21
Calculative Trust and Relational Trust in
Inter-Organizational Relationships
An empirical research on the effect of trust on relationship performance and the
influence of disclosing behavior and interdependence
Janet Drenth Master Accountancy
Faculty of Economics and Business University of Groningen Supervisor: A. Rehman Abbasi Co-assessor: dr. D.B. Veltrop 25-06-2018 Word count: 8307
Abstract
Little research has been done on empirically assessing different bases for trust in relation to the relationship performance of inter-organizational relationships (IORs). This study looks into two types of trust. First, calculative trust, based on rational calculations that consider whether complying with the organizational relationship outweighs the consequences of opportunistic behavior. Second, relational trust, based on prior expectations and beliefs that arose from past experience. The findings of this study demonstrate that both calculative trust and relational trust positively influence relationship performance, with relational trust showing a stronger effect on relationship performance compared to calculative trust. However, there are moderating effects. When firms have a positive disclosing behavior, relational trust is more effective in relation to the relationship performance. In contrast, when the level of disclosing behavior is low, calculative trust relates stronger to relationship performance. According to the interdependence between partners, this factor has a negative influence on the relationship between relational trust and relationship performance. The findings of this study suggest that managers should take external factors into consideration when focusing on different types of trust in IORs.
Keywords: trust, calculative approach, relational approach, disclosing behavior, interdependence, signaling, transaction cost economics, social exchange theory
Table of Contents
Chapter 1. Introduction ... 4
Chapter 2. Theoretical framework ... 7
Calculative trust and relational trust ... 7
Factors that influence trust in an IOR ... 8
Trust from an economic perspective ... 9
Trust from a sociological perspective ... 10
Moderating effect of disclosing behavior ... 11
Moderating effect of interdependence ... 13
Conceptual model ... 15
Chapter 3. Methodology ... 16
Sampling and data collection method ... 16
Measurement ... 16
Control variables ... 17
Data analysis ... 18
Regression model ... 19
Chapter 4. Analyses and results ... 20
Analyses ... 20
Descriptions and correlations ... 20
Results ... 22
Chapter 5. Discussion and conclusion ... 26
Reference list ... 31
Chapter 1 Introduction
Formations of inter-organizational relationships (IORs) have increased strongly since the 1980s and this is likely to continue (Nicolaou et al., 2011; Scheer et al., 2003; Parkhe, 1993; Anderson, 1990). IORs generate a certain value for firms that they cannot create on their own. A firm can choose to benefit from this created value for their own advantage or distribute the value among the partners in the IOR. This consideration results in much tension and causes trust between partners to be very important (Scheer et al., 2003). Trust is considered to make managers act fairly and make them more future-orientated, which allows firms to have the shared belief that, in the long-term, rewards are distributed fairly among partners (Claro and Claro, 2008). A lack of trust between partners is the most common reason for IOR failures (Nicolaou et al., 2011).
Most previous research studied trust as an aggregate aspect (Lewicki and Bunker, 1996; Kramer, 1999), but trust consists of different bases and the transactions in IORs rarely depend on only one source of trust (Scheer et al., 2003; Zaheer and Harris, 2006). This research focuses on two types of trust, namely calculative trust, which comes from an economic approach, and relational trust, which comes from a sociological approach. Both approaches to trust have their own characteristics (Poppo et al., 2016). Calculative trust considers rational calculations to be the base for trust within collaborations, a partner is only perceived as trustworthy when underlying economic calculations show that it would be in their best interest to act fairly (Schilke and Cook, 2015). Relational trust gives priority to trust from a more social argument. In this view, shared identity and shared values are seen as the main drive for trustworthiness (Hardin, 1992). A shared identity enables a party to trust their partner to act on its behalf (Lewicki and Bunker, 1996). Value congruence assures firms that their partners fully consider their interest (Long and Sitkin, 2006). To get a better understanding of the influences of different types of trust, this study examines the effectiveness of both types of trust in relation to the relationship performance according an IOR.
Previous research is done on these different types of trust, but these studies did not relate them to relationship performance. For example Poppo et al. (2016) studied calculative and relational trust, but limited their study to supplier performance. Schilke and Cook (2015) and Long and Sitkin (2006) researched the effectiveness of both types of trust, however, not in relation to the performance of an IOR.
Empirical literature proposes that the effectiveness of trust depends on external factors. However, previous research also suggests further research to examine which factors may stimulate and discourage the effectiveness of trust (Das and Rahman, 2010; Krishnan and Martin, 2006). This research contributes new findings to attempt to fill this gap in the existing literature. To achieve this, the moderating effects of two factors on the relationship between trust and relationship performance are studied. The first factor is firms’ disclosing behavior, meaning the degree to which partners voluntarily disclose information to each other. The motivation of firms to voluntarily disclose information is an interesting research topic. Previous research found that, unless there is an increase in mandatory requirements regarding revealing information, firms continue to disclose information voluntarily to their partners (Watson et al., 2002; Dumontier and Raffournier, 1998). Explanations as to why firms choose to enact on disclosing information and how it could add value are scarce (Alexy et al., 2013). This study focuses on the underlying reasons of companies in deciding to voluntarily disclose information and how this disclosing behavior may be of value to the relationship between trust and relationship performance. The second moderating factor is the interdependence between IORs. Empirical research concerning the relation between interdependence and relationship performance resulted in inconsistent findings and suggests further research on the effects of interdependence in different contexts (Buchanan, 1992; Kumar et al., 1995).
The findings of this study show that calculative trust and relational trust are both positive, but not equally related to relationship performance. Furthermore, when the level of disclosing behavior is high, the influence of relational trust on relationship performance differs from the influence of calculative trust on this performance. With interdependence as a moderating factor, relational trust is more effective on relationship performance than calculative trust. Some of the findings are in contrast with the expectations, which is explained in the discussion.
This study contributes to the existing literature in twofold. First, this study contributes to empirical research explaining the relationship between trust and relationship performance from two different perspectives of trust. Second, this study explicates how the effectiveness of both perspectives of trust is moderated by the factors of disclosing behavior and interdependence.
Practically, this study emphasizes the responsibility of managers in a relationship with business partners concerning their awareness, especially managers’ awareness in relation to different trust perspectives that might influence their behavior in the collaboration. Thereby, this research has implications for managers on how to act in partnerships with other companies. Furthermore, the influence of disclosing behavior and interdependence on the effectiveness of trust should get more attention, since this supports managers to achieve the best outcome from
their business relationships (Lewicki and Bunker, 1996). Therefore, this study contributes to the existing literature in answering the following two outstanding questions: how do calculative trust and relational trust influence the relationship performance in IORs? And how are these relationships influenced by the disclosing behavior of firms and the degree of interdependence between partners?
The remainder of this study is structured as follows. Chapter 2 describes the theoretical framework, consisting of a distinction between relational trust and calculative trust and an introduction to the moderating effects. In this chapter, the hypotheses, as illustrated in the conceptual model in figure 1 are substantiated with theoretical foundation. Chapter 3 contains the methodology used in this research, including the sampling and data collection, measurement instruments and reliability and validity concerns. In chapter 4, the analysis and results of this study are reported. Finally, chapter 5 consists of a discussion and conclusion, including research implications, managerial implications, limitations and suggestions for further research.
Chapter 2 Theoretical framework
This chapter starts with a further substantiation of the types of trust examined in this research, since various types of trust affect the relationship performance of an IOR differently. The different approaches of trust are explained using transactional cost economics theory and social exchange theory. After a further understanding of why different types of trust are important for managers in making decisions regarding the IOR, the influence of two external factors on the relationship between trust and relationship performance are explained. At the end of this chapter, in figure 1, the conceptual model shows a summary of the relationships studied in this research.
Calculative trust and relational trust
Trust can be approached from different perspectives. From an economic approach, trust is based on punishments and rewards according to opportunistic behavior and involves a calculative process (Sako and Helper, 1996). The transaction cost economics (TCE) theory can explain this behavior of managers, since opportunism is one of the key assumptions this theory relies on (Das and Rahman, 2010). The TCE theory considers managers to be focused on minimizing transaction costs and thereby identifying mechanisms that leads to the most efficient transaction in collaborations (Williamson, 1981). Calculative trust is future-oriented and exists when “the benefits of cheating on a partner do not exceed the costs of being caught” (Claro and Claro, 2008: p.293). Calculative trust wields rational predictions in the form of calculations to prevent partners from trusting blindly (Doney and Cannon, 1997). This type of trust is seen as the best way to assure solidarity and influence the relationship performance in a positive way (Williamson, 1996).
From a sociological approach, trust is assumed to be more effective when partners behave in accordance with prior expectations and beliefs (Cranston, 2011). This so-called relational trust refers to “the extent to which there is a consonance with respect to each group’s understanding of each other’s expectations and obligations” (Cranston, 2011: p.62). Relational trust originates from believing strongly in the honesty and goodwill of managers (Zaheer and Harris, 2006). Regarding the social exchange theory (SET), a business relationship develops trust and a mutual commitment over time, which means that the longer the relationship holds, the stronger the relational trust is (Cropanzano and Mitchell, 2005). Higher levels of relational trust make it more likely that managers take the interest of their partners into consideration when making decisions regarding the collaboration. Thereby, relational trust reduces negotiation costs and risks of
opportunistic behavior (Long and Sitkin, 2006; Poppo et al., 2016) and is thus expected to positively influence the performance of the collaboration.
Factors that influence trust in an IOR
According to the TCE theory, firms focus on minimizing transaction costs related to opportunistic behavior (Dyer and Singh, 1998; Das and Rahman, 2010). Transaction costs increase with the hazards of opportunism, but can also increase as a result of information asymmetry and interdependence, which in turn can influence the effectiveness of trust in an IOR (Williamson, 1981). This study examines two factors that might influence the relationship between trust and relationship performance, namely disclosing behavior and interdependence. As stated above, information asymmetry increases transaction costs, and therefore, information is seen as a valuable concept. The degree of voluntary information disclosure by managers shows the disclosing behavior of a firm (Watson et al., 2002). Voluntary disclosure can be presented in, for example, reports, management forecasts, analysts’ presentations or social media (Healy and Palepu, 2001). This presented information reduces the information asymmetry between organizations and is used by managers to make decisions (An et al., 2011). Thereby, voluntary disclosure of information provides a more intensive monitoring opportunity for other companies (An et al., 2011; Hill and Jones, 1992). Since an increase in monitoring activities might be an incentive for managers to act in their stakeholders’ best interest, it follows that the higher the possibilities for monitoring are, the less managers act in an opportunistic way. Moreover, increased monitoring makes managers try to achieve a better image (Watson et al., 2002).
Interdependence is defined as “the motivational investment in the relationship and the replaceability of the partner” (Geyskens et al., 1996: p.4). Replaceability is defined as “the difficulty of replacing a partner because of switching costs or the lack of alternative partners” (Geyskens et al., 1996: 4). When the degree of interdependence is higher, the risks of misinterpretations and mistakes are higher and trust between organizations obtains a more important role in the way that it affects the relationship performance (Krishnan and Martin, 2006). The degree of interdependence between partners strongly depends on the base of the relationship.
Trust from an economic perspective
Calculative trust considers a firm to be trustworthy if, by means of rational calculations, there is reasonable substantiation to believe that it would be in that firm’s economic best interest to be trustworthy (Hardin, 1992). Calculative trust works with incentives in the form of penalties and rewards, which play an important role for managers to achieve the desired relationship performance (Poppo et al., 2016). When calculative trust exists, these incentives make partners believe that the economic outcome of working in line with the agreement of the collaboration outweighs the costs of opportunism (Srinivasan and Brush, 2006). This motivates managers to achieve cooperation and performance goals, by maximizing expected gains and minimizing expected losses from their transactions (Williamson, 1993). Calculative trust has a long-term focus, the longer the firm’s expectation of positive transactions in cooperation, the higher the relationship performance (Parkhe, 1993). Managers who fail to increase the performance in response to the incentives may lack calculative trust and consequently do not believe that their efforts are properly rewarded by the partner (Long and Sitkin, 2006).
In the situation that managers consider opportunistic behavior regarding their contract with a partner, the potential future loss and benefits of this behavior has to be taken in consideration. When the potential benefit outweighs the loss from violating the contract, managers would choose to act in their own best interest. This can be explained by the fact that firms, from the perspective of calculative trust, only choose to cooperate when their expectations of payoffs of the collaboration are positive (Lewicki and Bunker, 1996). A higher level of calculative trust decreases the level of conflicts between partners, which makes it less likely that managers will consider opportunistic behavior (Gulati, 1995).
In conclusion, since incentives related to calculative trust stimulate cost effective transactions and discourage opportunistic behavior, calculative trust is expected to offer a superior way to ensure cooperation between companies and to increase relationship performance.
Trust from a sociological perspective
In the relational trust view, trust is based on shared identities and collective values between partners (Claro and Claro, 2008). A shared identity between partners creates mutual understanding, which is a foundation for the growth of trust (Cranston, 2011). Such mutuality results in lower negotiation costs, lower risks of opportunistic behavior and helps managers to make decisions in line with the interest of their partner (Krishnan and Martin, 2006; Zaheer et al., 1998). This support in decision-making that relational trust facilitates can also be explained from the perception that relational trust provides stability in partnerships. Stability reduces the demand for continually monitoring the partner and revaluating the relationship (Dyer and Singh, 1998). Based on the signalling theory, stability of the degree to which partners act cooperatively is indicated by positive signals. This theory, which originates from explaining behavior in labour markets (Spence, 1973), perceives a partner as trustworthy if they provide positive signals (Lindenberg, 2000). Positive signals of behavioral expectations are known as relational signalling, which is seen as the basis for building trust and expected to create positive future expectations about a firm (Vosselman and Van der Meer-Kooistra, 2009).
The effectiveness of relational trust on relationship performance can also be explained through the commitment between partners. A sense of commitment motivates managers to behave in the most optimal way regarding the outcome of the relationship, rather than taking advantage of the collaboration (Beckert, 2009).
In conclusion, when a collective identity between partners is developed and when partners are committed to shared values, firms are expected to be more devoted to the same objectives (Lewicki and Bunker, 1996). Relational trust is expected to reduce transaction costs and risks of opportunistic behavior and offers opportunities for an improved IOR. Therefore the expectation is that relational trust is positively related to relationship performance.
Moderating effect of disclosing behavior
The relationship between trust and relationship performance is explained under hypotheses 1 and 2. Different factors might influence the effectiveness of trust on relationship performance. The next part examines disclosing behavior as a moderator on the relationship between trust and relationship performance.
From an economic perspective
From a calculative view of trust, managers have incentives to compare costs and benefits in order to make business decisions (Lewicki and Bunker, 1996 ). For example, when managers have to make a decision whether to disclose certain information, they calculate the most optimal degree of disclosing information and base their decision on that (Healy and Palepu, 2001).
Taking the TCE theory as base, managers use voluntary disclosure to minimize transaction costs in a way that information asymmetry risks are reduced (Poppo et al., 2008). Disclosing behavior is closely related to information asymmetry, because, if there is asymmetry in the information availability between partners, managers might consider opportunistic behavior when the benefits of shirking outweigh the cost of getting caught (Anderson and Jap, 2005). Costs and benefits are central aspects regarding the calculative view of trust. Voluntary disclosure is important in this as it lowers the agency costs and positively influences the relationship performance (Watson et al., 2002; An et al., 2011). This indicates that a higher information asymmetry leads to more risks, including opportunities for opportunism, which indicates negative trustworthiness of a firm. However, when firms are willing to disclose more information to partners, they will appear trustworthy.
In conclusion, disclosing behavior is expected to positively influence the effectiveness of calculative trust on relationship performance, since a positive disclosing behavior has a direct influence on the information asymmetry risks and the related agency costs. This makes calculative trust, which is based on costs and benefits, between partners more relevant in their impact on the relationship performance of IORs.
Hypothesis 3a: The disclosing behavior of firms has a positive moderating effect on the relationship between calculative trust and relationship performance
From a sociological perspective
When there is relational trust, partners have a mutual understanding, share a common identity and prefer to work in line with each other’s interest (Lewicki and Bunker, 1996). By disclosing information, partners become more aware of each other’s norms and values and as a result gain a better understanding of the identity of a firm and the related interests (Poppo et al., 2016).
The signalling theory explains why firms voluntarily disclose information (Spence, 1973). When a manager voluntarily discloses information, the underlying reason could be to positively signal its excellence to partners. Signalling is a response to information asymmetry in relationships, where one firm has certain information which the partner firm has not (Watson et al., 2002). Asymmetries can be diminished if the firm with more information signals this private information to the partner. Thereby, signalling allows partners to monitor their partner’s behavior, which reduces monitoring costs (Li et al., 2010). Especially positive information is effective to signal, because firms can distinguish themselves from other firms and therefore these firms are perceived as more trustworthy (Dye and Sridhar, 1995). Consequently, high quality firms are expected to engage more often in voluntarily disclosure practices compared to lower quality firms (Watson et al., 2002).
Sharing valuable information with a partner stimulates the relationship between relational trust and relationship performance. A company that voluntarily discloses information builds a better image and, as result, benefits from sharing information in order to create an open environment (An et al., 2011). An open environment makes partners more aware of each other, supports a mutual understanding between partners and stimulates partners to work in line with each other’s interest. These are indicators of relational trust which contribute to a better relationship performance as a result of voluntarily disclosing information.
Following the arguments mentioned above, the disclosing behavior of firms is expected to have a positive influence on the relationship between relational trust and relationship performance.
Hypothesis 3b: The disclosing behavior of firms has a positive moderating effect on the relationship between relational trust and relationship performance.
Moderating effect of interdependence
Next to the moderating effect of disclosing behavior, the degree of interdependence is also expected to influence the effectiveness of trust on relationship performance. This part examines the potential influence of interdependence on the relationship between trust and relationship performance.
From an economic perspective
According to the TCE theory, transaction costs can arise as a result of high interdependence between partners (Williamson, 1981). For example, specialized assets or specific investments cause higher interdependence between partners (Das and Rahman, 2010). These assets and investments result in higher costs and are less applicable for other transactions (Chiles and McMackin, 1996).
In the existence of calculative trust, managers believe that complying with the collaboration results in a better outcome than acting in a self-interested, opportunistic manner (Poppo et al., 2016). A lower chance for opportunistic behavior increases the effectiveness of integration and coordination in the partnership and therefore decreases the risks for misunderstandings (Krishnan and Martin, 2006). In high interdependence relationships, it is more risky for firms to engage in opportunistic behavior, since it affects both partners: they both have much to lose and often face high exit barriers. This makes it more likely that partners experience their relationship as a win-win opportunity, rather than an opportunity to take risks. (Kumar et al., 1995).
In conclusion, interdependence between partners leads to higher transaction costs. Without the existence of calculative trust, risks for misunderstandings and opportunistic behavior arise between independent partners. On the other hand, when the interdependence between partner is lower, trust has a weaker impact on the relationship performance, because the chances of misinterpretations and mistakes are lower (Gulati and Singh, 1998). This said, calculative trust between partners is expected to be of more effect on the relationship performance when interdependence is higher.
Hypothesis 4a: The interdependence of partners has a positive moderating effect on the relationship between calculative trust and relationship performance.
From a sociological perspective
It is important to be aware of the degree of interdependence in an IOR, because it defines each partner’s ability to influence the other (Hibbard et al., 2001). This is consistent with the SET theory, which states that interdependence has the potential for a firm to be influenced by their partner (Cropanzano and Mitchell, 2005).
Relational trust is important in stimulating a better understanding between partners and therefore ensures a better interpretation of the actions and decisions of a firm. When partners are dependent on each other, it is even more important to know a lot about the decisions and actions taken by the partner firm, since it is more likely that the changes one partner makes affect the other partner in an unforeseen way (Nooteboom, 2002). Furthermore, in high interdependence relationships are more requirements for relational-specific transactions and the exchange process is less standardized. Relational trust is important to help coordinate these exchanges (Cannon and Perreault, 1999). Thereby, interdependence increases the performance of a relationship, since it stimulates a partner’s desire to maintain the relationship and avoid opportunistic behavior (Palmatier et al., 2007).
In conclusion, higher interdependence involves more requirements regarding transactions, higher unforeseen changes and therefore makes relational trust an important factor to coordinate this. This should be done in a way which meets both partners’ desires and improves the understanding between the partners, which is expected to have a positive effect on the relationship performance of the IOR.
Hypothesis 4b: The interdependence of partners has a positive moderating effect on the relationship between relational trust and relationship performance.
Conceptual model
The six hypotheses formulated in the previous sections are modelled below in figure 1, the conceptual model. This study examines two direct relationships and four indirect, moderating effects. In addition, four control variables that might influence the relationships are included in this research.
Chapter 3 Methodology
Sampling and data collection method
The main purpose of this research is to provide evidence-based answers to support the hypotheses developed in the previous chapter. In order to gather useful information, the supervisor of this research created a survey, since surveys are the most valuable method for collecting data requiring opinions and beliefs of managers about IORs (Fahy, 1998; Lev and Zarowin, 1999). The survey is conducted by 7 interviewers, postgraduate students of the University of Groningen. As the organizations in the sample are Dutch, a Dutch version of the survey is developed. The survey is checked through a series of quality tests, a pre-test and is of sufficient size to gain a well-substantiated outcome. The target respondents are managers of private or public limited companies with knowledge about a collaboration their firm participates in. The approached companies need to meet a set of requirements to ensure a minimum firm size of at least 10 employees and a minimum turnover of 2 million per annum.
The respondents are contacted by email or phone and asked to fill out the survey questions based on the relationship of which they know most. The interviewers obtained the surveys in a face-to-face setting with the respondents, which contributes to a more reliable dataset. The respondents are also offered an incentive in the form of a report of the results. Both the personalization of the surveys and the nonmonetary incentive contributed to a more valuable survey, since it increases response rates (Fahy, 1998). The response rate is 77% resulting in 111 complete surveys.
Measurement
The measures for the independent, dependent and moderating constructs are based on the research of Poppo and Zenger (1998), Poppo et al. (2016), Kingshott (2006) and Geyskens (1996). The constructs include variables measured by a seven-point Likert-scale from “strongly disagree” (1) to “strongly agree” (7). Appendix A shows the measurement instruments used for each construct.
Consistent with the research of Poppo and Zenger (1998), the relationship performance is measured on the level of satisfaction of the respondent with three common performance goals central to relationship performance: the overall cost, the quality of the output or service and the responsiveness to problems or inquiries.
Calculative trust is measured by three items based on the research of Poppo et al (2016). The first two items are predicated on rewards and punishments, namely the expected honestly and whether the behavior of both parties is perceived as trustworthy because of high costs and punishments of misconduct. The third item contains the expectation of the manager whether the relationship with the partner will continue for a long time.
The measurement of relational trust includes three items consistent with the research of Poppo et al (2016). These items are shared identification, shared understanding and thinking alike. Together, these items measure shared identity, the highest level of relational trust.
Disclosing behavior is measured based on four items adapted from Kingshott (2006). These items contain the extent to which partners inform each other about changes and provide each other with helpful information. The degree to which information is provided can measure the perceived behavior of a partner concerning disclosing information (Kingshott, 2006).
Interdependence is measured using two items based on the research of Geyskens (1996). This measurement tests the replaceability of the firm, in a way that other firms exist that could provide comparable products or services. Replaceability is an important measure for interdependence since it includes opportunity costs of the value that would be lost if the relationship ended and switching costs associated with termination and replacement (Geyskens, 1996).
Control variables
This study controls, consistent with prior research (Schilke and Cook, 2015; Poppo et al., 2008), four extraneous constructs that might influence the relationships examined in this research. These constructs include the firms size, the age of the collaboration, the industry the company operates in and whether the collaboration is local or international.
Previous research argued that a firm’s size affects the relationship performance in a positive way (Claro and Claro, 2008), since larger firms have greater leverage, more bargaining power and lower costs for collecting and processing information (Watson et al., 2002; Poppo et al., 2008). In this study, the firm size is measured by the number of employees.
Firms in an IOR develop a mutual understanding over time, which makes it less likely to get into a conflict with the partner the longer the relationship holds (Parkhe, 1993). The age of the collaboration, measured in terms of years of a partnership, creates stability and may lead to a better chance of building trust between partners which will result in a higher relationship performance (Suh and Kwon, 2006; Schilke and Cook, 2015).
Companies participating in the survey differ in industry. Firms operating in different industries can have different expectations of their partners, requiring different levels of trust. Since most of the firms in the survey operate in the manufacturing and service industry, this control variable is measured using dummy variables indicating whether a firm is active in the service industry (1) or in the manufacturing industry (0).
Firms in different countries can have different norms and values and are often required to adhere to different legislation rules, which can influence the relationship performance (Alford, 1993). This variable is measured by making a distinction between local IORs (1), where both partners are Dutch, and international IORs, where the partner is from a foreign country (0).
Data analysis
The data analysis starts with testing the construct validity to ensure that the different items of the variables are loading together as a construct. First, the adequacy of the sample is tested by conducting a Kaiser-Meyer-Olkin (KMO) and Barlett’s test. The outcome of the KMO test of .743 is appropriate, because the value is above the required minimum of 0.6 (Crane et al., 1991; Andersen and Herbertsson , 2003). The Barlett’s test is significant (p < .05) at a level of 0.000 and thus suitable for a factor analysis (Williams et al., 2010). An exploratory factor analysis is used to ensure that the constructs load on separate models. After removing two items of calculative trust, the constructs loaded as theoretically expected and thus the construct validity is guaranteed. The results are shown in Appendix A.
The average variance extracted (AVE), measuring the convergent validity, range from .48 to .74. The composite reliability (CR) of the constructs range from .68 to .88. A minimum AVE of 0.5 is accepted when the CR is higher than 0.6, because the validity of the construct in that case is still adequate (Fornell and Larcker, 1981; Huang et al., 2013). Only relational trust, with an AVE of .48 does not meet this requirement. However, the Cronbachs Alpha also measures the reliability to ensure internal consistency of multiple item variables. This test shows a satisfactory reliability for the constructs on the base of an acceptable minimum of 0.5 (DeVellis, 2003; Kline, 2011). All together, these results show sufficient validity and reliability. The results are presented in Appendix A.
Furthermore, common method bias is a potential problem in behavioral research that arises when measures of two or more variables in a dataset are collected from the same respondent (Podsakoff and Organ, 1986). In this study, the data of the independent, dependent, moderating and control variables are gathered from the same respondent. When the respondents have a tendency to provide consistent answers to survey questions that are not intended to be
related, a problem of unfounded correlations can arise (Chang, 2010). To control for this potential problem, a common method assessment is executed in the form of a Harman one-factor test (Poppo et al., 2016; Podsakoff and Organ, 1986). The maximum variance explained by a single factor is 29,77 percent. This is sufficient, because a percentage lower than 50% indicates that a dataset does not suffer from the common method bias (Fuller et al., 2016).
Regression model
Based on the hypotheses, the regression model is formulated as follows:
Relationship Performance = β0 + β1 (LN_Firm_Size) + β 2 (LN_Firm_Age) + β3 (Industry) + β4 (Country) + β5 (CALC_Trust) + β6 (REL_Trust) + β7 (Dis_Bhvr) + β8 (Dep_Ptnr) + β9 (CALC_Trust * Dis_Bhvr) + β10 (REL_Trust * Dis_Bhvr) + β11 (CALC_Trust * Dep_Ptnr) + β12 (REL_Trust * Dep_Ptnr) + εi
Relationship performance is the dependent variable, which is regressed against the control variables firm size (LN_Firm_Size), age of the collaboration (LN_Firm_Age), industry and country, the direct effects of calculative trust (CALC_Trust) and relational trust (REL_Trust) and the moderating effects of disclosing behavior (Dis_Bhvr) and interdependence (Dep_Ptnr).
Chapter 4 Analyses and Results
Analyses
A multiple regression analysis is performed to test the hypotheses prepared in the previous chapters. Before this analysis is performed, a Durbin-Watson test is executed to ensure the interdependence of observations. This test results in a score of 2.226, which is sufficient since it is close to 2 (Teo, 2014; Garson, 2012). To guarantee that the data in this research has a normal distribution, a Skewness and Kurtosis test is performed. With a relatively high outcome for firm size and age of the collaboration, these two control variables are transformed into a log. Consequently, the issues regarding Skewness and Kurtosis are resolved and thus the normal distribution of all variables are ensured.
Descriptions and correlations
Table 1 presents the descriptive statistics of the means, the standard deviations of the constructs and the correlation between the constructs. The first five variables shown in table 1 are all measured by a seven-point Likert scale. The score of the relationship performance is, given the higher mean and the lower standard deviation, substantively higher compared to the other variables. This indicates that, on average, more positive scores are given to the questions regarding relationship performance. Furthermore, the low mean of interdependence shows that, on average, the respondents does not perceive the relationship between the firm and the partner highly dependent.
According to the control variables, the average firm size in terms of number of employees is 7,958 people and the average length of a collaboration is 9.87 years. The country variable shows a mean of .77, which indicates that the majority of the partnerships are local IORs, meaning both partners are Dutch companies.
The highest correlation found in this research is between relational trust and relationship performance (r = .349, p < 0.01). However, the correlation between calculative trust and relationship performance (r = .237, p < 0.01), disclosing behavior and relationship performance (r = .311, p < 0.01) and between disclosing behavior and relational trust (r = .322, p < 0.01) are also high. Furthermore, the age of the collaboration is negatively correlated to calculative trust (r = -.243, p < 0.01). This is in contrast with the expectation that calculative trust has a long-term focus and thus gets stronger the longer the relationship holds (Parkhe, 1993).
Var iab le M ean S .D. 1 2 3 4 5 6 7 8 9 10 1. R elations hip P erf orma nc e 5.28 .99 1.000 2. C alcula ti ve Tr ust 5.20 1.51 .237*** 1.000 3. R elational Tr ust 4.08 1.21 .349*** .056 1.000 4. Disc losi ng B eha vior 4.64 1.15 .311*** .088 .32 2* ** 1.000 5. Inte rde p ende nc e 3.89 1.45 .012 -.111 -.117 .062 1.000 6. F irm S iz e 7957 25361 .077 .047 -.070 .082 .155* 1.000 7. Age of the coll abora ti on 9.87 10.87 -.122 -.243*** -.088 .070 .212** .115 1.000 8. C ountr y .77 .42 -.043 .025 .113 .019 .134* -.006 -.089 1.000 9. Ma nufa cturin g indus tr y .23 .43 -.121 .001 -.21 4* * -.085 .029 .033 .131* -.109 1.000 10. S er vice indu str y .21 .41 .012 .156* .053 -.137* .075 .016 -.073 .116 -.230*** 1.000 Ta ble 1: De sc riptio ns of me ans, st anda rd d eviations and c orr elations Note : N = 111; p* <.10; **p < .05; ***p < .01 . O ne -tailed
22
Results
Table 2 shows the regression results of this research. Model 1 shows the control variables, model 2 the direct effects and model 3 presents the moderating effects of disclosing behavior and interdependence. The F-test shows a significant effect for model 2 (F = 3.049, p < 0.01) and model 3 (F = 3.791, p < 0.01). The adjusted R² shows a change from .157 in model 2 to .262 in model 3, resulting in a significant change of .105 (p < .01), this indicates a sufficient goodness of fit of model 2 and 3.
To look into potential multicollinearity problems, the collinearity statistics variance inflation factor (VIF) and the tolerance levels are used. The highest value of the VIF is 1.471, well below the maximum of 10 (Wu, 2007). The tolerance levels are all between 0.6 and 0.9, which is sufficient according to the minimum level of 0.1. This implies no problems according to multicollinearity.
Hypothesis 1 predicts a positive influence of calculative trust on relationship performance. This direct effect of calculative trust on relationship performance shows a positive and significant relation (β = .188, p < .05). This is consistent with the expectation and therefore hypothesis 1 is supported.
Hypothesis 2 predicts a positive influence of relational trust on relationship performance. This direct effect of relational trust on relationship performance shows a positive and significant relation (β = .283, p < .01). Hence, hypothesis 2 is supported.
Furthermore an extra direct effect is found between disclosing behavior and relationship performance (β = .187, p < .05), this implies that a positive disclosing behavior has a positive influence on the relationship performance.
Hypothesis 3a predicts that the disclosing behavior of a firm has a positive moderating effect on the relationship between calculative trust and relationship performance. The regression results for this relation are negative and significant (β = -.263, p < .01). To enhance the interpretation of this moderating effect, figure 2 shows a further explanation. When the calculative trust between partners is low, a positive disclosing behavior is favourable to obtain a higher relationship performance. In conclusion, this finding is in contrast with the expectation that disclosing behavior has a positive moderating effect and therefore hypothesis 3a should be rejected.
Hypothesis 3b predicts a positive influence of disclosing behavior on the relation between relational trust and relationship performance. The results indicate that this moderating effect is positive and significant (β = .143, p < 0.1). Figure 3 provides a better insight in this relation and shows that when relational trust is low, the degree of disclosing behavior hardly changes the
relationship performance. However, when relational trust is high, a positive disclosing behavior leads to an increase of the relationship performance. The role of the disclosing behavior in relation to the relationship performance gets more important the higher the relational trust is. Hence, hypothesis 3b is supported.
Hypothesis 4a predicts a positive moderating effect of interdependence on the relation between calculative trust and relationship performance. The regression results indicate that there is no effect of interdependence on the established relation from hypothesis 1, because the results are insignificant. Therefore, hypothesis 4a should be rejected.
Hypothesis 4b predicts that the interdependence between partners has a positive influence on the relation between relational trust and relationship performance. The results show a negative and significant relation (β = -.173, p < .05). This relationship is further explained in figure 4, showing that when relational trust is low, high interdependence results in better relationship performance. However, when relational trust is high, the degree of interdependence does not matter for the performance of the relationship. Based on these findings, hypothesis 4b should be rejected, since results indicate that the opposite is true. The interdependence between partners negatively influences the positive relation between relational trust and relationship performance.
Table 2: Regression results
Note: N = 111 *p<0.1 **p<0.05 ***p<0.01. One-tailed Dependent variable
Relationship Performance
Model 1 Model 2 Model 3
β (SE) β (SE) β (SE) Control variables Firm size .069 (.101) .060 (0,093) .040 (.088) Age of collaboration -.272 (.235) -.212 (.223) -.254 (.211) Service industry -.050 (.241) -.050 (.227) -.194 (0,219) Manufacturing industry -.273 (.231) -.273 (.231) -.137 (.203) Country -.158 (.230) -.249 (.214) -.298 (.204) Independent variables H1: Calculative trust .188** (.091) .263 (.092) H2: Relational trust .283*** (0,096) .206 (.092) Disclosing behavior .187** (.093) .260*** (.093) Interdependence .078 (.091) .150* (.089) Moderating effects H3a: Disclosing behavior * Calculative trust -.263*** (.079) H3b: Disclosing behavior * Relational trust .143* (.109) H4a: Interdependence * Calculative trust -.102 (.096) H4b: Interdependence * Relational trust -.173** (.087) Model summary Adjusted R² -.015 .157 .262 F-value .723 3.049*** 3.791*** ∆ Adjusted R² .172 .105 ∆ F^2 6,316*** 4,560***
Figure 2. The moderating effect of disclosing behavior on the relationship between calculative trust and relationship performance
Figure 3. The moderating effect of disclosing behavior on the relationship between relational trust and relationship performance
Figure 4. The moderating effect of interdependence on the relationship between relational trust and relationship performance
4,6 4,8 5 5,2 5,4 5,6 5,8 6 6,2 6,4
Low Relational Trust High Relational Trust
R elatio ns hi p P erf orm ance Low Disclosing Behavior High Disclosing Behavior 4,6 4,8 5 5,2 5,4 5,6 5,8 6
Low Relational Trust High Relational Trust
R elations hip P erf orma nc e Low Interdependence High Interdependence 0 1 2 3 4 5 6 7
Low Calculative Trust High Calculative Trust
R elatinos hip P erf orma nc e Low Disclosing Behavior High Disclosing Behavior
Chapter 5 Discussion and Conclusion
This last chapter contains the discussion and conclusion. First, a summary of the findings and the research implications are provided. Second, the managerial implications are presented. This chapter ends with a discussion of the limitations and suggestions for further research.
Most empirical research focuses on trust as an aggregate aspect (Poppo et al., 2016; Scheer et al., 2003; Zaheer and Harris, 2006). To gain a broader view of the influence different perspectives of trust has on the relationship performance of an IOR, this study separated trust in calculative trust and relational trust. Consistent with the expectations, the results confirm that rewards and penalties motivate managers in a positive way regarding the performance of a collaboration (Long and Sitkin, 2006; Parkhe, 1993) and thus show that calculative trust is positively related to relationship performance. Furthermore, relational trust is also positively related to relationship performance, which is consistent with the expectation that relational trust, in the form of a mutual understanding and commitment between partners cause firms to be more devoted to the same objectives (Lewicki and Bunker, 1996). From the two types of trust, relational trust has a stronger positive effect on relationship performance.
In addition, the relationship between relational trust and relationship performance is positively influenced by a positive disclosing behavior as theoretically expected. However, contrary to the expectations, a positive moderating effect of disclosing behavior negatively influences the effectiveness of calculative trust on relationship performance.
Lastly, although interdependence was expected to have a positive moderating effect on the relation between relational trust and relationship performance, the opposite is true. The results show that interdependence negatively influences the relationship between relational trust and relationship performance. No significant evidence is found regarding the impact of interdependence on the relation between calculative trust and relationship performance.
Overall, the findings challenge the effect that trust has in different circumstances and types of relationships and contribute to the previous, conflicting, literature by providing new insights (Poppo et al., 2016; Kumar et al., 1995; Gulati and Singh, 1998, Krishnan and Martin, 2006).
Notwithstanding, the results of this study have implications. Firstly, the finding that relational trust is stronger related to relationship performance compared to calculative trust is in contrast with the research of Poppo et al (2016: p.23), who stated “calculative trust appears to have a stronger effect than relational trust”. This can be explained by the difference in industries. In this study 28% of the respondents work in the service and banking industry, forming the largest group. The research of Poppo et al (2016) mainly studies firms in the manufacturing industry. The service and banking industry requires intensive interpersonal interaction, where relational trust is expected to play an important role, whereas calculative trust is more effective in the manufacturing sector because it is more effective at managing operational decisions (Poppo et al., 2016). This difference in industries influences the importance of calculative trust and relational trust and can therefore explain the contrasting findings of this research with the research of Poppo et al (2016).
Secondly, although a positive moderating effect of disclosing behavior on the relation between calculative trust and relationship performance was expected, the results showed the opposite. This can be explained by the reasons firms have for making decisions. For example, a manager’s consideration to voluntarily disclose information, from a calculative view of trust, is calculated to ensure the most optimal degree of providing information (Healy and Palepu, 2001). A higher disclosing behavior, which means a lower information asymmetry, enables firms to better calculate and estimate the chance for rewards and penalties and support managers to act in a way that is the most interesting for themselves. This results in a more self-interested decision and may not be the best decision for an optimal relationship performance (Healy and Palepu, 2001). This explains the finding of this research that a positive disclosing behavior negatively influences the relation between calculative trust and relationship performance.
Thirdly, this study expected a positive moderating effect of interdependence on the relationship between relational trust and relationship performance, based on the existing literature that higher interdependence between partners requires more relational-specific transactions which leads to more risks for opportunistic behavior and increased chances of misinterpretations and mistakes (Kumar et al., 1995). The existence of relational trust could mitigate these risks, and was therefore expected to be of more importance on the relationship performance when the interdependence between partners is higher. However, the results of this study presents evidence for a negative effect of interdependence on the relation between relational trust and relationship performance. This can be explained by the measurement of interdependence used in this study, which calculates the interdependence between partners as a construct. This means that there is no insight in whether an unequal dependency exists between
partners. However, it is conceivable that one of the partners is more dependent on their partner and this could result in different outcomes. A partner with greater dependency has a greater interest in maintaining the relation, due to sunk costs (Palmatier et al., 2007).
The less dependent partner can use their partners dependence to suggest changes that are in their best interest and can be less willing to negotiate. The power asymmetry that arises reduces the effectiveness of trust (Anderson, 1990) and can therefore explain the negative moderating effect of interdependence found in this research.
The findings of this research have also practical implications. The results of this study enhance managers to become more aware of the influences of their decisions. According to the limited research to different perspectives of trust, logically many managers are not aware of the existence of the different types of trust, and if they are, they might still not know how these different types can influence the relationship performance of an IOR. An important contribution of this research for managers is that the type of trust that should be relied on is dependent on the type of industry the firm operates in. If a firm operates in the service industry and has a collaboration with another partner in this industry, managers can achieve the most optimal relationship performance when the relational trust between the partners is ensured. Since the service industry mostly relies on intensive interpersonal interaction, where relational trust is expected to play an important role. Calculative trust is more important in the manufacturing sector since this type of trust is more effective at managing operational decisions.
As a direct effect, disclosing behavior is positively related to relationship performance. This implies that managers should strive to voluntarily disclose information to their partners to achieve the best outcome of the collaboration. Especially when partners have less trust in each other, managers could see disclosing information as a solution for an improved collaboration. As can be seen in figure 2 and 3, in a situation of low relational or low calculative trust, a positive disclosing behavior contributes to the relationship performance. Thus, providing more information to the partner when the trust between partners is not optimal stimulates the outcome of the collaboration.
However, the findings of this study have various limitations, which provide opportunities for future research. First, since the data in this research is gathered through a survey, a respondent bias occurs. Respondents can be biased by their preferences for answers or expectations of the survey. Second, all the firms that participated in the survey are Dutch, which makes it difficult to tell how universal the results are if they are applied to firms in other countries. Third, the survey was taken from one firm participating in an IOR, which may result in a single-informant bias. Fourth, the sample size, although fairly distributed, is quite small,
which causes generalizability problems (Pallant, 2011). Future research could gather data from a larger sample size and extend the research to different countries. Also, to limit the respondent bias and single-informant bias, future research could gather data by multiple sources.
Data could for example be gathered by combining a survey with in-depth interviews, including both partners in the IOR. This method would gather more detailed information and the generalizability of the results will increase.
Furthermore, the correlation between calculative trust and age of the collaboration is negative in this study. This is in contrast with the expectation that trust develops over time (Parkhe, 1993). However, the data of this study is gathered at one period in time and therefore limited to give information about the development of trust in the collaboration over the years. To improve the understanding of the development of trust it would be beneficial for future research to ask the same respondents to fill out the survey every year.
There are more limitations regarding the methodology. The exploratory factor analysis showed that the three items of calculative trust did not form a construct together, two items had to be deleted. Therefore, the measurement of calculative trust is based on only one item. Second, the relational trust measure is based on three items, but the reliability of this construct is quite low. According to this, the reliability of the data is questionable and should therefore be used carefully. To improve this reliability, future research could expand the survey with more questions relating to calculative trust and relational trust.
Another direct relation found in this research is the positive relationship between disclosing behavior and relationship performance. However, this relationship can be endogenous. This study found that a more positive disclosing behavior leads to a better performance of the IOR. Disclosing behavior is the explanatory variable in this relationship. However, this relationship can also work the other way around; an improved relationship performance can be the reason that firms want to disclose more information, because positive information increases a firm’s willingness to disclose information (Watson et al., 2002; Xiao et al., 2004). In this situation, the relationship performance explains the disclosing behavior. Future research could control this endogenous problem by using the lead-lag approach; this approach uses a two-stage regression, where the data gathering is split in two separate periods to deal with endogeneity problems (Dhaliwal et al., 2001). Thus, data relating to the explanatory variable should be gathered in the first period and the data relating to the explained variable in the second period.
With respect to the moderating effect of interdependence, in contrast to the expectation, a higher dependency has a negative influence on the relationship between relational trust and relationship performance. The measurement of interdependence is a construct that measures the overall dependency of both partners. This construct limits the possibility to measure whether there is asymmetry in the dependency level of the partners. Taking this limitation into consideration, future research could measure the degree of dependency on the partner separately from the dependency of the partner. Finally, future research should continue examining the different perspectives of trust and expand it with more types of trust.
Reference list
An, Y., Davey., H and Eggleton, I.R.C. (2011). Towards a comprehensive theoretical framework for voluntary IC disclosure. Journal of Intellectual Capital, 12 (4); 571-585)
Andersen, T. and Herbertsson, T. (2003). Measuring globalization. IZA Discussion paper series;
817
Anderson, E. (1990). Two firms, one frontier: On assessing joint venture performance. MIT
Sloan Management Review, 31 (2); 19.
Anderson, E. and Jap, S.D. (2005). The dark side of close relationships. Sloan Management
Review, 46 (3); 75
Alford, A. (1993). The relative informativeness of accounting disclosures in different countries.
Journal of accounting research; 183-223
Alexy, O., George, G. and Saler, A.J. (2013). Cui Bono? The Selective Revealing of Knowledge and its Implications for Innovative Activity. Academy of Management Review, 38 (2); 270-291
Beckert, J. (2009). The social order of markets. Theory and society, 38 (3); 245-269
Buchanan, L. (1992). Vertical Trade Relationships: The Role of Dependence and Symmetry in Attaining Organizational Goals. Journal of Marketing Research,; 65-75
Cannon, J. P., and Perreault Jr, W. D. (1999). Buyer-seller relationships in business markets.
Journal of marketing research; 439-46
Chiles, T. H., and McMackin, J. F. (1996). Integrating variable risk preferences, trust, and transaction cost economics. Academy of management review, 21 1); 73-99
Claro, D.P. and Claro, P.B.O. (2008). Managing Trust Relationships: Calculative, Affective, Belief and Performance. Brazilian Administration Review, 5 (4); 289-303
Crane, D. R., Busby, D. M. and Larson, J. H. (1991). A factor analysis of the Dyadic Adjustment Scale with distressed and nondistressed couples. American Journal of Family Therapy, 19 (1); 60-66
Cranston, J. (2011). Relational Trust: The Glue that Binds a Professional Learning Community.
Journal of Educational Research, 57 (1); 59-72
Cropanzano, R., and Mitchell, M. S. (2005). Social exchange theory: An interdisciplinary review. Journal of management, 31 (6); 874-900
Das, T.K. and Rahman, N. (2010). Determinants of Partner Opportunism in Strategic Alliances: A Conceptual Framework. Journal of Business and Psychology, 25 (1); 55-74
DeVellis, R. F. (2003). Scale development: Theory and applications. Applied social research methods series. Bickman, L and DJ Rog
Dhaliwal, D. S., Li, O. Z., Tsang, A., and Yang, Y. G. (2011). Voluntary nonfinancial disclosure and the cost of equity capital: The initiation of corporate social responsibility reporting. The
accounting review, 86 (1); 59-100
Doney, P.M. and Cannon, J.P. (1997). An examination of the nature of trust in buyer-seller relationships. the Journal of Marketing; 35-51.
Dye, R.A. and Sridhar, S.S. (1995). Industry-Wide Disclosure Dynamics. Journal of
Accounting Research, 33 (1); 157-174
Dyer, J.H. and Singh, H. (1998). The Relational View: Cooperative Strategy and Sources of Interorganizational Competitive Advantage. The Academy of Management Review, 23 (4); 660-679
Dumontier, P. and Raffournier, B. (1998). Why Firms Comply Voluntarily with IAS: an Empirical Analysis with Swiss Data. Journal of International Financial Management and
Fahy, J. (1998). Improving Response Rates in Cross-Cultural Mail Surveys. Industry Marketing
Management, 27 (6); 459-467
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research; 39-50
Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., and Babin, B. J. (2016). Common methods variance detection in business research. Journal of Business Research, 69 (8); 3192-3198
Garson, G. D. (2012). Testing statistical assumptions. Asheboro, NC: Statistical Associates
Publishing
Geyskens, I., Steenkamp, J.E.M., Scheer, L.K. and Kumar, N. (1996). The effects of trust and interdependence on relationship commitment: A trans-Atlantic study. International Journal of
Research in Marketing, 13 (4); 303-317
Gulati, R. (1995). Does Familiarity Breed Trust? The Implications of Repeated Ties for Contractual Choice in Alliances. The Academy of Management Journal, 38 (1); 85-112
Gulati, R. and Singh, H. (1998). The architecture of cooperation: managing coordination costs and appropriation concerns in strategic alliances. Administrative Science Quarterly, 43,; 781– 814
Hardin, R. (1992). The Street-Level Epistemology of Trust. Politics & Society, 21 (4); 505-529
Healy, P.M., and Palepu, K.G. (2001). Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature. Journal of accounting and
economics, 31 (1-3); 405-440
Hibbard, J.D., Kumar, N. and Stern, L.W. (2001). Examing the Impact of Destructive Acts in Marketing Channel Relationships. Journal of marketing research, 38 (1); 45-61
Hill, C.W.L. and Jones, T.M. (1992) Stakeholder-Agency Theory. Journal of Management
Huang, C. C., Wang, Y. M., Wu, T. W., and Wang, P. A. (2013). An empirical analysis of the antecedents and performance consequences of using the moodle platform. International
Journal of Information and Education Technology, 3 (2); 217
Kingshott, R.P. (2006). The impact of psychological contracts upon trust and commitment within supplier–buyer relationships: A social exchange view. Industrial Marketing
Management, 35 (6); 724-739
Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling, 3rd edn Guilford Press. New York
Kramer, R.M. (1999). Trust and distrust in organizations: emerging perspectives, enduring questions. Annual Review of Psychology, 50 (1); 569–596
Krishnan, R. and Martin, X. (2006). When does trust matter to alliance performance? Academy
of Management Journal, 49 (5); 894-917
Kumar, N., Scheer, L.K. and Steenkamp, J.E.M.. (1995). The effects of perceived interdependence on dealer attitudes. Journal of marketing research (1995): 348-356
Lev, B. and Zarowin, P. (1999). The Boundaries of Financial Reporting and How to Extend Them. Journal of Accounting Research, 37 (2); 353-385
Lewicki, R. J. and Bunker, B. B. (1996). Developing and maintaining trust in work relationships. Fronties of theory and research; 114-139
Li, Y., Xie, E., Teo, H. H., and Peng, M. W. (2010). Formal control and social control in domestic and international buyer–supplier relationships. Journal of Operations Management,
28 (4); 333-344
Lindenberg, S. (2000). It takes both trust and lack of mistrust: The workings of cooperation and relational signaling in contractual relationships. Journal of management and governance, 4 (1-2); 11-33
Long, C.P. and Sitkin, S.B. (2006). Trust in the balance: how managers integrate trust-building and task control. Handbook of trust research; 87-106
Nicolaou, A.I., Sedatole K.L. and Lankton, N.K (2011). Integrated Information Systems and Alliance Partner Trust. Contemporary Accounting Research, 28 (3); 1018-1045
Nooteboom, B. (2002). Trust: Forms, foundations, functions, failures and figures. Edward
Elgar Publishing
Pallant, J. (2011). Survival manual. A Step By Step Guide to Data Analysis Using SPSS
Palmatier, R.W., Dant, R.P. and Grewal, D. (2007). A Comparative Longitudinal Analysis of Theoretical Perspectives of Interorganizational Relationship Performance. Journal of
Marketing, 71 (4); 172-194
Parkhe, A. (1993). Strategic Alliance Structuring: A Game Theoretic and Transaction Cost Examination of Interfirm Cooperation. The Academy of Management Journal, 36 (4); 794-829
Podsakoff, P. M., and Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of management, 12( 4); 531-544.
Poppo, L., and Zenger, T. (1998). Testing altermative theories of the firm: transaction cost, knowledge-based, and measurement explanations for make-or-buy decisions in information services. Strategic management journal; 853-877
Poppo, L. Zhou, K.Z. and Zenger, T.R. (2008). Examining the Conditional Limits of Relational Governance: Specialized Assets, Performance Ambiguity, and Long-Standing Ties. Journal of
Management Studies, 45 (7); 1195-1216
Poppo, L., Zhou, K.Z. and Li, J.J. (2016). When Can You Trust ‘Trust'? Calculative Trust, Relational Trust, and Supplier Performance. Strategic Management Journal, 37 (4); 724-741
Sako, M. and Helper, S. (1996). Determinants of trust in supplier relations: Evidence from the automotive industry in Japan and the United States. Journal of Ecnonomic Behavior &
Organization, 34 (3); 387-417
Scheer, LK., Kumar, N. and Steenkamp, J.E.M. (2003). Reactions to perceived inequity in U.S. and Dutch interorganizational relationships. Academy of Management Journal, 46 (3); 303-316 Schilke, O. and Cook, K. (2015). Sources of alliance partner trustworthiness: integrating calculative and relational perspectives. Strategic Management Journal, 36 (2); 276-297
Spence, M. (1973). Job Market Signalling. The quarterly Journal of Economics, 87 (3); 355-374
Srinivasan, R., and Brush, T. H. (2006). Supplier performance in vertical alliances: The effects of self-enforcing agreements and enforceable contracts. Organization science, 17 (4); 436-452
Suh, T. and Kwon, I. W. G. (2006). Matter over mind: When specific asset investment affects calculative trust in supply chain partnership. Industrial Marketing Management, 35 (2); 191-201
Teo, T. (2014). Handbook of quantitative methods for educational research. Springer Science & Business Media.
Vosselman, E. and Van der Meer-Kooistra, J. (2009). Accounting for control and trust building in interfirm transactional relationships. Accounting, Organizations and Society, 34(2), 267-283.
Watson, A., Shrives, P. and Marston, C. (2002). Voluntary disclosure of accounting ratios in the UK. British Accounting Review, 34 (4); 289-313
Williams, B., Onsman, A., and Brown, T. (2010). Exploratory factor analysis: A five-step guide for novices. Australasian Journal of Paramedicine, 8 (3)
Williamson, O.E. (1981). The Economics of Organization: The Transaction Cost Approach.
