The impact of organizational culture on contract management and performance: a dyadic approach

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The impact of organizational culture

on contract management and

performance: a dyadic approach

R.M. (Robert) van der Wielen - s2203669

University of Groningen

Faculty of Economics and Business

Nettelbosje 2

Groningen, 9747 AE

e-mail: r.m.van.der.wielen@student.rug.nl

Master Thesis

June 2016

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Acknowledgements

Without the help of a number of people, this thesis would have been a worthless piece of paper. First of all, I would like to thank my supervisors at the University of Groningen. Dr. Manda Broekhuis for her valuable feedback and her endless dedication. Dr. Martijn van der Steen for quickly recognizing the core message of my thesis and the challenging questions that resulted from that. And last, but certainly not least, I would like to thank drs. ing. Henk Faber. I wish him and his family all the best in these difficult times, and want to thank him for his contribution to this thesis.

Next to the supervisors at the University of Groningen, I would also like to thank Jan Willem Kootstra and Bart van Dillewijn for their valuable help and for the lots of fun we have had. I admire their openness in sharing information, their well-considered feedback and their willingness to help me graduate.

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Abstract

The aim of this study is to investigate the relationship between organizational culture, the adoption of governance mechanisms and contract performance outcome. Online survey results were collected of 54 contracts, evaluated by both the buyer and contractor. Hypotheses were tested through linear regression analyses and independent samples t-tests. The findings demonstrate that a communication and team orientation in culture positively influences the adoption of relational governance, and ultimately contract performance outcome. Moreover, this study confirms earlier views that organizational cultural similarity between buyer and contractor is not something to aspire, as it does not increase contract performance outcome. Related to this, it was found that contract performance outcome is higher when the contractor is more results or communication oriented than the buyer. This study leaves room for future research to further investigate the latter issue, and also to consider a configuration approach in analyzing the impact of organizational culture on the adoption of governance mechanisms and contract performance outcome.

Key words: organizational culture, contract performance outcome, relational governance, contractual

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1. Introduction

Outsourcing of services continues to grow and is on the agenda of many organizations (Wiengarten et al., 2013). When outsourcing services to suppliers, the performance of the buying organization becomes, to a certain extent, dependent on supplier performance (Lindgreen et al., 2013; Cao & Lumineau, 2015). Moreover, there is a risk that the supplier acts in a self-serving (i.e. opportunistic) manner (Handley & Angst, 2015; Vosselman & van der Meer-Kooistra, 2009). Organizations use contracts to reduce this risk (Bai et al., 2016; Tate et al., 2009). In a contract, the terms of the agreement between buyer and supplier are specified and can range from informal promises to formalized agreements (Schepker et al., 2014).

After a contract has been closed, the contract management phase starts (Broekhuis & Scholten, 2016; Van Weele, 2014a). In this phase, the relationship between buyer and supplier (called contractor in the remainder of this study) can be managed through relational and contractual governance (Cao & Lumineau, 2015; Poppo & Zenger, 2002). Relational governance refers to “the extent to which the relationship is governed by trust, flexibility, solidarity, information exchange, fairness, and informal rules and procedures” (Cao & Lumineau, 2015: 24). Contractual governance, on the other hand, refers to “the extent to which roles, obligations, responsibilities, contingency adaptation, and legal penalty are specified or well-detailed in formal agreements” (Cao & Lumineau, 2015: 24). Organizations seek for an appropriate ratio of adopted relational and contractual governance in managing their relationship (Cao et al., 2013; Kim & Choi, 2015).

Existing literature identifies several factors that influence the ratio of adopted relational and

contractual governance, such as the level of asset specificity (Poppo & Zenger, 2002), technological

uncertainty (Handley & Angst, 2015) and organizational culture (Beugelsdijk et al., 2006; Jarratt & O’Neill, 2002; Kirsch et al., 2002). This research focuses on the role of organizational culture, which expresses patterns of values and beliefs that are manifested in, among others, practices by organizational members (Denison, 1990; Pothukuchi et al., 2002). So far, it is not clear how organizational culture of buyer and contractor affects the ratio of adopted governance mechanisms to manage their relationship. This research investigates the impact of distinctive cultural orientations of buyer and contractor on the

ratio of adopted contractual and relational governance.

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7 2006; Schilke & Cook, 2015) and information sharing (Cao et al., 2015; McCarter et al., 2005). However, the existing literature is not complete. Many contractual and relational governance factors are not yet covered. Moreover, the reported linkages are scattered many around different studies. This research thus combines and enriches existing literature in considering the impact of organizational culture on the total package of contractual and relational governance factors.

Differences in cultural orientations between buyer and contractor could also affect the ratio of adopted governance mechanisms (Lavie et al., 2012). Additionally, these organizational cultural differences might impact contract performance outcome (see e.g. Pothukuchi et al., 2002; Beugelsdijk et al., 2009). Contract performance outcome is defined as 1) the satisfaction of buyer or contractor about quality and overall cost of the product or service, and as 2) the degree to which buyer or contractor act in accordance to the agreements made within and outside of the contract (see e.g. Cao & Lumineau, 2015). This research investigates also the impact of differences in distinct cultural orientations between buyer and contractor on the adoption of governance mechanisms and contract performance outcome. Thereby, a contribution to literature is made in two ways. Firstly, this research is the first to consider the impact of differences in distinct cultural orientations, whereas extant literature only considered their combination (see e.g. Beugelsdijk et al., 2009). Secondly, this research is the first to consider their impact on contract performance outcome, whereas previous research considered relationship or joint venture performance (see e.g. Pothukuchi et al., 2002; Beugelsdijk et al., 2009).

Organizational culture might also indirectly affect contract performance outcome, through the (mis)alignment of organizational culture and governance mechanisms (Barringer & Harrison, 2000; Handley & Angst, 2015; Youngdahl et al., 2010). Alignment indicates the extent to which buyer and contractor base their ratio of adopted governance mechanisms upon their organizational culture, to enhance contract performance. An example of alignment is adopting a high ratio of contractual governance (characterized by formal agreements) in a stability oriented environment (characterized by formal rules and procedures). In this case, the cultural values of stability orientation align with the characteristics of contractual governance. The alignment between governance and culture will help to increase contract performance (Handley & Angst, 2015).

In line with the above discussed issues, the following research question is formulated:

Does organizational culture influence the adoption of governance mechanisms and ultimately the contract performance outcome in buyer-supplier relationships?

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8 on the adoption of governance mechanisms and contract performance outcome. Lastly, a contribution is made to the governance alignment literature (e.g. Handley & Angst, 2015) by being the first study to consider organizational culture to align with governance.

This study makes a contribution to practice as well. Most managers tend to manage what they can see instead of what they cannot see, such as organizational culture (Gattorna, 2006). This study highlights the importance of managing organizational culture and provides clues to managers on how to set up contract management, by indicating which governance mechanisms and distinct cultural orientations are positively related to the performance of contracts.

The remainder of this study is organized as follows. In the next section, the main concepts of

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2. Literature review

This section presents the theoretical background of this research. Firstly, contractual and relational governance will be defined. Secondly, the six dimensions of organizational culture and their influence on the adoption of governance mechanisms will be discussed. Thirdly, organizational cultural difference will be linked to the adoption of governance mechanisms and to contract performance outcome. Lastly, theory concerning governance-culture alignment will be discussed.

2.1. Contractual and relational governance

Contracts can be managed through contractual and relational governance mechanisms (Cao & Lumineau, 2015; Poppo & Zenger, 2002; Rai et al., 2012). Both modes will be explained briefly. These explanations will be used to relate organizational culture to the adoption of contractual and relational governance.

2.1.1 Contractual governance

Contractual governance refers to “the extent to which roles, obligations, responsibilities, contingency adaptation, and legal penalty are specified or well-detailed in formal agreements” (Cao & Lumineau, 2015: 24). Contractual governance is also mentioned formal contract management (Li et al., 2010) or transactional governance (Broekhuis & Scholten, 2016; Lindgreen et al., 2013).

Contractual governance protects buyer and contractor against opportunism and conflict (Cao & Lumineau, 2015), and can improve clarity about the roles, responsibilities, and performance

expectations of buyer and contractor (Handley & Angst, 2015).The formal written rules can be used as

a guide in the relationship with another firm (Abdi & Aulakh, 2012) and reduce goal misalignment (Handley & Angst, 2015).

In general, literature defines three main contractual governance constructs (see e.g. Goo et al., 2009; Rai et al., 2012; Schepker et al., 2014). As most studies use different terminologies, it is decided to choose the terminology of Rai et al. (2012). Their first contractual governance construct is goal

expectations, which refers to the extent to which outsourcing objectives and goals have been agreed

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10 demand, or for adapting to environmental contingencies (Goo et al., 2009; Schepker et al., 2014). See Table 1 for an overview of the three contractual governance constructs and their definitions.

Written contracts cannot cover everything that happens in the contract management phase (Li et al., 2010). After all, the development of a fully specified contract is often impossible or impractical (Klein et al., 1978; Williamson, 1979), due to bounded rationality and uncertainty (Goo et al., 2009). There is a need to combine contractual governance with relational governance (Goo et al., 2009; Jayaraman et al., 2013; Liu et al., 2009), which will be explained in the next section.

2.1.2 Relational governance

Relational governance refers to “the extent to which the relationship is governed by trust, flexibility, solidarity, information exchange, fairness, and informal rules and procedures” (Cao & Lumineau, 2015: 24). Relational governance is also mentioned social control (Li et al., 2010) and relational mechanism (Jayaraman et al., 2013).

Relational governance can reduce partner opportunism (Cao & Lumineau, 2015), encourage desirable behavior (Dyer & Singh, 1998) and ensure fulfilment of obligations (Uzzi, 1997).

Uzzi’s (1997) categorization of relational governance has received significant attention in literature. He defined three key constructs of relational governance, being 1) information exchange, 2)

trust and 3) conflict resolution. The information that is exchanged includes strategy and profit margins,

as well as tacit information acquired through learning by doing (Uzzi, 1997). Information exchange enables the development of a shared understanding between buyer and contractor about needs, capabilities and performance (Rai et al., 2012). Besides information exchange, trust is also an important relational aspect (Griffith & Myers, 2005; Handley & Angst, 2015. Trust is conceptualized as the degree of expectation that the contract partner will act predictable, fulfill agreed obligations, and behave fairly even if opportunism is possible (Rai et al., 2012). Lastly, conflict resolution (or joint problem solving) is important as conflicts are inevitable (Goo et al., 2009; Rai et al., 2012). Conflict resolution can be defined as the extent of amicable agreement and joint resolution among contract partners in conflict situations. See Table 1 for an overview of the constructs and their definitions.

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11 Table 1. Contractual and relational governance constructs and definitions (source: Rai et al., 2012)

Mode and construct Definition

Contractual governance

Goal expectations The extent to which outsourcing objectives and goals

have been agreed to and explicitly included up front in the contract.

Activity expectations The degree of detailed and precisely defined service

levels in the contract.

Contractual flexibility The degree to which the contract enables quick and

easy adjustment to uncertainties and contingencies that emerge.

Relational governance

Information exchange The extent of proactive sharing or exchange of

meaningful and timely information between buyer and contractor.

Trust The degree of expectation that the contract partner

will act predictably, fulfill agreed obligations, and behave fairly even if opportunism is possible.

Conflict resolution The extent of amicable agreement and joint resolution

among contract partners in conflict situations.

2.2 Organizational culture and the adoption of contractual and relational

governance

In this section, the expected influence of organizational culture on the adoption of contractual and relational governance will be discussed. There is a general agreement among researchers that culture expresses patterns of values and beliefs that are manifested in, among others, practices by organizational members (Denison, 1990; Pothukuchi et al., 2002). Organizational culture is best being measured at the practices level (Cadden et al., 2013).

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12 orientation, stability orientation and team orientation. These dimensions are chosen for two main reasons. Firstly, the dimensions are reflecting organizational practices, which is the best level at which organizational culture can be best measured (Cadden et al., 2013). Secondly, the six dimensions of Beugelsdijk et al. (2006) cover a broad range of organizational cultural aspects. They provide a more complete picture of organizational culture than, for example, the competing value framework (CVF) (see e.g. Cao et al., 2015; Zu et al., 2010). The values and beliefs related to communication orientation and employee orientation are not well covered in the CVF, for example.

In the next section, each dimension and its relation to contractual or relational governance will be discussed. For an overview of the organizational culture dimensions and their short descriptions, see Table 2.

Table 2. Organizational cultural dimensions and descriptions

Organizational cultural dimension Description

Results orientation The extent to which competitiveness, goal

achievement, incentives and clarity of tasks are emphasized.

Employee orientation The extent to which employees are encouraged to be

fair, generous and tolerant.

Communication orientation The extent to which openness in communication,

information sharing and criticizing are emphasized.

Innovation orientation The extent to which employees are encouraged to take

risks and make proposals for change.

Stability orientation The extent to which rules, regulations and procedures

are emphasized.

Team orientation The extent to which cooperation, teamwork and

participation are emphasized.

2.2.1 Results orientation

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13 In a results oriented environment, there are high demands for employees concerning their results (Beugelsdijk et al., 2009). The use of incentives is emphasized (Cao et al., 2015), specific goals are used to motivate employees (Naor et al., 2008) and it is clear what tasks need to be done (Beugelsdijk et al., 2006). It is likely that in such environments, contracts contain a high degree of goal expectations that are related to roles and responsibilities, and that these contracts are managed through performance monitoring, measurement and incentives. Therefore, the following is hypothesized:

H1. The degree of results orientation in a buyer-supplier relationship is positively related to the

adoption of contractual governance in contract management.

2.2.2 Employee orientation

Employee orientation refers to a concern for people (Hofstede et al., 1990). One of the key indicators of employee orientation is that an organization has concern for personal problems of employees (Hofstede et al., 1990; Beugelsdijk et al., 2006). This dimension is similar to the humane orientation dimension of House et al. (2001), which refers to the degree to which organizations encourage and reward its employees for being fair and altruistic.

It is likely that in employee oriented environments, contract management is characterized by fairness and solidarity. Solidarity stimulates a joint approach to problem solving (Poppo & Zenger, 2002). Furthermore, employees in employee oriented environments are generous and very tolerant of mistakes (House et al., 2001). This is likely to have a positive influence on the extent of amicable agreement and joint resolution among contract partners in conflict situations. Therefore, the following hypothesis can be formulated:

H2. The degree of employee orientation in a buyer-supplier relationship is positively related to the

adoption of relational governance in contract management.

2.2.3 Communication orientation

Communication orientation stimulates participation and openness in communication (Christensen & Gordon, 1999). This orientation reflects whether managers and employees communicate well, share information and are able to openly criticize each other instead of resorting in self-defensive tactics (Beugelsdijk et al., 2006; Verbeke, 2000). It is likely that this orientation positively influences the extent of proactive sharing or exchange of meaningful and timely information between buyer and contractor, which is an important characteristic of relational governance (Cao & Lumineau, 2015). Therefore, the following can be hypothesized:

H3. The degree of communication orientation in a buyer-supplier relationship is positively related to

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2.2.4 Innovation orientation

Innovation orientation refers to the encouragement of taking risks and to innovate (Christensen & Gordon, 1999; O’Reilly et al., 1991). Employees are encouraged to make all kinds of proposals for change (Beugelsdijk et al., 2006). Change might force the buyer or contractor to adapt or modify an initial agreement (Poppo & Zhou, 2014). This requires flexibility, which is a characteristic of relational governance (Abdi & Aulakh, 2012; Cao & Lumineau, 2015). Firms with a strong focus on innovation will be more willing to collect information for future developments (Cao et al., 2015). It is likely that this orientation positively influences information exchange in managing the relationship between buyer and contractor. Therefore, the following hypothesis can be formulated:

H4. The degree of innovation orientation in a buyer-supplier relationship is positively related to the

adoption of relational governance in contract management.

2.2.5 Stability orientation

Stability orientation focuses on order, rules, and regulations (Deshpandé et al., 1993). Employees in stability oriented environments are used to following rules and regulations (Ruppel & Harrington, 2001) and effectiveness is represented by consistency and achievement of clearly stated goals (Deshpandé et al., 1993). Such an environment offers little or no encouragement for employees to participate in dealing with new problems and contingencies (Cao et al., 2015). Stability orientation has many similarities with the hierarchical culture (see e.g. Cao et al., 2015; Naor et al., 2008; Zu et al., 2010).

It is likely that in a stability oriented environment, contracts contain a high degree of goal expectations and activity expectations in terms of precise service levels and clearly defined roles and responsibilities. Employees are likely to prefer service level objectives to be clearly stated in formal agreements instead of having a lot of flexibility. Therefore, the following hypothesis can be formulated:

H5. The degree of stability orientation in a buyer-supplier relationship is positively to the adoption of

contractual governance in contract management.

2.2.6 Team orientation

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15 It is likely that in team oriented environments, contract management is characterized by shared decision making and joint problem solving. Therefore, the following hypothesis can be formulated:

H6. The degree of team orientation in a buyer-supplier relationship is positively related to the adoption

of relational governance in contract management.

2.2.7 Organizational cultural differences and the adoption of governance mechanisms

Handley and Angst (2015) indicated that cultural differences between buyer and contractor is a very interesting direction for research. Organizational cultural differences between the buyer and contractor might negatively impact the development of mutual trust, the exchange of information (Lavie et al., 2012), the empathy levels and solidarity between buyer and contractor (Beugelsdijk et al., 2009; Jap & Ganesan, 2000). Solidarity can be defined as a feeling that issues between buyer and contractor will be treated as joint concerns (Jap & Ganesan, 2000), which is an element of relational governance (Cao & Lumineau, 2015). Differences in organizational culture might lead to misunderstandings and conflicting communication methods (Cadden et al., 2013; Pothukuchi et al., 2002), which are likely to negatively influence the proactive sharing of information between buyer and contractor or joint resolution in conflict situations. Therefore, the following hypothesis can be formulated:

H7. Cultural differences between buyer and contractor are negatively related to the adoption of

relational governance in contract management.

2.2.8 Organizational culture and contract performance outcome

Governance alignment matters (Handley & Angst, 2015; Sampson, 2004). In this study, alignment indicates the extent to which buyer and contractor base their ratio of adopted governance mechanisms upon their organizational culture, to enhance contract performance. Alignment between the adopted governance mechanisms and the organizational culture of buyer and contractor is expected to have a positive effect on contract performance outcome (Handley & Angst, 2015). In contrast, misalignment between cultural values and governance mechanisms decreases contract performance outcome (Barringer & Harrison, 2000; Handley & Angst, 2015). An example of alignment is adopting a high ratio of contractual governance (characterized by formal agreements) in a stability oriented environment (characterized by formal rules and procedures). In this case, the cultural values of stability orientation align with the characteristics of relational governance, as a result of which relational governance is more effective. In such a situation, the buyer and contractor are more likely to act in accordance to the agreements made within and outside of the contract, compared to a situation of misalignment.

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16 of either relational or contractual governance, as hypothesized in the previous paragraphs. Therefore, the influence of the individual cultural orientations on contract performance outcome is mediated by the adoption of governance mechanisms. Contract performance is expected to increase by adopting contractual governance in a results or stability oriented environment, or by adopting relational governance in an employee, communication, innovation or team oriented environment. The following hypothesis can be formulated:

H8. The adoption of governance mechanisms mediates the impact of organizational culture on contract

performance outcome.

Organizational cultural differences may also directly influence contract performance. Common norms and values are considered to be important characteristics of successful partnerships (Ploetner & Ehret, 2006). For example, Pothukuchi et al. (2002) found that organizational cultural difference negatively affects satisfaction about the cooperation, trust, communication or commitment. Cultural differences can negatively impact operational effectiveness (Youngdahl et al., 2010). It is likely that organizational cultural differences negatively impact contract performance. Therefore, the following hypothesis can be formulated:

H9. Cultural differences between buyer and contractor are negatively related to contract performance

outcome.

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Figure 1. Conceptual model1

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3. Methodology

3.1 Sample and data collection procedure

The unit of analysis in this study is the contract between buyer and contractor. The sample was drawn from an existing database of the Operations department, and from contact information provided by the Heads of Departments of IT and Human Resources within one buyer firm. The sample consisted of 63 different contracts of the buyer firm with 62 different contractor firms. These contracts were managed by 29 employees of the buyer, who provided contact information of the main partner in managing the contract at the contractor firm. All contract managing employees at both buyer and contractor side were contacted either face-to-face or by phone to ask for and confirm their cooperation. Prior to sending the final version, the survey was pretested among four employees within the buyer firm and two employees within two contractor firms. Based on their feedback, modifications were made to increase precision and understandability in the wording of items and instructions.

The final survey link was distributed by e-mail. Data was collected through Qualtrics, an online survey tool. After a maximum of two reminders, dyadic data has been collected of 54 different contracts, evaluated by 27 different employees at the buyer side (a 93.1% response rate) and 54 employees at the contractor side (a 85.7% response rate). Table 3 presents an overview of these respondent’s job titles. Table 4 shows the number of contracts and descriptive statistics of contract size per department at the buyer firm.

Table 3. Titles of respondents

Buying firm respondents Contractor firm respondents

Title Number Percentage Title Number Percentage

Head of Department 3 11.1 Director 5 9.3

Focal point 7 25.9 Account manager 18 33.3

Engineer 9 33.3 Contract manager 4 7.4

Contract manager 2 7.4 Sales manager 5 9.3

Supplier manager 2 7.4 Service manager 4 7.4

Plant manager 1 3.7 Project manager 5 9.3

Other 3 11.1 Engineer 3 5.6

Other 10 18.5

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19 Table 4. Number of contracts and contract size, listed per department at the buyer firm

Contract size (€)

Department Respondents Contracts Mean S.D. Min. Max.

Operations 19 44 313,933 629,292 3,333 3,000,000

IT 5 7 3,064,286 2,295,778 200,000 6,000,000

Human Resources 3 3 293,333 159,478 110,000 400,000

Total 27 54 - - - -

3.2 Survey instrument

This research contains three main variables: 1) organizational culture, 2) adoption of governance mechanisms and 3) contract performance outcome. Each of these variables are operationalized. Existing measures were adopted. If necessary, the wording was adapted to fit the investigative context of this paper.

Organizational culture was measured using the instrument developed by Beugelsdijk et al.

(2006). The measurement items were evaluated on a seven-point Likert scale, ranging from “completely disagree (=1)” to “completely agree (=7)” (see Appendix A and B). Organizational cultural difference was measured by calculating the difference in scores of buyers and contractors on the six dimensions.

The extent to which buyer and contractor adopt contractual governance (CG) and relational

governance (RG) was measured with a twelve-item scale, adapted from Rai et al. (2012). The items

measuring contractual governance (CG1, CG2, CG3, CG4, CG5 and CG6) and relational governance (RG1, RG2, RG3, RG4, RG5 and RG6) can be found in Appendix A. As Handley and Angst (2015) also did, the items are worded in way that is familiar and clear to the respondents. The measurement items were scored on a seven-point Likert scale, ranging from “completely disagree (=1)” to “completely agree (=7)”.

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20 Table 5. Main constructs, measurement items and respondents

Construct Measurement items2 _Respondent

Results orientation (RO) RO1, RO2, RO3, RO4 Buyer & Contractor

Employee orientation (EO) EO1, EO2, EO3, EO4, EO5 Buyer & Contractor

Communication orientation (CO) CO1, CO2, CO3, CO4, CO5 Buyer & Contractor

Innovation orientation (IO) IO1, IO2, IO3 Buyer & Contractor

Stability orientation (SO) SO1, SO2, SO3 Buyer & Contractor

Team orientation (TO) TO1, TO2, TO3 Buyer & Contractor

Contractual governance (CG) CG1, CG2, CG3, CG4, CG5, CG6 Buyer

Relational governance (RG) RG1, RG2, RG3, RG4, RG5, RG6 Buyer

Contract performance outcome (CPO) CPO1, CPO2, CPO3, CPO4, CPO5 Buyer & Contractor

3.2.1 Control variables for the adoption of governance mechanisms

To control for possible effects of other factors on the adoption of contractual and relational governance, a number of control variables were taken into account. For an overview of the control variables, definitions and respondents, see Table 6.

Contractors are expected to rely more on contractual governance when asset specificity (AS) increases (Poppo & Zenger, 2002). Asset specificity refers to the degree to which assets are tailored to a specific process or task and cannot be easily reused outside of a contract with one buyer (Jayaraman et al., 2013). This control variable is measured with a four-item scale (AS1, AS2, AS3 and AS4) and can be found in Appendix B. The measurement items were evaluated on a five-point Likert scale, ranging from “completely disagree (=1)” to “completely agree (=5)”. Asset specificity was measured only from the perspective of the contractor, because the contractor has most knowledge to answer the statements.

High technological uncertainty (TU) makes it difficult for organizations to develop fully specified and complete contracts (Crocker & Reynolds, 1993; Williamson, 1979). Technological uncertainty refers to the rate and predictability with which the exchange environment of the contract is changing (Handley & Angst, 2015). This control variable is measured with a three-item scale (TU1, TU2 and TU3) and can be found in Appendix B. TU1 and TU2 were evaluated by a seven-point scale, ranging from “very slowly (=1)” to “very quickly (=7)”. TU3 was evaluated by a seven-point scale, ranging from “very easy to monitor (=1)” to “very difficult to monitor (=7)”. Technological uncertainty is only measured from the perspective of the contractor, because the contractor has most knowledge to answer these statements.

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21 The length of the relationship (LR) between the buyer and contractor is a key determinant of relational governance (Poppo & Zenger, 2002). This control variable is measured with a single-item scale (LR1), see Appendix A. This item is measured in number of years.

Contract size (CS) is also taken into account as a control variable. It can be expected that larger

contracts will generally receive more attention than smaller contracts. Contract size refers to the annual amount of money that is paid to the contractor (see CS1 in Appendix A). This question was answered by the buyer.

Another control variable is measurement difficulty (MD). Measurement difficulty refers to the extent to which the delivered service lends itself to reliable measurement of performance (Poppo & Zenger, 2002; Rai et al., 2012). Measurement difficulty positively influences contractual governance (Poppo & Zenger, 2002). This control variable is measured with a single-item scale (MD1) and can be found in Appendix A. This item was evaluated by a seven-point scale, ranging from “very difficult (=1)” to “very easy (=7)”, and is only measured from the perspective of the buyer, because the buyer has sufficient knowledge to answer this and a difference score does not make any sense.

Operational disruption risk (ODR) may contribute to the relative dependency of the buyer to

the contractor (Handley & Angst, 2015). Operational disruptions can be defined as unforeseen events that interfere with the normal flow of goods or materials (Ellis et al., 2010). This control variable is measured with a two-item scale (ODR1 and ODR2) and can be found in Appendix A. Operational disruption risk is only measured from the perspective of the buyer.

3.2.2 Control variables for contract performance outcome

Four of the control variables for relational and contractual governance will be also be used as control variables for contract performance outcome. Firstly, asset specificity (AS) is likely to increase contract performance outcome, as high asset specificity of contractor creates a lock-in situation (contractor dependent upon buyer) (Handley & Angst, 2015). As a result, the contractor is more likely to act in accordance to the agreements within and outside of the contract, which also increases the likelihood that the buyer is satisfied about the performance of the contract. Secondly, the length of the relationship (LR) might impact contract performance outcome as well. The lengthier the relationship, the more buyer and contractor know each other. This in turn increases the likelihood that contractor and buyer behave in accordance to the agreements within and outside the contract, which is likely to also increase satisfaction about performance. Thirdly, contract size (CS) is used as a control variable as larger contracts are expected to positively impact the likelihood that contractor and buyer behave in accordance to the contract. Lastly, technological uncertainty (TU) is positively related to contract completeness, which decreases the likelihood of the buyer or contractor to behave in accordance to the contract (Handley & Angst, 2015), and will likely negatively influence satisfaction about performance of the contract.

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22 For the same reasons as for asset specificity, this is likely to increase contract performance outcome. This control variable (SD1) was measured with a single item and with a seven-point scale, ranging from “very easy (=1)” to “very difficult (=7)”, see Appendix A.

Table 6. Overview of control variables, definitions and respondents

Control variable Definition Respondent

Asset specificity (AS) The degree to which assets are tailored to a specific Contractor

process or task and cannot be easily reused outside of a contract with one buyer (Jayaraman et al., 2013).

Technological The rate and predictability with which the exchange Contractor

uncertainty (TU) environment of the contract is changing

(Handley & Angst, 2015).

Length of the Number of years of doing business with a contractor Buyer

relationship (LR) as a buyer.

Contract size (CS) The annual amount of money that is paid to Buyer

the contractor by the buyer.

Measurement The extent to which the delivered service lends itself Buyer

difficulty (MD) to reliable measurement of performance

(Poppo & Zenger, 2002; Rai et al., 2012).

Operational disruption The risk of the occurrence of unforeseen events that Buyer

risk (ODR) interfere with the normal flow of goods or materials

(Ellis et al., 2010).

Switching difficulty (SD) The degree of difficulty to switch to an alternative Buyer

Contractor as a buyer.

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3.3 Data analysis

The data analysis was done in seven main steps. Firstly, exploratory factor analysis (EFA) was performed in combination with the Cronbach’s alfa scores to assess reliability and construct validity of each construct. Secondly, the resulting variables were tested for non-response bias through an independent samples t-test. Thirdly, the responses on organizational culture on the buyer side were averaged per department, taking into account the interclass correlation coefficients (ICC’s). Then, these averaged responses of the buyer and the responses of the contractor were summed, and the main variables were checked for normal distribution. Sixthly, the control variables of contract size (CS) and length of the relationship (LR) received scales. Finally, the suitable tests for the hypotheses were identified.

3.3.1 Exploratory factor analysis (EFA)

The possible existence of common method bias was tested through Harman’s one-factor test, one of the most widely used techniques by researchers (Podsakoff et al., 2003). One single factor accounted for 21.95% of the total variance for the buyer variables, and 15.81% of the total variance for the contractor variables. These two percentages are well below the threshold of 50%. Thus, common method bias was unlikely to be an issue in this study.

Before exploratory factor analysis could be performed, a number of items were recoded. These items are labelled with (R) in Appendix A and B. After recoding, construct validity was checked by means of an exploratory factor analysis (EFA) with varimax rotation. Cases with missing values were excluded listwise. Each measure a) should have a loading of greater than 0.5, b) should not have a loading of greater than 0.4 to more than one factor, and c) should load into the correct factor (Song et al., 2011).

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24 uncertainty all had Cronbach’s alpha values of over 0.60, which is considered by Beugelsdijk et al. (2006) as the conventional cutoff level. Considering this, and their high factor loadings, it was decided to retain these items and constructs.

Based on the factor analysis and the Cronbach’s alpha’s, a number of items were excluded from further analysis because they did not meet one or more criteria from Song et al. (2011). These items are CG4, CG5, CG6, RO3, CO1, IO3, TO3 and TU3. Furthermore, the variables of employee orientation (EO) and stability orientation (SO) were excluded from further analysis, as the Cronbach’s alfa of the items was too low (<0.4) (see Appendix C). These items also had many cross-loadings or loadings on the wrong factors. The items that were left were computed into appropriate variables by taking the averages.

3.3.2 Non-response bias

To check for possible non-response bias, differences in responses on the main variables between early and late respondents were tested (Armstrong & Overton, 1977). Therefore, the buyer respondents and contractor respondents were split into two groups: those that responded without a single reminder and those that responded after one or several reminders by email. Then, independent samples t-tests were performed to compare the responses of these two groups on the main variables, being RO, CO, IO, TO, RG, CG and CPO. The results of these t-tests can be found in Appendix D, and revealed that no significant differences existed between the two groups (at 95% significance level). Thus, it could be assumed that the respondents did not have any different views from the respondents, and non-response bias was unlikely to be an issue in this study.

3.3.3 Departments at the buyer side

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25 Table 7. First exploratory factor analysis results and Cronbach’s α

Construct Std. Loading

Results orientation (Cronbach’s α = .855)

(RO1) .922

(RO2) .859

(RO4) .789

Communication orientation (Cronbach’s α = .693)

(CO2) .829

(CO3) .693

(CO4) .691

(CO5) .564

Innovation orientation (Cronbach’s α = .698)

(IO1) .807

(IO2) .795

Team orientation (Cronbach’s α = .788)

(TO1) .886

(TO2) .837

Contract performance outcome (Cronbach’s α = .827)

(CPO1) .655

(CPO2) .687

(CPO3) .837

(CPO4) .820

(CPO5) .745

Total variance explained 69.5%

N 81

KMO (Kaiser-Meyer-Olkin measure of sampling adequacy) .65

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26 Table 8. Second exploratory factor analysis results and Cronbach’s α

Construct Std. Loading

Asset specificity (Cronbach’s α = .748)

(AS1) .720

(AS2) .770

(AS3) .763

(AS4) .703

Technological uncertainty (Cronbach’s α = .618)

(TU1) .786

(TU2) .859

Operational disruption risk (Cronbach’s α = .924)

(ODR1) .929

(ODR2) .930

Contractual governance (Cronbach’s α = .741)

(CG1) .891

(CG2) .848

(CG3) .732

Relational governance (Cronbach’s α = .897)

(RG1) .872 (RG2) .851 (RG3) .869 (RG4) .896 (RG5) .793 (RG6) .552

Total variance explained 73.6%

N 54

KMO (Kaiser-Meyer-Olkin measure of sampling adequacy) .67

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27

3.3.4 Combining scores of buyer and contractor

An average total score of RO, CO, IO and TO of buyer and contractor was calculated. This was done by summing up the individual scores on RO, CO, IO and TO of the contractor and the department scores of the buyer (as computed at 3.3.3), and divide by two. As a result, it was possible to test the hypotheses, which discuss the degree of total RO, CO, IO or TO in buyer-supplier relationships.

3.3.5 Normality tests

Prior to testing the hypotheses, the normality assumptions were checked for the main variables, being RO, CO, IO, TO, RG, CG and CPO. The skewness and kurtosis scores before the removal of outliers can be found in Appendix F. The skewness and kurtosis scores have to be in between -1.96 and 1.96 to assume data is normally distributed (Bai & Ng, 2005). As some of the scores exceeded these limits, potential outliers were detected through box-plots (see Appendix F). Extreme outliers – indicated with a star in the box plot (see Appendix F) – were removed. Due to the low sample size, one single extreme outlier can cause the data set to be not normally distributed. The extreme outliers were investigated and it was decided that these outliers did not contribute any value to this research, as they were stand-alone cases and did not reflect any relevant trend. The removals resulted in skewness and kurtosis scores within the required boundaries (see Appendix F). Thus, the hypotheses could be tested with linear regression analyses and independent samples t-tests (see section 3.3.7).

3.3.6 Scaling CS and LR

To be able to test the hypotheses through linear regression analysis, the variables of contract size (CS) and length of the relationship (LR) received interval scales (see Table 9 and 10).

Table 9. Scales of Length of the Relationship (LR)

Scale number Number of years Frequency

1 0-2 10

2 3-5 20

3 6-8 6

4 9-11 6

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28 Table 10. Scales of Contract Size (CS)

Scale number Number of euro’s Frequency

1 <100,000 25 2 100,000-199,999 4 3 200,000-299,999 5 4 300,000-399,999 2 5 >400,000 14 3.3.7 hypotheses testing

Due to the exclusion of employee orientation (EO) and stability orientation (SO), H2 and H5 were not tested. The remaining hypotheses were tested in SPSS. H1, H3, H4, H6 and H8 were tested through linear regression analyses. H7 and H9, which concern organizational cultural differences, were tested through independent samples t-tests.

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4. Results

In this section, the results of the linear regression analyses and independent samples t-tests will be presented. The descriptive statistics and bivariate correlations of the main variables can be found in Table 11. The items on contract performance outcome have been answered by both buyer and contractor. The answers of the contractor will be indicated by CCPO in the remainder of this study.

4.1 Organizational culture and the adoption of contractual and relational

governance

To test H1, H3, H4 and H6, linear regression analyses were performed between the organizational cultural dimensions that were left after factor analyses (RO, CO, IO and TO) and the two governance modes (CG and RG). The regression analyses involved a number of steps. After controlling for the control variables in step one, the main effects of RO, CO, IO and TO were added in step two to five. The results of the regression analyses can be found in Table 12.

The results show that results orientation does not significantly affect contractual governance (B = .28; p > .10). Thus, H1 was not supported. Communication orientation has a significant positive effect on relational governance (B = .73; p < .01). Therefore, H3 was supported. However, it turned out that communication orientation also relates positively to contractual governance (B = .59; p < .05). This was not hypothesized, but provides room for discussion. Innovation orientation was found to be related to relational governance (B = .56; p < .05). However, the R2_(.24)_{was not significant (p > .10) and therefore}

H4 was not supported. Lastly, a significant positive effect of team orientation on relational governance (B = .56; p < .05) was found, and H6 was therefore supported.

4.2 Organizational cultural differences and contract performance outcome

To test H9, the difference between the scores on RO, CO, IO and TO of the buyer and the scores of the contractors was calculated. This difference score was calculated in three ways:

1) The scores of the buyer were subtracted from the scores of the contractor, resulting in either negative or positive scores;

2) An absolute difference scores was defined, irrespective whether buyer or contractor scored higher or lower on an item; and

3) An overall difference score was calculated, which is the sum of the difference scores on RO, CO, IO and TO as calculated in steps 1) and 2).

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Table 11. Descriptive statistics and bivariate correlations

Variable Mean S.D. RO CO IO TO CG RG CPO CCPO

Results orientation (RO) 6.00 .29 1.00

Communication orientation (CO) 5.20 .47 -.03 1.00

Innovation orientation (IO) 5.51 .38 .05 .12 1.00

Team orientation (TO) 5.18 .50 .12 .61** .26 1.00

Contractual governance (CG) 5.73 .67 .12 .49** .11 .39** 1.00

Relational governance (RG) 5.41 .75 .07 .25 .20 .32* .25 1.00

Contract performance outcome (CPO) 3.74 .65 .17 .14 .05 .25 .05 .45** 1.00

Contractor contract performance outcome (CCPO) 4.09 .37 .27 -.36* .20 -.18 -.29* .09 .16 1.00

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31 Table 12. Results from the regression analyses on relational and contractual governance

Relational governance Contractual governance

Step Variables 1 2 3 4 5 1 2 3 4 5

Control variables

1 Length of relationship (LR) .09 .09 .15* .14 .10 .06 .05 .11 .10 .06

Contract size (CS) .09 .09 .09 .08 .10 .01 -.01 .01 .01 .02

Measurement difficulty (MD) .03 .02 .06 .09 .06 -.18** -.20** -.15* -.17* -.15*

Technological uncertainty (TU) .03 .03 -.13 .01 -.06 .25* .28** .12 .25* .20

Asset specificity (AS) .11 .12 .13 .16 .10 -.02 -.03 .00 -.01 -.04

Operational disruption risk (ODR) -.12* -.13* -.18*** -.14** -.16** .04 .05 -.01** .04 .02

Main effects

2 Results orientation (RO) .13 .28

3 Communication orientation (CO) .73*** .59**

4 Innovation orientation (IO) .56** .08

5 Team orientation (TO) .56** .33

R2 _.15 _.15 _{.30** .24} _.29** _.24* _.27* _{.34** .24} _.26*

∆ R2 _.15 _.15 _{.30** .24} _.29** _.24* _.27* _{.34** .24} _.26*

Adjusted R2 _.03 _-.00 _{.18** .10} _.17** _.12* _.13* _{.23** .10} _.13*

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To test H9, independent samples t-tests were performed. The results can be found in Table 13 to 17. These tables contain only the significant results.

Table 13. T-test of difference in results orientation (with the scores calculated in step 1)

More negative RO difference More positive RO difference

(n = 22) (n = 30) Mean

Variables Mean SD Mean SD Difference

CPO 4.00 0.60 3.56 0.64 .44**

CCPO 4.20 0.43 3.99 0.29 .21*3

*p < 0.10, **p < 0.05, ***p < 0.01

Table 14. T-test of difference in communication orientation (with the scores calculated in step 1) More negative CO difference More positive CO difference

(n = 27) (n = 25) Mean

CPO 3.90 0.64 3.58 0.65 .32*

*p < 0.10, **p < 0.05, ***p < 0.01

Tables 13 and 14 contain the results of the t-tests performed with the difference scores calculated in step 1. As stated before, the difference scores have been split into two groups, using the median value. For the results in Tables 13 and 14, this implies that the values below the median are more negative than the values above the median. For results orientation, the t-tests for CPO and CCPO were significant (see Table 13). For communication orientation, the t-test for CPO was significant (see Table 14). These results imply that contract performance outcome increases when the difference score on results and communication orientation becomes more negative. In other words, the more results or communication oriented a contractor is compared to the buyer, the higher will be the contract performance outcome. Table 15. T-test of difference in team orientation (with the scores calculated in step 2)

Low TO difference High TO difference

(n = 22) (n = 30) Mean

CPO 3.46 .63 3.95 .61 -.49***

CCPO 3.98 .45 4.15 .28 -.17*

*p < 0.10, **p < 0.05, ***p < 0.01

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33 Table 16. T-test of difference in results orientation (with the scores calculated in step 2)

Low RO difference High RO difference

(n = 26) (n = 26) Mean

CPO 3.52 .65 3.97 .60 -.45**

*p < 0.10, **p < 0.05, ***p < 0.01

Tables 15 and 16 provide the results of the t-tests between low and high absolute difference scores. For team orientation, the t-tests for both CPO and CCPO were significant (see Table 15). For results orientation, the t-test for CPO was significant (see Table 16). These results imply that a higher difference in results or team orientation between buyer and contractor leads to a higher contract performance outcome.

Table 17. T-test of overall cultural difference (sum of difference scores calculated at step 2)

Low overall difference High overall difference

(n = 25) (n = 27) Mean

CCPO 3.95 .30 4.20 .39 -.25**

*p < 0.10, **p < 0.05, ***p < 0.01

Finally, Table 17 provides the results of the t-tests between low and high overall (absolute) difference scores. In other words, it is the sum of the absolute differences scores of all cultural dimensions (RO, CO, IO and TO). The t-test for CCPO was found significant (see Table 17). This result suggests that a higher difference in organizational culture (for RO, CO, IO and TO) leads to a higher contract performance outcome.

The results in Table 13 to 17 do not support H9. Instead, the results in Tables 15, 16 and 17 show that a higher difference in organizational culture leads to a higher contract performance outcome. Furthermore, the results in Tables 13 and 14 indicate that the more results or communication oriented the contractor is compared to the buyer, the higher the contract performance.

4.3 Organizational cultural differences and the adoption of contractual and

relational governance

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34 Table 18. T-test of difference in results orientation (with the scores calculated in step 2)

Low RO difference High RO difference

(n = 26) (n = 26) Mean

RG 5.22 .77 5.65 .68 -.42**

*p < 0.10, **p < 0.05, ***p < 0.01

4.4 Governance-culture alignment and contract performance outcome

To test H8, the mediation effect of RG or CG in the relationship between organizational culture and contract performance outcome was tested. Prior to testing the mediation effect, a regression analysis was performed to test the effect of RG or CG on CPO and CCPO. For the results of these regression analyses, see Appendix G. The results show that contractual governance does not significantly affect CCPO, as the R2 _{value of the model is not significant (B = .16; p > .10). Similarly, relational governance}

does not significantly affect CCPO (B = .01; p > .10). For the regression analyses involving CPO, the results show that CG does not significantly affect CPO (B = .00; p > .10), whereas RG does (B = .45; p < .01).

An important pre-condition for testing mediation effects is that the independent variable (RO, CO, IO or TO) should relate significantly to the mediator (RG or CG) and that the mediator should significantly relate to the dependent variable (CPO or CCPO). Hence, from previous regression analyses (see Appendix G and Table 12), it could be concluded that it was possible to test a mediation effect for CO and TO on CPO, with RG as the mediator. The results of these tests are displayed in Table 19. Step 1 to 7 have been reported before (see section 4.1 and the previous paragraphs in this section), and will therefore not be explained here. Instead, the results of step 8 and 9 will be reported.

The results in Table 19 show that RG has a significant positive effect on CPO, controlling for CO (B = .48; p < .01). The Sobel test showed that the indirect effect is significant (Sobel z = 2.24; p < .05). Additionally, the results in Table 19 show that RG has a significant positive effect on CPO, controlling for TO (B = .39; p < .01). The Sobel test showed that the indirect effect is significant (Sobel

z = 1.93; p < .10). Thus, these results indicate that the relationship between TO or CO and CPO is fully

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Table 19. Results from regression analyses on mediation effect of RG and CG

Relational governance (RG) Contract performance outcome (CPO)

Step Predictor 1 2 3 4 5 6 7 8 9

Control variables

1/4 Length of relationship (LR) .09 .15* .10 .07 .08 .05 .03 .01 .02

Contract size (CS) .09 .09 .10 -.07 -.07 -.06 -.11* -.11** -.09

Measurement difficulty (MD) .03 .06 .06 - - - -

Technological uncertainty (TU) .03 -.14 -.06 .08 .04 .06 .05 .08 .04

Asset specificity (AS) .11 .13 .10 -.11 -.10 -.15 -.07 -.07 -.09

Operational disruption risk (ODR) -.12* -.18*** -.16** - - - -

Switching difficulty (SD) - - - -.03 -.04 -.06 -.01 .00 -.03

Main effects

2/5 Communication orientation (CO) - .73*** - - .20 - - -.16 -

3/6 Team orientation (TO) - - .56** - - .30 - - .14

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5. Discussion

Does organizational culture influence the adoption of governance mechanisms and ultimately the contract performance outcome in buyer-supplier relationships? To answer this research question, this study developed a model in which six organizational cultural dimensions of Beugelsdijk et al. (2006) influence contractual or relational governance, and ultimately contract performance outcome. The results are mixed. An overview of the hypotheses and the results can be seen in Table 20.

Table 20. Overview of hypotheses testing

Hypotheses Results

H1 Results orientation (+) → contractual governance Not supported

H3 Communication orientation (+) → relational governance Supported

H4 Innovation orientation (+) → relational governance Not supported

H6 Team orientation (+) → relational governance Supported

H7 Organizational cultural differences (–) → relational governance Not supported

H8 Organizational culture → adoption of governance

mechanisms → contract performance outcome Partly supported

H9 Organizational cultural differences (–) →

contract performance outcome Not supported

5.1 Organizational culture and the adoption of contractual and relational

governance

No support was found for H1, hypothesizing a positive relationship between results orientation and contractual governance. There could be several reasons for this. Firstly, the data on results orientation in this study have a low standard deviation, relative to e.g. communication or team orientation (see Table 11). This in combination with the low number of respondents could make it difficult to detect significant linear relationships. Secondly, a theoretical reason might be that focusing too much on results negatively impacts the patience and interest to develop clear long-term contractual agreements, just as it negatively impacts the patience and interest to develop long-term relationships (see e.g. Beugelsdijk et al., 2006). Buyer and contractor might focus too much on quickly closing the contract, to reap the short-term benefits of the agreements made.

H3 was not rejected, which indicates that communication orientation and relational governance are positively related. Moreover, communication orientation also positively influences contractual governance. This was not hypothesized. A reason might be that the willingness and ability to openly communicate, share information and criticize each other leads to clearer agreements and contracts, as

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37 communication orientation on both contractual and relational governance is in line with the view that communication is a basic requirement for cooperation in buyer-supplier relationships (see e.g. Prahinski & Benton, 2004; Chen & Paulraj, 2004). It should be noted, however, that due to the exclusion of three items in the factor analysis, contractual governance only reflects goal and activity expectations. Contractual flexibility was left out in the analysis. This limits the results, as the total package of contractual governance has not been covered.

No support was found for H4, hypothesizing a positive relationship between innovation

orientation and relational governance. This somewhat contrasts the findings of Beugelsdijk et al. (2006), who found a significant positive effect of innovation orientation on the sharing of information – an element of relational governance – with a partner. A reason for these contrasting findings could be the limited sample size of this study, compared to the study of Beugelsdijk et al. (2006). A theoretical reason might be that innovation orientation positively influences information sharing, but not conflict resolution or trust. For example, it could be that an innovation orientation leads more unpredictable behaviour of buyers or contractors, as they are constantly looking for new opportunities for their organization. A decreasing expectation that the partner will behave predictable will also decrease trust (Rai et al., 2012). Support was found for the positive relationship between team orientation and relational governance (H6). This is in line with the findings of Cao et al. (2015) and Zu et al. (2010), who already found a positive relationship between team orientation and the sharing of information, one element of relational governance. This study enriches their findings by showing that team orientation positively influences all relational governance factors, including trust, conflict resolution and information exchange (Rai et al., 2012).

5.2 Organizational cultural differences and the adoption of contractual and

relational governance

No support was found for the negative relationship between differences in organizational culture and relational governance (H7). Instead, the results suggest that a higher difference in results orientation leads to a higher degree of adoption of relational governance. A theoretical reason for this might be that more difference in results orientation is compensated by more communication and information exchange, in order to get to know each other’s norms and values and to make sure buyer and contractor are on the same page. A shared understanding of the differences in culture can increase trust (Beugelsdijk et al., 2009). Further theory development and research on this issue is needed.

5.3 Organizational cultural differences and contract performance outcome

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38 in line with Cadden et al. (2013), who found that organizational cultural similarity between buyer and contractor is not something to aspire, because it might not have the expected positive effects on the performance of a supply chain. This study contributes to the findings of Cadden et al. (2013) by proving the effects on contract performance outcome.

The results also show that the more results or communication oriented the contractor is compared to the buyer, the higher will be contract performance outcome. To the knowledge of the researcher, this has not been covered in literature before. A theoretical reason for the proven relationship might be that when a contractor is more willing or able to communicate and steer on results, it gives the impression to the buyer that it is motivated to make sure the contract performs well. This might lead to more trust and a certain goodwill to resolve conflicts in the interests of both partners, two elements of relational governance. In turn, relational governance enhances contract performance outcome, as is also clear from the results in section 4.4. The issue of a contractor being more results or communication oriented than the buyer is an interesting area for future research.

The impact of organizational culture on contract management and performance: a dyadic approach