus top management has to choose where to focus its attention. Simons

(2000) suggests that reliance on beliefs, boundary and diagnostic systems can lead to

the efficient use of management attention. Beliefs systems can motivate employees

(i.e. explore new technology, entry in new markets, sign contracts with new cargo

owners etc), boundary systems are used to define limits of acceptable behavior (i.e.

verify accordance with the I.S.M Code and other regulations for safe operations of

vessels) and diagnostic control systems identify critical success factors by working onan exceptional basis (i.e. emphasis is put on cost reduction or on the adoption of a

new technology etc.). As a result, these three levers of control are concerned with

strategic issues that have a smaller information deficit. On the other hand, interactive

control systems are used to help top management deal with strategic uncertainties that

consume greater amounts of management attention because of the larger information

deficit they comprise (i.e. safety of operations as a strategic uncertainty, in cases

where one of companys vessels has suffered a severe marine accident).Consequently, I test the following hypotheses:

Hypotheses Group D

Hypothesis D1: The emphasis shipping companies place on a beliefs system is


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The performance implications of the LOC framework

Organizational learning is critical to maintaining competitive advantage in todaysglobal, competitive business world (Widener, 2007), and thus it leads to enhanced

delivery outcomes (Chenhall, 2005). Literature provides evidence that organizational

learning is positively associated with organizational performance. More specifically

Tippins & Sohi (2003), Chenhall (2005) and Chenhall & Langfield-Smith (2007)

provide evidence that organizational learning enhances delivery outcomes. On the

other hand, since managers are able to process a limited amount of information, an

environment characterized by an inefficient use of management attention will result inineffective managerial actions (Widener, 2007). Efficient use of management

attention leads managers to focus on firms critical issues and this leads to enhanced

organizational performance. Widener (2007) finds empirical evidence that the

efficient use of management attention leads to increased performance levels.

Empirical studies in both the management control and management literatures have

employed the framework to explain how organisations use their MCS to encourage

innovation and learning while simultaneously exerting control over how goals are

achieved (Abernethy & Brownell, 1999; Bisbe & Otley, 2004; Bonner, Ruekert &

Walker, 2002; Marginson, 2002; Tuomela, 2005). These suggestions lead the last

group of hypotheses tested in this paper:

Hypotheses Group E

Hypothesis E1: Orientation to learning is positively associated with firmperformance.

Hypothesis E2: Efficient use of management attention is positively associated with

firm performance.

3. Study design and method

The study responds to calls in the literature for mixed methods research that provides

insights into different uses of MCS and their interrelations (Modell, 2005). The

effectiveness of MCS is properly evaluated in terms of their combined effects,

requiring a holistic view of the controls used by organizations (Alvesson & Karreman,

2004 M d 2010) Thi id th bl i t d ith diff t d fi iti f


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3.1 Questionnaire Survey

Sample Choice

The population of firms targeted by this survey consists of all Greek-owned ocean-

going merchant marine shipping companies that own more than 4 ships each at the

time of study, a total of 200 companies. The shipping sector is an appropriate research

sample for several reasons. The levers of control are best explored in large

organizations because smaller firms can alter patterns of behavior through more

informal means (Simon, 1995; Mundy, 2010). Furthermore, the firms were largeenough to ensure that organizational and strategic variables apply (Miller & Otley,

1987) and to ensure that formal MCS are in place (Bouwens and Abernethy, 2000). In

addition, shipping companies operate in an industry known for its innovation and

capacity to respond quickly to new challenges, suggesting that their MCS are

influential in the attainment of its goals. Finally, shipping companies MCS are

comprehensive and systemic, and have been developed over a number of years from

its own global best practices. Companies were identified from the Greek Shipping

Publications 2007 database.2

Subsequently, data from a survey of top managers in 87 shipping companies have

been collected and used. Department and general managers were chosen as

respondents because they are aware of the firms MCS. In addition, they occupy a

position in which they have knowledge about strategic issues and other items asked

in the survey. English and Greek versions of the questionnaire were developed and

validated3.4 The questionnaire was pre-tested in two steps. First, three academicswere asked to revise the questionnaire. Three managers were subsequently

interviewed. They were asked to complete the questionnaire and provide comments

on its form and content. Minor adjustments were made in terms of wording and

presentation.

2Total Number of companies in Greek Shipping Publication Catalogue: 891

- Less Companies owning less than three vessels 487

- Less Foreign Companies operating in Greece 14

- Less Companies with Passenger Vessels, tugs and barges 175

- Less only Management Companies (not owners) 6

- Less non- ocean going fleet shipping companies 9


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After designing and pilot testing the questionnaire, it was sent to the targeted firms

along with an introductory letter directed to the managers5 of the company. The

introductory letter sent briefly described the motivation for the study and offered the

managers a copy of the results. This mailing was followed up with two rounds of e-

mails repeating the same information and at least five telephone calls. The

respondents had the option to complete the survey on line or on paper and even

through a telephone or face to face interview. Confidentiality was guaranteed to all

respondents.

Out of the 200 companies targeted, information was gathered from 93 companies, i.e.a response rate of 46,5%. In 28 cases, the survey was completed in face-to-face

interviews and as a result it was an opportunity to explore the reasoning behind the

respondents answers. After eliminating unsuitable responses, 87 of the completed

surveys were utilized in the analysis.6Table A provides the demographic data of the

sample. Panel A presents the general information about the sample, Panel B provides

information upon the position of the respondents to the questionnaire and Panel C

provides the statistics of the main constructs of the survey.

INSERT TABLE A AROUND HERE

In most cases the respondent was a top manager from one of the technical, operations

or finance departments of the firm. The age of the firms was between 2 and 110

years, averaging 24 years, and the average shipping company in the sample had 16

vessels. In order to analyze the potential presence of non-response bias, a two stepanalysis was conducted. First, respondents were compared with non-respondents in

terms of the sample characteristics size and age. Independent t-tests did not reveal

significant differences between respondents and non-respondents in terms of size and

age. Then, the main construct measures (latent variables)7 were checked for

dissimilarities between the immediate respondents and the respondents to the follow-

up surveys. Independent samples t-tests did not reveal differences. As a result, non-

response bias is not a major concern in this sample.

INSERT TABLE B AROUND HERE

Measurement of Variables


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breakdown in core internal business processes and impedes the firms ability to

implement its strategy (Simons, 2000). I measure operations risk through four survey

questions that ask respondents how critical the firms safety, quality, reliability, andefficiency of their operations are to organizational success. Competitive risk is the

risk inherent in the marketplace. The new entrants to the marketplace can pose

problems that make it difficult for a shipping firm to successfully create value and

remain competitive (Simons, 2000). I measure using two questions that capture ease

of entry to the industry and the extent to which competition is fragmented. This

measure presents some differences from the measure used by Widener (2007). The

initial measure by Widener included also questions about substitute products,

customers decision to switch costs, customers ability to set prices and the difficulty

of firms to change suppliers. After the initial interviews it became evident that these

questions were not relevant to the context in which shipping companies operate. The

prices of the services are set by the freight market so clients negotiating power is

limited. Clients can substitute companies if not satisfied with the service provided but

not the service itself because it is highly standardized. The current survey does not

take into account the asset impairment risk8as well, since no actual data (i.e. financial

statements) were available for the shipping companies. The exploratory factoranalysis reveals that the questions used to measure strategic risk load on two factors. I

label the first one operational risks since the four questions chosen ex ante to measure

operational risk load on factor 1. The next two questions related to competitive risk

ease of entry to the industry and nature of the competition load on the second factor

which I label Competitive Risks. Overall, the constructs capture 83% of the explained

variance. The Cronbachs Alpha for operational and competitive risk is 0.96 and 0.43,

respectively. Thus, the analysis uses two survey proxies for strategic risk, operational

risks and competitive risks.The following table indicates the main measurement information stemming from the

factor analysis:

INSERT TABLE 1 AROUND HERE

Strategic Uncertainties

Strategic uncertainties are uncertainties that top managers monitor to ensureorganizational goal achievement (Simons, 1990). Similar to strategic risk, I try and

measure a variety of types of strategic uncertainties by asking respondents to assess

the extent to which top managers monitor various uncertainties in order to ensure that

the goals of the firm are achieved. I include 10 different types of uncertainties in order

to capture uncertainties relevant across firms in the cross-section that may follow


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service industry and the unique characteristics of this service cannot be replicated by

adjacent industries. Overall, the constructs capture 80% of the explained variance.

The Cronbachs Alphas for the four factors are 0.76, 0.57, 0.87, and 0,80 respectively.The following table summarizes the measurement criteria and the factor analyses

results:


Control systems

This study is based on the LOC framework; therefore, I measure the extent firms

emphasize boundary, beliefs, diagnostic, and interactive controls (Simons, 2000;Widener, 2007). Boundary systems are the controls that reign in the workforce and

establish the out-of bounds for employee actions. I measure boundary systemsusing

four questions that ask respondents to indicate the organizations use of a code of

business conduct and systems that communicate areas/actions that should be avoided.

Beliefs systems are the controls that inspire the workforce to take desired actions. I

measure belief systems using four questions that assess the use of an organizational

mission statement and communication of core values. Factor analyses reveal thatboundary and belief are uni-dimensional with explained variance of 76% and 86%,

respectively. The Cronbachs Alphas are 0.89 and 0.95, respectively.

Diagnostic systems provide routine information to managers about key measures and

progress towards goals. In contrast, interactive systems require tremendous top

management involvement. Although firms may use many control systems either

interactively or diagnostically, this study investigates the use of the PM system for

two reasons. First, an effective PM system is viewed as being increasingly important

to the success of firms in todays competitive environment thus, in the cross-section,the PM system should be important across firms. Second, the results of this study can

contribute to a long stream of research on performance measures (see e.g., Ittner &

Larcker, 1998). I measure both diagnostic and interactive systems by using questions

and concepts from Henri (2006), Simons (2000), Kaplan and Norton (1996) and

Widener (2007). Since both sets of questions enquire about the PM system, I use an

exploratory factor analysis across all questions to ensure discriminant validity.

Fourteen questions about goals, monitoring, commonalities, and key success factorsload on factor 1, which I label diagnostic controls. Two questions that specifically

mention the involvement of top and/or operating managers load on factor 2, which I

label interactive controls. The distinguishing feature between diagnostic and

interactive systems is the involvement of top and operating managers. In this study,

interactive control corresponds to two of the properties having to do with the


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Costs, benefits and performance

Based on the discussion in Simons (2000) and Widener (2007) I measure management

attention using four questions that ask about the ability to focus attention, effectively

leverage time, reduce need for constant monitoring, and how the control system

impacts attention. Organizational learning is dependent upon whether the organization

has a culture that is suitable and enables learning (Galer& Van Der Heijden, 1992). I

use a previously validated scale (Henri, 2006; Hult & Thomas, 1998) comprised of

four questions to capture learning. Performance is measured using a previously

validated scale (Roth & Jackson, 1995). I ask the respondents to assess their

organizational performance relevant to their goals on four dimensions: overall,profitability, market share, and delivery system. I use this measure since it was

previously validated for both service and manufacturing firms. Perceived measures of

performance have been used due to the lack of actual data that did not allow for cross-

validation of the performance construct. Factor analysis reveals that the three

constructs are uni-dimensional and explain 68%, 67%, and 71% of the variance,

respectively. The Cronbachs Alphas are 0.85, 0.83, and 0.86, respectively.

The measurement of the variables dealing with the costs (management attention) and

the benefits (organizational learning) coming from the use of the LOC framework and

the measurement of the performance variable are listed below:


3.2 Field Interviews

This work relies heavily on data collected on the field. The field portion of the study

was designed to provide a rich understanding of the phenomena of interest and the

relevant context. Data were collected from primary resources in the form of semi-

structured interviews. The level of management selected for interview straddles the

strategic levels of the participating companies. The personal interview format allowed

the establishment of a rapport with managers and provided the opportunity to talk

about important issues concerning the design of MCS. Hypotheses that were derived

from the extant literature have been refined after a few field visits. Over prolonged

engagement with the field helped the development of familiarity which informed the

design of the hypotheses and the preparation of data9. Familiarity with the field and its

actors may enable the researcher to obtain or construct very rare, very detailed, or

otherwise remarkable kinds of data that may in turn be instrumental in refining the

i i i h i h i i i h i i


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through more informal means (Simons, 1995; Mundy, 2010). Also, this industry is

known for its innovation and capacity to respond quickly to new challenges,

suggesting that MCS are influential in the attainment of this goal. Shipping

companies formal MCS are systemic and comprehensive and have been developed

over a number of years. The factors outlined above suggest an interesting and

appropriate research environment in which to study the holistic levers of control

framework. The researcher did not have any previous relationship with any of the

companies participating in the interviews (i.e. previous employment etc). This

eliminates the potential for biases caused by lack of distance in interpreting events

(McCracken, 1988). Knowledge of the industry has been received through

participation of the researcher to a series of seminars and events relevant to the

regulatory framework underlying the industry. Moreover, the researcher has been

granted access to the MSc in Shipping (University of Piraeus) where she attended a

series of lectures concerning the operation of shipping companies, maritime

accounting and audit etc.

Data Sources

Field interviews have been used in association with survey results in order to provide

a multifaceted, richer picture of the LOC framework. The field study phase was an

important part of the research method. Knowledge gathered in the interviews resulted

in useful exploratory findings. It also allowed the tailoring of a firm- specific

questionnaire that improved prospects for success in the survey portion of the study.

Furthermore focusing on a single industry provides depth to the study and allows

controlling for several industry specific conditions- including regulations and

environmental conditions- factors that may be relevant to the introduction of MCS in

a company. The level of management selected for interview straddles the strategic

levels of the organization. Their goals derive directly from the organisations key

objectives and they use a range of MCS to manage the activities of their subordinates,

who are managers and other employees.

The qualitative part of this research was developed by using exploratory interviews

with thirty experts in the shipping industry. The interviews were largely semi-

structured10

and the interview guide was designed to provide highly focused

interviews with the participants, with an agreement to follow- up by phone if required.


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notions of the control systems, the triangulation of these with the interview data

collected from other parts of the organization allows the approach of some inter-

subjective understanding of the factors leading to the use of control systems. The

explanations offered by some survey respondents were also used for cross-validation

through comparisons with interview data where applicable. Where inconclusive or

unexpected survey findings emerged (i.e. the role of competition in the industry), the

interviews did provide a useful basis for advancing the internal validity of the

research (Modell, 2005) These unexpected survey findings may thus stimulate theory

extension by energizing the quest for refined or alternative theoretical explanations

(Jick, 1979; Modell, 2005). As a result, the qualitative analysis focuses on the

unexpected or differentiated results stemming from the survey part of the research.

The interviews were audio-taped and then transcribed verbatim and in full (Mc

Cracken, 1988). The length of their employment within the company under study

ranged from 2 to 18 years. The inclusion of several newcomers has the potential to

uncover practices that longer serving employees may take for granted (McKinnon,

1989; Mundy, 2010). A summary of the findings was presented to each participant for

comment and for correction of any factual errors.

As a final means of validation, we presented preliminary findings from the survey and

interview study at a meeting with a number of key participants from the shipping

companies. Follow up interviews with the survey participants also have helped to

clarify the importance on contextual factors on the use of the LOC framework.

4. Results

Quantitative findings

The partial least squares (PLS) approach to structural equation modelling (using

SmartPLS11

) was used to test these hypotheses. PLS is a component-based modellingtechnique that simultaneously examines theory (structural model) and measures

(measurement model). The advantages in using PLS are (a) its ability to handle

multiple exogenous and endogenous constructs at the same time, (b) its ability to

handle multicollinearity among endogenous constructs and (c) its ability to create


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analyzing the data collected. The sample size of 87 is consistent with the sample size

requirements for PLS (Chin & Newsted, 1999).

Since the distributional properties of estimates are unknown in PLS, the traditional

parametric- based technique for significance testing is not appropriate (Chin, 1998).

Instead, bootstrapping resampling12

procedures were used in this study to estimate the

significance of path coefficients in the model. Also, because PLS is distribution free,

overall model fit statistics such as those associated with covariance-based structural

equation modelling is not appropriate (Hulland, 1999). Consequently, the R2is used

to assess the stability of the model.13

The goodness- of-fit measure for the modeltested equals 0,59.

Although PLS simultaneously estimates parameters for the measurement and

structural models, the two models are analyzed and interpreted separately (Hulland,

1999). The measurement model is that component of the general model in which

latent variables are prescribed. Latent variables are unobserved variables implied by

the covariances among two or more indicators. Often referred to as factors, latentvariables are free of random error and uniqueness associated with their indicators. For

the model tested the latent variables are Operating Uncertainties, Competitive

Uncertainties, Technological Uncertainties, Strategic Risks, Competitive Risks,

Beliefs systems, Boundary systems, Diagnostic Control Systems, Interactive Control

Systems, Management Attention, Learning and Performance. The structural model is

that component of the general model that prescribes relations between latent variables

and observed variables that are not indicators of latent variables. The multipleregression model is a structural model without latent variables and limited to a single

outcome. When the measurement and structural components are combined, the result

is a comprehensive statistical model that can be used to evaluate relations among

variables that are free of measurement error (Hoyle, 1995).

Since Partial Least Squares model is comprised of the two models (measurement

model and structural model), their applications to the present study are separatelydiscussed below.

The measurement model

The measurement model evaluates the relationship between measures and constructs


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constructs. Most measures are above the 0.70 loading level, indicating that the

measures share more variance with their respective constructs than with error

variance (Table 7). All loadings are statistically significant at the 0.001 level (pvalues are one-tailed). The composite reliability for the constructs ranges from 0,77

to 1,10 (all higher than 0,70 level suggested by Nunnaly (1994)).

To establish the validity of the survey variables, both content and construct validity is

examined as suggested by Nunnally (1994). Content validity is assessed through (1) a

review of questions for face validity, (2) the process of variable construction, and (3)

the computation of an empirical measure of internal consistency. Construct validity isassessed through (1) the specification of an appropriate domain of observables

underlying the construct and using validated measures where possible, (2) factor

analyses, which reveals relations among the observables and support the uni-

dimensionality of constructs, (3) multiple questions loadings in excess of 0,70 in

support of convergent validity, and (4) lack of significant cross-loadings in support of

discriminant validity (Nunnaly, 1994).

In order to perform these assessments, several steps were taken. First, the existing

literature was reviewed thoroughly in order to establish appropriate domains of study.

For example, Simons research on the LOC framework and the research of subsequent

authors provided evidence for the variables used and the relations between variables.

Second, previously validated questions were used where appropriate. Third, the topic

was discussed with several managers from multiple departments of shipping

companies with the purpose of gaining more knowledge about the domain beingmeasured. Moreover, academicians along with shipping companies managers

reviewed the questions for face validity. Furthermore, empirical tests were conducted

(i.e. reviewed range of responses, calculated Cronbachs alpha for reliability, and

factor analyses) in order to establish both content and construct validity (Nunnally,

1994). As suggested by Nunnally (1994) factor analysis among other applications

may be used to determine:

Groupings or clusterings of variables

Which variables belong to each group and how strongly they belong

How many dimensions are needed to explain the relations between variables


20/50

Convergent validity is assessed using the average variance extracted (AVE). AVE

measures of 0,5 or more are considered to demonstrate adequate convergent validity

(Chin, 1998). The AVEs of all the constructs are more than 0,60, providing evidenceof adequate convergent validity.

Discriminant validity for the constructs is assessed by comparing the square roots of

AVEs to the correlation between constructs; providing an assessment of the extent to

which a construct shares more variance with its measures than with other constructs.

This is demonstrated in the correlation matrix in Table 6, Panel A, which includes

correlation among constructs in the off- diagonal and the square roots of AVE in thediagonal. The diagonal elements are all greater than their respective off-diagonal

elements, indicating adequate discriminant14

validity15

.

INSERT TABLE 6 ABOUT HERE


The structural model

The structural model was used in testing the hypothesized relationships between the

theoretical constructs as depicted in Figure 1. A summary of the path coefficients

(and their associated t-values) and the R2

s of the endogenous constructs are

presented in Table 8.



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5. Discussion

The relationship between strategic risks and uncertainties and the Levers of

Control Framework

Hypotheses group A predict that the extent to which shipping companies face

strategic risks and uncertainties is positively associated with the emphasis these

companies place on the beliefs, boundary, diagnostic and interactive control systems.

Results surprisingly contradict previous findings by Simons (2000) and Widener

(2007).Hypothesis A1 is partially supported. Beliefs systems are positively and

significantly associated with technological uncertainties and operating risks.

Boundary systems are positively associated with technological uncertainties and

operating risks but negatively associated with competitive uncertainties. Diagnostic

and interactive systems are both positively associated with technological

uncertainties.

Operational risks and uncertainties

The results of the survey partially support hypothesis A. Operational Risks16

and

Uncertainties17

are positively associated with the beliefs, boundaries and diagnostic

systems but negatively associated with the interactive control systems. Literature

suggests that operational risks and uncertainties are positively associated with the

performance measurement systems in an interactive control systems usually when the

companies face uncertainties related to innovation risk, product introduction and

market competition (Simons, 1991). However, the interviews reveal that shipping

companies face low degrees of innovation risk since the service provided is mostly

standardised. There are limited opportunities for service innovation apart from some

companies which did reveal that they occasionally offer tailored services to the cargo

owners. The priority of the shipping company is mostly to provide a safe and timely

service since these are the attributes that are highly evaluated from the market. Asstated by the operations manager of a dry-bulk company located in Athens:

I really cannot think of any way that would improve further the innovation of our

services. The type of service provided is standardised and the employment of vessels

is based on the quality of the service provided and that is synonymous to safety and


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In addition, the operational uncertainties that deal with the scale and scope effects are

not associated with the beliefs, boundary and interactive systems. This result stems

from the PLS analysis (Table 8). The nature of the business provides a possibleexplanation for this finding. Economies of scope are not relevant to shipping

companies since the vessels are usually designed to carry one type of product (i.e.

tankers vs. Dry bulk) and this cargo belongs to a single charterer. For the economies

of scale, the same logic prevails: if a shipping company wishes to increase its market

share, then it needs to proceed to serious investments (i.e. purchase of vessels,

purchase of equipment, hiring of staff, registration fees, insurance fees, etc), which

do not increase the capital expenditure. Thus, it seems to be expected that the scale

and scope effects are not instilled into the beliefs, the boundaries and the interactive

PMS of the shipping companies in this study.

Competitive Risks and Uncertainties

Competitive risks deal with the ease of entry for this particular industry and the

extent to which competition is fragmented. The PLS analysis reveal that competitiverisks are negatively associated with the beliefs and boundary systems of the

companies in the sample. The finding contradicts results from previous studies

(Widener, 2007; Simons, 1994)

The survey results reveal that there is a high degree of fragmentation of the

competition in shipping industry; there is a considerable amount of shipping

companies that own small shares in the market. The market targeted by shipping

companies is global and more specifically: every cargo owner around the world is a

potential new customer for us as revealed by the Finance Manager of a Tanker

company located in Athens. The capital intensity of the industry does not allow

shipping companies to expand to the degree that allow them to have a significantly

higher share in the market than their competitors. Moreover, the cyclicality of the

industry makes the management of the company reluctant to new investments and to

new markets.

The capital intensive character of the business and the cyclicality effect provide also

the reasons for the significant barriers to entry for new entrepreneurs in the shipping

market. The particularities of the market ranging from the definition of freights to the

increased regulatory framework and the international market make it particularly


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24/50

At the same time, the competitive uncertainties (i.e. market changes, competitors

tactics) constitute a significant part of the dynamic nature of the business. The upper

level management encourages innovative ideas from departmental managers and staffin order to enhance dialogue and collaboration in the business. For shipping

companies, that is translated as limited boundaries, since they want to give

employees the initiative to explore the market frequently and propose proactive

solutions. The CEO of a tanker company located in Peiraieus explains:

The monitoring of the change in the market and the behaviour of competitors form

part of our tracking system of market upheavals. The cyclicality effect keeps usconscious all the time and we encourage our employees to take proactive actions

when needed. Recently, our operations manager decided upon a different type of

charter party agreement for our fleet, due to the recent changes of our competitors

behaviour in the market.

Technological Uncertainties

Finally, PLS results conclude that technological uncertainties are positivelyassociated with all four levers of control. The results are in accordance with previous

research results stemming from Widener (2007). This category of uncertainties

includes the introduction of new technology and to the possible technological

changes that may occur.

The relationship among the four Levers of Control

Hypotheses B1, B2 and B3 test the existence of interrelations among beliefs systems

and the other three control systems, i.e. boundary systems, diagnostic controls and

interactive controls. PLS results confirm that the emphasis shipping companies place

on the beliefs system is positively associated with the emphasis they place on the

boundary system, the diagnostic system and the interactive system. These findings

are consistent with the argument that the beliefs system influences and complements

each of the other control systems in the LOC framework (Simons, 2000; Widener,

2007).

In addition, the interactive use of PMS was hypothesized to be positively related to

the diagnostic use of PMS (Hypothesis B5). This hypothesis is not supported since

the structural path coefficient is not statistically significant and not even at the


25/50

the industry operates. For instance, shipping companies track the freight rates

interactively, in the sense that they try to monitor closely the trends in the market.

Due to the cyclicality of the industry and the past experiences, the experts in thefreight markets are never sure what to expect. The market is very dynamic and

dependant on a number of internal and external factors ranging from the prices of

commodities to political reasons. However, the interactive use of the monitoring of

the freight rates does not necessary lead to their diagnostic use, simply because the

market is unpredictable. The experts cannot develop any learning capabilities due to

this dynamic environment that can allow them rely on diagnostic controls for this

issue. The Operations manager of a large tanker company located in Athens explains:

The monitoring of the freight markets is an intensive task and it has become even

more important due to the extended periods of recession that we have experienced

recently...The markets have become very dynamic recently and we cannot rely on a

report about the freight markets every month or every week... It requires a lot of our

attention. That is probably why we have partly outsourced this activity and we have

an ongoing collaboration with a large brokerage office in Piraeus... However, it is

very difficult to say that we have learned the freight market. Every recession happens

for a different reason. Most of the times they started quite unexpectedly which

justifies the need for regular monitoring of the markets.

The link between organizational learning and the Levers of Controls

Hypotheses group C predicted that all four control systems are positively associated

with organizational learning. The coefficients on the paths from Beliefs systems and

Diagnostic controls to Organizational Learning are significant and in the

hypothesized direction, thus providing support for Hypotheses C1 and C3. As

shipping companies place more emphasis on diagnostic uses of the PMS and the

beliefs system they have an organization more amenable to learning (Widener, 2007).

Simons (1990) suggests that the structure found in formal management control

systems facilitates organizational learning. However, PLS results imply a negativerelationship between interactive control systems and organisational learning. The

interactive control system may be more organic and influence organizational learning

through the formal structure of the diagnostic control system (Widener, 2007). In

order to understand this finding, I restricted the paths between the other control


26/50

area of interest, which may include a change in the way the market operates, a

regulatory change or a technological improvement. Shipping companies decide to

control those uncertainties interactively for a specified period in time; however, thisdoes not necessarily lead them to improve their learning since the underlying

assumptions upon which the changes lie may change dramatically in a short period of

time. On the other hand, for those procedures that seem to be stable over time, the

management decides to shift the control systems from an interactive use to a

diagnostic view. This shift signifies that the measure present less noise and more

stability and they can allow management and staff to implement diagnostic controls

that can improve learning over time. An example is provided by the Safety Manager

of a tanker company located in Peiraieus :

Before an audit is due from the I.S.M everybody is quite nervous...we try to collect

all the necessary documents and for about two months the safety department needs to

control intensively every activity of the other departments in order to ensure that they

fulfil the requirements of the I.S.M... After the first time we have gone through this

procedure we realised that the hard copies system for the collection of the reports

from the captains was too slow that did not allow the timely collection of the

documents. This fact, led to the introduction of an on line system for the collection of

the documents from the captains. Now, we do not have to chase the captains every

time we are due for audit, but instead the system notifies them aboutthe due dates for

the submission of their reports. On a monthly basis, we review the system in order to

check for any outstanding reports.The relationship between boundary systems and diagnostic systems is positive

meaning that shipping companies that rely on a boundary system need to rely at a

diagnostic system as well in order to maintain the necessary balance needed for the

control structure. An example is given by the safety manager of a tanker company

located in Piraeus:

In our company we implement strict safety rules. This is important in order toensure the efficiency of our services. The safety rules can include the non-alcohol

policy of the company on board, the responsibilities of the captain, the

responsibilities of the crew, the restriction of access to the machinery for the crew

etc. At the same time, we need to inspect regularly that employees abide by the safety


27/50

significant and at the hypothesized direction, providing support for hypothesis HD1.

Hypotheses HD2 and HD3 are not supported. The finding about boundary systems is

also consistent with Widener (2007). The efficient use of management attention islinked neither with boundary nor with diagnostic systems. Boundary systems for the

shipping companies are actually divided in two categories; the ones stemming from

the internal needs of the company and the ones that originate from the international

safety rules and regulations but they become embedded into the companys rules.

Since the environment upon shipping companies operate is dynamic, there are

continuous changes in the safety rules and regulations. These changes create the need

for the management of the company to try to adapt the boundary systems to the new

circumstances, thus leading to a not fully efficient use of management attention. In

addition, the overall changing environment of shipping companies does not always

allow for the diagnostic monitoring of the above mentioned control systems. As a

result, management attention n appears to have a negative relationship to diagnostic

control systems. This is also explained by the fact that both boundary and diagnostic

levers of control work as negative forces to constrain undesirable behaviour and toensure compliance with the organisational goals. Also, there is a positive relationship

between boundary and diagnostic control systems (Hypothesis B4).

Since boundary and diagnostic systems go hand in hand, it is obvious that diagnostic

control systems will not support learning for the same reasons.

Hypothesis HD4 predicted that the interactive use of PMS consumes management

attention. In other words, a cost of using an interactive control system is the use ofmanagement attention (Widener, 2007). The negative coefficient on the structural

path between Interactive systems and Management Attention provides support for

hypothesis HD4. Since interactive control system focuses organizational attention

and stimulates the emergence of new strategies over time, managers choose to use

not many systems interactively for economic reasons: interactive control systems

demand frequent management attention throughout the organization and, therefore,

exact high opportunity costs by diverting attention from other tasks. As it is

supported by the technical manager of a tanker company located in Athens:

A critical point in time for every management company is when the port state

authorities find a significant discrepancy in a vessel, and then the vessel is arrested...


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The relationship between the efficient use of management attention, learning and

performance

PLS results indicate a positive relationship between both organizational learning and

management attention with performance18

. However, the results are statistically

significant only for the case of organisational learning. Shipping companies make

significant investments for the training of their employees. Training may include

information about new trends in market, new technologies, the implementation of

new legislation etc. Through training, shipping companies try to compete effectively

in the highly competitive environment they survive and thus increase theirperformance.

The technical manager of a bulk carriers shipping company stated that: The key to

our success is learning. This may mean learning by doing or learning by training.

Our company focuses on both aspects of learning. We try to learn from our mistakes;

from the penalties from the port state controls; from an accident that happened in the

past. However we also try to train our personnel to the new trends in the shipping

markets; this involves training about new technologies, emerging markets, new

shipyards, compliance with new legislation, equip the personnel with the necessary

certificates etc. This is an ongoing process. It never stops if we want to experience

the trust of our charterers and the continuous hire of our vessels.

On the other hand, management attention seems to have a positive relationship only

with beliefs systems19

, but overall this leads to increased performance. Both Simons

(1995) and Widener (2007) have found that the efficient use of management attention

leads to increased performance. So, maritime companies need to use management

attention interactively if they wish to reap the benefits.

This also forms a part of the traditional operation of the upper level management in a

Greek shipping company.

In this point it is important to underline the importance of the structure of a typical

Greek maritime company. In most of the cases, Greek shipping companies are family

oriented, meaning that the upper level management is comprised from the founder/

owner and his close family. The lack of transparency in the financial results (as

explained before there are not formally issued statements) make the upper level


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approval from the owner himself and this applies for all the departments of the

company.Then, even if the ship owner is sick we have to visit him at home to get

the confirmation about emergency issues concerning claims and defectsTechnical Manager, Dry Bulk Company, Athens

This issue becomes definitely more important in large firms (firms that manage more

that 8 vessels) rather than in small management companies. The centralization of

decision making in maritime companies is a result of the long tradition of Greek

shipping companies that used to respond this way to the cyclicality of the industry.

The owner/founder used to be the person whose decisions could make a differencefor the viability of the company and who was the one to blame for in case of wrong

judgment. Moreover, the majority of the ship owners used funds for further

investments stemming either from their direct profits or from bank loans. Since the

industry is capital intensive and the funds needed for investments are high, ship

owners used to build long term relationships based on mutual trust with the bankers

in order to guarantee the financing of their projects. Therefore, they are feeling fully

responsible for the success of their business and the would like to control any aspect

of it as stated by the CEO of a large tanker company based in Athens. As a result,

they diffuse their attention on different aspects of the business simultaneously, but

overall this proves to be efficient in terms of performance. It leads to a centralised

decision making and monitoring structure that minimises distortion and it is

particularly useful in dealing with environments that present high levels of

uncertainty.

6. Concluding comments

The current study tries to validate the results of Simons (1995) Levers of Control in

the context of shipping companies by presenting the power of the contextual factors.

The paper employs a mixed method approach which allows to extend findings beyond

those observable using a single method, by identifying empirical contradictions that

might otherwise be missed (Denzin, 1978) and observing convergence in findings

from different strands of the research, thereby building confidence in the research

(Grafton, Lillis & Mahaba, 2011).

Th t t d t i t id l ti f th l ti hi t di d d th


30/50

reduction explain the interactive use of cost and market controls that shipping

companies employ. As a result, the contextual framework in which shipping

companies operate seems to have a strong impact on the validation of the LOCframework.

The current study contributes to a small but growing stream of research concerned

with the overall nature of the LOC framework and the relations between its various

elements. While recent studies have attempted to enhance our understanding of

individual levers, the current study underlies the importance of using the framework

in its entirety in order to gain a comprehensive understanding of the interface between

managers and MCS in their attempts to guide, direct and control organisational

capabilities (Mundy, 2010).

The results presented in this study contribute to the emerging literature in accounting

and control concerned with the interdependencies of control systems and their

implications in the context of service companies. By establishing the importance of

the interdependencies of control systems, this study calls for more work to deepen

our understandings of the trade-offs faced by service sectors companies whenimplementing MCS.

The study is subject to several potential limitations. First, the focus on a single

industry- shipping sector- rather than multiple industries may limit the generalizability

of the results, particularly with respect to service sector companies, since each sector

operates in a totally different environment (i.e. it is difficult to compare shipping

companies to hospitality companies or hospitals or the banking sector). Second,

ideally this study should have used real-time data, rather than relying on the

recollections of survey respondents, and should have employed triangulation (i.e.

more than one respondent per firm) to minimize memory biases and avoid that one

particular manager makes sense of the past. However, such study would have been

particularly costly and time consuming. Third, the study also presents potential

survival and self-selection biases. I partially mitigated survival biases by including

firms in the range from 2 to 110 years old and I tried to minimize the self-selectionproblem by increasing efforts to maximize the rate of response. Moreover, steps were

taken to ensure the reliability of the data (i.e. random sample, pre-test of survey

instrument, tests for construct and content validity). All diagnostic tests show that

there is no reason to expect bias (common method test non response bias) Also


31/50

to reduce observer bias and illusionary correlations by the need to match evidence

from multiple data sources and naturally test procedural reliability or reproducibility

through within study triangulation (Ihantola & Kihn, 2011).The findings of the study suggest avenues for further research on the relation

between controlling and enabling uses of MCS. The study derives a number of

factors that facilitate or hinder managers attempts to use the holistic LOC

framework. Further research is required to ascertain the extent to which these factors

are valid in other organisations, and to test formally the relation between the different

levers of control. In addition, social processes play a major role in the use of controls

(Marginson, 1999), suggesting further research into the effect of informal controls on

the use of MCS. The implications for information and communication infrastructures

that can facilitate the use of MCS remain unclear (Hartman & Vassen, 2003; Mundy,

2010). Finally, the study interviewed a single level of senior management in the

participative organisations. Future research could investigate how managers at

different levels attempt to use the LOC framework under the specified factors.A

natural extension of this study would be the selection of an interesting firm from therespondents and the investigation of the notions of MCS, strategy and

complementarity of control systems in more depth. In addition, it would underlie the

importance of different contextual factors that exist under specific settings.

Langfield- Smith (1997) suggests that this type of information would be beneficial to

researchers who employ contingency theory.


32/50

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Appendix: Variables Measurement

Strategic Risks

Safety of vessels

Quality of services

Reliability of servicesEfficiency of services

New industry entrants

Fragmented Market

Strategic Uncertainties

New Technology

Technological Changes

Competitorsmarket tactics


Changes

Diffusion of knowledge

Costs increase

Scale effectsScope effects

Services innovation

Belief Systems


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Performance Measurement

Progress towards goalsMonitor results

Compare outcomes

Review key measures

Enable discussion

Enable continuous debate

Enable common view

Tie organization together

Focus on common issues

Focus on critical success factors

Develop common vocabulary

Top managers pay day-to-day attention

Top managers interpret information

Operating managers frequently involvedTop managers pay little attention (RC)

Operating managers are involved infrequent (RC)

Organizational Learning

Learning is the key to improvement

Values include learning

No learning endangers our futureLearning is an investment

Management Attention

Focus attention

Effectively leverage time

Reduce need for constant monitoring

W/O control attention spread thinly

Performance

Overall organizational performance


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TABLE A - Sample Description

Panel A: Sample Selection

Number of shipping companies targeted 200

Number of respondents 93

(46,5%)

Less- Respondents not fitting the selection criteria:

Firms owning less than four vessels at the time of the

survey

6

Final Sample 87

Panel B: Position of the Respondents

Position of Respondents Number of Respondents Percentage of Respondents

Managing Director 10 10%

Technical Managers 16 16%

Operations Managers 18 18%

Safety Managers 15 15%

Fleet Managers 18 18%

Finance Managers 8 8%

Others 20 16 16%

Total Sample 10121

100%

20

Others include:Position of Respondents #of

Respondents

% of

Respondents

Claims and Insurance Managers 2 2%

Crew Managers 3 3%


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Panel C: Descriptive Statistics of the Sample (N=87)

Variable Mean Std Deviation Lower

Quartile

Median Upper

Quartile

Size (# Vessels) 12,64 16,34 0 10 110

Age (# Years of company) 26,92 21,47 2 22 128

Boundary Controls 3,30 1,15 2,43 3,50 4,00

Beliefs Controls 3,87 0,88 3,50 4,00 4,50

Diagnostic Controls 3,59 0,71 3,23 3,73 4,06

Interactive Controls 2,98 0,63 2,50 3,00 3,50

Attention 3,41 0,83 3,00 3,50 4,00

Learning 4,00 0,83 3,50 4,00 4,75

Performance 3,74 0,69 3,25 3,75 4,00

TABLE B - Non Response Bias

Panel A: Shipping Industry Composition

Mean for :

Variable Target

Companies

Sample

Companies

Difference in

means

T-test

(Pr>t)*

Wilcoxon

Test (Pr>z)*

Size (# Vessels) 12,35 12,64 -0,29 0,746 0,777

Age (# Years of

company)

30,54 26,92 -3,61 0,515 0,112


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TABLE C: Demographic Data

Panel A: Participants in the interviewPosition Number of

participants

Technical Managers 9

Finance Managers 7

Operations Managers 5

Safety Managers 4

Supply Managers 2

Chartering Managers 1

Crew Managers 1

Claims Managers 1

Total 30

Panel B: Statistics of the interviewees

Mean Range

Length of service in

company (years)

14,5 4-30

Length of time in current

position (years)

7,2 2-12

Interview duration(minutes) 92 82-105


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TABLE 1: Strategic Risks

TABLE 2: Strategic Uncertainties

Strategic Risk Measurement Criteria Cronbachs

alpha

Explained

Variance

Operations Risk 4 survey questions about:

Safety

Quality

Reliability

efficiency

0,96 83%

Competitors Risk 2 survey questions about:

assessment of customer

pressure

assessment of competitorspressure

0,73

Strategic Uncertainties Measurement criteria Cronbachs

alpha

Explained

Variance

Operating Uncertainties 1

Scale effects

Scope Effects

Service Innovation

0,76 80%

Operating Uncertainties 2 Diffusion of knowledge

Cost increase

0,66

Technological Uncertainties New technology

Technological Changes

0,80

Competitive Uncertainties

Competitors market tactics


Market change

0,87


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TABLE 3: Levers of Control

TABLE 4: Cost, Benefit and Performance Variables

Variables Measurement Cronbachs

alpha

Explained

Variance

Management

Attention

4 questions about:

Ability to focus attention

Effectively leverage time

Reduce need for constant monitoring

Control systems impact on attention

0,846 68%

Organizational

learning

Pre-tested questions : Hult & Thomas (1998);

Henri (2006); Widener (2007)

0,834 67%

Performance Pre-tested questions : Roth & Jackson (1995) 0,861 71%

LOC Framework Measurement Criteria Cronbachs

alpha

Explained

VarianceBeliefs Systems 4 questions about:

The use of an organizationalmission statement

Communication of core values

0,891 76%

Boundary Systems 4 questions about:

The organizations use of a code of

conduct The existence of systems that

communicate areas/actions to be

avoided

0,948 86%

Diagnostic Control

Systems

Pre-Validated questions used: Kaplan &

Norton (1996); Simons (2000); Henri

(2006); Widener (2007)

0,957 62%

Interactive Control

Systems

0,750


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TABLE 5 - Construct Validity

Belief Systems Factors (0,76)

Mission statement communicates values 0,808

Top managers communicate values 0,890

Workforce is aware of values 0,907

Mission statement inspires 0,883

Cronbachs alpha 0,891

Boundary Systems Factors (0,86)

Defines appropriate behaviour 0,916

Informs about off-limits behaviour 0,953

Communicate risks to be avoided 0,953

Workforce aware of code of conduct 0,897


Factors (0,62)

Performance Measurement Diagnostic Interactive

Progress towards goals 0,799 -0,027

Monitor results 0,751 -0,097

Compare outcomes 0,751 -0,083Review key measures 0,802 0,035

Enable discussion 0,810 0,142

Enable continuous debate 0,885 0,073

Enable common view 0,799 0,025

Tie organization together 0,794 0,073

Focus on common issues 0,780 -0,175

Focus on critical success factors 0,825 0,031Develop common vocabulary 0,786 0,031

Top managers pay day-to-day attention 0,687 0,022

Top managers interpret information 0,882 -0,029

O i f l i l d 0 812 0 112


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TABLE 5 (cont.)

Construct ValidityManagement Attention Factors (0,68)

Focus attention 0,833

Effectively leverage time 0,826

Reduce need for constant monitoring 0,842

W/O control attention spread thinly 0,810


Performance Factors (0,71)

Overall organizational performance 0,833

Overall organizational profitability 0,836

Relative market share 0,827

Overall productivity of the delivery syste 0,864


Strategic Uncertainties Factors (0,80)

Operational

Uncertainties (1)

Operational

Uncertainties (2)

Competitive

Uncertainties

Technologica

Uncertainties

New Technology -0,045 -0,115 -0,049 0,941

Technological changes 0,011 0,007 0,087 0,886

Competitor market tactics -0,130 0,060 0,901 0,146New industry entrants 0,110 -,026 0,842 -0,141

Change 0,021 0,017 0,898 0,044

Diffusion of knowledge -0,133 0,830 0,139 0,131

Costs increase 0,129 0,886 -0,083 -0,222

Scale effects 0,909 0,083 -0,168 0,121

Scope effects 0,793 -0,135 0,308 -0,198

Service innovation 0,527 0,081 -0,010 0,437

Cronbachs alpha 0,767 0,569 0,875 0,800

Strategic Risks Factors (0,83)


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46

TABLE 6 - Discriminant Validity

Panel A

Operational

Uncertaintie

Operatio

Uncertai

(2)

Competi

Uncertai

Technolo

Uncertain

Operati

Risks

Compet

Risks

Belief

Systems

Boundary

Systems

Diagnostic

Systems

Interactive

Systems

Organizat

Learning

Manageme

Attention

Performan

Operational

Uncertainties

0,6443

Operational

Uncertainties

0,1717 0,8209

Competitive

Uncertainties

0,2289 0,4664 0,8913

Technological

Uncertainties

0,1154 0,5556 0,3005 0,9145

OperationalRisks

-0,1367 0,2893 0,1074 0,6715 0,9402

Documents

Final Version IPA Paper Reference 38