“Relational trust and management control mechanisms in buyer-supplier relationships:
Are they complements or substitutes in explaining relationship performance?”
by
Klaas Arjen Bootsma
S2184184
Smaragdstraat 48
9743 KW Groningen
k.a.bootsma@student.rug.nl
University of Groningen
Faculty of Economics and Business
January 23, 2017
Thesis supervisor MSc Organisational & Management Control:
Abdul Rehman Abassi
“Relational trust and management control mechanisms in buyer-supplier
relationships: Are they complements or substitutes in explaining
relationship performance?”
AbstractResearch on the inter-relationships between trust, management control mechanisms (MCMs) and relationship performance in inter-organisational relationships (IORs) remains bifurcated. Using survey data of the buyer-perspective of 128 buyer-supplier relationships, I investigate whether relational trust complements or substitutes social, behavioural, and output MCMs in explaining relationship performance in buyer-supplier relationships. Contrary to the hypothesised relationships, I find that relational trust is complementary to both behavioural and output MCMs in explaining relationship performance. No clear complementary or substitutive joint impact of relational trust and social MCMs on relationship performance emerges from the analysis. The results provide new insights whether a social type of trust, i.e. relational trust, complements or substitutes different types of MCMs in explaining relationship performance. This study extends transaction cost theory, social exchange theory, and relational exchange theory by showing that a combination of these theoretical approaches regarding trust and MCMs is important in managing IORs. The findings advance the management control literature and operations and supply chain management literature by illustrating that to trust and to control appear to be different approaches in managing IORs.
Table of contents
1. Introduction 4
2. Theoretical background 6
2.1. Management control mechanisms (MCMs) 6
2.2. Trust 8
2.3. Theoretical foundation 9
2.4. The interplay between trust and management control mechanisms in explaining performance
10
2.5. Hypothesis development 11
3. Methodology 15
3.1. Sample and data collection 15
3.2. Measures 16
3.3. Reliability and validity 18
4. Analysis and results 18
5. Discussion 22
6. Conclusion 25
6.1. Managerial implications 25
6.2. Limitations and future research 26
7. References 29
8. Appendices 34
Appendix A. Measurement instruments 34
1. Introduction
In today’s world, where organisations increasingly engage in inter-organisational relationships (IORs), they face the issue of how to effectively manage these IORs (Liu, Vredenburg, and Steel, 2014). The high failure rates of joint ventures and strategic alliances (Faems, Janssens, Madhok, and Van Looy, 2008; Cao and Lumineau, 2015), as well as the difficulties buying organisations experience in establishing high supplier performance (Huang, Cheng, and Tseng, 2014; Poppo, Zhou, and Li, 2016), spur the debate what factors explain and improve relationship performance. This study focuses on this debate in the context of buyer-supplier relationships, for which the importance is stressed to investigate how buyers manage the relationships with their suppliers to improve relationship performance (Cousins, Handfield, Lawson, and Petersen, 2006; Poppo et al., 2016).
Literature suggests two main factors that explain relationship performance: management control mechanisms (MCMs) and trust (e.g., Das and Teng, 1998; Poppo and Zenger, 2002; Lui and Ngo, 2004; Cao and Lumineau, 2015). Transaction cost economics (TCE) argues that formal contractual safeguards are the means to establish appropriate control in IORs and enhance relationship performance (Williamson, 1985; Faems et al., 2008; Zhou and Xu, 2012). Social exchange theory (SET) and relational exchange theory (RET), however, believe that TCE overstates the role of formal MCMs and neglects sociological aspects like trust and more social forms of control to successfully manage IORs (Ring and Van de Ven, 1992; Palmatier, Dant, and Grewal, 2007; Faems et al., 2008). Some scholars find trust and MCMs to be complementary; they address each other’s limitations and jointly improve relationship performance (Fryxell, Dooley, and Vryza, 2002; Poppo and Zenger, 2002; Cao and Lumineau, 2015). Others argue that trust and MCMs substitute in the light of relationship performance (Lui and Ngo, 2004; Malhotra and Lumineau, 2011). Contracts are not needed when a partner can be fully trusted, and when no trust is present contracts can compensate. To date, it remains unclear which theoretical stance explains the role of trust and MCMs on relationship performance best, and how trust and MCMs interact to improve relationship performance. To address these issues, I study how trust and MCMs jointly influence relationship performance.
Literature specifies two main typologies of MCMs. I choose social, behavioural, and output MCMs as types of MCMs, which are identified in the management control literature (Das and Teng, 1998, 2001; Turner and Makhija, 2006). This typology is preferred over the typology of relational and contractual governance that is often referred to in the operations and supply chain management literature, and groups trust together with social forms of control under the construct of relational governance (Cao and Lumineau, 2015). Management control scholars, however, argue that trust should be distinguished from MCMs and studied separately (Zaheer and Venkatraman, 1995; Das and Teng, 1998). As this study investigates the interplay between relational trust and MCMs, relational trust should be separated from MCMs, and the typology of social, behavioural, and output MCMs is used.
As previous literature is inconclusive about how trust and MCMs jointly impact relationship performance, I aim to shed more light on whether relational trust complements or substitutes social, behavioural, and output MCMs in explaining relationship performance in buyer-supplier relationships, leading to the following research question:
Do relational trust and social, behavioural, and output management control mechanisms function as complements or substitutes in explaining relationship performance in buyer-supplier relationships?
Buyer-supplier relationships provide the ideal context for this study. Trust and MCMs are important factors in many types of IORs (Svensson, 2001). Vertical IORs like buyer-supplier relationships are becoming more and more important since organisations increasingly make use of outsourcing and increasingly depend on suppliers for key resources and capabilities (Srinivasan, Mukherjee, and Gaur, 2011). The trust-control-performance inter-relationships are mainly studied for horizontal IORs (e.g., strategic alliances and joint ventures), but less for vertical IORs (Aulakh, Kotabe, and Sahay, 1996; Poppo and Zenger, 2002; Poppo et al., 2016). The high interdependence between a buyer and a supplier implies that buyer-supplier relationships leave sufficient potential for social MCMs and trust to come into play, besides relying on formal forms of control like behavioural and output MCMs (Cao and Lumineau, 2015).
relationships. Third, I seek to enrich TCE, SET, and RET by furthering the insights whether the TCE focus on behavioural and output MCMs is more appropriate, or that relational trust and social MCMs, as advocated by SET and RET, are more suitable in improving relationship performance.
This study is also of interest to practitioners. Managers who are tasked with managing buyer-supplier relationships should be aware of the importance of trust and MCMs in improving relationship performance. The right combination of types of trust and MCMs can help managers to achieve high relationship performance (Lui and Ngo, 2004; Cao and Lumineau, 2015).
The remainder of this study is organised as follows. Chapter 2 provides the theoretical background, hypothesis development, and conceptual model. Chapter 3 presents the methodology by outlining the sampling and data collection, as well as the measures included in the survey, and addresses reliability and validity concerns. Chapter 4 outlines the analyses performed to test the hypotheses and presents the results of the analyses. Chapter 5 reviews the results in light of the theory and literature discussed in Chapter 2. Chapter 6 ends this study with concluding remarks, managerial implications, limitations, and directions for future research.
2. Theoretical background
This chapter discusses the theoretical background of the research question. I discuss MCMs and trust first. Thereafter, I review the theoretical foundation and literature on trust and MCMs as complements and substitutes in explaining relationship performance. Subsequently, hypotheses are developed to outline the expected relationships.
2.1. Management control mechanisms (MCMs)
MCMs receive extensive attention in literature, but lack a widely agreed upon definition (Merchant and Van der Stede, 2012). This study takes a broad view on MCMs by defining them as “all the devices or systems managers use to ensure that the behaviours and decisions of their employees are consistent with the organisation’s objectives and strategies” (Merchant and Van der Stede, 2012: 6). This intra-organisational view on MCMs can be translated to a buyer-supplier relationship context as “all the devices or systems organisations use to ensure that the behaviour and decisions of their suppliers are consistent with the organisation’s objectives and strategies.
relations and shared norms and values to manage IORs (Das and Teng, 2001; Zhou and Xu, 2012). Behavioural and output MCMs are equivalent to contractual governance, since both use formal and written rules and contracts to outline the behaviours and responsibilities of the IOR partners (Das and Teng, 2001; Ryall and Sampson, 2009). However, one main difference exists between these literature streams. Where operations and supply chain management literature regards trust as a form of control within relational governance (Griffith and Myers, 2005; Liu et al., 2009; Cao and Lumineau, 2015), management control literature believes that trust cannot necessarily be seen as a form of control (Das and Teng, 1998). MCMs aim to influence and affect the behaviours and actions of IOR partners; trust does not do so (Das and Teng, 1998). Trust is about having a positive notion and attitude of the partner’s behaviour, norms, and values (Das and Teng, 1998; Rousseau et al., 1998). Additionally, trust involves the believe that the IOR partner performs in a way that is in alignment with the trustor’s best interests, even when no form of control is present (Das and Teng, 1998). To trust and to control are different aspects in relation to managing IORs, and the presence of trust determines to what extent IOR partners rely on which types of MCMs (Faems et al., 2008). When a partner can be fully trusted, there is no need for any form of MCMs (Das and Teng, 1998).
The typology of relational and contractual governance that the operations and supply chain management literature suggests does not suit the research question, as it regards trust as part of relational governance. Therefore, the typology offered by the management control literature is used to represent the different types of MCMs, since this literature stream argues that trust is not a MCM. This typology is discussed next.
Social MCMs encompass organisational values, norms, and cultures to evaluate IORs, encourage desired behaviour, and foster goal congruence between IOR partners (Das and Teng, 1998; Liu et al., 2014). This congruence leads to high commitment and motivation to reach the relationship goals, thereby reducing the need to contractually specify detailed rules and procedures (Das and Teng, 1998). As such, detailed written contracts are not of key importance (Dyer and Singh, 1998). In contrast, social sanctions and peer pressure are the means to control the IOR partner and enhance relationship performance (Cannon, Achrol, and Gundlach, 2000).
Behavioural MCMs measure and monitor the appropriateness of the process that leads to inter-organisational outcomes (Das and Teng, 2001). In contrast to social MCMs, writing contracts is important. In specifying each party’s preferred behaviour, behavioural MCMs reduce opportunism and form a safeguard for IORs (Williamson, 1985; Reuer and Ariño, 2002, 2007). Behavioural MCMs regulate partner behaviour, thereby reducing opportunism and increasing the predictability of the partner’s behaviour (Das and Teng, 1998; Poppo and Zenger, 2002). Examples of behavioural MCMs are standardised reporting programs and routines (Chen, Park, and Newburry, 2009), and information usage and exchange clauses (Das and Teng, 1998).
specify the rights and duties of the partners, as well as key performance measures, based on which the relationship performance can be evaluated and action (e.g., in the form of penalties) can be taken when the output does not conform to the standards set (Das and Teng, 2001; Ryall and Sampson, 2009). In a buyer-supplier relationship context, output MCMs are mainly concerned with the consistency and timeliness of production, services, and payments (Şengün and Wasti, 2007).
2.2. Trust
Trust is defined in the literature in many ways; a universally agreed upon definition does not seem to exist. Trust is defined consistent with previous research on trust in IORs as “a state of mind, an expectation held by one trading partner about another, that the other will behave in a predictable and mutually acceptable manner” (Sako, 1991: 377). When studying trust in IORs, it needs to be recognised that trust encompasses many different types due to its broad and diverse nature (Zaheer and Venkatraman, 1995; Lui and Ngo, 2004). It depends on the type of trust whether trust and MCMs complement or substitute each other (Jiang, Li, Gao, Bao, and Jiang, 2013).
Trust can be divided into a social and an economic dimension (Kramer, 1999; Schilke and Cook, 2015). March (1994) argues that social types of trust should be studied, because they value the decision maker’s intellectual capabilities correctly. Trust inherently is a social concept (McAllister, 1995; Kramer, 1999). Decisions on trust are based on social and relational bases, not on conscious calculation and rational bases (Kramer, 1999; Saparito et al., 2004). Within the social dimension, trust types like relational trust, goodwill trust, and affect-based trust are represented (McAllister, 1995; Kramer, 1999; Poppo and Zenger, 2002; Saparito et al., 2004). According to Rousseau et al. (1998) and Saparito et al. (2004), relational trust provides the most complete representation of the social trust dimension. Therefore, this study examines relational trust.
2.3. Theoretical foundation
In the literature, there are three main theories on the interplay between trust and MCMs in managing IORs and explaining relationship performance: transaction cost economics (TCE), social exchange theory (SET), and relational exchange theory (RET).
TCE takes an economic and contractual approach to managing IORs (Williamson, 1985, 1993). Opportunism and bounded rationality are its key behavioural assumptions and MCMs play an important role in addressing these behavioural assumptions (Williamson, 1985, 1993). Effectively designed MCMs reduce the potential that the IOR partner behaves opportunistically (Williamson, 1993). MCMs like contractual arrangements and safeguards can be used to protect against opportunism between organisations (Williamson, 1993; Palmatier et al., 2007), implying that TCE focuses on output MCMs to manage an IOR. Likewise, TCE covers aspects of behavioural MCMs. Behavioural MCMs can contractually specify how an IOR partner should behave and how this partner should carry out its operations (Parkhe, 1993; Reuer and Ariño, 2007), as well as how the partner will be monitored (Heide, Wathne, and Rokkan, 2007). However, due to bounded rationality, it is impossible to manage an IOR by contractual arrangements that account for all contingencies (Williamson, 1985; Chiles and McMackin, 1996; Cannon et al., 2000). Contracts inherently are incomplete, but can be useful in managing IORs and mitigating opportunism (Williamson, 1993). Alternative forms of control need to be present for effective control beyond the constraints of opportunism and bounded rationality; contracts cannot capture the social and relational aspect of IORs (Palmatier et al., 2007).
SET and RET complement the formal and contractual approach of TCE with a more social and relational approach (Palmatier et al., 2007; Faems et al., 2008). TCE recognises that transaction costs need to be seen in a social context and discusses trust as an important social factor, but nevertheless views trust as calculative rather than relational, thus still taking an economic perspective (Williamson, 1993; Cao and Lumineau, 2015). SET proponents argue that social factors, including a social approach to trust, need to be taken into account in addition to TCE perspectives in understanding IORs (Cook, 1977; Cook and Emerson, 1978; Granovetter, 1985). Trust is important in establishing a stable social relationship in IORs (Blau, 1964; Cropanzano and Mitchell, 2005). Hereby, SET extends the economic view of TCE on control with a sociological view. SET is mainly concerned with social relations rather than contracting, and shared norms and values are of key importance (Cao and Lumineau, 2015), similar to social MCMs (Das and Teng, 1998, 2001). SET contends that both trust and social MCMs are ways to address the limitations of the economic views of TCE (Cropanzano and Mitchell, 2005; Faems et al., 2008; Huang et al., 2014). According to SET, not only formal contracts can punish IORs; social relationships can do so as well (Blau, 1964; Cropanzano and Mitchell, 2005).
al., 2007). Whereas SET argues that social interactions and socially embedded relationships are key for effective governance and control, RET focuses on relational norms such as flexibility, information exchange, solidarity, and continuity expectations about the IOR (Heide and John, 1992; Aulakh et al., 1996). These relational norms are considered to be effective means to manage IORs (Aulakh et al., 1996; Cannon et al., 2000). MCMs only function well when a set of shared social values and relational norms in managing an IOR exists between the IOR partners (Kaufmann and Dant, 1992; Faems et al., 2008). These shared values and norms are the key control aspects of social MCMs. RET is mainly concerned with social MCMs when it comes to specifying which types of MCMs are most effective in IORs, as the main focus of RET is sociological rather than economic (Cao and Lumineau, 2015), and shared values and norms are considered important, (Zhou and Xu, 2012).
To conclude, the abovementioned theories theoretically underpin how organisations can effectively manage IORs using trust and MCMs. However, they do not agree upon what the interplay between trust and MCMs in explaining relationship performance exactly is, as is discussed next. 2.4. The interplay between trust and management control mechanisms in explaining performance
TCE, SET and RET provide a theoretical basis for understanding why and how trust and MCMs are important in IORs. Literature discusses the inter-relationships between trust, MCMs, and relationship performance in various ways. Broadly speaking, there is debate in the literature whether trust and MCMs are complements or substitutes in explaining relationship performance.
On the one hand, scholars regard trust and MCMs as substitutes in explaining relationship performance. TCE argues that formal contractual safeguards like behavioural and output MCMs are the most effective means to manage IORs and improve relationship performance (Williamson, 1985, 1993). TCE hereby gives only a minor role to trust. According to TCE, trust is important in IORs, but the focus should be on MCMs to improve relationship performance (Williamson, 1993). Contractual safeguards signal the lack of trust in IORs and undermine the development and presence of trust in IORs (Lui and Ngo, 2004; Jiang et al., 2013). Likewise, when a partner can be fully trusted, there is no need to spend time and resources on developing and establishing MCMs (Zaheer, McEvily, and Perrone, 1998; Inkpen and Currall, 2004; Ben-Ner and Putterman, 2009). Following this reasoning, the presence of a high degree of trust between the IOR partners implies that MCMs are less needed in the IOR. Consequently, these arguments suggest that trust and MCMs are substitutes in explaining relationship performance.
but formal contractual safeguards could counteract this abuse and breach of trust (Li, Poppo, and Zhou, 2010). From a different perspective, it is argued that contractual safeguards inherently are incomplete due to the bounded rationality of the IOR partners (Chiles and McMackin, 1996; Cannon et al., 2000). Trust aids in overcoming the bounded rationality by ensuring IOR partners that incompletenesses in the contract are dealt with in a fair manner (Chiles and McMackin, 1996). In these examples, trust and MCMs reinforce each other: a higher degree of trust improves relationship performance when it is accompanied by a higher degree of appropriate MCMs (Das and Teng, 1998; Beamish, 2013).
2.5. Hypothesis development
The discussion of the joint impact of trust and MCMs on relationship performance so far has mainly regarded these concepts as unidimensional. Since the theoretical foundation underlying trust, MCMs and relationship performance is discussed, as well as the differing views in theory and literature on the inter-relationships between trust and MCMs in explaining relationship performance, it is now time to investigate the inter-relationships between the specific types of trust and MCMs that are included in this study: relational trust and social, behavioural, and output MCMs.
Goodwill trust concerns “the expectation that some others in social relationships have moral obligations and responsibility to demonstrate a special concern for other’s interests above their own” (Barber, 1983: 14). It focuses on the belief that a partner acts in good faith and with the same intentions to establish a satisfactory and successful relationship (Nooteboom, 1996). Here, the overlap with the shared values, norms, motives and interests as key elements of relational trust becomes prevalent. Saparito et al. (2004) confirm this similarity by providing evidence of convergent validity between goodwill trust and relational trust (r = .76, p < .001). Affect-based trust and relational trust also share some key aspects. Affect-based trust encompasses trust based on emotional bonds between organisations (Lewis and Weigert, 1985). When an organisation believes that their partner cares about the relationship and is willing to satisfy each other’s needs, the relationship is based on affect-based trust (Lewis and Weigert, 1985). Chowdhury (2005) adds that affect-based trust, just as relational trust, concerns being considerate of shared values and interests between partners. Caring about each other and satisfying each other’s interests and needs are overlapping aspects of affect-based trust and relational trust. Furthermore, McAllister (1995) and McAllister, Lewicki, and Chaturvedi (2006) note that affect-based trust and goodwill trust overlap in the genuine concern for other parties in the relationship and satisficing each other’s intrinsic values. To conclude, relational trust, affect-based trust and goodwill trust are regarded as trust dimensions that are similar to some extent. Consequently, whilst previous research on affect-based trust and goodwill trust in relation to MCMs and relationship performance cannot be regarded as a perfect basis, it yields some insights into the expected relationships between relational trust and MCMs in the light of relationship performance.
output MCMs and goodwill trust as substitutes, and suggest that this substitutive effect is also in place when looking at how satisfied relationship partners are about the relationship.
Similar findings are reported for the relationship between affect-based trust and behavioural and output MCMs in explaining relationship performance. As affect-based trust suggests that relationship partners care about each other and are attentive to each others’ needs, a partner can believe that specifying behaviour and processes in a contract is not necessary (Lewicki and Bunker, 1996). This substitutive reasoning applies also the other way around. When a low degree of behavioural and output MCMs is to be included in a contract, this needs to be compensated for by a mutual understanding of each other’s expectations, and the values and norms that are important in the relationship (Fryxell et al., 2002). In both scenarios, affect-based trust substitutes with behavioural and output MCMs in explaining relationship performance.
To conclude, previous research finds a substitutive relationship between behavioural and output MCMs and either goodwill or affect-based trust in explaining relationship performance. I expect to find the same relation for behavioural and output MCMs and relational trust, and thus hypothesise the following:
Hypothesis 1: In buyer-supplier relationships, behavioural MCMs and relational trust function as substitutes in explaining relationship performance.
Hypothesis 2: In buyer-supplier relationships, output MCMs and relational trust function as substitutes in explaining relationship performance.
According to Poppo et al. (2016), relational trust is best accompanied by a socially focused control system in a relationship. Control systems that aim at goal congruence and social commitment of both parties improve relationship performance. Das and Teng (1998) suggest that goodwill trust is complementary to social MCMs, as goodwill trust in combination with social MCMs allows partners the autonomy and freedom to decide what is best for the relationship. The partners trust that their shared values and norms are lived by, and their mutual understanding of relationship goals is complied with.
interests are taken care of and that a more formal way of governing and monitoring the relationship is not necessary. Consequently, affect-based trust and social MCMs are complements in explaining relationship performance (Fryxell et al., 2002). Social MCMs must be complemented by affect-based trust to improve relationship performance. Das and Teng (2001) argue similarly, even though they focus on goodwill trust. Social MCMs aim at creating shared goals, beliefs and norms. Hereby, the mutual understanding between the partners about what is important in the relationship is increased, and partners internalise the relationship goals. This process increases the partner’s commitment and motivation and breeds goodwill trust.
Based on the presented suggestions and empirical evidence in previous literature, I hypothesise that social MCMs and relational trust complement each other in explaining relationship performance:
Hypothesis 3: In buyer-supplier relationships, social MCMs and relational trust function as complements in explaining relationship performance.
The conceptual model in Figure 1 displays the hypotheses. Figure 1. Conceptual model
Notes.
“–“ represents a substitutive effect on relationship performance “+” represents a complementary effect on relationship performance
3. Methodology
This chapter discusses the methodology of this study. First, I present the sampling and data collection procedure. Thereafter, I discuss the measures that are included in the survey. Subsequently, I explain how the reliability and validity of this study is ensured.
3.1. Sample and data collection
The hypotheses require key informant data from the buyer, the supplier, or both sides of a buyer-supplier relationship. In line with the majority of survey research on IORs, this study relies on single informants from the buyer-side of the relationship only (e.g., Lui and Ngo, 2004; Cousins et al., 2006; Poppo et al., 2016). Supply chain management stresses that it is important to investigate how buyers manage the relationships with their suppliers to improve relationship performance (Cousins et al., 2006). Following other studies on trust and MCMs, I collect data through a survey (e.g., Poppo and Zenger, 2002; Lui and Ngo, 2004; Şengün and Wasti, 2007; Schilke and Cook, 2015).
This study focuses on organisations involved in manufacturing activities, since they contain a wide range of purchasing arrangements and provide a sampling frame of adequate size (Zaheer et al., 1998; Schilke and Cook, 2015). Supply chain and purchasing managers are the key informants, as they are most knowledgeable on buyer-supplier relationships (Poppo et al., 2016). Target respondents are identified through researching member lists of manufacturing industry associations. Hereby, a sample of 1985 target respondents is build, occasionally involving multiple target respondents from the same organisation. Not all organisations report the contact details of their supply chain or purchasing managers and staff publicly on the Internet. Therefore, the contact details consist of general organisational contact information, as well as specific departmental and employee contact information. The survey is pretested by seven master and PhD students on the structure, clarity of instructions, and use of language. The survey is improved based on the feedback on the completeness, relevance, and wording of the items. Furthermore, a Dutch version of the survey is developed as the majority of the organisations in the sample is Dutch. This version is pretested in the same manner, focusing on its clarity, consistency and accuracy in comparison with the original English survey items.
Non-responding organisations receive a reminder to participate after two weeks to increase the response rate, following Dillman (1978, 2007). Respondents who partially completed the survey are contacted and asked to complete the survey. After one wave of reminders, the final sample consists of data on 128 buyer-supplier relationships, including eight partially completed surveys that provide data on the key variables of the study, but not on the demographics of the respondents. 28 contact details out of the initial sample of 1985 proved to be incorrect, ultimately resulting in an effective response rate of 6.54%. The majority of the respondents are Dutch and are employed in The Netherlands (93.3%, n = 120; and 94.2%, n = 120, respectively) within an organisation that is smaller than its supplier in terms of the number of employees (54.7%, n = 128). The majority of the respondents purchase products from its supplier that belong to the chemicals sector (57.8%, n = 128), and does business with its supplier for more than 10 years (65.6%, n = 128). Following Cannon and Perreault (1999), I add three questions to the survey about the respondent’s confidence in completing the survey, and his/her involvement with and knowledgeability about the relationship with his/her supplier. The mean for these three questions is 6.04 on a seven-point Likert scale, indicating that the respondents have sufficient knowledge about the supplier and the buyer-supplier relationship when filling out the survey.
Non-response bias is assessed for internal validity concerns (Zaheer et al., 1998). To test for non-response bias, early and late respondents are compared on several key variables: organisation age, relative size difference, length of prior organisational relationship with the supplier, length of prior personal relationship with the supplier, and supplier performance. Hereby, it is assumed that late respondents are similar to non-respondents (Armstrong and Overton, 1977). The first and last quartiles of the early and late returned surveys are compared on the key variables for significant mean differences using independent samples t-tests. The results of the t-tests do not indicate significant differences between early and late respondents at the 95 per cent confidence level, suggesting that non-response bias is not a serious problem.
Common method bias is a typical issue in survey research. Common method bias is a serious problem when a factor analysis shows that a single factor accounts for the majority of the variance. Harman’s one-factor test is performed by loading all items of the independent and dependent variables in an unrotated exploratory factor analysis (Podsakoff and Organ, 1986). This test extracts five factors with eigenvalues larger than 1. These five factors explain 74.41 per cent of the variance, with the first factor explaining only 27.58 per cent of the total variance. This indicates that common method bias is unlikely to be a serious problem in this study.
3.2. Measures
Social MCMs is measured using a measurement scale adapted from Şengün and Wasti (2007). This scale includes items that focus on how organisations cooperate and communicate, and whether transaction partners understand each other. Five items measure social MCMs. Even though its reliability reported by Şengün and Wasti (2007: α = .68) does not meet the conventional threshold of .70 (Nunnally, 1978), since it is close to this threshold and it is used in a study on buyer-supplier relationships, this scale is perceived appropriate for this study.
Behavioural MCMs is measured using a three-item measurement scale adapted from Bai, Sheng, and Li (2016). This scale is perceived to be suitable for this study, as it focuses on buyer-supplier relationships. The questions focus on the degree to which behavioural MCMs are present in the contract between the buyer and the supplier, and more specifically on provisions for technological standards, as well as the buyer’s right to audit supplier’s manufacturing procedures and inspect the supplier’s facilities.
Output MCMs is measured using a three-item measurement scale adapted from Bai et al. (2016). This scale is perceived appropriate for this study, as it focuses on buyer-supplier relationships. The questions focus on the extent to which output MCMs as interim goals, performance standards, and delivery deadlines are specified in the contract between the buyer and the supplier.
Relational trust is measured using a measurement scale adapted from Poppo et al. (2016). This measurement scale is deemed appropriate for this study, due to its focus on a buyer-supplier relationship. Three items measure relational trust, focusing on the degree of a shared identity and understanding among the relationship partners, as well as the degree to which they think like one another.
Relationship performance is studied using the measurement scale of Poppo et al. (2016) on supplier performance. This scale is selected since supplier performance is widely regarded as an appropriate measure of relationship performance in studies on inter-organisational relationships that take a buyer-perspective (Zaheer et al., 1998; Cannon and Perreault, 1999; Poppo et al., 2016). With this four-item scale, respondents evaluate the relationship performance by their perception of the performance of the supplier on aspects as the quality, cost, and delivery of the supplied product. This scale is measured on a seven-point Likert-scale where “1” represents “needs great improvement” and “7” represents “excellent”.
Ngo, 2004). Prior partner experience is measured by the number of years the buyer has done business with its supplier.
3.3. Reliability and validity
Factor analysis ensures the convergent and discriminant validity (Karlsson, 2009). Before a factor analysis is performed, the Kaiser-Meyer-Olkin (KMO) test and the Bartlett’s test of sphericity assess the sampling adequacy. The KMO score of .761 exceeds the conventional threshold of .500, and Bartlett’s test of sphericity is highly significant (p = .000). This indicates sufficient sampling adequacy and thus allows the execution of a factor analysis.
A confirmatory factor analysis (CFA) is performed for a 5-factor model using SPSS AMOS 24 to ensure that the survey items load on separate variables. The CFA based on all survey items yields acceptable factor loadings ranging from .65 to .97 and acceptable Cronbach’s alphas ranging from .75 to .89. A number of fit indices are used to evaluate the model fit: the comparative fit index (CFI), the incremental fit index (IFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA). The model fit, however, is insufficient (CFI < .90; IFI < .90; TLI < .90; RMSEA > .08). Therefore, items should be deleted to resolve model fit issues. Appendix A reports the results of the analysis after item deletion, including the factor loadings, goodness of fit indices, and Cronbach’s alphas. After removing one item for behavioural MCMs and one item for output MCMs, the goodness of fit indices indicate an acceptable model fit (CFI = .93; IFI = .93; TLI = .91; RMSEA = .08). Therefore, the model fits the data satisfactorily (Anderson and Gerbing, 1988). All factor loadings remain sufficiently high and positive, ranging from .65 to .97, providing evidence of convergent and discriminant validity.
After item deletion, the Cronbach’s alphas of the constructs range from .76 to .91, meeting the conventional threshold of .70 (Nunnally, 1978). The average variance extracted (AVE) for the constructs ranges from .58 to .84, exceeding the threshold of .50 (Fornell and Larcker, 1981). The Cronbach’s alphas and AVE indicate sufficient convergent validity and reliability of all multi-item scales. Furthermore, the maximum shared variance (MSV) and average shared variance (ASV) are smaller than the AVE, demonstrating additional evidence of discriminant validity. The inter-correlations of the constructs are calculated to ensure discriminant validity and reliability, and should not exceed .700 (Tabachnick and Fidell, 2001). The highest inter-correlation is 0.380, demonstrating satisfactory discriminant validity and reliability (see Table 1).
4. Analysis and results
correlations are rather low; the highest correlation is found for behavioural MCMs and output MCMs (r = .380, p < .01). This is not surprising, as scholars occasionally group these two MCMs as formal MCMs (e.g., Das and Teng, 1998, 2001; Jiang et al., 2013; Huang et al., 2014). It is of some interest that the correlation between prior partner experience and relational trust is low (r = .045, ns), despite the fact that prior partner experience between organisations often is regarded as a source of trust (Lui and Ngo, 2004).
Table 1. Descriptive statistics and correlations
Variable Mean S.D. 1 2 3 4 5 1 Relationship performance 5.72 .79 2 Social MCMs 5.91 .85 -.339*** 3 Behavioural MCMs 4.46 1.95 -.024 .137 4 Output MCMs 5.39 1.39 -.001 .278*** -.380*** 5 Relational trust 4.19 1.37 -.102 .247*** -.108 .149*
6 Prior partner experience 4.54 .72 -.184** .071 -.143 .002 .045 Note: N = 128; *p < .10; **p < .05; ***p < .01 (two-tailed)
Table 2. Results of hierarchical multiple regression
Variable Relationship performance
Model 1 Model 2 Model 3
Control variable Prior experience 0.255** (.122) -0.216** (.118) -0.197** (.116) Direct effects Social MCMs -0.351*** (.089) -0.320*** (.088) Behavioural MCMs 0-.016 (.092) 0-.029 (.090) Output MCMs 0-.097 (.093) 0-.034 (.097) Relational trust (RT) -0.025 (.087) -0.024 (.086) Interaction effects RT x Social MCMs 0-.034 (.070) RT x Behavioural MCMs -0.122* (.086) RT x Output MCMs -0.154** (.084) R2 0.034 -0.151 -0.205 F-value 4.400** -4.336*** -3.832*** ΔR2 -0.117 -0.054 ΔF -4.208*** -2.691**
Notes: N = 128; *p < .10; **p < .05; ***p < .01 (one-tailed); standard errors reported in parenthesis.
to 1.397) and above .1 (ranging from .716 to 1.000), respectively. Consequently, multicollinearity is not a serious problem. The addition of the interaction terms increases the R2 of Model 3 to .205 over .151 in Model 2, demonstrating a significant change of .054 (p < .05) over Model 2.
A simple slope analysis plots the interactions between relational trust and the MCM types to better understand the effects of the interaction terms on relationship performance, as is discussed next. Plots are made for when relational trust is one standard deviation above and below the mean. The above-mean value is interpreted as high relational trust, and the below-mean value is interpreted as low relational trust. Figures 2 to 4 present these plots.
Figure 2. The interaction effects of relational trust and behavioural MCMs on relationship performance.
Figure 3. The interaction effects of relational trust and output MCMs on relationship performance. -1,2 -1 -0,8 -0,6 -0,4 -0,2 0
Low behavioural MCMs High behavioural MCMs
R el ati on sh ip p er for man ce Low relational trust High relational trust -1,2 -1 -0,8 -0,6 -0,4 -0,2 0
Low output MCMs High output MCMs
Figure 4. The interaction effects of relational trust and social MCMs on relationship performance.
Hypothesis 1 predicts that relational trust and behavioural MCMs substitute in explaining relationship performance. The direct effect of behavioural MCMs on relationship performance is negative and insignificant (β = -.016, p > .10), as shown in Model 2. As shown in Model 3, the interaction term of relational trust and behavioural MCMs is positive and marginally significant (β = .122, p < .10). From Figure 2, it follows that relationship performance is better when both a high level of behavioural MCMs and relational trust are present, compared to when one of both is high and the other low. Thus, behavioural MCMs and relational trust are complements instead of substitutes in explaining relationship performance, and Hypothesis 1 is not supported.
Hypothesis 2 predicts that relational trust and output MCMs substitute in explaining relationship performance. The direct effect of output MCMs on relationship performance is negative and insignificant (β = -.097, p > .10), as shown in Model 2. As shown in Model 3, the interaction term of relational trust and output MCMs is positive and significant (β = .154, p < .05). From Figure 3, it follows that relationship performance is better when both a high level of output MCMs and relational trust are present, compared to when one of both is high and the other low. Thus, output MCMs and relational trust are complements instead of substitutes in explaining relationship performance, and Hypothesis 2 is not supported.
Hypothesis 3 predicts that relational trust and social MCMs complement in explaining relationship performance. As shown in Model 3, the interaction term of relational trust and social MCMs is insignificant (β = -.034, p > .10). Where the direct effect of social MCMs on relationship performance is positive and highly significant (β = .351, p < .01), the interaction with relational trust is negative and insignificant. Figure 4 shows that when a low level of social MCMs is present, a high level of relational trust slightly improves relationship performance compared to low levels of relational trust. Figure 4 illustrates that the level of relational trust under high levels of social MCMs is
-1,4 -1,2 -1 -0,8 -0,6 -0,4 -0,2 0
Low social MCMs High social MCMs
irrelevant. Thus, in combination with the insignificant interaction effect of relational trust and social MCMs in Model 3 of the regression analysis, it can be concluded that Hypothesis 3 is not supported. 5. Discussion
This study investigates the joint impact of relational trust and social, behavioural, and output MCMs on relationship performance. It hypothesises that relational trust interacts differently with the three types of MCMs in explaining relationship performance. The empirical results indicate that relational trust and behavioural MCMs function as complements in explaining relationship performance. The same complementary relationship is found for relational trust and output MCMs. No significant joint impact of relational trust and social MCMs on relationship performance is found in this study. The results contribute to literature and theory in several ways, as set out below.
understand how they explain relationship performance in buyer-supplier relationships, and IORs in general.
Second, this study shows how relational trust and social MCMs interact in explaining relationship performance. Interestingly, the result for the joint impact of social MCMs and relational trust on relationship performance (Hypothesis 3) does not yield conclusive results. The direct effect of social MCMs on relationship performance is positive and significant, implying that a social approach to controlling a buyer-supplier relationship is important and can improve relationship performance. When relational trust comes into play, this positive effect is eroded. The degree of relational trust is irrelevant when the relationship is controlled solely by social MCMs (see Figure 4). This contradicts Poppo et al. (2016), who argue that social MCMs are best accompanied by relational trust in improving relationship performance. Consequently, it can be concluded that a high degree of social MCMs does not need to be accompanied by relational trust to improve relationship performance in buyer-supplier relationships, contrary to what was hypothesised. This contradicting finding could be found because social MCMs already encompass trust in its focus on organisational values, norms, and cultures. However, if relational trust were similar to social MCMs, I would expect a stronger correlation between both constructs (r = .247, p < .01), and I would expect relational trust to be complementary to social MCMs in explaining relationship performance. I find no complementary relationship, and the rather low correlation makes it difficult to regard relational trust and social MCMs as similar forms of control. This might imply that the operations and supply chain management literature might have to reconsider whether (relational) trust and social MCMs can be grouped under the construct of relational governance. A better explanation for the contradicting result might be that since social MCMs provide a social control approach to managing buyer-supplier relationships, a social type of trust is superfluous in improving relationship performance. Only one social approach to managing buyer-supplier relationships is important: relational trust or social MCMs. Where both the direct effects of social MCMs and relational trust on relationship performance are positive, their joint impact on relationship performance is negative. In the context of this study, social MCMs are preferred; only the social MCMs approach can significantly improve relationship performance. Consequently, it can be concluded that a social approach to trust might not be the same as a social approach to MCMs in explaining relationship performance of buyer-supplier relationships, thereby adding to the argument of management control scholars that to trust and to control are two different aspects in IORs (Das and Teng, 1998; Faems et al., 2008). Therefore, operations and supply chain scholars might reconsider whether they view trust, and social dimensions of trust in particular, as part of the relational governance form.
and RET both argue that a social approach to control is best when organisations decide on what types of MCMs to employ in IORs (e.g., Cannon et al., 2000; Cropanzano and Mitchell, 2005; Faems et al., 2008; Cao and Lumineau, 2015). The results show that of the three MCMs included in this study, only social MCMs have a significant positive effect on relationship performance, thereby confirming the SET and RET view that social forms of control are most effective in improving relationship performance, as opposed to the economic forms of control that TCE proposes. TCE does recognise that a social context factor like trust is important to consider in IORs, but where TCE proposes an economic type of trust, namely calculative trust (Williamson, 1993), the results show that a social type of trust, relational trust, is complementary to behavioural and output MCMs in explaining relationship performance. Hereby, this study extends TCE by showing that besides the proposed economic approach to trust (Williamson, 1993), a social approach to trust would be important to consider as well as a complementary element to behavioural and output MCMs in explaining relationship performance. This finding supports the view of SET that trust is essential to establish successful IORs (Cropanzano and Mitchell, 2005; Palmatier et al., 2007), and compared with TCE a more social approach to trust like relational trust is necessary to understand IORs (Cook, 1977; Cook and Emerson, 1978; Granovetter, 1985). Relational trust can help to overcome and address the limitations of opportunistic behaviours and bounded rationality in TCE. Hereby, a combination of TCE and SET perspectives in managing IORs can lead to improved relationship performance. Additionally, SET contends that both trust and social MCMs are ways to address the limitations of the economic views of TCE (Cropanzano and Mitchell, 2005; Huang et al., 2014). However, no significant interaction effect is found between relational trust and social MCMs, implying that the presence of both relational trust and social MCMs does not improve relationship performance. Rather, the results extend SET by showing that when social MCMs are present, relational trust is not necessary in the relationship. However, when IOR partners rely on MCMs other than social MCMs, relational trust should be present to achieve satisfactory relationship performance.
6. Conclusion
The main objective of this study is to investigate the joint impact of specific types of trust and MCMs on the performance of supplier relationships. Using empirical survey data of the buyer-perspective of 128 buyer-supplier relationships, the research question that this study answers is as follows: do relational trust and social, behavioural, and output management control mechanisms function as complements or substitutes in explaining relationship performance in buyer-supplier relationships?
By answering this research question, this study has provided three main contributions. First, the results advance the insights in the debate whether specific types of trust and MCMs are complements or substitutes in explaining relationship performance (e.g., Fryxell et al., 2002; Poppo and Zenger, 2002; Lui and Ngo, 2004; Cao and Lumineau, 2015). The results suggest that a social type of trust, relational trust, is complementary to more formal MCMs, i.e., behavioural and output MCMs, in explaining relationship performance. On the contrary, no clear complementary or substitutive relationship is found for relational trust and social MCMs in explaining relationship performance.
Second, this study contributes to the operations and supply chain management literature (Griffith and Myers, 2005; Liu et al., 2009; Cao and Lumineau, 2015) and the management control literature (Das and Teng, 1998, 2001; Turner and Makhija, 2006) by illustrating that to trust and to control appear to be different aspects in managing IORs. The results suggest that the view of management control scholars that trust is not a form of control might be more appropriate than the view of operations and supply chain management scholars who regard trust as a form of control and group trust together with social MCMs as relational governance.
Third, this study empirically advances the theoretical arguments of TCE, SET, and RET regarding the inter-relationships between trust, control, and performance. This study enriches TCE literature (Williamson, 1985, 1993) by showing that relying only on formal MCMs – behavioural and output MCMs – does not lead to improved relationship performance. The results support SET (Granovetter, 1985; Cropanzano and Mitchell, 2005; Faems et al., 2008) and RET (Aulakh et al., 1996; Palmatier et al., 2007; Faems et al., 2008) by showing that relying only on social MCMs can improve relationship performance. This illustrates that the social and relational SET and RET perspectives on control are better suitable for improving relationship performance than the economic TCE perspective. Furthermore, a social type of trust, namely relational trust, can complement behavioural and output MCMs in improving relationship performance. Here, the combination of TCE and SET perspectives can improve relationship performance.
6.1. Managerial implications
highlight the importance of taking trust and MCMs into account in managing buyer-supplier relationships and achieving satisfactory relationship performance. When relying solely on MCMs to manage the buyer-supplier relationship, and not on trust, social MCMs can achieve the best relationship performance. This study cautions against relying too narrowly on extensive contractual safeguards like behavioural and output MCMs, as these are negatively related to relationship performance. Rather, managers should invest in developing social MCMs, i.e., shared values, norms, and cultures between the buyer and the supplier. However, when behavioural and output MCMs are accompanied by the presence of relational trust between the buyer and the supplier, the combination of this type of trust and one of these types of MCMs can foster satisfactory relationship performance. Therefore, in addition to contracts, supply chain and purchasing managers should value the importance of developing relational trust for improving relationship performance. Furthermore, the number of years that the buyer has done business with its supplier is positively related to the relationship performance. This suggests that relationship performance improves over time, and supply chain and purchasing managers might thus be cautious with terminating the relationship with a supplier that does not perform as expected in the early years of the relationship. Rather, managers should aim at developing long-term relationships with their suppliers. As the relationship length increases, the buyer and the supplier can accumulate experience in contracting and relationship building with each other. This experience can be used for the benefit of the relationship, and relationship performance might be improved.
6.2. Limitations and future research
Besides the aforementioned contributions, this study has also several limitations that provide interesting avenues for future research. First, the representativeness of the sample raises the usual reservations regarding the generalisability of the findings. The sampling frame consists nearly completely of Dutch organisations, and only focuses on organisations engaged in manufacturing activities. Thus, generalising the results to other countries and industries may be unwarranted. Surely, cultural aspects can affect trust and MCMs (Fryxell et al., 2002). Similarly, a country’s legal system may influence the legal enforceability of contractual safeguards (Poppo and Zenger, 2002). The relationships this study finds may for example be different for Asian buyer-supplier relationships. Therefore, future research on trust, MCMs and performance in other countries and industries is advised to make better inferences about how trust, MCMs and performance are inter-related in buyer-supplier relationships.
research could investigate the joint impact of relational trust and social, behavioural, and output MCMs on relationship performance in horizontal IORs.
Third, this study focuses on the buyer-side of buyer-supplier relationships, without data from suppliers about their view on relational trust, social, behavioural, and output MCMs, and relationship performance in the buyer-supplier relationship. This inevitably brings about certain reservations about the generalisability of the findings, as this study does not investigate whether asymmetric views exist of the trust that is present between the partners, an under-researched topic in the literature on trust and control (Zaheer and Zaheer, 2006; Graebner, 2009; De Jong and Dirks, 2012). Even though there is evidence that partners have similar perceptions of trust in IORs (e.g., Anderson and Narus, 1990; Zaheer et al., 1998), future research that includes respondents from both the buyer- and the supplier-perspective would be valuable.
Fourth, this study only examines a social type of trust, relational trust; it does not investigate the relationships between multiple types of trust and the three types of MCMs. Future research could study multiple types for both trust and MCMs. The classifications of the types of trust (Kramer, 1999; Lui and Ngo, 2004; Jiang et al., 2013) and MCMs (Luo, 2005; Chen et al., 2009; Malhotra and Lumineau, 2011) are not consistent across the existing literature. How different types of trust and MCMs interact and influence supply chain management is an emerging area of research (Malhotra and Lumineau, 2011). As Jiang et al. (2013) argue, it depends on the type of trust whether trust and MCMs complement or substitute in explaining relationship performance. Therefore, multiple and preferably diverse types of trust and MCMs should be studied in future research to better understand how they explain relationship performance. In addition to relational trust, calculative trust could for example be included in future research, as it is regarded as an economic type of trust and as the opposite of relational trust (Kramer, 1999).
Fifth, this study regards trust and MCMs as static rather than dynamic constructs. However, trust and MCMs cannot necessarily be regarded as static concepts; their manifestation in IORs might change over time (Inkpen and Currall, 2004). Also, the conceptual arguments and empirical analyses only concern on-going buyer-supplier relationships. However, trust might already play an important role in the early stages of buyer-supplier relationships, for example in the partner search and selection phase (McKnight, Cummings, and Chervany, 1998; Schilke and Cook, 2015). The positive effect of the length of the prior partner experience on relationship performance suggests that temporal dynamics between trust and MCMs in influencing relationship performance could be at play. Therefore, future research could focus on longitudinal data to more closely investigate how the interplay of trust and MCMs evolves as the buyer-supplier relationship progresses.
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