The effects of supply chain collaboration on performance and transaction cost advantage: The moderation and nonlinear effects of governance mechanisms

Accepted Manuscript The effects of supply chain collaboration on performance and transaction cost advantage: The moderation and nonlinear effects of governance mechanisms Ki-Hyun Um, Sang-Man Kim PII:

S0925-5273(18)30150-6

DOI:

10.1016/j.ijpe.2018.03.025

Reference:

PROECO 6995

To appear in:

International Journal of Production Economics

Received Date: 21 February 2017 Revised Date:

30 October 2017

Accepted Date: 27 March 2018

Please cite this article as: Um, K.-H., Kim, S.-M., The effects of supply chain collaboration on performance and transaction cost advantage: The moderation and nonlinear effects of governance mechanisms, International Journal of Production Economics (2018), doi: 10.1016/j.ijpe.2018.03.025. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Title Page

Manuscript Title: The Effects of Supply Chain Collaboration on Performance and Transaction Cost

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Advantage: the Moderation and Nonlinear Effects of Governance Mechanisms

Address

Affiliation

E-mail / Fax

First Author

Ki-Hyun Um

30, Pildongro 1gil, Junggu, Seoul, 04620, Korea

Corresponding Author

Sang-Man Kim

#405, Dongdaemoongu, Seou Orbis hall, School of Management, Kyung Hee University, 1 Hoegi-dong, Dongdaemun l, South Korea

Survey & Health Policy Research Center Dongguk University, Seoul, Korea School of Management, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul, Korea

[email protected]

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Name

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[email protected] Fax : 0082-2-961-0515

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Funding

This work was supported by Kyung Hee University [grant number 20160694]

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Abstract

A buying firm attempts to seek economic and social benefits through supply chain collaboration. Successful

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collaboration is predicted not only to strengthen a buying firm performance but also to reduce transaction costs. Establishment of an appropriate governance is of a great help in stabilizing a relationship and strengthening performance. Therefore, this study aims to identify underlying factors that constitute collaboration and transaction cost advantage, to explore effects of supply chain collaboration on firm performance and transaction cost advantage, and to examine the moderation effect of governance mechanisms in the proposed relationships. Data were obtained via a web survey of Korean manufacturing firms across different industry sectors. Confirmatory factor analysis was performed to assess the unidimensionality, reliability, and validity of a largescale survey and hierarchical regression analysis was conducted for the hypotheses testing. The results indicated that supply chain collaboration leads to better firm performance and transaction cost advantage and that

ACCEPTED MANUSCRIPT performance results in transaction cost advantage. A further analysis of the moderation effect of governance mechanisms indicated that firm performance with contractual governance yields better transaction cost advantage and that supply chain collaboration with contractual governance results in better transaction cost advantage than with relational governance. The findings contribute to the supply literature by providing

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theoretical and empirical implications. In theory, various collaborative practices in the supply chain and types of transaction cost are identified. Valid and reliable scales are also confirmed through successive stages of measurement analysis. In practice, clear definition of supply chain collaboration offers guidance in designing appropriate and effective collaborative activities which can result in a better performance. Managers are also

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advised to identify contexts in which either a contractual governance or a relational governance can be best utilized.

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Keywords: supply chain collaboration, firm performance, transaction cost advantage, governance

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mechanisms, moderation and curvilinear effects

ACCEPTED MANUSCRIPT The Effects of Supply Chain Collaboration on Performance and Transaction Cost Advantage: the Moderation and Nonlinear Effects of Governance Mechanisms

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Abstract

A buying firm attempts to seek economic and social benefits through supply chain collaboration. Successful collaboration is predicted not only to strengthen a buying firm performance but also to

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reduce transaction costs. Establishment of an appropriate governance is of a great help in stabilizing a relationship and strengthening performance. Therefore, this study aims to identify underlying factors

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that constitute collaboration and transaction cost advantage, to explore effects of supply chain collaboration on firm performance and transaction cost advantage, and to examine the moderation effect of governance mechanisms in the proposed relationships. Data were obtained via a web survey of Korean manufacturing firms across different industry sectors. Confirmatory factor analysis was

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performed to assess the unidimensionality, reliability, and validity of a large-scale survey and hierarchical regression analysis was conducted for the hypotheses testing. The results indicated that supply chain collaboration leads to better firm performance and transaction cost advantage and that

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performance results in transaction cost advantage. A further analysis of the moderation effect of governance mechanisms indicated that firm performance with contractual governance yields better

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transaction cost advantage and that supply chain collaboration with contractual governance results in better transaction cost advantage than with relational governance. The findings contribute to the supply literature by providing theoretical and empirical implications. In theory, various collaborative practices in the supply chain and types of transaction cost are identified. Valid and reliable scales are also confirmed through successive stages of measurement analysis. In practice, clear definition of supply chain collaboration offers guidance in designing appropriate and effective collaborative activities which can result in a better performance. Managers are also advised to identify contexts in which either a contractual governance or a relational governance can be best utilized.

ACCEPTED MANUSCRIPT Keywords: supply chain collaboration, firm performance, transaction cost advantage, governance mechanisms, moderation and curvilinear effects

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Introduction Over the last two decades, firms have relied heavily on collaboration with partners to seize internal and external opportunities (Cao and Zhang, 2011; Wallenburg and Schäffler, 2014). Collaboration

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refers to more than two parties’ working together with the pursuit of completing tasks and eventually achieving joint goals (Liao et al., 2017). Firms have strategically recognized the importance of supply

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chain collaboration (SCC) (Abdi and Aulakh, 2017; Chen et al., 2017) to seek higher efficiencies in sourcing, planning, producing, and distributing (Soosay and Hyland, 2015). SCC enables firms to share gains and losses, greatly extend their resources and capabilities beyond their boundaries, and exchange key information, thus eventually resulting in better performance and overall cost reduction (Cao and Zhang, 2011; Chen et al., 2017). Many a global company such Samsung, Sony, Apple, and

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IBM have relied heavily on close collaboration with their partners for sustainable competitive advantage. Supply chains are now being exposed to more dynamic environments, caused by globalization and competition, rapid growth in technologies, and fluctuations in customer demand,

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and therefore focus firms more on collaborative efforts (Soosay and Hyland, 2015).

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Despite the history and benefits of SCC, many partnerships suffer from unwanted outcomes (Fawcett et al., 2015). Those poor outcomes may result from uncertainty (Katsikeas et al., 2009), goal incongruence (Prosman et al., 2016), and absence of governances (Huang et al., 2014) that can effectively control and manage the relationships. The potential causes that jeopardize improvements in performance have prevented numerous firms from harvesting advantages of SCC (Fawcett et al., 2015). SCC seems to be of great importance, but extant literature challenges SCC, arguing that the concept is incomplete in terms of its conceptualization (Flynn et al., 2010). Various definitions of SCC have yielded inconsistent findings, suggesting that components of collaboration can be contingent upon contextual variables such as relation length, supplier involvement, and dependency

ACCEPTED MANUSCRIPT (Cao and Lumineau, 2015; Cao and Zhang, 2011). A rich body of literature has concentrated on the operationalization of SCC that broadens our understandings of its concept on this expanding area (Blome et al., 2014; Chen et al., 2017; Gimenez and Sierra, 2013; Grekova et al., 2014; Lu et al., 2012; Ramanathan and Gunasekaran, 2014). However, the current understanding of SCC offers few

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frameworks for accurately capturing the extent of SCC (Cao and Zhang, 2011). Existing theories have provided support for the development of SCC. For instance, the Resource-based view (RBV) theory argues that firms can achieve sustainable advantages by combining resources (e.g., core competence,

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dynamic capability, absorptive capacity) in a unique way (Barney, 1991). According to RBV, a buying firm can strengthen core values by investing in relation-specific assets and exploiting resources,

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knowledge, and know-how of its key suppliers, all of which make it challenging for its competitors to imitate (Cao and Zhang, 2011; Fawcett et al., 2015; Jap, 2001). This view explains that a buying firm’s superiority can be yielded through heterogeneity (Cao and Zhang, 2011). The Relational view (RV) theory suggests that superior performance is generated within networks (Dyer and Singh, 1998). This view delineates that firms can cultivate supernormal profit that cannot be made by either firm in

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isolation but can be generated only through an exchange relationship (Dyer and Singh, 1998; Cao and Zhang, 2011). The transcendent value can be elaborated when collaborative partners share and combine idiosyncratic resources and knowledge through investment in relation-specific assets,

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knowledge-sharing routines, and the establishment of effective governance modes (Fawcett et al., 2015). Those theories emphasize the importance of collaboration by taking non-relational and

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relational aspects of collaboration into account. An integrated approach to SCC yields the better predictability of evaluating impacts of SCC on performance. Therefore, we will identify the nature and characteristics of SCC and investigate its impact on firm performance. Second, in the examination of consequences of SCC, existing literature has unexplored transaction cost advantage achieved through SCC. Transaction costs are expenses incurred in transactional processes, from searching exchange partners and negotiating and enforcing contracts, to monitoring performance and adjusting to situational conditions (Williamson, 2008). While collaboration with suppliers creates a source of sustained competitive advantage, supplier opportunism may threat to the

ACCEPTED MANUSCRIPT achievement of a joint goal (Huang et al., 2014; Xie et al., 2016). Supplier opportunism, viewed as a supplier’s self-interest-seeking behaviors with guile (Williamson, 1991), endangers an exchange relationship because the supplier is likely to show diminished responsibilities, deliver incorrect information, or make false promises (Yan and Kull, 2015). Such behaviors expose a buying firm to

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transaction risks regarding disappointing returns on investment in the relationship or leakage of valuable assets (Yan and Kull, 2015). Supplier opportunism seems likely to appear, especially when situations are unfavorable (Williamson, 1991). To protect an exchange relationship from a supplier’s

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opportunism, a buying firm must supervise the supplier’s current and future behaviors, the protective efforts that increase transaction costs (Wacker et al., 2016; Yang et al., 2016). However, effective

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collaboration can signal that a supplier makes genuine commitments to an ongoing relationship (Dahlstrom and Nygaard, 1999). As such, if a buying firm confirms improvements in its performance, the company can save considerable expenses of what would otherwise be paid such as controlling, monitoring, and negotiating its suppliers. This study will thus demonstrate impacts of SCC and firm

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performance on transaction cost advantage.

Third, regarding the specific setup of supply chain collaboration, previous literature has paid particular attention to selection of appropriate governance modes in an effort to mitigate suppliers’

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opportunism (Abdi and Aulakh, 2017; Bai et al., 2016; Cao and Lumineau, 2015; Prosman et al., 2016; Wacker et al., 2016). The exchange hazard is a potential concern for a buying firm because, it, if not

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fixed or removed, is detrimental to an ongoing relationship. To avoid the potential issue, supply chain members call for an effective governance by which transactions are regulated and guided (Cao and Lumineau, 2015). Governance, which deals with operational and structural aspects of collaboration between involved parties, falls into two main types. One is contractual governance, which refers to the extent to which a collaborative relationship is governed by a formal contract which specifies formal rules, obligations, and duties (Cao and Lumineau, 2015; Zhou and Poppo, 2010). The other type relational governance refers to the extent to which an inter-organizational relationship is governed by social relations and shared norms (Poppo et al., 2008; Zhou and Xu, 2012). While previous research has typically explored antecedents (e.g., opportunism, uncertainty) (Poppo and Zenger, 2002; Yang et

ACCEPTED MANUSCRIPT al., 2016) and consequences (e.g., information sharing, performance, collaboration) (Liu, et al., 2009; Lu, et al., 2015; Schmoltzi and Wallenburg, 2012; Wu, et al, 2014) of governance mechanism, little is known about the moderation effect of governance mechanism. In addition, previous literature has produced contradictory and inconsistent findings. Specifically, one school of thought views the

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interplay of governance as a substitute that the dependence on one governance reduces the other (Ghoshal and Moran, 1996; Li et al., 2010). A second one defines the relationship that the dependence on one governance is independent of the dependence of the other (i.e., complementary) (Poppo and

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Zenger, 2002; Yang et al., 2011). The relationship between contractual and relational governance, however, does not necessarily have to play by an existing rule and may be contingent upon situational

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and contextual factors (Abdi and Aulakh, 2017). Instead, this study explores and identifies an appropriate mode of governance that can leverage SCC and performance. An issue of the moderation effect of governance mechanisms on the SCC, performance, and transaction cost advantage appears to have gained less attention. This issue should be addressed as a mismatch between SCC and the mode of governance can jeopardize a current relationship and impede the achievement of a joint goal.

strengthen performance.

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Therefore, we will explore which governance may serve better to facilitate collaboration and

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This study aims (1) to investigate the effect of supply chain collaboration on a buying firm performance; (2) to analyze the effect of the performance on transaction cost advantage; (3) to

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examine the direct effect of supply chain collaboration on transaction cost advantage; and (4) to explore the moderation effect of governance mechanisms on each relationship. This paper is organized as follows. We provide the literature on supply chain collaboration, performance, transaction cost advantage, and governance mechanisms, and propose a research framework. We then discuss the research design including the sampling and data collection, and measurement selection. We display the results and analysis. Finally, we present the summaries of this study including both academic and managerial implications, limitations, and future considerations.

ACCEPTED MANUSCRIPT Literature Review Supply chain collaboration Supply chain collaboration (SCC) has strategically gained much attention from firms which wish to create a comparative advantage over competitors (Chen et al., 2017; Fawcett et al., 2015; Liao et al.,

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2017; Ramanathan and Gunasekaran, 2014; Soosay and Hyland, 2015). SCC refers to no less than two autonomous firms working together across their boundaries for the fulfillment of a shared goal (Cao and Zhang, 2011; Chen et al., 2017; Flynn et al., 2010; Yan and Dooley, 2013). SCC enables firms to

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share gains and losses, exploit resources of their external partners, lower transaction costs, increase productivity, and improve profitability (Cao and Zhang, 2011). Such advantages can be explained by

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existing organizational theories that have provided support for the development of collaboration. For example, the Resource-based view (RBV) theory suggests that a firm can create sustainable and competitive advantage through the exploitation of resources from its external partners (Barney, 1991). The combination of idiosyncratic resources from the partnering firms can produce unique, valuable, and inimitable resources, thus providing competitive advantage (Barney, 1991; Cao and Zhang, 2011).

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The Relational view (RV) theory extended this theory and considers firms’ networks as the unit of analysis (Dyer and Singh, 1998). This view focuses on a “relational rent” referring to “a supernormal profit jointly generated in an exchange relationship that cannot be generated by either firm in

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isolation and can only be created through the joint idiosyncratic contributions of the specific alliance

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partners” (Dyer and Singh, 1998, p.662). Relational rents can be created through relation-specific assets, knowledge-sharing routines, complementary resources/capabilities, and effective governance (Dyer and Singh, 1998; Soosay and Hyland, 2015). Applied to the development of SCC, this view points out that firm performance can be enhanced by exploiting and combining distributed resources in the supply chain (Soosay and Hyland, 2015). The Social exchange (SE) theory explains the formation of a relationship by stressing the role of trust in the relationship stability (Cao and Lumineau, 2015; Palmatier et al., 2007). This theory emphasizes voluntary actions of exchange parties which are motivated by the returns determined by the subject cost-benefit analysis and the comparison of alternatives (Cao and Lumineau, 2015). The underlying assumptions of this theory are

ACCEPTED MANUSCRIPT non-contractual obligations and reciprocity. In the supply chain context, buyers and suppliers are expected to continually discharge their duties and invest in relational-specific assets as a sign of genuine commitment to a relationship.

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While those theories provide a theoretical ground for the development of SCC, however, various definitions and components have failed to produce consistent results. A number of factors have appeared such as collaborative planning (Ramanathan and Gunasekaran, 2014), collaborative execution (Ramanathan and Gunasekaran, 2014), information sharing (Cao and Zhang, 2011), joint

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activities (Jap, 2001), dedicated investment (Jap and Ganesan, 2000), goal congruence (Cao and Zhang, 2011, Yan and Dooley, 2013) communication (Cao and Zhang, 2011, Yan and Dooley, 2013;

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Zhang and Cao, 2017), incentive alignment (Cao and Zhang, 2011; Simatupang and Sridharan, 2005), risk sharing, knowledge creation (Hult et al., 2006), decision synchronization (Simatupang and Sridharan, 2002), and resource sharing (Cao and Zhang, 2011; Ramanathan and Gunasekaran, 2014). Such various variables are dependent on the focus of SCC (i.e., process focus and relational focus). A

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process-focus of view places more emphasis on a business process where heterogeneous parties work together toward a mutual goal while a relational focus of view stresses the formation of close partnerships. Combining both process and relational focus, we define SCC as shared processes in

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which a buyer and a supplier closely work from planning to execution for the achievement of a joint goal. Among various dimensions from the previous literature, we encompass six sub-factors, namely:

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information sharing, goal congruence, decision synchronization, incentive alignment, resource sharing, and collaborative communication. We do not deal with other factors such as joint activities, risk sharing, and joint knowledge creation because they are overlapped to some extent with the current factors and because they are not suitable for the aim of the present research. We will respectively explain the definition of the other six factors used in this study. Information Sharing refers to the extent to which information about transactions is shared among supply chain members. The quality of information is determined by the extent to which appropriate, accurate, complete, confidential, and timely information is exchanged between members. (Cao and

ACCEPTED MANUSCRIPT Zhang, 2011; Sheu et al., 2006). Information sharing (e.g., sales, inventory, forecasts, and promotion) enables supply chain members to jointly plan a goal and precisely forecast future events. Goal congruence refers to the extent to which supply chain members have an agreement about a shared goal (Angeles and Nath, 2001). If supply chain members realize the importance of a supply chain

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relationship, they are willing to show their genuine commitments to the relationship through which they can achieve desired outcomes. Decision synchronization is letting the both parties’ interests in supply chain operations coincide (Simatupang and Sridharan, 2002). It emphasizes the importance of

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utilizing all relevant information at each process and optimizing benefits of the supply chain (Simatupang and Sridharan, 2002). Key supply chain management decisions leading to operational

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performance vary from planning to execution such as strategy planning, scheduling, order shipment, production, inventory management, and distribution. Incentive alignment refers to “the process of sharing costs, risks, and benefits of the relationship” (Simatupang and Sridharan, 2005, p.265). Incentive alignment allows supply chain members to distribute gains and benefits fairly as well as to share corresponding costs and risks. Participants in the supply chain can gain desired outcomes

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corresponding to their responsibilities for risks. Resource sharing means the extent to which existing resources are accessed and utilized between supply chain members (Cao and Zhang, 2011). Resource sharing varies from the availability of physical resources (e.g., equipment, technology) to that of

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intangible ones (e.g., knowledge, know-how) beyond the boundary of each party. Exchange parties can take advantage of utilizing the other party’s resources, which, otherwise, would have to be

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purchased thereby resulting in higher costs. Collaborative communication is defined by the extent of openness and frequency of communication (Cao and Zhang, 2011). The effectiveness of communication differs in openness, frequency, and interaction (Goffin et al., 2006). Zhang and Cao (2017) revealed that the quality of collaborative communication could be determined by frequent contract, open and two-way conversation, level of informal communication, various channels, and discussion.

ACCEPTED MANUSCRIPT Firm performance Performance includes two critical criteria: effectiveness and efficiency within processes (Neely, 1999). Effectiveness refers to the extent to which expected outcomes are achieved, whereas efficiency refers

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to the extent of utilization of a firm’s resources without loss. A great deal of attention has been paid to conceptualize the construct of firm performance (Cai and Yang, 2008). To generate high performance, firms must establish an environment in which (1) resources are accessed from a shared “resource pool”; (2) losses and risks are shared with members; and (3) there is joint-decision making (Lecoeuvre,

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2016). Collaboration in which business process between a buyer and its key suppliers are unified as a whole is a primary driver for the firm performance (Chen et al., 2013; Flynn et al., 2010). For the

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development of firm performance, we base its conceptualization on four priorities of the order fulfillment process: cost, quality, speed, and flexibility (Chen et al., 2013; Hult et al., 2006) In the supply chain management, the extent to which supply chain members engage in processes of the supply chain is coupled with their outcomes (Vickery et al., 2003). A buying firm performance

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could vary under governance modes (Cao and Lumineau, 2015) and the level of collaboration (Chen et al., 2013b) and cooperation (Cai and Yang, 2008). Supply chain relationships aim to meet the future demand, fulfill customers’ expectation, and reduce cost (Chopra and Meindl, 2001) through the

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quality of collaboration. Existing study has provided support for the relationship between collaboration and performance in the supply chain management (Cao and Zhang, 2011; Chen et al.,

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2013; Simatupang and Sridharan, 2005). Resource and information sharing enables supply chain members to enhance abilities to fulfill a customer’ needs, reduce operational costs and delivery time, and increase agility and responsiveness to market demand and uncertainty (Simatupang and Sridharan, 2005). Decision synchronization allows idiosyncratic resources and relevant information beyond firms’ boundaries to be efficiently utilized be, and goal congruence enables suppliers to strive to meet supply chain objectives rather than seeking their own interests (Simatupang and Sridharan, 2005). Supply chain collaboration is an important source of a strategy would enable a buying firm and its suppliers to ceaselessly coordinate in the complex chain beyond and across organizational boundaries.

ACCEPTED MANUSCRIPT Interactive and effective collaboration can increase the supply chain’s agility and responsiveness, resulting in better order fulfillment processes in terms of cost, quality, speed, and flexibility. Therefore, we propose that:

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Hypothesis 1: Collaboration has a significant positive effect on a buying firm performance

Transaction cost advantage

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Transaction cost theory (TCE) lends theoretical support to explaining supply chain collaboration (Soosay and Hyland, 2015; Williamson, 2008). In TCE, transaction costs are the expenses resulting

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from selecting an appropriate exchange partner, negotiating and crafting contracts, resolving conflicts, and revising the existing agreements when conditions change (Williamson, 1985). Transaction costs are contingent upon how transactions are structured. Williamson (1975) explained the occurrence of transaction costs under the assumption of a human-beings’ bounded rationality, which stems from the

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intractability of decision problems and the limited resources. When applied to the business world, bounded rationality restricts a buying firm’s ability to select qualified suppliers and draw up contracts that could identify all sources of potential future contingencies and conflict (William, 1985). The

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human limitations attribute transaction costs to two exchange hazards: opportunism and maladaptation (Crook et al., 2013). Opportunism refers to an actor’s self-seeking behaviors when circumstances are

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unfavorable (Williamson, 1975). Because suppliers can potentially engage in opportunistic behaviors, transaction costs regarding identifying and monitoring potential opportunists and crafting safeguards are inevitable for buyers. Maladaptation occurs however trustworthy economic actors may be, because of constant changes in circumstance. In the supply chain, maladaptation can occur in a case that a supplier is unable (unwilling) to satisfy needed requirements (Williamson, 1999). Maladaptation sparks the occurrence of transaction costs in a buying firm’s efforts to protect its relation-specific assets. Maladaptation costs are incurred by the termination of a relationship that unavoidably forces a buying firm to search out an appropriate supplier and draft new agreements (Crook et al., 2013).

ACCEPTED MANUSCRIPT Transaction costs can be decomposed into ex ante and ex post according to the start of a relationship (Barthélemy and Quélin, 2006; Grover and Malhotra, 2003; Pilling et al., 1994) Ex ante transaction costs result from searching for an appropriate supplier and writing up a contract at the beginning of a relationship. Search and contracting costs refer to the costs of selecting and involving a qualified

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partner in the supply chain process and of negotiating and writing a mutual agreement. As the relationship continues, ex post transaction costs are incurred such as monitoring and enforcement costs. Monitoring and enforcement costs are caused by monitoring each party’s behaviors and then

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taking the actions necessary to confirm whether they perform their obligations already specified in the predetermined contract.

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This study focuses solely on ex post transaction costs and embraces three elements of the ex post transaction costs: monitoring cost, solving cost, and detecting cost (Grover and Malhotra, 2003; Pilling et al., 1994). In the supply chain relationship, if a buyer is convinced that a supplier is reliable and thus less likely to act against the buyer, the buyer will save the costs associated with monitoring

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the fulfillment of the supplier’s obligations and detecting the supplier’s opportunistic behaviors. (Rindfleisch and Heide, 1997). Problem-solving costs can be reduced through standard solutions that are already specified in a mutually acceptable contract. A well-written contract that specifies locus of

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responsibility and ways of problem-solving can lower the possibility of renegotiating for the recurrent transactions (Grover and Malhotra, 2003). As a result, a buyer can take advantage of reduced

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transaction costs associated with a supplier. This study refers to such advantages as transaction cost advantage. As a buyer seeks to not only reduce transaction costs through a partnership but also strengthen its performance, it is worth studying transactions costs as a pertinent consequence of collaboration and performance. To the best of our knowledge, the effect of a buyer’s performance on transaction cost advantage has not been empirically investigated. However, Bharadwaj and Matsuno (2006) reported that a supplier’s efforts into improvements in its buyer’s performance provide the buyer with transaction cost advantage. To support this, they exemplified that if a supplier has contributed to reductions in the

ACCEPTED MANUSCRIPT order cycle time or improvement in billing accuracy, the buying firm may save its unnecessary time and costs associated with evaluating and monitoring its supplier and seeking out a qualified supplier. The presence of improvements in a buyer’s performance provides important clues that would enable

eventually lead to long-term relationships. Therefore, we assume that:

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the buyer to build a trust in its supplier, to continuously coordinate supply chain processes, and to

Hypothesis 2: A buying firm’s enhanced performance dedicated by its supplier has a positive effect on

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transaction cost advantage

Initiating and maintaining a collaborative relationship requires both exchange firms to continuously

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invest into relation-specific assets and the development of joint business practices (Yan and Kull, 2015). Collaborative efforts enable partners to share information and resources in ways to create synergic effects and seize opportunities (Mikalef and Pateli, 2017). Relation-specific assets are resources that both a buyer and a supplier allocate to the relationship (e.g., purpose-specific knowledge, specialized machines, and development of data exchange systems) (Wacker et al., 2016;

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Yan et al., 2016). Both collaborative efforts and relation-specific assets can serve to support the relationship and minimize opportunistic behaviors because such investments would be of no utility unless the relationship continued (Dyer, 1997; Yan and Kull, 2015). Recurrent collaborative activities

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enable a buying firm to accumulate more knowledge about its supplier’s behaviors and responsibilities for the relationship, and the accumulated knowledge can allow the buyer to accurately

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evaluate and predict the supplier’s current and future actions (Jap and Anderson, 2003). Through the repeated collaboration, the buying firm is convinced that its supplier invests genuine efforts into the ongoing transaction, thus demotivated from controlling and supervising the supplier’s behaviors (Lumineau and Henderson, 2012). The genuine collaboration signals a mutual understanding of maintaining the current relationship. Because both firms understand that seeking their own interests will have more to lose, either firm is less vulnerable to unethical exploitation. This study assumes that as a relationship continues, a buying firm considers recurrent and interactive collaboration as a sign of the positive relationship, a sign that allows the buyer to spend fewer resources monitoring and curbing

ACCEPTED MANUSCRIPT opportunistic behaviors of the supplier. Therefore, this study hypothesizes that: H3: Collaboration has a positive effect on transaction cost advantage

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Governance mechanisms

Governance in the supply chain refers to the official and unofficial principles ruling an exchange between supply chain members (Cao and Lumineau, 2015). Governance specifies manners in which a

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buying firm and a supplier are expected to perform specific tasks to fulfill a joint objective. Both parties often hold a feeling of doubt and uncertainty about whether their expectations could be unmet

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or whether the other party will not act as promised, especially when it faces unfavorable circumstances in which bargaining power lowers, market uncertainty increases, and/or conflict rises. (Jap and Ganesan, 2000). Those circumstances lead exchange parties to establish a stable governance to support a relationship and achieve a joint objective.

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The Transaction cost economics (TCE) embraces the role of contracts in managing unavoidable exchange hazards (Williamson, 1985). A contract refers to the extent to which exchange parties are tied in a formal written format that specifies duties, roles, rights, and contingencies (Mesquita and

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Brush, 2008). Contractual governance offers an underlying structure in which transactional activities between economic actors are conducted. In the supply chain relationship, contractual governance

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prevents supply chain members from seeking their own interests in several ways (Wang et al., 2011). A contract mainly focuses on three parts: (1) the fundamental elements focusing on the key principles (e.g., delivery deadline and quality standards); (2) the preventive elements focusing on settling unpredictable events; and (3) the governance-related elements focusing on the ways of maintaining relationships (e.g., a clear clause of penalties, incentives, and rewards, the termination of a contract, and conflict handlings) (Lu, et al., 2015). Contracts increase operation understanding and demotivate exchange parties from avoiding certain actions necessary for exchanges and seeking opportunism. Because providing false information or cheating behaviors are regarded as a sign of contract violation,

ACCEPTED MANUSCRIPT such behaviors cannot be accepted (Seggie et al., 2013). Contracts can contribute to curbing opportunistic behaviors by enforcing legal rules and standards. Contracts catalyze the coordination of supply chain (Schepker et al., 2014; Cao and Lumineau, 2015). The coordination can be achieved through a clearly-stated contract that helps shape the precise role of each party, simplify the decision-

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making process, and manage disputes between exchange parties. In short, contractual governance can promote a predictable collaborative environment that minimizes exchange hazards and facilitate supply chain collaboration.

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In contrast, relational governance is conceptualized as the extent to which exchange parties are governed by social relations, shared norms, and trust (Poppo et al., 2008; Zhou and Xu, 2012).

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Relational governance concentrates on a self-enforcing mechanism with informal structure (Li et al., 2010; Liu et al., 2009). Social exchange (SE) theory advocates the role of relational governance in facilitating collaboration and curbing opportunistic behaviors in that social interactions and socially embedded relationships are pivotal to developing and strengthening stable relationships (Granovetter,

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1985). Relational governance is effective in inter-firm activities in several ways. Relational governance provides a deeper understanding of the fulfillment of exchange expectations and joint goals, both of which, in turn, motivate exchange parties to invest genuine efforts because the shared

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expectation and joint objectives formed by trust are drivers for the exchange parties to pursue the best interests of the exchange rather than individual interests (Dyer and Singh, 1998; Liu et al., 2009;

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Wang et al., 2016). Relational governance also promotes an environment for information and transparency by activating the flow of knowledge transfer between parties. Relational governance curbs opportunistic behaviors through the creation of reduced information asymmetry that allows exchange moral hazards to be detected with ease (Wang et al., 2016).

Moderation effect of governance mechanisms among the theoretical constructs. Supply chain collaboration can give benefits to all exchange partners in terms of risk and cost reductions and improvements in productivity and profitability. Despite its effectiveness, however,

ACCEPTED MANUSCRIPT transaction costs incurred by coordination, compromise, and inflexibility are inevitable in the collaborative partnership. Since the effect of supply chain collaboration on firm performance and transactional cost advantage appears to be multifaceted and complicated, a contingency approach may be applied to clarify the complex issue (Sousa and Voss, 2008). There are many other environmental

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and contextual factors that could influence firm performance and transactional cost advantage, and so are governance mechanisms. The effect of collaboration on performance differs to the extent to which both parties are tied in governance mechanisms. Contractual governance and relational governance

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have been empirically found to be effective in maintaining a relationship and eventually contributing to improvements in firm performance in different ways. Contractual governance provides clarified

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ways to execute certain transactional tasks and solve disputes and conflicts, which in turn strengthen the transaction efficiency and effectiveness (Poppo and Zenger, 2002). Relational governance contributes to the facilitation of collaboration (Poppo and Zenger, 2002; Zhou et al., 2015) in that trust-based understanding offers an environment in which exchange parties are willing to share relevant information and their resources under the assumption the dedicated resources are used to

Narayanan et al., 2015).

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leverage opportunities and meet exchange expectations of both parties (Dyer and Chu, 2000;

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The effect of performance on transaction cost advantage also differs by governance mechanisms. Governance mode theory assumes that buyers and suppliers choose the best governance that can breed

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the best outcome (Brouthers et al., 2003). The best governance is determined by the extent to which better performance and cost reduction are achieved. A mismatched governance leads exchange parties to suffer from underperformance and competitors’ challenges. Governance modes provide different contributions to the achievement of transaction cost advantage. Contractual governance offers a clear set of obligations and responsibilities necessary for the fulfillment of a joint goal, and penalties if the requirements are unmet. The presence of contracts allows exchange parties to work as promised and restrict opportunistic behaviors because a breach of the predetermined contracts will impose social sanctions, such as a loss of participation in future business and isolation from the network (Zhou and Xu, 2012). Relational governance in which shared norms, expectations, and values are formed helps

ACCEPTED MANUSCRIPT increase a buying firm performance in that benefits corresponding to the achievement of the performance will be given to its supplier in return (e.g., long-term relationship). Relational governance also cultivates credibility and benevolence, making exchange members interested in the needs of each other (Dyer, 1997). A buying firm can yield transactional cost advantage from the

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presence of relational governance because a shared sense of identity motivates a supplier to be attached to shared values and seek the best interests of the transaction. Those leave less room for opportunism. A supply chain relationship with different governance modes could have different

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supply chain collaborative efforts, achieve different levels of firm performance, and obtain various levels of transaction cost advantage. Thus, we hypothesize that governance mechanisms positively

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moderate the relationships built in the framework.

Hypothesis 4: governance mechanisms positively moderate the relationship between supply chain collaboration and performance.

Hypothesis 5: governance mechanisms positively moderate the relationship between performance and

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transaction cost advantage

Hypothesis 6: governance mechanisms positively moderate the relationship between supply chain

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collaboration and transaction cost advantage

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Insert. Figure 1. The research framework

Research Methodology

Sampling and data collection Supply chain collaboration represents the bilateral relationship between supply chain members. Therefore, we conceptualize the theoretical constructs to investigate the dyadic relationship between a buying firm (i.e., manufacturers) and its key supplier. We measured the theoretical constructs only

ACCEPTED MANUSCRIPT from a buying firm’s point of view. A web survey was conducted in South Korea to test the hypotheses of this study. As an important global manufacturing base, South Korea is a major powerhouse to uphold the global economy. In South Korea, smartphones, electronic products, automobiles, and even other manufactured products are now being manufactured and exported

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worldwide. Thus, South Korea may be an ideal setting for conducting supply chain research.

To obtain a representative sample, we randomly selected 2000 manufacturing firms. The “key informant” identified in this study included chief executive officers, vice presidents, directors, and

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operation officers. The representative of a firm should be at senior management level, who has better understanding and expertise in the processes and capability of his or her company. The use of a single

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respondent may not be suitable for firm-level studies but becomes a common practice in recent empirical studies on operations management (e.g., Liu et al., 2016). The selected firms covered an extensive range of industries, including manufacturing of electronics, automotive, steel, foods, and pharmaceuticals. We only targeted respondents who meet the following inclusion criteria: (1)

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currently have a primary supplier; (2) have relevant field experiences (at least seven years); (3) work at a managerial level; and (4) produce only physical products. This study deliberately excludes service firms because there are different production processes in product-manufacturing and service-

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generating firms (Ettlie and Rosenthal, 2011). During a two-month period (between Nov. and Dec. in 2016), we performed data collection and processing. An email list of the target 2000 manufacturing

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firms was obtained from a Korean professional agent company that holds senior level email lists. Before conducting a web-survey, we confirmed whether the emails were valid and usable to obtain actual emails. 127 emails with different names from the same company, with failure notification, or in the unacknowledged state were discarded from the actual survey distribution. We followed the procedures from the work of Liu et al. (2016). First, all identified key informants were sent an invitation to join the survey. The invitation presented the objectives of this study, a request for them to join the survey, and a way of collecting their contact information. Questionnaires were then sent to the potential respondents who agreed to answer the survey. To encourage a response, we sent remainder emails after the questionnaires were first sent out. 42 questionnaires were discarded due to insincere

ACCEPTED MANUSCRIPT reporting or missing information. The following steps were used to identify incomplete reports: (1) remaining missing values; (2) determining outliers that did not pass range checks (means and standard deviation); (3) checking the data flow to identify consistent values; and (4) finding out idiosyncratic patterns based on previous experience and common sense. Finally, 304 useful questionnaires were

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collected, with a response rate of 16.2%.

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Insert. Table1. The sample demographics

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To assess the potential for non-response bias, we compared the responding and nonresponding firms by conducting a t-test (Flynn et al., 2010). This study observed no significant difference between two groups regarding key firm characteristics, suggesting that non-response bias is not a significant concern. In addition, follow-up phone calls with a few non-responding firms indicated that they did

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not participate because of lack of time or unwillingness to reveal confidential information.

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Insert. Table 2. Comparisons of early and late respondents

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Measurement items

An English questionnaire was first developed by adopting previously and empirically tested measures from the existing literature. All constructs were measured on a 6-point Likert scale (i.e., 1 = strongly disagree and 6 = strongly agree). Because this study was conducted in South Korea, the English questionnaire was translated into Korean by three experts from different fields (Van de Vijver and Leung, 1997). A professional translator who was unfamiliar with the context of this study was asked to translate the Korean questionnaire back to English. No semantic discrepancies appeared between the translated questionnaire and the original English version. Then, this study pretested the

ACCEPTED MANUSCRIPT questionnaire with 30 firms to purify the instruments adopted by different existing studies and secure acceptable reliability and validity. Scale modification was carried out through the feedback (e.g., rewriting items, changing wording and the style, and removing some items). SCC, which is the independent variable in this study, is operationalized as a second-order factor that consists of six-sub

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factors that were derived from Cao and Zhang (2011): information sharing, goal congruence, decision synchronization, incentive alignment, resource sharing, and collaborative communication. Performance, the mediator, is measured with four sub-factors adopted from Hult et al. (2006): cost,

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quality, speed, and flexibility. Transaction cost advantage, the dependent variable, is conceptualized as a higher order factor that is measured through three sub-components: monitoring cost, solving cost,

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and detecting cost (Grover and Malhotra, 2003). Finally, contractual governance and relational governance are measured with five items adopted from Zhou and Poppo (2010) and Liu et al. (2009), respectively.

The previous work demonstrated a few control variables that could affect firm performance (Liu et al.,

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2016). This study included several factors such as industry type, ownership type, firm size, relationship length, types of supplied (i.e., tangible, intangible), and types of market (i.e., import, export). Dummy variables were used for industry type, ownership type, types of supplied, and types

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of market. Actual numbers were entered into firm size and relationship length.

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Measurement validation

Prior to hypotheses testing, we undertook several statistical analysis to assess validity and reliability of the instruments. Confirmatory factor analysis was performed to assess the unidimensionality, reliability, and validity of the measurement items. The results from this analysis revealed that all item loadings were statistically significant, and ranged from .709 to .904; the composite reliabilities for the fifteen factors were above the cutoff of .7, and ranged from .794 to .929; and the estimates of AVEs for these factors were greater than the critical value of .5, and ranged from .616 to .814. The model fit was found to be adequate (χ2 = 2157.973, df = 1216, p=0.000, χ2/df = 1.775, CFI = 0.927, RMSEA =

ACCEPTED MANUSCRIPT 0.051, RMR = 0.054). These results satisfied the criteria and provided evidence for convergent validity. We estimated the reliability for each construct by calculating Cronbach's α. The reliability values for all constructs ranged from .793 to .927, which were larger than the threshold of .70, and

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indicated a high degree of internal consistency (Chin, 1998). To assess discriminant validity, we compared the square root of the AVE with the absolute value of the correlation coefficients from the other latent variables. Fornell and Larcker (1981) insisted that the square root of the AVE for each construct must be larger than its correlations with all other constructs.

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The results revealed that the AVE for each construct was larger than all the corresponding squared correlations, which provided additional evidence of discriminant validity. Although several inter-

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construct correlations were higher than the threshold of 0.60, the results of this study revealed that the highest variance inflation factor value was 2.427, less than the benchmark value of 3.3 suggested by Diamantopoulos and Siguaw (2006). Therefore, this study did not suffer from multicollinearity.

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Insert. Table 3. Descriptive statistics and correlation matrix

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Insert. Table 4. Survey items and confirmatory factor analysis results

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Common method bias

Because we obtained the data from a single source in each company with a self-report questionnaire, common method bias may be a serious concern. To detect whether this study suffers from common method bias, we performed two tests: (1) Harman’s one-factor test and (2) the common latent factor test (Podsakoff et al., 2003). The rationale behind the Harman one-factor test is that if common method bias appears, either (a) only one factor will emerge from the analysis or (b) one or more general factors will underlie and account for the variance (Podsakoff et al., 2003). Harman’s onefactor test identified ten factors, with the first factor accounting only for 22.445 percent of the total variance explained, indicating no serious common method bias.

ACCEPTED MANUSCRIPT In addition to the Harman’s test, we performed a confirmatory factor analysis. We tested two latent variable models, with one measurement model with just traits and the other with traits and a method factor (Podsakoff et al., 2003). The results showed that the fit for the traits-only-model (i.e., χ2/df = 1.770, CFI = 0.920, IFI = 0.949, and RMESA = 0.048) was similar to the fit for the method-factor-

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model (i.e., χ2/df = 1.721, CFI = 0.916, IFI = 0.967, and RMESA = 0.045). The overall factor structure remained valid even in the inclusion of the unmeasured method factor. We, therefore, concluded that common method bias may not be a serious problem in this study (Satorra and Bentler,

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2001).

Second-order factor vs. First-order factor

We operationalized three underlying factors (i.e., Transaction costs advantage, Performance, Supply chain collaboration) as second-order constructs. To demonstrate that the second-order factor models were more suitable than the first-order models, we used the T coefficient as an indicator of better fit.

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To estimate the T coefficient, we calculated the ratio of the chi-square from the first-order model to that from the second-order model. A value that is larger than the threshold of 0.8 indicates that the

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second-order factor is superior to the first-order factor (Doll et al., 1995). Table 5 showed the estimated target coefficients between the first- and the second-order models for

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each construct. The T coefficients for the three underlying factors demonstrated the second-order models should be accepted as a more accurate representation of model structure than the first-order model because they represented a more parsimonious explanation of the observed covariance.

Insert. Table 5. Fit indices for the first- and second-order models

Hypotheses testing

ACCEPTED MANUSCRIPT For the causal hypotheses testing, we performed a hierarchical regression analysis that offers an analysis of an examination for a moderation effect. To avoid concerns regarding the multicollinearity issue, we converted independent variables and moderators into standardized ones (i.e., supply chain collaboration, performance, contractual governance, and relational governance) before entering them

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into the regression model. In addition, interaction terms were created by multiplying those standardized constructs. To examine the effect of supply chain collaboration on performance, and the moderation effects of governance mechanisms on the relationship, we developed four models: (1) M1

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served as a reference model, including only control variables; (2) M2 included an independent variable; (3) M3 added the two moderating variables (i.e., contractual governance, relational

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governance); and (4) M4 placed the interaction terms. We examined the contribution from M1 to M4 by comparing the significance of the F-statistic associated with the change in R2 (Pedhazur and Schmelkin, 2013). We carried out the same procedures for the relationships between performance and transaction cost advantage (From M5 to M8), and between supply chain collaboration and transaction cost advantage (From M9 to M 12). The control variables entered in M1(M5, M9) represented such as:

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(1) types of industry (electronics, automobiles, steel, foods, or pharmaceuticals, pharmaceuticals used as a reference point); (2) types of supplies (tangible or intangible, intangible used as a reference point); (3) types of outcomes (imported or exported, exported used as a reference point); (4) types of

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ownership (state- owned or private-owned, state-owned used as a reference point); (5) relationship

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length (actual numbers were entered); and (6) number of employees (actual numbers were entered). Given that “Chang in F value” was found to be significant from M1 (M5, M9) to M4 (M8, M12), we took the empirical results of regression into account. For the supply chain collaboration and performance hypothesis, the empirical results revealed that higher supply chain collaboration leads directly to better performance (β = 0.754; p = 0.000), thus supporting H1, while two hypothesized moderation effects (M4) are found non-significant. More specifically, while each moderator in M3, whether contractual or relational, is positively associated with supply chain collaboration, the moderation

effects

(i.e.,

collaboration*contractual

governance

and

collaboration*relational

governance) are found to be non-significant, thus failing to support H4. Among control variables,

ACCEPTED MANUSCRIPT types of company (e.g., imported) are negatively associated with performance and relationship length is positively associated with performance only in M1. For the performance and transaction cost advantage hypothesis (from M5 to M8), the empirical results

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revealed that higher performance is positively associated with transaction cost advantage (β = 0.898; p = 0.000), thus supporting H2. In addition to the main effect, we found that contractual governance positively moderates the relationship between performance and transaction cost advantage (β = 0.064; p = 0.035), whereas relational governance does not. Among control variables, types of company (e.g.,

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imported) are negatively associated with transaction cost advantage in M5. Another variable

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automobile is also positively associated with transaction cost advantage through M6 to M8. Finally, for the direct effect of supply chain collaboration on transaction cost advantage, we found that higher supply chain collaboration is positively related to transaction cost advantage (β = 0.698; p = 0.000), thus supporting H3. For the moderation effect testing, both contractual governance and relational governance are found to positively moderate the relationship between supply chain

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collaboration and transaction cost advantage, thus supporting H6. More specifically, contractual governance (β = 0.112; p = 0.029) is found to be more effective in the collaboration and transaction cost advantage link (β = 0.104; p = 0.040). Among control variables, types of company (e.g., imported)

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are found to be negatively associated with transaction cost advantage through M9 to M12.

Insert. Table 6. The results of hypotheses

Insert. Table 7. The summary of hypotheses testing results

Post-hoc analysis (Linear and non-linear effects of governance mechanisms) In addition to the proposed model testing, we performed a post-hoc analysis to explore the effects of levels of governance mechanisms on supply chain collaboration, performance, and transaction cost advantage using a hierarchical analysis because the results from table 6 revealed that governance

ACCEPTED MANUSCRIPT mechanisms appear to play different roles in the formation of three theoretical constructs. To thoroughly investigate contributions of governance mechanisms to those constructs, we additionally examined their linear and non-linear effects by adding two square terms of contractual governance and relational governance. M10, M13, and M16 represented the only inclusion of the control variables;

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M11, M14, and M17 included the control variables and the linear effects of two types of governance; and M12, M15, and M18 displayed the quadratic effects of governance mechanisms.

For the main effects of governance mechanisms on three different theoretical constructs, we found

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interesting results that while all of the main effects are positively related to the constructs, the different roles of governance mechanisms are identified. That is, relational governance is more

powerful in transaction cost advantage.

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effective in supply chain collaboration and firm performance, whereas contractual governance is more

In addition to the linear effects of governance mechanisms, some of the non-linear effects were examined. The empirical findings exhibited that the achievement of supply chain collaboration differ

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across levels of governance mechanism in a conflicting manner. Thais is, the quadratic effect of contractual governance on supply chain collaboration is significant but negative (i.e., an inverted Ushaped effect), whereas that of relational governance is significant and positive (i.e., a U-shaped

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effect). The evidence suggested that until a certain level is reached, increasing contractual governance (relational governance) leads to (lowers) supply chain collaboration. Once a maximum (minimum)

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point is met, the curve turns downward (upward), implying that supply chain collaboration declines (rises). For the examination of the non-linear relationship between governance mechanisms and transaction cost advantage, we identified that the negative coefficient of the quadratic term for relational governance is indicative of a concave non-linear relationship. The inverted U curve indicated that until a maximum point relational governance contributes positively to transaction cost advantage. Thereafter, the advantage diminishes with a further increase in the relational governance level. No curvilinear effect of governance mechanisms on performance appeared. Those additional findings (i.e., main effects and quadratic effects) provided further support for different governance

ACCEPTED MANUSCRIPT roles in contributions to shaping supply chain collaboration, firm performance, and transaction cost advantage.

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Insert. Table 8. Results of the hierarchical analysis for a post-hoc analysis Insert. Figure 2. The quadratic effects of governance mechanisms

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Discussion

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Theoretical Implications

The objectives of this study are to examine how supply chain collaboration shapes a buying firm performance, how increased performance enables a buying firm to take advantage of transaction cost, and how supply chain collaboration directly contributes to a buying firm’s transaction cost advantage. This study additionally investigates the moderation effects of governance mechanisms on those

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hypothesized relationships.

This study has confirmed valid and reliable measurement items for supply chain collaboration and transaction cost advantage, both of which were treated as a second-order factor in this study. All

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measurement items were rigorously tested through several statistical analyses, such as CFA, reliability, and the validity of the comparisons between the first- and second-order constructs. Consistent with

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previous research (Cao and Zhang, 2011; Simatupang and Sridharan, 2005), the findings from this study are expected to broaden our understanding of supply chain collaboration and transaction cost advantage by using measurement items that were tested and demonstrated high reliability and validity. The unambiguous definition may help both researchers and business practitioners to design an effective and efficient environment for supply chain collaboration and transaction cost advantage. We have also identified that supply chain collaboration is positively associated with performance and transactional cost advantage, the empirical evidence that corresponds with earlier finding (Cao and Zhang, 2011; Liao et al., 2017; Narayanan et al., 2015). Close collaboration enables supply chain

ACCEPTED MANUSCRIPT members to elaborate on operational performance in ways that: (1) resource and information sharing causes considerable cost reduction in the order fulfillment process (Ramanathan and Gunasekaran, 2014); (2) shared goals and synchronized decision enable a buying firm and its key suppliers to build a long-term relationship through mutual benefits from the supply network (Scholten and Schilder,

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2015); (3) collaborative communication could increase speed and flexibility by jointly solving problems and reacting to market demands in a fast manner (Roh et al., 2014); and (4) incentive alignment can significantly increase responsiveness (Simatupang and Sridharan, 2005; Cao and Zhang,

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2011). Supply chain collaboration also contributes to the creation of transaction cost advantage in ways that: (1) proactive collaboration through frequent and active communication, and information

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and resource sharing reduce information asymmetry in which a supplier’s opportunism is identified; (2) recurrent collaboration increases a buyer’s predictability with more knowledge accumulated about a supplier’s behaviors and responsibilities for a relationship (Jap and Anderson, 2003); and (3) repeated collaboration allows a buying firm to precisely evaluate its supplier’s dedication to a relationship (Lumineau and Henderson, 2012). This finding heightens the importance of a design of

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supply chain collaboration practices to yield satisfactory performance as well as to increase transaction cost advantage. The effects of collaboration on performance and transaction cost advantage are accumulated and self-reinforced (Ramanathan and Gunasekaran, 2014; Scholten and

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Schilder, 2015) as relationships continue (Cao and Zhang, 2011; Ramanathan and Gunasekaran, 2014).

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This study has verified the direct and positive relationship between performance and transaction cost advantage. Increased performance signals a positive relationship between a buying firm and its suppliers. This evidence implies that a buying firm’s recognition of its performance enhancement relives a potential concern that its suppliers will act opportunistically. The enhanced performance thus demotivates the buyer from supervising and monitoring its suppliers’ behaviors and performance. This empirical finding is consistent with the findings from Narayanan et al. (2015) and Bharadwaj and Matsuno (2006). Earlier study provided support for the opposite direction that performance can be enhanced by a buyer’s efforts to control and regulate a supplier’s behaviors and performance. Although this rationale also sounds logical, however, it can differ from a relationship stage. We argue

ACCEPTED MANUSCRIPT that if a relationship is mature especially at the beginning of a relationship, transaction cost advantage is less likely to be achieved because both a buyer and a supplier are required to invest their time, efforts, and resources into developing and stabilizing the relationship. However, through recurrent collaborations and better performance achievement, those exchange partners gradually realize mutual

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benefits from the supply chain relationship that can deter opportunism of each party.

In addition to the direct and indirect effects, this study seeks to examine the moderation effect of governance mechanisms. First, the empirical findings have shown that neither governance moderates

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the relationship between supply chain collaboration and firm performance. The findings displayed in table 6 and 8 have indicated that governance modes may act as an antecedent of supply chain

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collaboration in that contracts and shared norms and expectations must be needed before a relationship occurs (Lumineau and Henderson, 2012; Poppo and Zenger, 2002). Second, regarding the relationship between performance and transaction cost advantage, we found that performance combined with contractual governance may cause great effectiveness in transaction cost advantage

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while relational governance may not. This evidence is consistent with earlier findings (Lu et al., 2015; Wacker et al., 2016; Williamson, 1985) that the contractual governance shapes positive outcomes. According to transaction cost economics, firms in exchange need to establish an appropriate

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governance that can provide better performances. A contract that specifies missions, obligations, and penalties and rewards is a driver for the fulfillment of objectives of a joint relationship. With this

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respect, transaction cost advantage can be attained through the enhanced performance coupled with a contract that a supplier must conform to. A breach of a contract will lead both members to suffer from financial (e.g., costs incurred by delayed orders and products, and searching out another partner) and nonfinancial losses (e.g., loss of future business opportunities, exclusion of the supply chain network). Third, supply chain collaboration combined with governance mechanisms can create a synergic effect on transaction cost advantage. The empirical findings have suggested that contractual governance entails actual collaborative processes, whereas relational governance represents shared values and agreed behaviors (Tangpone et al., 2010; Zhou et al., 2015). When homogeneous parties work together whose business practices are different, misunderstandings and misinterpretation can occur. A

ACCEPTED MANUSCRIPT contract can provide a basic guideline for executing collaborative operational processes. Relational governance works as a catalyst for creating the atmosphere of collaboration through jointly shaped expectations, norms, and values. Therefore, while serving different purposes, both governances can

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create transaction cost advantage achieved by supply chain collaboration. Finally, yet importantly, a post-hoc analysis has further verified the effects of different levels of governance mechanisms on supply chain collaboration, performance, and transaction cost advantage. An inverted U-shaped relationship between contractual governance and supply chain collaboration

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suggests that contractual governance is effective in supply chain collaboration at some point, but after reaching the point, an increasing level of contractual governance no longer works for the achievement

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of supply chain collaboration. Conversely, a U-shaped relationship between relational governance and supply chain collaboration implies that even after a certain point is met, supply chain collaboration grows at an increasing rate as relational governance continues to rise. Those curvilinear effects explain that heavy reliance solely on contractual governance can deter supply chain collaboration. In

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addition, another inverted U-shaped relationship between relational governance and transaction cost advantage reveals that after a maximum point is reached, the transaction cost advantage diminishes with an increase in relational governance. The finding is consistent with earlier work stating that in a

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joint relationship where contractual governance dominates, relational governance safeguards exchanges by curbing opportunism through self-enforcement (Tangpong et al., 2010; Zhou et al., 2015)

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or that governance is not really effective.

Managerial Implications

The model development and empirical results help managers view the supply chain relationship in multiple ways. At first, this study provides guidance for managers to design supply chain collaboration activities by taking multi-dimensions of supply chain collaboration into account. If collaboration is ineffectively performed, the occurrence of transaction cost is inevitable for coordinating and solving inflexibility. So managers are required to set an optimized level of

ACCEPTED MANUSCRIPT collaboration through different governance forms. The reconceptualized definition of supply chain collaboration allows managers to set up appropriate strategies by looking into the components of collaboration, and such strategies will contribute to activating the effective collaboration based on the consensus that both parties agree upon. In this case, a well-specified contract enables managers to

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make the collaboration work in a right direction and so does trust. However, a buying firm must pay close attention to the reliance of contractual governance on the planning and execution of supply chain collaboration because the exchange relationship governed by extensive usage of the contract can

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fail to achieve desired outcomes.

The positive relationship between collaboration and performance implies that buyers and suppliers

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should create a positive-sum situation which buyers and suppliers can jointly benefit from. Supply chain members should be aware that if they pursue their own interests, a whole benefit can be shrunk and the relationship no longer lasts. Long-term relationships can not only produce mutual benefits but also eventually facilitate value of co-creation. Firms are thus required to design appropriate

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collaborative activities to safeguard exchanges.

This study has verified multi-dimensions of transaction cost. This finding is essential to managers in that, unlike production cost, transaction cost is difficult to identify and measure. A buying firm is

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forced to allocate substantial resources to assess its supplier’s performance and monitor the supplier’s current behaviors. Reducing such costs lies at the center of operation management. Rather than

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spending considerable resources on safeguarding exchange hazards related opportunism, a buying firm can save transaction costs by considering the confirmation of effectiveness in the buyer’s performance. In other words, such effectiveness can be regarded as a reliable sign from the buyers’ point of view that its suppliers are fully committed to the relationship. Thus, the necessity of monitoring and assessing a supplier’s behaviors and performance can be reduced. Finally, regarding governance modes, the findings have implied that both contract and relational governance may serve as leveraging performance and reducing transaction costs. This study indicated that managers should find an optimized level of reliance on both governances. In a word, the

ACCEPTED MANUSCRIPT appropriate use of contracts can help reconcile conflicts and systemize rewards and penalty, and the accumulation of trust may foster collaboration through better communication, shared norms and expectations. In summary, the flexible use of contracts and trust may contribute to the strength of

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collaboration and performance, and the stability of long-term relationships.

Limitations and Future Research

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This study also reveals several limitations. The small number of firms is a limitation that generalization beyond manufacturing firms may be limited. While this study has attempted to include

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a representative of leading manufacturing firms in South Korea for the generalization, the properties from this manufacturing sector can be different from those in other manufacturing sectors, thus creating challenges for generalization. Future study replicating this research should be carried out across multiple industries for an understanding of supply chain collaboration and governance effects.

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Another challenge is that this study relied on a cross-sectional study, which estimates the perceptions of subjects at one time. Since collaboration, transaction cost, and trust may differ over time, a longitudinal study may be needed to capture how effects of those constructs would change by

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different time.

Finally, this study also suffers from the method bias because of the self-reporting survey method of

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data collection. While this study has relied on several statistical procedures to detect common method bias, it does not necessarily mean this study is free of common method bias. Data collection from multiple sources, therefore, should be needed to improve reliability with little measurement error.

Conflict of interest We declare no conflicts of interest.

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ACCEPTED MANUSCRIPT Table 1. The sample demographics N

Percentage (%)

Respondent titles 19

6.3

Vice president

80

26.3

Director

108

35.5

Operation officer

97

31.9

Industry 139

Automobile

60

Steel

18

Foods

31

Pharmaceutical

56

Ownership State-owned

11~20 21~30 31~40 Working years 7~10

5.9

10.2 18.4

18

5.9

286

94.1

229

75.4

61

20.1

12

3.9

2

0.6

132

43.4

120

39.5

21~30

48

15.8

31~40

4

1.3

TE D

11~20

19.7

M AN U

Privately-owned The length of relationship 7~10

45.7

SC

Electronic

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Chief executive officer

Number of employees <100

100

32.9

100~300

40

13.2

300~500

7.2

16

5.3

>=700

126

41.4

AC C

EP

22

500~700

Table 2. Comparisons of early and late respondents Mean early respondents (N=42)

Mean late respondents (N=52)

t-value

Sig. (2-tailed)

2.40

2.04

1.117

.267

14.45

14.88

-.266

.791

Company types

1.71

1.77

-.597

.552

Ownership

2.00

2.00

0.000

1.000

The number of employees

3.50

3.10

1.099

.275

Annual sales

3.83

3.67

.461

.646

Annual profits

2.45

2.25

.553

.581

Variables

Industry types The number of working years

ACCEPTED MANUSCRIPT Table 3. Descriptive statistics and correlation matrix Variables

Means

SD

1

2

3

4

5

0.253

0.095

0.314

0.007

0.118

0.328

0.141

6

7

8

9

10

11

12

13

0.34

0.343

0.223

0.209

0.237

0.396

0.327

0.242

0.271

0.261

0.004

0.307

0.355

0.095

0.094

0.154

0.214

0.325

0.216

0.27

0.243

0.157

0.06

0.024

0.141

0.119

0.191

0.026

0.057

0.042

0.077

0.042

0.001

0.316

0.309

0.206

0.179

0.251

0.249

0.296

0.269

0.34

0.271

0.013

0.025

0.025

0.04

0.027

0.015

0.002

0.014

0.001

0.007

0.497

0.153

0.204

0.275

0.371

0.256

0.345

0.274

0.303

0.11

0.174

0.185

0.397

0.347

0.299

0.288

0.298

0.506

0.256

0.166

0.217

0.299

0.213

0.526

0.345

0.187

0.301

0.314

0.244

0.251

0.288

0.353

0.241

0.336

0.356

0.358

0.334

0.432

0.477

0.458

0.514

0.469

4.047

0.855

Contractual governance

4.385

0.85

.503**

Monitoring cost

3.206

0.987

.309**

.343**

Solving cost

2.822

0.967

.560**

.573**

.376**

Detecting cost

3.405

1.087

0.083

0.06

.396**

0.035

Information sharing

4.285

0.89

.583**

.554**

.245**

.562**

.114*

Goal congruence

4.373

0.878

.586**

.596**

.156**

.556**

.157**

.705**

Decision synchronization

3.612

1.079

.472**

.308**

.375**

.454**

.158**

.391**

.332**

Incentive alignment

3.586

1.071

.457**

.307**

.345**

.423**

.201**

.452**

.417**

.729**

Resource sharing

3.699

1.045

.487**

.392**

.437**

.501**

.164**

.524**

.430**

.711**

.725**

Collaborative communication

4.108

0.953

.629**

.463**

.162**

.499**

.122*

.609**

.630**

.506**

.587**

.619**

Quality

4.225

0.989

.572**

.570**

.239**

.544**

0.04

.506**

.589**

.407**

.432**

.501**

.580**

Speed

4.191

0.928

.492**

.465**

.206**

.519**

0.12

.587**

.547**

.466**

.549**

.537**

.597**

.657**

Cost

4.052

0.937

.521**

.520**

.277**

.583**

0.023

.523**

.537**

.547**

.560**

.594**

.598**

.691**

.717**

Flexibility

4.042

1.013

.511**

.493**

.206**

.521**

-0.085

.550**

.546**

.461**

.494**

.491**

.578**

.677**

.685**

SC

M AN U

Note:

0.531

1. Correlations were below the diagonal and squared correlations were above the diagonal.

AC C

EP

TE D

2. ** path is significant at 0.01; * significant at 0.05.

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Relational governance

14

0.383

15

0.533

.730**

ACCEPTED MANUSCRIPT Table 4. Survey items and confirmatory factor analysis results Construct and items

Factor loading

Standardized loading

SE

t-value

1.1

0.804

0.077

14.203

Information sharing (CR = 0.838; AVE = 0.633; Cronbach's α = 0.837) Our firm and this supply chain partner exchange

information

RI PT

Relevant Timely Accurate complete (e) confidential (e)

Our firm and this supply chain partner have agreement on the goals of the supply chain

0.821

1##

0.761

SC

Goal congruence (CR = 0.907, AVE = 0.710; Cronbach's α = 0.914)

1.062

0.073

14.523

0.959

0.82

0.053

18.233

0.923

0.815

0.051

18.022

0.955

0.858

0.048

19.908

1##

0.877

1.02

0.789

0.066

15.385

0.872

0.714

0.065

13.49

0.991

0.843

0.059

16.838

1##

0.82

0.999

0.809

0.068

14.611

0.909

0.785

0.064

14.126

1##

0.759

use cross-organizational teams frequently for process design and improvement

1##

0.748

dedicate personnel to manage the collaborative processes

0.92

0.736

0.06

15.267

share technical supports

0.972

0.813

0.075

12.917

share equipment (e.g. computers, networks, machines)

1.027

0.79

0.074

13.943

pool financial and non-financial resources (e.g. time, money, training)

1.104

0.836

0.074

14.824

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Our firm and this supply chain partner have agreement on the importance of collaboration across the supply chain Our firm and this supply chain partner have agreement on the importance of improvements that benefit the supply chain as a whole

Our firm and this supply chain partner agree that our own goals can be achieved through working toward the goals of the supply chain

Our firm and this supply chain partner jointly layout collaboration implementation plans to achieve the goals of the supply chain (e) Decision synchronization (CR = 0.871; AVE = 0.629; Cronbach's α = 0.868)

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Our firm and this supply chain partner jointly plan on promotional events develop demand forecasts manage inventory plan on product assortment

EP

work out solutions (e)

Incentive alignment (CR = 0.828; AVE = 0.616; Cronbach's α = 0.824) Our firm and this supply chain partner

AC C

co-develop systems to evaluate and publicize each other’s performance (e) share costs (e.g. loss on order changes)

share benefits (e.g. saving on reduced inventory costs) (e) share any risks that can occur in the supply chain The incentive for our firm commensurate with our investment and risk Resource sharing (CR = 0.889; AVE = 0.617; ; Cronbach's α = 0.890) Our firm and this supply chain partner

ACCEPTED MANUSCRIPT Collaborative communication (CR = 0.908; AVE = 0.666; ; Cronbach's α = 0.903) Our firm and this supply chain partner 1.19

0.823

0.085

13.929

have open and two-way communication

1.182

0.841

0.084

14.011

have informal communication

1.191

0.825

0.085

13.956

have many different channels to communicate

1.237

0.87

0.085

14.516

1##

0.711

1##

0.901

We have seen an improvement in the quality of the order fulfillment process with time

0.992

0.886

0.044

22.576

Based on our knowledge of the order fulfillment process, we think it is of high quality

1.005

0.861

0.047

21.291

Quality (CR = 0.914; AVE = 0.779; Cronbach's α = 0.913) The quality of the order fulfillment process in our firm is getting better with time

Speed (CR = 0.888; AVE = 0.727; Cronbach's α = 0.885) The length of the order fulfillment process in our firm is getting shorter with time

SC

influence each other’s decisions through discussion rather than request

RI PT

have frequent contacts on a regular basis

1##

0.877

0.914

0.896

0.043

21.119

0.802

0.78

0.048

16.758

1##

0.806

We have seen an improvement in the cost associated with the order fulfillment process with time

1.084

0.906

0.058

18.671

Based on our knowledge of the order fulfillment process, we think it is cost efficient

1.086

0.816

0.067

16.184

1##

0.904

We have seen an improvement in the flexibility of the order fulfillment process with time

1.076

0.94

0.04

26.98

Based on our knowledge of the order fulfillment process, we think it is flexible

1.056

0.861

0.048

22.001

1##

0.781

1.055

0.844

0.072

14.65

0.956

0.806

0.068

14.107

1##

0.788

1.049

0.834

0.075

14.036

1.076

0.83

0.066

16.314

1.109

0.884

0.063

17.719

M AN U

We have seen an improvement in the cycle time of the order fulfillment process with time Based on our knowledge of the order fulfillment process, we think it is short and efficient Cost (CR = 0.881; AVE = 0.712; Cronbach's α = 0.875)

The cost associated with the order fulfillment process in our firm is getting better with time

Flexibility (CR = 0.929; AVE = 0.814; Cronbach's α = 0.927)

TE D

The flexibility of the order fulfillment process in our firm is getting better with time

Monitoring cost (CR = 0.852; AVE = 0.657; Cronbach's α = 0.849)

It is easy to tell if we were receiving fair treatment from this supplier (e)

EP

It takes significant effort to detect whether or not this supplier conforms to specifications and quality standards (Reverse corded) We are in a good position to evaluate how fairly this Supplier

deals with us (e)

AC C

Accurately evaluating this supplier requires a lot of effort (Reverse corded) There is not much concern about this supplier taking advantage of this relationship It is not costly, in time and effort, to clearly monitor the performance of this supplier (e) Solving cost (CR = 0.794; AVE = 0.658; Cronbach's α = 0.793) The approach to solving problems in our relationship with this supplier is clear-cut There are standard solutions or approaches to problems that might occur with this supplier Problem solving is often challenging, due to the nature of component or service (Reverse corded) (e) Although solutions to problems can be achieved, they would often need to be highly customized (Reverse corded) (e) Detecting cost (CR = 0.909; AVE = 0.715; Cronbach's α = 0.909) Concerning the likelihood of this supplier taking advantage of its relationship with our firm (e) There are no incentives for this supplier to pursue this supplier's interests at the expense of our interests It is easy for this supplier to alter the facts in order to get what the supplier wanted (Reverse corded)

ACCEPTED MANUSCRIPT There is a strong temptation for this supplier to withhold or distort information for this supplier's benefits (Reverse corded) (e) It is difficult for this supplier to promise to do things and get away without actually doing them later

1.096

0.863

0.064

17.183

1##

0.804

We believe in the supplier because it is sincere

1.223

0.789

0.085

14.45

Though the circumstances change, we believe that the supplier will be ready and willing to offer us assistance and support

1.109

0.734

0.084

13.274

When making important decisions, the supplier is concerned about our welfare or interests

1.271

0.827

0.083

15.287

We can count that the supplier's future decisions and actions will not adversely affect us

1.411

0.85

0.089

15.787

1##

0.771

There exists, from this supplier’s perspective, a significant motivation to take advantage of unspecified or unenforceable contract terms (Reverse corded) (e)

RI PT

Relational governance (CR = 0.896; AVE = 0.632; Cronbach's α = 0.894)

When it comes to things that are important to us, we can depend on the supplier’s support

We have a specific, well-defined agreement with this partner We have customized agreements that detail the obligations of both parties

Most aspects of our relationship are specified in the contract (e)

Our contract precisely defines what will happen in case of unexpected events

Note: 1. An item marked with (e) is eliminated.

0.975

0.775

0.074

13.161

0.958

0.709

0.08

11.992

1.014

0.798

0.075

13.548

M AN U

We have detailed contractual agreements specifically designed with this partner

SC

Contractual governance (CR = 0.844, AVE = 0.576; Cronbach's α = 0.914)

1##

0.75

TE D

2. ## Values were not calculated because loading was set to 1 to fix construct variance.

Table 5. Fit indices for the first- and second-order models

Supply chain collaboration

Chi-square (df)

Normed Chi-square

CFI

NNFI

RMSEA

first-order

583.745

2.264

0.939

0.897

0.056

second-order

700.932

2.561

0.908

0.865

0.057

first-order

92.844

1.934

0.986

0.972

0.056

second-order

97.194

1.944

0.985

0.97

0.056

first-order

43.903

1.689

0.988

0.971

0.048

second-order

51.315

1.901

0.984

0.966

0.055

AC C

Firm performance

Model

EP

Construct

T coefficient 0.833

0.955

Transaction cost advantage

0.856

ACCEPTED MANUSCRIPT Table 6. The results of hypotheses Firm performance

Transaction cost advantage

Dependent variables M1

M2

M3

M4

M5

M6

M7

M8

M9

M10

M11

M12

0

0.015

0.029

0.038

0.018

0.018

0.017

0.015

0.018

0.032

0.041

0.042

Automobile

0.042

-0.001

-0.003

-0.002

0.102

.064*

.064*

.065*

0.102

0.062

0.059

0.069

Steel

-0.006

0.061

0.036

0.036

-0.007

-0.002

0.001

-0.001

-0.007

0.055

0.037

0.034

Foods

0.012

0.029

0.003

0.007

0.011

0

-0.003

0.001

0.011

0.026

0.007

0.014

Tangible

-0.036

0.047

0.033

0.036

-0.035

-0.003

-0.004

-0.006

-0.035

0.042

0.032

0.027

Imported

-.131**

-.104**

-.092**

-.086**

-.131**

-0.014

-0.014

-0.016

-.131**

-.106**

-.096**

-.095**

Private-owned

-0.033

-0.012

0.002

0.003

-0.048

-0.018

-0.016

-0.019

-0.048

-0.028

-0.015

-0.024

Relationship length

.119*

0.026

0.039

0.048

0.088

-0.019

-0.016

-0.015

0.088

0.002

0.013

0.017

0.1

0.016

-0.015

-0.013

0.093

0.003

0

0

0.093

0.016

-0.01

-0.015

.754***

.557***

.558***

.698***

.562***

.549***

Main effect Supply Chain Collaboration Firm Performance

.898***

Moderators

.931***

.924***

.113**

.105**

0.007

0.021

.188***

.191**

Relational

.228***

.226***

0.055

.063*

0.054

0.064

TE D

Contractual

Interaction terms Collaboration * Contractual

Performance * Contractual Performance * Relational

0.023

Change in F value

1.797*

-0.079

.112**

-0.009

.104** .064** 0.047

0.568

0.616

0.621

0.054

0.765

0.002

0.002

0.054

0.454

0.028

0.009

372.246***

19.310***

2.850*

1.872*

1241.347***

1.288*

1.491*

1.872*

270.755***

8.872***

2.839*

AC C

Change in R2

EP

Collaboration * Relational

Note:

SC

Number of employees

M AN U

Electronic

RI PT

Industry

1. *** path is significant at 0.01; ** significant at 0.05; * significant at 0.1

ACCEPTED MANUSCRIPT Table 7. The summary of hypotheses testing results Hypotheses

Support for hypotheses

H1

Supply chain collaboration

Firm performance

Supported

H2

Firm performance

Transaction cost advantage

Supported

H3

Supply chain collaboration

H4a

Contractual governance positively moderates: Supply chain collaboration

H4b

Relational governance positively moderates: Supply chain collaboration

H5a

Contractual governance positively moderates: Firm performance

H5b

Relational governance positively moderates: Firm performance

H6a

Contractual governance positively moderates: Supply chain collaboration

H6b

Relational governance positively moderates: Supply chain collaboration

Supported

Transaction cos advantage

Failed to support

Firm chain performance

Transaction cost advantage

RI PT

Firm performance

Failed to support Supported

Failed to support

Transaction cost advantage

Supported

Transaction cost advantage

Supported

M AN U

SC

Transaction cost advantage

Table 8. Results of the hierarchical analysis for a post-hoc analysis Dependent variables

Supply chain collaboration M10

M11

Electronic

-.020

-.002

Automobile

.056

.025

Steel

-.089

Foods

-.022

Tangible

-.110*

-.072*

-.072*

Imported

-.036

.031

.032

Private-owned

-.028

-.014

-.016

Relationship length

.124**

.050

Number of employees

.111*

.067

M14

M15

M16

M17

M18

.009

.000

.021

.026

.118

.098

.106

.029

.042

.008

.009

.030

.061

.056

-.126***

-.126***

-.006

-.038

-.039

.018

.040

.035

-.020

-.014

.012

.001

.003

.037

.060

.061

-.036

-.004

-.003

-.037

-.059

-.051

-.131**

-.066

-.066

.099

.046

.041

-.033

-.007

-.008

.083

.050

.053

.048

.119*

.062

.062

-.049

-.017

-.010

.064

.100

.032

.033

-.180***

-.099**

-.087*

Relational Quadratic effect

TE D

AC C

Contractual

.160***

.109**

.293***

.277***

.383***

.380***

.602***

.649***

.468***

.478***

.258***

.295***

EP

Contractual

Change in F value

Note:

-.144***

-.048

.105**

Relational

Change in R2

Transaction cost advantage

M13

Industry

Main effect

Firm performance

M12

-.012

.018

-.128**

.066

.484

.014

.052

.448

.002

.068

.314

.017

2.324**

157.314***

4.706***

1.797*

130.978***

.451***

2.378**

74.190***

3.986***

1. *** path is significant at 0.01; ** significant at 0.05; * significant at 0.1

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

EP

TE D

Figure 1. The research framework

AC C

Figure 2. The quadratic effects of governance mechanisms