Relational mechanisms, formal contracts, and local knowledge ...

Strategic Management Journal Strat. Mgmt. J., 31: 349–370 (2010) Published online EarlyView in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/smj.813 Received 11 July 2006; Final revision received 18 August 2009

RELATIONAL MECHANISMS, FORMAL CONTRACTS, AND LOCAL KNOWLEDGE ACQUISITION BY INTERNATIONAL SUBSIDIARIES JULIE JUAN LI,1 * LAURA POPPO,2 and KEVIN ZHENG ZHOU3 1 Department of Marketing, College of Business, City University of Hong Kong, Kowloon Tong, Hong Kong 2 School of Business, University of Kansas, Lawrence, Kansas, U.S.A. 3 School of Business, The University of Hong Kong, Pokfulam, Hong Kong

This research focuses on relational and contractual mechanisms and examines their impact on foreign subsidiaries’ acquisition of tacit and explicit knowledge from local suppliers. Using survey data from 168 foreign subsidiaries operating in China, this study finds broad support for the proposed analytical framework. When the foreign subsidiary and supplier share common goals, the foreign subsidiary acquires greater levels of both explicit and tacit knowledge; trust between the two parties promotes the acquisition of greater levels of tacit than explicit knowledge. However, access to the local supplier network through the focal supplier enables the foreign subsidiary to acquire greater levels of explicit but not tacit knowledge. Formal contracts play a complementary role in knowledge acquisition: contracts enhance the acquisition of explicit knowledge and further strengthen the effects of relational mechanisms on tacit and explicit knowledge acquisition. Overall, these findings provide important implications for foreign subsidiaries regarding how to acquire local knowledge in host countries through both formal and informal mechanisms. Copyright  2009 John Wiley & Sons, Ltd.

INTRODUCTION In a knowledge economy, a firm’s ability to acquire and ultimately assimilate and absorb knowledge from its external environment—its absorptive capacity—is an important determinant of firm growth, survival, and economic performance. Prior work shows that subsidiaries or joint ventures are more likely to survive and prosper when foreign parents effectively transfer their managerial, technical, and marketing knowhow to local subsidiaries (e.g., Lane, Salk, and Lyles, 2001; Lyles and Salk, 1996; Steensma and Lyles, 2000). Such research also highlights knowledge spillovers from foreign to local firms in Keywords: trust; ties; shared goals; knowledge; contracts; international subsidiaries; China *Correspondence to: Julie Juan Li, Department of Marketing, College of Business, City University of Hong Kong, Kowloon Tong, Hong Kong. E-mail: [email protected]

Copyright  2009 John Wiley & Sons, Ltd.

emerging economies, given the stronger marketing and technological capabilities of foreign firms (Steensma et al., 2008). Works further demonstrate certain factors that influence knowledge acquisition and learning, including the use of formal structural mechanisms such as managerial oversight, incentives, and training programs (Inkpen, 2008; Lane and Lubatkin, 1998; Lyles and Salk, 1996); relational mechanisms such as trust and shared values (Dhanaraj et al., 2004; Szulanski, 1996); and knowledge characteristics such as relatedness, ambiguity, and complexity (Lane et al., 2001; Szulanski, 1996; Zander and Kogut, 1995). A careful review of this literature, however, identifies several significant gaps. First, though extant literature highlights the important role of relational mechanisms such as network ties, shared values, and trust in knowledge acquisition and transfer, few studies examine their relative effects on the acquisition of tacit versus explicit knowl-

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edge. Distinguishing between tacit and explicit knowledge is important because they purportedly differ with regard to the ease and effectiveness of knowledge acquisition (e.g., Dhanaraj et al., 2004; Inkpen, 2000). Tacit knowledge is complex, hard to articulate, and difficult to transfer, whereas explicit knowledge is codifiable and can be transmitted without loss of integrity (Nonaka and Takeuchi, 1995; Polanyi, 1967). Because most empirical works tend to lump all knowledge into a single category (Nobeoka, Dyer, and Madhok, 2002), the issue of how various relational mechanisms differentially affect the acquisition of tacit and explicit knowledge remains underexamined. Second, whether formal mechanisms, such as contracts, have a desirable, positive effect on knowledge acquisition is subject to controversy. Some argue that formal controls derail the intrinsic motivation and effort required to transfer tacit knowledge (Adler, 2001; Osterloh and Frey, 2000), whereas others claim that formal controls and procedures generally facilitate the transfer of knowledge (Lane and Lubatkin, 1998; Lyles and Salk, 1996). Still others posit that a mix of formal and relational mechanisms may be necessary to manage complex interfirm relationships (Das and Teng, 1998; Poppo and Zenger, 2002). According to Cohen and Levinthal, one key source of absorptive capacity is ‘the structure of communication between the external environment and the organization’ (Cohen and Levinthal, 1990: 132). Although recent works show that external relationships such as interfirm ties and networks are critical to the acquisition of valuable knowledge (Dyer and Hatch, 2006; McEvily and Marcus, 2005; Tiwana, 2008), it is still unresolved and unexplored as to how formal contracts interact with relational mechanisms to affect knowledge acquisition for interfirm relationships. Third, previous research mainly focuses on knowledge transfer from parent firms to international subsidiaries or among subsidiaries within multinational corporations (MNCs). Yet when operating in unfamiliar markets, international subsidiaries rely heavily on local businesses to secure needed resources and understand local market conditions, business practices and networks, and host country-specific commercial practices and cultures (Li, Poppo, and Zhou, 2008; Steensma et al., 2008). Foreign subsidiaries depend particularly on local knowledge to help them adapt their products, access promotion channels, select market Copyright  2009 John Wiley & Sons, Ltd.

segments, and upgrade their technology for local markets (Tsang, 2002). Although previous work shows that foreign firms realize improved performance when they partner with domestic rather than foreign firms, few studies address an additional venue for value creation, namely, the foreign subsidiaries’ acquisition of local knowledge from domestic suppliers. This contextualization of the knowledge transfer setting is important to establish boundary conditions for theory, as well as generate managerial insights for foreign firms. To address these research gaps, we develop a framework (see Figure 1) to examine the effects of relational and formal mechanisms on local knowledge acquisition of foreign subsidiaries from their domestic suppliers. We first consider how three relational mechanisms, namely, brokered access, shared goals, and trust, differentially affect the acquisition of explicit and tacit local knowledge. We further examine the role of formal contracts and the collective effects of formal contracts and relational mechanisms in local knowledge acquisition. Taken together, our efforts aim to uncover how foreign subsidiaries use formal and relational mechanisms to acquire explicit and tacit local knowledge in host countries.

THEORY AND HYPOTHESES Relational mechanisms and local knowledge acquisition The resource-based view advances that a firm’s unique resources and capabilities are key drivers of superior performance. A recent extension of this logic posits that firms may generate abnormal returns from resources and capabilities that reside in their relationships with other firms (Dyer and Singh, 1998; Inkpen, 2000). Because a firm’s exchange partners offer important sources of new ideas and information, such relationships constitute ‘a unique and productive resource for value creation’ (Madhok and Tallman, 1998: 327; McEvily and Marcus, 2005). Recent work further shows that knowledge sharing between a focal firm and its broader supplier network does not appear to ‘leak’ to the suppliers’ exchanges with other buyers, suggesting that the network can be a source of capability development (Dyer and Hatch, 2006). Applying this approach to our context, an international subsidiary’s local business network contains multiple potential sources of knowledge: Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

Relational Mechanisms, Contracts, and Local Knowledge Acquisition Formal contracts Relational mechanisms Indirect ties Brokered access

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H2

H3a~c

Knowledge acquisition

H1a-c

Explicit knowledge

Direct ties Shared goals Trust

Tacit knowledge

Controls - Firm age - Firm size - Link duration - Asset specificity - Entry mode - Industry type - Cultural distance - Local knowledge importance - Supplier age - Supplier size - Supplier performance

Figure 1.

The conceptual model

local suppliers, customers, production partners, technical institutes, and public agencies. Most consider suppliers and customers as the leading sources of new information, because the focal supplier serves as a critical source for coordinating local market operations (Dyer and Hatch, 2006; Uzzi, 1997) and lead customers provide important sources of product innovation knowledge (Zhou, Yim, and Tse, 2005). McEvily and Marcus (2005) further find, in their survey of manufacturers, that capabilities acquired from suppliers and customers differ qualitatively: the former tend to be implementation and operation based, whereas the latter are more product related. In addition, manufacturers tend to have uniformly high level of ties with customers, making them a less likely source of competitive advantage. In contrast, close ties with suppliers have greater variation and may be more valuable for achieving competitive advantage through capability acquisition. These findings indicate that to deepen our understanding of knowledge acquisition, we need to focus on a specific network source. Following Dyer and Nobeoka (2000), we examine the relationship dyad between an international subsidiary and its major local supplier. We consider two alternative ways through which foreign subsidiaries may acquire local knowledge from their focal Copyright  2009 John Wiley & Sons, Ltd.

supplier: direct and indirect interactions. According to knowledge transfer literature, direct interactions are substantial, focused, and intense, with the greatest propensity to transfer knowledge (Ahuja, 2000). Two of the most salient characteristics of such relationships are shared goals and trust (e.g., Inkpen and Tsang, 2005; McEvily and Marcus, 2005). Shared goals promote mutual understanding beyond contractually specified clauses regarding price, quantity, and quality and fuel the exchange of resources and knowledge by creating greater levels of interaction and projecting the exchange into the future (Tsai and Ghoshal, 1998). Trust establishes a basis of intimacy, predictability, and reliability, which leads parties to be more open and receptive to the transfer and acquisition of knowledge (Dyer and Hatch, 2006; Inkpen and Tsang, 2005). Indirect interactions, an important yet relatively unexplored characteristic of relationships, instead refer to access to more distant firms through the focal partner (Tiwana, 2008; Yli-Renko, Autio, and Sapienza, 2001). In this study, we focus specifically on the supplier’s network scope (brokered access hereafter), which we define as the degree to which the focal supplier enables the foreign subsidiary access to a broader, local network of suppliers. Such brokered access may confer legitimacy and facilitate the foreign Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

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subsidiary’s access to scarce resources and new sources of knowledge (Galaskiewicz, Bielefeld, and Dowell, 2006; Vanhaverbeke, Duysters, and Noorderhaven, 2002). Despite this rich theoretical backdrop, empirical investigations of how various relational factors influence knowledge acquisition in interorganizational exchanges remain limited (Dyer and Hatch, 2006; McEvily and Marcus, 2005), and their relative effects on different types of knowledge acquisition are still underexplored. Therefore, we examine how brokered access, shared goals, and trust differentially affect explicit versus tacit knowledge acquisition. These three relational mechanisms represent the indirect and direct facets of an exchange relationship. Because relational mechanisms may have different abilities to effect knowledge transfer (McEvily and Marcus, 2005), we examine how each mechanism affects knowledge acquisition. Brokered access The value derived from social ties depends critically on the willingness of each party to help the other party obtain knowledge to which it lacks access. Although knowledge access often occurs directly between those parties that form the relational tie, each party may facilitate access to information and resources beyond that available in the direct tie. For example, a foreign subsidiary may gain indirect access to the local supplier network through a focal supplier. In effect, the focal supplier brokers access and knowledge flows, which broaden the subsidiary’s network and access to new knowledge sources (Galaskiewicz et al., 2006; Tiwana, 2008; Yli-Renko et al., 2001). Prior work highlights the importance of network access, particularly in emerging economies, because trade is coordinated largely through social networks. This heavy reliance on a social, rather than a market mechanism to connect buyers and suppliers occurs because of the unpredictability of the legal system, the general lack of reliable public information, and the difficulty associated with knowing whom to trust and who has the required business competencies (Keister, 2001; Li et al., 2008). Penetrating business networks, however, is difficult for international subsidiaries initially because of a liability of foreignness (Zaheer, 1995) and Copyright  2009 John Wiley & Sons, Ltd.

because credible market information is not readily available in an emerging economy (Li et al., 2008). Without brokered access, exchange relationships may lack the legitimacy necessary for foreign subsidiaries and local parties to view each other as proper, desirable, and reliable firms with which to conduct business (Vanhaverbeke et al., 2002). In this aspect, brokered access serves as one important mechanism for foreign subsidiaries to establish a broader network. Consistent with this logic, Batjargal (2003) shows that legitimate ties promote a new venture firm’s access to necessary others, such as venture capital firms. Because the focal supplier has greater intimate knowledge of the foreign subsidiary’s capabilities and skills, it can facilitate knowledge transfer by acting as an intermediary. By forging connections, the foreign subsidiary can reach a wider range of local knowledge. These more distant contacts, however, are more likely to transfer explicit rather than tacit knowledge. First, as weaker structural links, brokered access is characterized by more distant and less frequent interaction (Uzzi, 1997), which is more likely to provide public information (Vanhaverbeke et al., 2002). Weaker ties also are less motivated to expend the effort necessary to identify and share useful tacit knowledge or communicate it in a way that it is readily understood and absorbed by the recipient (Hansen, 1999; Levin and Cross, 2004). Second, as a bridge, the focal supplier would be more effective at transmitting explicit knowledge, facts, and discrete information because explicit knowledge can be transmitted through simple communication without loss of integrity (Hansen, 1999; Kogut and Zander, 1992). Tacit knowledge is simply more difficult to transfer across indirect organizational interfaces because of its embeddedness in organizational routines and processes (Inkpen, 2000; Koka and Prescott, 2002). Therefore, brokered access is most effective for acquiring explicit knowledge. Hypothesis 1a: Brokered access has a stronger positive effect on the acquisition of explicit than tacit local knowledge. Shared goals Shared goals refer to a bilateral understanding, approach, and vision for achieving tasks and outcomes, which ultimately promote the exchange Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

Relational Mechanisms, Contracts, and Local Knowledge Acquisition relationship as a whole and help project the exchange into the future (Tsai and Ghoshal, 1998). According to Inkpen and Tsang, shared goals mitigate the tension between cooperation and competition; otherwise, ‘knowledge may flow very slowly or not at all’ (Inkpen and Tsang, 2005: 159). Because shared goals help partners recognize that cooperation can enhance their individual competitive positions as well as their joint competitive position, parties are more willing to share ideas and know-how. When a relationship enjoys this shared vision, partners tend to engage in joint problemsolving processes and thus have more opportunity to exchange resources and knowledge (Inkpen, 2008; McEvily and Marcus, 2005). This common goal of achieving a competitive advantage in a bilateral manner harmonizes partners’ interests and motivates them to share knowledge. For international transactions in emerging economies, parties have different resource sets. Foreign subsidiaries usually have advanced technical capabilities and strong basic research capabilities, whereas local firms have unique knowledge about the supply of goods, distribution of end products, and local markets (Steensma et al., 2008). Due to the lack of reliable information sources in emerging economies, explicit local knowledge is not publicly available to foreign firms (Li et al., 2008). Accordingly, the bilateral intent fostered through shared goals is needed for foreign subsidiaries to learn such local knowledge. For example, close interactions can reveal explicit knowledge gaps, and the dominant supplier will readily inform the foreign subsidiary of this knowledge so that both parties may realize gains from the exchange. Shared goals are also likely to support the acquisition of tacit knowledge. With shared goals, partners have similar perceptions about how they should interact, which helps establish a foundation of common understanding and the means to achieve the collaborative purposes (Das and Teng, 1998). This social bond harmonizes their social interaction and enables the subsidiary to obtain tacit knowledge, such as the supplier’s engineering resources, negotiation skills, or relationship management capabilities (Nobeoka et al., 2002). Because of this deeper understanding of each other’s operations, parties transfer knowledge more readily across organizational boundaries. This mutual orientation to their joint work may also enable them to blend their resources more Copyright  2009 John Wiley & Sons, Ltd.

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effectively, leading to a potential source of value creation (Madhok and Tallman, 1998; Tiwana, 2008). Thus, shared goals smooth the transfer process by avoiding communication misunderstandings and reducing negotiation time, which in turn speeds up knowledge exchanges and decreases the ‘stickiness’ of interorganizational knowledge transfer. Therefore, we propose: Hypothesis 1b: Shared goals have a positive effect on the acquisition of both explicit and tacit local knowledge.

Trust At the interfirm level, trust refers to the extent to which a firm believes that its exchange partner is honest and/or benevolent (Zaheer, McEvily, and Perrone, 1998). Because trust eases communication among parties, it is viewed as a critical driver of knowledge transfer: When trust exists, the recipient is more likely to be open and receptive to the knowledge offered by another (Inkpen and Tsang, 2005; Uzzi, 1997). This intimacy is also associated with frequent communication (Szulanski, 1996) and coordination flexibility, because parties are more willing to respond quickly to interfirm requests (Das and Teng, 1998). A major obstacle to interfirm knowledge transfer is the potential leakage of valuable knowledge (Dyer and Singh, 1998; Inkpen, 2000). Trust helps overcome this obstacle by establishing a level of behavioral predictability and reliability through the accumulation of exchange experiences. That is, a belief that the partner will not use knowledge at the focal firm’s expense increases parties’ willingness to share valuable knowledge. Moreover, trust enables greater cooperation between the recipient and the knowledge source by creating the mutual understanding that both parties will consider the interests of the other (Lane et al., 2001). For example, trust may foster knowledge transfer by establishing idiosyncratic sharing routines to facilitate learning of specified information and know-how (Dyer and Singh, 1998) and increasing the overall level of information exchange between parties (Tsai and Ghosal, 1998). We extend existing literature by suggesting that trust fosters the acquisition of greater levels of Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

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tacit than explicit knowledge. For exchanges characterized by interfirm trust, the adjoining behavioral processes are more akin to those that support the transfer of tacit knowledge than those that enable explicit knowledge transfer. As Uzzi (1997) points out, trust is associated with close, intimate relationships. Whereas transferring tacit knowledge across organizational boundaries is generally difficult because of its sticky and hard-to-codify nature, close and intense interactions between exchange partners constitute an effective mechanism to transfer such knowledge. Not only does exposure to the source unit’s work environment and socialization process greatly encourage the transfer of tacit knowledge (Nonaka and Takeuchi, 1995), but the willingness to spend significant time together and maintain stable relationships also facilitates tacit knowledge transfer (Kotabe, Martin, and Domoto, 2003; Nonaka and Takeuchi, 1995). In contrast, we do not expect to observe an equally strong relationship between trust and the acquisition of explicit knowledge. Most exchange relationships originate with the transfer of explicit information as a prerequisite for establishing a credible and effective basis of economic exchange. Because explicit information can be acquired through direct communication, including written documents, close and intimate relationships are not necessary. Consistent with this point, Yakubovich (2005) notes that explicit information is readily transferable if direct contact exists between exchange parties. Koka and Prescott (2002) also posit that a trust network can transmit more sensitive and richer information than other types of networks (see also Dhanaraj et al., 2004). McEvily and Marcus (2005) similarly argue that strong ties are not necessary for explicit knowledge transfers. Thus, trust facilitates the acquisition of tacit more than explicit knowledge. Hypothesis 1c. Trust has a stronger positive effect on the acquisition of tacit than explicit local knowledge. The complementary role of contracts Whereas existing literature primarily focuses on how relational mechanisms affect knowledge transfer, few works examine an alternative vehicle—the formal contract. Firms seek contracts to mitigate self-interest, and thus opportunistic behavior, Copyright  2009 John Wiley & Sons, Ltd.

which otherwise seriously undermines the performance of interorganizational exchanges (Williamson, 1996). Formal contracts spell out the obligations and roles of both parties in the relationship, arrange for enforcement by third parties, and specify objectives, rules, and procedures for resolving disputes (Cannon and Perreault, 1999; Reuer and Ariño, 2007). By clarifying task and performance expectations, incorporating information provisions and requirements, and instituting penalties for noncompliance, contracts mitigate uncertainty and risks associated with opportunistic behavior. Thus, contracts enhance control and reduce the agency problem inherent in market exchanges (Malhotra and Murnighan, 2002; Williamson, 1996). Consistent with the dominant view of contracts as a control vehicle (versus a knowledge acquisition vehicle), previous research posits that the role of formal contracts in knowledge acquisition and sharing is minimal because the most valuable information that a firm can obtain is likely to be tacit (e.g., Adler, 2001; Madhok and Tallman, 1998). For example, specific contractual language cannot address such aspects as technical know-how or skills (Inkpen, 2000). Moreover, the difficulty of measuring the value of or pricing tacit knowledge makes it hard to devise a detailed contract for sharing it (Dyer and Singh, 1998; Koka and Prescott, 2002). While they are less likely to affect tacit knowledge acquisition, contracts may facilitate the acquisition of explicit knowledge. When contracts codify each party’s rights, duties, obligations, and responsibilities and specify goals (Reuer and Ariño, 2007), they create formal operating procedures that require the communication of explicit knowledge. For example, more formalized contracts that specify the technologies underlying the task may also require information or the right to monitor the use of the technology. Related, more complete and customized contracts often require reports with performance measurements (Barthélemy and Quélin, 2006). The specification of performance metrics is a form of symbolic communication and further increases the level of explicit knowledge exchange between parties when they implement related activities (Grant, 1996). Because contracts constitute an important platform for communication, a requisite byproduct is information exchange, especially codifiable information and routines that support the use of contracts. Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

Relational Mechanisms, Contracts, and Local Knowledge Acquisition Hypothesis 2: Formal contracts have a stronger positive effect on the acquisition of explicit than tacit local knowledge. Whereas contracts both structure and require communication, it remains unclear whether they enhance or dampen the knowledge transfer benefits of relational mechanisms. We posit that formal contracts may complement the use of relational mechanisms in promoting knowledge acquisition in three distinct ways: (1) contracts represent a stock of related knowledge that increases the focal firm’s ability to absorb new knowledge through relational mechanisms; (2) contracts provide a template for coordinating the transfer of knowledge, which the firm can then apply in interactions with more distant suppliers; and (3) contracts provide formal specification and assurance, complementing the informal specification of shared goals and informal assurance of trust. In these ways, contracts reduce cognitive and coordination barriers and thus strengthen the impact of relational mechanisms on knowledge acquisition. Our logic regarding the interactive effect of contracts and each relational mechanism follows. Contracts and brokered access The acquisition of new knowledge depends critically on a sufficient basis of prior related knowledge (Cohen and Levinthal, 1990; Grant, 1996). Prior knowledge includes basic skills, shared language, and potential technological developments. Without prior related knowledge, the cognitive mechanisms that enable managers to assimilate and accumulate new knowledge are largely undetermined. As a result, a firm’s ability to add or accumulate new knowledge is limited. Therefore, prior knowledge effectively reduces a cognitive barrier to knowledge acquisition. By accumulating prior related knowledge, a firm is better situated to accumulate new knowledge (Cohen and Levinthal, 1990). Although relational mechanisms ease social barriers to knowledge flows, they cannot overcome cognitive barriers: if the receiving firm does not possess a sufficient base of related knowledge, knowledge absorption is limited. Because contracts specify roles, rules, and procedures, they represent a level of shared knowledge with regard to technologies, operating policies, and managerial Copyright  2009 John Wiley & Sons, Ltd.

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techniques. That is, contracts represent a stock of related knowledge. Because the local supplier network is organized around a common production functionality, related knowledge between the buyer and focal supplier forms a solid base to absorb the new knowledge held by the local supplier network. Foreign subsidiaries are then able to accumulate greater explicit knowledge from the supplier network regarding subtle differences in firm-specific uses and practices. Thus, contracts as a stock of related knowledge reduce cognitive barriers and enable brokered access to be a more effective conduit for acquiring new knowledge. Organizing principles, which structure information flow between diverse units to minimize communication problems and ease coordination, represent a second challenge of effective knowledge acquisition (Zander and Kogut, 1995). When partners employ a coordination device, communication can occur more efficiently, and, depending on the type of coordination device, it may reduce the conflict that arises from differing objectives. Existing literature recognizes routines as one possible coordinating device (Grant, 1996), and recent work argues that documents detailing best practices represent codified routines (Kale and Singh, 2007). A codified template is akin to a recipe for success, and its value derives from the ability of parties to carry over these best practices to manage other tasks (Zollo and Winter, 2002). Building on this logic, we suggest that contracts contain routines that support complex forms of interaction and communication by triggering a set of sequenced actions and activities. Contracts typically are customized with better specifications over time to reflect learning from both successes and mistakes (Mayer and Argyres, 2004; Zhou, Poppo and Yang, 2008). When the buyer and focal supplier carry over these formal routines to communication with more distant suppliers in the local network, the codified routines resemble a format for inquiring about local technology and managerial and operational practices. In effect, contracts give the party a blueprint for guiding the communication and thus filling in relevant but important pieces of knowledge. Armed with this codified template, contracts help organize the communication with more distant but related sources, such as the local supplier network, and therefore foster coordination and ease explicit knowledge acquisition from brokered access. Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

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Hypothesis 3a: Formal contracts and brokered access have a positive, collective effect on the acquisition of explicit local knowledge. Contracts and shared goals Contracts also may complement the role of shared goals in knowledge acquisition. Because contracts formalize and specify precise goals and expectations, parties are less likely to misunderstand each other or fail to discuss their intent and terms for exchange fully. In contrast, when parties rely only on verbal acknowledgements of the communication, they may attribute different meanings to the stated understanding or recall the information differently or selectively. Alternatively, they may not think through the resource constraints, equity considerations, or knowledge requirements needed to support their goals. With contracts, however, parties are more likely to understand the specific agreement and obligations of each party, because they must write them down clearly in formal agreements. Thus, by formally specifying goals and expectations, exchange parties know whom to contact, what information to seek, and whom to work with in joint problem-solving activities. With this stock of formally specified, common knowledge, parties more effectively assimilate and absorb the tacit knowledge that becomes accessible through the strong social bonds associated with high levels of shared informal goals. Thus, contracts enhance the focal firm’s ability to absorb new, tacit knowledge and decrease misunderstandings that can arise through verbal communication. Shared goals also may enhance the level of explicit knowledge associated with formal contracts. Because contracts are inherently incomplete (Williamson, 1996), they are unlikely to codify all forms of explicit knowledge related to the transaction. When parties recognize a gap in knowledge, strategic posturing may result, because the parties may choose to withhold some pieces of information strategically. Yet with shared goals, knowledge exchange is less likely to be held up or strategically misdirected, because the partners have similar perceptions about how they should interact. This shared understanding helps establish a foundation of common understanding and the means to achieve the collaborative purposes, which forestalls coordination problems arising from conflicts of interest (Das and Teng, 1998). Copyright  2009 John Wiley & Sons, Ltd.

Hypothesis 3b: Formal contracts and shared goals have a positive, collective effect on the acquisition of explicit and tacit local knowledge. Contracts and trust A third way in which contracts may enhance knowledge acquisition is through their complementary relationship with trust. Whereas trust establishes norms and expectations about appropriate behavior to lower perceptions of risk (e.g., opportunism), it also produces considerable risk if it is abused or misplaced (Dyer and Singh, 1998; Uzzi, 1997). That is, trusted relationships are vulnerable to deceit; concerns about opportunism and knowledge leakage remain. Because ‘contracts narrow the domain and severity of risk to which an exchange is exposed’ (Poppo and Zenger, 2002: 708), contracts establish a formal basis of assurance for mutual trust and provide an institutional basis for future cooperation. Consistent with this reasoning, recent work shows that the risk allocation element of contracts persists over time with presumably trusted exchange parties (Dyer and Hatch, 2006; Reurer and Ariño, 2007). In this way, contracts provide formal assurance that complements the informal assurance of trust. With such formal assurance, parties are more likely to transfer tacit knowledge; by establishing safe boundaries for knowledge flows, contracts, in conjunction with trust, promote greater acquisition of tacit knowledge than trust alone. Contracts also formalize lessons learned from trusted relationships in prior periods by refining the procedures and processes that better facilitate coordination and information sharing (Mayer and Argyres, 2004). Because localized, tacit knowledge disappears when specific persons change jobs, formal operating procedures are necessary to preserve and improve the efficient use of resources. These operational routines complement the social mechanism of trust by creating a structure for coordination, facilitating processes, and establishing safe boundaries for knowledge flows. Similar to the logic advanced regarding contracts and shared goals, the proposed complementarity may work in reverse. Whereas contracts encourage explicit information flows through their specific provisions and enforcement, they are necessarily incomplete and cannot specify all types of useful and needed information required to optimize exchange performance. Trust helps overcome this Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

Relational Mechanisms, Contracts, and Local Knowledge Acquisition limitation by encouraging the exchange of contractually unspecified but valuable information; parties are willing to go beyond contractual stipulations because of normative conventions underlying trust-based relationships, such as feeling obliged to provide accurate, timely information, or norms of reciprocity (McEvily, Perrone, and Zaheer, 2003). As a result, trust fosters adaptation by facilitating knowledge exchange that is not contractually specified but necessary to promote the exchange. Therefore: Hypothesis 3c: Formal contracts and trust have a positive, collective effect on the acquisition of explicit and tacit local knowledge.

METHOD Data collection and sample Our focus on local knowledge acquisition requires an empirical setting in which foreign firms must acquire and employ local knowledge to compete and prosper. China provides a rich context for this empirical requirement. Because of China’s fast growing economy and huge market potential, it is one of the largest recipients of foreign direct investment and hosts the largest number of foreign affiliates in the world (UNCTAD, 2008). However, like many emerging or transitional economies, China challenges foreign entrants because its social, political, and legal institutions influence markets and the operation of firms in important yet unfamiliar ways (Zhou, Tse, and Li, 2006). Germane to our study, information access often remains private, making it difficult for companies to assimilate local knowledge (Li et al., 2008). Our study focuses on the relationship dyad between a foreign subsidiary and its major local supplier, which provides critical knowledge about business operations in a new market (McEvily and Marcus, 2005). We obtained a sampling frame of foreign manufacturing subsidiaries identified from the 22,000 Businesses in P.R.C., maintained by the China International Business Investigation Co. We restricted our sample to subsidiaries that meet the following criteria: (1) for-profit subsidiaries that potentially are in need of both the technical and the managerial know-how of local firms; (2) subsidiaries with only one foreign parent; and Copyright  2009 John Wiley & Sons, Ltd.

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(3) foreign wholly owned or foreign-dominated equity ventures. We collected the relevant data through face-toface, on-site interviews. We first called to identify two senior managers in each subsidiary as informants, because our pilot study showed that senior managers are knowledgeable about crosscorporate boundary issues such as knowledge transfer and networking activities. The senior managers chose their major local suppliers and responded to all questions with respect to their firm’s relationship with that supplier. Of the 500 firms contacted, 212 agreed to participate, and we successfully interviewed 336 senior managers from 168 firms, yielding a response rate of 34 percent. The majority of respondents were top executives (i.e., presidents, CEOs, vice presidents, directors, or general managers). Among the 168 firms, 45 percent are joint ventures, and the other 55 percent are wholly owned. With regard to nationality, the foreign parents of the subsidiaries in our sample come from 26 countries or regions such as Canada (3%), France (4%), Germany (8%), Hong Kong (6%), Japan (14%), Singapore (2%), Taiwan (7%), the United Kingdom (3%), and the United States (12%). Our sample also represents a variety of manufacturing industries, including machinery (7%), electronics (9%), textiles (4%), food processing (6%), semiconductors (5%), chemical and allied products (8%), rubber and plastics products (7%), motor vehicles (4%), and others. For the purpose of our analysis, we averaged the responses of the two informants to obtain scores for each subsidiary. We justify this data aggregation in two ways. First, for each of the constructs, we compute the correlation between the responses of the two senior managers and find generally high and positive correlations, ranging from 0.65 to 0.97. Second, we calculate ICC(2), a form of intraclass correlation, to assess to reliability of the mean scores (James, 1982). The ICC(2) values vary from 0.63 to 0.94, well above the 0.60 cutoff. These results provide support for our aggregation in the subsequent analysis. We check for the possibility of nonresponse bias by comparing the respondents with nonrespondents in terms of the number of employees, sales volume, and age of the foreign subsidiary. The results of ANOVA show no statistically significant differences between respondents and nonrespondents on any of the subsidiary information (F = 0.58, p > 0.10; F = 0.89, p > 0.10; F = Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

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0.67, p > 0.10, respectively), which suggests no evidence of nonresponse bias.

Measures We developed the questionnaire on the basis of previous research and theories, as well as our field interviews. To develop the scale items and evaluate scale properties, we employed traditional psychometric approaches. We first created an initial pool of scale items on the basis of a thorough review of the literature and interviews with senior managers in foreign subsidiaries. The questionnaire was developed in English and translated into Chinese, then back-translated into English by a third party to confirm that it was an equivalent translation. We next refined the wording of several survey items on the basis of a pilot study with 30 senior managers. In the Appendix, we provide full details about these measures. Relational mechanisms. We examine three relational characteristics: brokered access, shared goals, and trust. We adapt the two-item measure of brokered access from Yli-Renko et al. (2001) that reflects the extent to which the major local supplier provides the subsidiary with a network of contacts. We measure shared goals using four items adapted from Tsai and Ghoshal (1998) that consider the level of shared goals in the dyadic relationship. Consistent with Zaheer et al. (1998), we operationalize trust with four items that tap the degree of perceived trust between the subsidiary and its major local supplier. Formal contracts. We adapt the measure of formal contracts from Cannon and Perreault (1999). It contains three items describing the extent to which the subsidiary has specific, customized, and detailed contractual agreements with the supplier. Knowledge acquisition. We differentiate two types of knowledge: explicit and tacit. Explicit knowledge is codifiable and can be transferred in formal language, whereas tacit knowledge is complex, abstract, and difficult to codify. We use two three-item scales adapted from Dhanaraj et al. (2004) and Tsang (2002) to measure explicit and tacit knowledge acquisition. Copyright  2009 John Wiley & Sons, Ltd.

Control variables We control for several potential sources of heterogeneity in our sample. Firm age and firm size likely affect knowledge acquisition because the longer a subsidiary has operated in a foreign country and the larger it is, the greater its learning capability. We measure firm age as the number of years a foreign subsidiary has operated in China and firm size as the logarithm of the number of employees in the subsidiary. We similarly control for the effects of supplier age and supplier size. We also control for link duration, asset specificity, and supplier performance. Prior studies suggest exchange history relates positively to knowledge sharing (Kotabe et al., 2003), and we measure it as the number of years that the foreign subsidiary and local supplier have had a business relationship. Asset specificity refers to transaction-specific investments with little value outside the exchange relationship (Williamson, 1996). We adopt the measure of supplier asset specificity from Cannon and Perreault (1999). Following Barden, Steensma, and Lyles (2005) and Steensma et al. (2008), we control for supplier performance, because better performing suppliers may account for the effect of relational mechanisms on knowledge acquisition. We adapt a three-item measure from Cannon and Perreault (1999). We further control for entry mode and industry type because the governance mode and industry type may have different knowledge requirements. We define both as dummy variables, such that entry mode equals zero for joint ventures and one for wholly owned subsidiaries; for industry type, one is a high-tech industry (e.g., computer, electronics), and zero reflects all other industries (e.g., textiles, furniture, food). Finally, we control for cultural distance and local knowledge importance. Cultural distance proxies for the level of conflict that arises from differing normative behaviors and likely has a negative impact on local knowledge acquisition (Lyles and Salk, 1996). We use four dimensions of national culture—individualism, masculinity, uncertainty avoidance, and power distance—to compute the cultural distance between the subsidiary’s home country and China. The information is from archival data; and we employ the procedure developed by Kogut and Singh (1988) to calculate a composite cultural distance index for each Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

Relational Mechanisms, Contracts, and Local Knowledge Acquisition subsidiary, NCDj =

4 i=1

{(Dij − DiChina )2 /VI }/4,

where NCDj is the cultural distance of country j from China, Dij is the index score for country j on cultural dimension i, DiChina is the index for cultural dimension i and China, and VI is the variance of the index for cultural dimension i. We also control for local knowledge importance, which may influence the local supplier’s willing to share knowledge. We measure it by a single item, namely, the degree to which local knowledge is important to the foreign subsidiary. Construct validity We assess the construct validity in several ways. First, we perform exploratory factor analyses with Varimax rotations and obtain appropriate factor solutions. We then run reliability analyses for each construct; the Cronbach’s alpha values are all greater than the 0.7 cutoff. We also use confirmatory factor analyses (CFA) to establish the validity of latent constructs with structural equation modeling (see the Appendix). The overall measurement model fits the data satisfactorily (χ 2 (271) = 512.23, p < 0.01; goodness-of-fit index [GFI] = 0.905, comparative fit index [CFI] = 0.948, incremental fit index [IFI] = 0.949; root mean square error of approximation [RMSEA] = 0.063). All factor loadings are highly significant (p < 0.001) and related to their respective constructs, indicating the unidimensionality and convergent validity of the measures (Anderson and Gerbing, 1988). The composite reliabilities range from 0.73 to 0.93, above the 0.7 cutoff. Thus, all of the constructs demonstrate adequate reliability and convergent validity. To test the discriminant validity of all eight latent constructs, we run a series of nested CFA model comparisons in which we constrain the correlation between each pair of constructs to one. For all 28 pairs, when we compare the constrained model with a freely estimated model, the difference is significant, in support of discriminant validity (Anderson and Gerbing, 1988). For example, the chi-square test for the explicit and tacit knowledge latent variables yields 12.93 (p < 0.001), which indicates the two constructs are distinct. We also examine the variance extracted by each construct Copyright  2009 John Wiley & Sons, Ltd.

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relative to its shared variance with other constructs. In all cases, the average variance extracted by each factor is much higher than its highest shared variance with the other constructs, in additional support of discriminant validity. These results thus show that our measures possess adequate reliability and validity (Anderson and Gerbing, 1988). In Table 1, we report the means, standard deviations, and zero-order correlations of all our variables.

ANALYSES AND RESULTS Our model examines the effects of brokered access, shared goals, and trust on knowledge acquisition. Because trust and shared goals may influence the number of contacts provided by the major supplier (i.e., brokered access), the relationship between brokered access and knowledge acquisition may be spurious. To correct for this potential source of endogeneity, we employ a three-stage hierarchical regression model (Hamilton and Nickerson, 2003). In Stage 1, as specified in Equation 1, we regress brokered access (BA) against shared goals and trust to estimate predicted values of BA. The results indicate both trust and shared goals relate positively to BA (b = 0.172, p < 0.05, b = 0.093, p < 0.10, respectively), lending support to the use of the three-stage model to correct for the potential endogeneity of BA. Then, we obtain residuals of brokered access that are free of influence of shared goals (SG) and trust (TR). BA = b0 + b1 (SG) + b2 (TR) + e to obtain

BAresidual = BA − BApredicted (1)

In Stage 2, we use BAresidual as the indicators of BA, which represent levels of brokered access not accounted for by shared goals and trust. That is, BAresidual is used in Equation 2 to estimate the effects of relational mechanisms and formal contract (FC) for each type of knowledge acquisition (i.e., Models 2 and 5 in Table 2). Knowledge acquisition = b0 + b1 (BAresidual ) + b2 (SG) + b3 (TR) + b4 (FC) + bcontrols Controls + e

(2)

In Stage 3, we add interaction terms between relational mechanisms and formal contract to test Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj


1.00 0.13† 0.43∗∗ 0.45∗∗ 0.04 0.01 −0.10 0.07 0.11 0.08 0.02 −0.16∗ −0.46∗∗ 0.11 0.22∗∗ 0.13† 4.03 1.00 6.54 1.17

0.16∗ 0.19∗ 0.22∗∗

4.58 2.21 6.42 0.78

2

1.00 0.42∗∗ 0.34∗∗ 0.43∗∗ 0.21∗∗ 0.19∗ 0.01 −0.08 0.15∗ 0.27∗∗ 0.07 0.06 −0.05 −0.13†

Notes: Sample size = 168. ∗∗ p < 0.01, ∗ p < 0.05, † p < 0.10.

1. Explicit knowledge 2. Tacit knowledge 3. Brokered access 4. Shared goals 5. Trust 6. Formal contracts 7. Firm age 8. Firm size 9. Link duration 10. Asset specificity 11. Entry mode 12. Industry type 13. Cultural distance 14. Local knowledge importance 15. Supplier age 16. Supplier size 17. Supplier performance Mean Min Max s.d.

1

5.08 2.35 7.00 0.93

0.10 0.12 0.26∗∗

1.00 0.12† 0.23∗∗ 0.12† 0.14∗ 0.05 0.08 0.08 −0.07 −0.03 0.06 −0.19∗

3

4

5.32 2.43 7.00 1.03

0.09 0.11 0.36∗∗

1.00 0.39∗∗ 0.06 0.08 0.03 0.09 0.28∗ −0.13† 0.01 0.06 −0.14∗

Table 1. Means, standard deviations, and correlations

4.40 2.38 7.00 0.72

0.13† 0.17∗ 0.38∗∗

1.00 0.18∗ −0.09 0.01 0.05 0.11 0.00 0.15∗ 0.01 −0.09

5

1.00 0.09 0.60∗∗ −0.05 0.08 −0.07 −0.04 −0.11

7

5.57 2.00 7.00 1.21

8.75 4.00 20.00 4.41

0.02 −0.02 0.13† 0.06 0.08 −0.03

1.00 −0.11 −0.01 −0.04 −0.18∗ −0.01 0.01 −0.03 −0.01

6

5.34 3.00 6.69 0.96

−0.10 −0.07 −0.02

1.00 −0.07 −0.02 0.02 0.05 0.18∗∗ 0.04

8

10

12

13

1.00 0.05 1.00 −0.08 0.10 1.00 0.11 −0.08 −0.05

11

1.00

14

4.95 1.00 15.00 4.04

3.08 1.00 6.57 1.42

0.55 0.00 1.00 0.50

0.48 0.00 1.00 0.50

3.32 0.33 8.29 2.25

4.53 2.00 7.00 0.84

0.07 0.17∗ 0.01 −0.07 0.06 −0.19∗ 0.06 −0.16∗ −0.04 0.09 −0.12 −0.01 0.10 0.10 0.09 0.02 −0.04 −0.21∗

1.00 0.09 1.00 −0.11 −0.03 0.06 0.07 0.05 −0.01 −0.04 0.01

9

9.46 1.00 45.00 12.16

1.00 0.32∗∗ 0.19∗

15

4.52 2.51 10.36 1.44

1.00 0.05

16

5.12 2.00 7.00 0.84

1.00

17

360 J. J. Li, L. Poppo, and K. Z. Zhou

Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

Relational Mechanisms, Contracts, and Local Knowledge Acquisition Table 2.

361

Standardized coefficient estimates (standard error) of regressions

Variables

Control variables Firm age Firm size Link duration Asset specificity Entry mode Industry type Cultural distance Knowledge importance Supplier age Supplier size Supplier performance

Explicit knowledge acquisition

Tacit knowledge acquisition

Model 1

Model 2

Model 3

Model 4

Model 5

Model 6

0.032 (0.027) 0.078 (0.019) 0.156∗

0.021 (0.027) −0.067 (0.018) 0.141∗

0.026 (0.026) −0.027 (0.015) 0.121∗

0.047 (0.016) −0.092 (0.056) 0.027

0.035 (0.019) 0.094 (0.051) 0.010

0.034 (0.018) −0.055 (0.050) 0.016

(0.030) 0.268∗∗

(0.028) 0.245∗∗

(0.028) 0.211∗∗

(0.018) 0.109

(0.018) 0.088

(0.017) 0.110

(0.061) 0.039 (0.156) 0.045 (0.160) −0.073

(0.059) 0.027 (0.159) 0.048 (0.160) −0.054

(0.058) 0.017 (0.156) 0.037 (0.159) −0.043

(0.047) 0.108 (0.134) −0.033 (0.106) −0.136∗

(0.047) 0.078 (0.139) 0.027 (0.140) −0.131∗

(0.046) 0.088 (0.139) −0.030 (0.143) −0.110†

(0.060) 0.053

(0.062) 0.060

(0.060) 0.053

(0.041) −0.313∗∗∗

(0.048) −0.292∗∗∗

(0.047) −0.271∗∗∗

(0.116) 0.160∗ (0.006) 0.195∗ (0.057) 0.144∗

(0.118) 0.136∗ (0.006) 0.186∗ (0.056) 0.126∗

(0.116) 0.128† (0.006) 0.172∗ (0.054) 0.124∗

(0.084) 0.060 (0.004) 0.225∗ (0.036) 0.085

(0.094) 0.056 (0.004) 0.212∗ (0.034) 0.074

(0.092) 0.056 (0.004) 0.188∗ (0.034) 0.064

(0.098)

(0.098)

(0.096)

(0.060)

(0.061)

(0.059)

0.221∗

0.156∗

0.101

0.087

(0.106) 0.181∗

(0.100) 0.159∗

(0.090) 0.199∗

(0.087) 0.187∗

(0.114) 0.156∗

(0.113) 0.139∗

(0.109) 0.338∗∗∗

(0.108) 0.313∗∗∗

(0.123) 0.152∗∗ (0.049)

(0.128) 0.152∗ (0.049)

Main effects Hypothesis 1a: Brokered access (BA) Hypothesis 1b: Shared goals (SG) Hypothesis 1c: Trust (TR) Hypothesis 2: Formal contract (FC) Interactions Hypothesis 3a: BA × FC


0.137∗ (0.097)

(0.110) −0.045 (0.044)

(0.111) −0.035 (0.043)

0.100 (0.087)


362


Table 2. (Continued ) Variables

Explicit knowledge acquisition Model 1

Hypothesis 3b: SG × FC Hypothesis 3c: TR × FC R2 R2 change Model F Df ∗∗∗

p < 0.001,

∗∗

0.225 5.859∗∗∗ 11,156

Model 2


Model 3 0.242∗∗ (0.106) 0.323∗∗∗ (0.081) 0.445 0.079∗∗ 6.739∗∗∗ 18,149

0.376 0.141∗∗∗ 6.019∗∗∗ 15,152

Model 4

0.322 7.694∗∗∗ 11,156

Model 5

0.446 0.124∗∗∗ 7.998∗∗∗ 15,152

Model 6 0.226∗∗ (0.096) 0.330∗∗∗ (0.060) 0.527 0.081∗∗ 8.621∗∗∗ 18,149

p < 0.01, ∗ p < 0.05, † p < 0.10.

the moderating effects, as in Equation 3 (see Models 3 and 6 in Table 2). We form product terms between contracts and trust, shared goals, and the residuals of brokered access. Because product terms can incur colinearity, we mean-center the variables before we construct the interaction terms (Aiken and West, 1991). We check for potential multicolinearity by assessing the variance inflation factors (VIFs) associated with each of the predictors in our models. The value of the VIFs ranges from 1.01 to 1.96, with a mean of 1.38, well below the 10.0 benchmark, which indicates no multicolinearity concern. In Table 2, we report the regression results of controls-only (i.e., Models 1 and 4) as well as the second- and third-stage models. Knowledge acquisition = b0 + b1 (BAresidual ) + b2 (SG) + b3 (TR) + b4 (FC) + bcontrols Controls + c1 (BAresidual × FC) + c2 (SG × FC) + c3 (TR × FC) + e

(3)

As Models 3 and 6 in Table 2 show, brokered access relates positively to explicit knowledge acquisition (b = 0.156, p < 0.05) but has no relationship with tacit knowledge acquisition (b = 0.087, p > 0.10). To determine whether a significant difference exists between the regression coefficients, we conduct an additional chi-square difference test using structural equation modeling. The test result shows a significant difference between the two coefficients (χ 2 (1) = 4.23, p < 0.05), in support of Hypothesis 1a. Shared goals relate positively to both explicit (b = 0.159, p < 0.05) and tacit (b = 0.187, p < 0.05) knowledge acquisition, in support of Hypothesis 1b. The Copyright  2009 John Wiley & Sons, Ltd.

relationship between trust and knowledge acquisition is significant for both explicit (b = 0.139, p < 0.05) and tacit (b = 0.313, p < 0.001) knowledge. An additional chi-square difference test shows a significant difference between the two coefficients (χ 2 (1) = 7.31, p < 0.01), in support of Hypothesis 1c. That is, trust relates to greater levels of tacit than explicit knowledge acquisition. In Hypothesis 2, we posit that contracts have a stronger impact on explicit than on tacit knowledge acquisition. As Table 2 shows, contracts relate positively to explicit knowledge (b = 0.152, p < 0.05) but are not related to tacit knowledge (b = −0.035, p > 0.10) acquisition. Further chi-square tests show a significant difference between the two coefficients (χ 2 (1) = 5.87, p < 0.05), in support of Hypothesis 2. In Hypothesis 3, we propose that relational mechanisms and contracts strengthen each other in their respective influences on knowledge acquisition. As we show in Models 3 and 6, the interaction of brokered access and contracts is significant for explicit knowledge acquisition (b = 0.137, p < 0.05), in support of Hypothesis 3a. Consistent with Hypotheses 3b and 3c, the interaction of shared goals and contracts has a positive influence on explicit (b = 0.242, p < 0.01) and tacit (b = 0.226, p < 0.01) knowledge acquisition, as does the interaction between trust and contracts on both explicit (b = 0.323, p < 0.001) and tacit (b = 0.330, p < 0.001) knowledge acquisition. To illustrate the nature of the interactions, we follow Aiken and West (1991) and depict the pattern of the interactions in Figure 2. Overall, these results provide strong support for Hypothesis 3. Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

Relational Mechanisms, Contracts, and Local Knowledge Acquisition

363

Hypothesis 3a: Brokered access and contracts Explicit knowledge acquisition

Explict Knowledge acquisition

High High formal contracts

Low formal contracts

Low Low

High

Brokered access

Hypothesis 3b: Shared goals and contracts Explicit knowledge acquisition



High formal contracts


High Tacit Knowledge acquisition

High



Low

Low Low

Shared goals

High

Low

High

Shared goals

Hypothesis 3c: Trust and contracts Explicit knowledge acquisition





Low

High


Tacit Knowledge acquisition

High


Low Low

Trust

Figure 2.

High

Trust

High

Interaction effects of relational mechanisms and contracts

Effects of control variables Link duration has a positive effect on explicit knowledge acquisition. The longer the exchange history, the greater the level of explicit knowledge a subsidiary acquires from its major local supplier. Asset specificity also has a positive effect on the acquisition of explicit knowledge. When the supplier invests in specialized assets, it becomes more willing to share easy-to-transfer knowledge. Not surprisingly, cultural distance impedes tacit knowledge acquisition, presumably because distance increases the difficulty of effectively communicating and understanding subtleties in language and customs. Consistent with the view that self-interested profit maximization undermines Copyright  2009 John Wiley & Sons, Ltd.

Low

complex forms of coordination in markets, local knowledge importance has a negative effect on tacit knowledge acquisition. That is, suppliers do not ‘give away’ valuable, important knowledge. This finding highlights the importance of developing relational and formal mechanisms in tacit knowledge acquisition. We further find that supplier age positively affects explicit knowledge acquisition. Older suppliers have accumulated rich experience in local markets that enable foreign firms to acquire more explicit knowledge. Supplier size has a positive effect on both types of knowledge acquisition, possibly because larger local suppliers tend to have more resources and capabilities, which facilitate the transfer of both tacit Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

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and explicit knowledge. Supplier performance also positively affects explicit knowledge acquisition. It thus appears that foreign subsidiaries are more likely to receive explicit knowledge from good suppliers. Additional analysis While most empirical studies of knowledge transfer attempt to explain knowledge acquisition with a specified set of explanatory variables, relational cycles that exist in interfirm arrangements are receiving greater attention (e.g., Barden et al., 2005; Steensma et al., 2008). One alternative specification is that knowledge transfer may be associated with greater levels of conflict, and thus lower levels of relational qualities. This logic implies that knowledge transfer affects relational factors, which is opposite to what we specify in our conceptual model. To address this causality concern, we employ a structural equation modeling approach to evaluate the potential bidirectional effects between relational mechanisms and knowledge acquisition. We use nonrecursive cross-sectional structural models to serve as a proxy for the true cross-lagged models in examining reciprocal relations. As Wong and Law (1999) suggest, ‘although the true effects may be longitudinal between some management constructs, it is not always possible for researchers to have data that match the exact time duration of the cross-lagged effects. In these cases, using the nonrecursive model as a proxy may be a viable alternative for studying reciprocal relations’ (Wong and Law, 1999: 71). Because the exact time lags between construct are either unknown or impractical in terms of measurement, studies in the strategy literature often use cross-sectional data to examine causal relations (e.g., Poppo, Zhou, and Ryu, 2008). We explore a nonrecursive cross-sectional model that contains links from relational mechanisms and knowledge acquisition as well as from knowledge to relational mechanisms (i.e., six pairs of reciprocal relations). The results show that brokered access has a positive effect on explicit knowledge acquisition (b = 0.162, p < 0.05), but the link from explicit knowledge acquisition to brokered access is not significant (b = 0.002, p > 0.10). Shared goals positively affect explicit (b = 0.160, p < 0.05) and tacit (b = 0.189, p < 0.05) knowledge acquisition, but the reversed links are Copyright  2009 John Wiley & Sons, Ltd.

not significant (b = 0.087, p > 0.10; b = 0.101, p > 0.10 for explicit and tacit knowledge, respectively). Trust relates positively to explicit (b = 0.142, p < 0.05) and tacit (b = 0.317, p < 0.001) knowledge acquisition, yet the reverse paths are not significant (b = 0.032, p > 0.10; b = 0.084, p > 0.10, respectively). These results support our original model specification: relational mechanisms, such as brokered access, shared goals, and trust, encourage foreign firms to obtain local knowledge in host countries.1 Thus, although our results do not dismiss the viability of relationship cycles, they also do not appear to account for the relationship between relational mechanisms and knowledge acquisition in our study.

DISCUSSION Recent works highlight interorganizational relationships as a valuable source of knowledge (Dyer and Hatch, 2006; McEvily and Marcus, 2005; Tiwana, 2008), which for our context is especially germane, because foreign subsidiaries operating in China must acquire local knowledge to compete effectively in this emerging economy. Our study contributes to this literature stream by examining how three relational mechanisms—brokered access, shared goals, and trust—differentially affect the acquisition of explicit and tacit knowledge from local suppliers. We further extend this literature theoretically and empirically to show that formal contracts enhance the positive effects of relational mechanisms on the acquisition of explicit and tacit knowledge. These findings contribute significantly to our understanding of how formal and informal mechanisms jointly affect an international subsidiary’s acquisition of local knowledge. As a first contribution, we show how indirect and direct relational mechanisms differentially affect the acquisition of tacit and explicit knowledge. Brokered access, a relatively unexplored indirect mechanism, promotes network access 1 We stress that because our cross-sectional design lacks the precision to make definitive conclusions about causality, this additional analysis does not rule out reciprocal effects between relational mechanisms and knowledge acquisition over a longer time period. With cross-sectional data, we cannot examine the dynamics of knowledge acquisition in international subsidiaries over time. Ideally, we would use data from two time periods, rather than the single time period currently available, to capture the inherent causal complexity in our model.


Relational Mechanisms, Contracts, and Local Knowledge Acquisition when a major supplier connects the foreign subsidiary to other local suppliers. Such access is particularly critical as foreign subsidiaries generally lack legitimacy and local connections in emerging economies, in which private access appears more reliable and trustworthy than public access. Thus, brokered access confers legitimacy to both the foreign subsidiary and the local supplier. Consistent with our logic, we find that brokered access relates to the acquisition of explicit, but not tacit, knowledge. We reason that because the major supplier functions as the conduit for knowledge flows from more distant, local suppliers to the foreign subsidiary, the supplier, as a broker, can more effectively transmit explicit than tacit knowledge. Related, more distant, local suppliers do not have the requisite motivation and intimacy with the foreign subsidiary to transfer tacit knowledge. Thus, brokered access mainly supports the transfer of explicit knowledge. We also confirm the significant role of two direct relational mechanisms, shared goals and trust, in knowledge acquisition. Shared goals promote joint problem solving, harmonize individual self-interests, and cast a forward-thinking orientation onto the exchange relationship. As a result of this commitment to cooperate, parties share necessary and valuable information, in the form of both explicit and tacit knowledge. These results are consistent with Inkpen and Tsang’s (2005) argument that shared goals promote exchanges of ideas and resources, that is, both tacit and explicit knowledge. We also predict and empirically show that trust is associated with a greater acquisition of tacit than explicit knowledge. Because trust reduces perceptions of unfair play, such as knowledge leakage and appropriation, and supports close, intimate connections, it is used most effectively to acquire tacit knowledge. These results confirm that trust lies at the heart of tacit knowledge exchange (Adler, 2001). Our second contribution is both theoretical and empirical: we clarify why formal contracts enhance the positive relationship of relational mechanisms and knowledge acquisition. Consistent with recent work that documents the need for explicit knowledge to support the use of contracts (Barthélemy and Quélin, 2006; Reurer and Ariño, 2007), we find that greater contractual specification increases the transfer of explicit knowledge. We reason that as contracts become more complete through Copyright  2009 John Wiley & Sons, Ltd.

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greater specification of formal operating procedures and controls, they necessarily enhance the communication of explicit knowledge. More novel are our findings and logic that formal contracts complement the positive impacts of each relational mechanism on the acquisition of tacit and/or explicit knowledge. We posit that by reducing cognitive and coordination barriers, contracts function to increase the foreign subsidiary’s absorptive capacity, thereby encouraging greater acquisition of knowledge than through relational mechanisms alone. Because contracts reflect a stock of related prior knowledge, they increase a firm’s absorptive ability to acquire and integrate new knowledge through relational mechanisms. Alternatively, because contracts serve as templates for coordinating the exchange, the foreign subsidiary and focal supplier can achieve more effective communication with distant suppliers. Moreover, because contracts provide formal specification and assurance, they complement the informal enforcement mechanism of shared goals and trust, resulting in greater knowledge acquisition through the combined contracts and these relational mechanisms. Finally, we reason that this complementarity may operate in reverse: shared goals and trust may facilitate greater knowledge flows when the knowledge is necessary to advance the exchange but not contractually specified, given the inherent incompleteness of contracts. These complementarity findings are contrary to the conventional wisdom that contracts erode the positive effects of relational mechanisms such as trust (Adler, 2001; Ghoshal and Moran, 1996; Madhok and Tallman, 1998). However, our findings are consistent with the increasing recognition that firms can benefit by purposefully combining formal and informal governance mechanisms. For example, a combination of contractual and social mechanisms is more effective for managing conflict (Dyer and Singh, 1998), and the simultaneous use of relational norms and customized contracts enhances exchange performance (Poppo and Zenger, 2002). Our study enriches this line of enquiry by empirically confirming that foreign firms should use formal and informal mechanisms simultaneously to facilitate local knowledge acquisition. A theoretical or empirical focus on either formal or relational mechanisms alone undermines the assessment of their collective benefits. Our third contribution pertains to the empirical context: knowledge flows from local suppliers Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

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to international subsidiaries, an undeveloped context in the knowledge transfer literature (see Dyer and Hatch, 2006; McEvily and Marcus, 2005). Whereas prior studies focus primarily on knowledge flows from headquarters to the subsidiary or flows among subsidiaries within MNCs, we suggest that the local supplier network also provides an important source of knowledge, especially in emerging economies like China in which information access is private. Managerial implications Our findings and context provide important implications for practitioners. One critical challenge facing foreign companies in emerging economies is how to acquire valuable knowledge to survive and succeed in local markets. Our findings suggest that managers in international subsidiaries must understand that relational mechanisms such as brokered access, shared goals, and trust are a viable means of acquiring local knowledge from their local suppliers. More important, managers should realize the differential effects of alternative relational mechanisms in obtaining local knowledge. For example, the best way to acquire tacit knowledge is to build trust with major suppliers; managers thereby need to interact and socialize with key suppliers often. Managers are also encouraged to devote considerable time and effort to establish shared goals with their suppliers in order to facilitate the acquisition of both explicit and tacit local knowledge. To acquire additional explicit knowledge, foreign subsidiaries can have key suppliers forge connections with more distant local suppliers. Therefore, it is important for foreign subsidiaries to select a major supplier that occupies a strong and central position within the local supplier network. Furthermore, international subsidiaries must recognize the significant role of contracts in local knowledge acquisition. The traditional wisdom is that formal contracts may not be effective in China due to its relatively less-developed legal institutions (Li et al., 2008; but see Zhou et al., 2008). Our findings suggest contracts play an important role in structuring knowledge exchange. Because contracts preserve former experience, serve as a template for exchange coordination, and provide formal specification and assurance, they increase the efficiency of local knowledge acquisition when coupled with relational mechanisms. Therefore, Copyright  2009 John Wiley & Sons, Ltd.

subsidiaries should specify contractual arrangements and use plural approaches (i.e., both contracts and relational mechanisms) to absorb greater local knowledge. Limitations and further research As an initial effort to address a complicated phenomenon, our study is subject to several limitations. First, our findings are based on data gathered from one side of the dyadic relationship, namely, the foreign subsidiary. A research design that includes information from both sides would enable the cross-validation of relationship-oriented constructs like trust. Obtaining data from both sides of the dyad also would permit a comparison of knowledge transfers from local firms to international subsidiaries with those from international subsidiaries to local firms, such as whether asymmetric knowledge flows erode relational quality and the stability of the exchange. Second, because cross-sectional data cannot test causal inferences, longitudinal work is needed to examine and confirm our logic. For example, Steensma et al. (2008) suggest that when joint venture partners have significant levels of conflict as well as extensive learning and knowledge transfer, they may face greater instability. Longitudinal work would also be able to examine the dynamic origins and timedependent effects of the complementary relationship between formal contracts and relational mechanisms, such as how and when they reinforce and support each other. Third, our study focuses on a dyadic level of analysis; but how individual and organizational factors affect interfirm relationships deserves more attention. For example, we do not know whether personal ties between leaders are a stronger determinant of network access. Recent works suggest the leadership ties are not a significant determinant of subsequent interorganizational exchanges (Barden and Mitchell, 2007); yet for our context, China, many studies highlight the importance of ties between business leaders (eg., Li et al, 2008; Li, Zhou, and Shao, 2009). Related, Mehra, Kilduff, and Brass (2001) show that personality factors determine which individuals occupy central network positions. But the impacts of individual characteristics on network access and subsequent knowledge transfer remain unknown. Thus, further research may explore interorganizational knowledge acquisition process with a multilevel analysis Strat. Mgmt. J., 31: 349–370 (2010) DOI: 10.1002/smj

Relational Mechanisms, Contracts, and Local Knowledge Acquisition across individuals and organizations (Brass 2001; Klein, Palmer, and Conn 2001). Fourth, international settings challenge the generalizability of our findings to nonemerging market contexts. Although context-specific research provides practitioner insights for firms operating in China, it is unclear whether this context imposes a boundary constraint on our conceptual model and findings. In particular, we do not know whether our logic for the complementary relationship between contracts and relational mechanisms is particular to the Chinese context, in which the use of contracts serves as living documents. Yet because global competition increasingly defines business, understanding how to acquire local knowledge in emerging markets represents a critical challenge. Our study informs this intriguing topic by showing how contracts and relational mechanisms influence the acquisition of local explicit and tacit knowledge in China. We hope that further research continues to explore and document how formal and informal mechanisms affect local knowledge acquisition in emerging economies.

ACKNOWLEDGEMENTS The authors thank Editor Will Mitchell and the two anonymous reviewers for their insightful and constructive comments on earlier versions. We also thank Africa Ariño, Tailin Chi, Simon Lam, Anne Parmigiani, and seminar participants at University of Kansas brown bag series for their helpful comments. This study was supported by the General Research Fund from the Research Grants Council, Hong Kong SAR Government (Project no. 9041409).

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APPENDIX: MEASUREMENT ITEMS AND VALIDITY ASSESSMENT Brokered access Cronbach’s α = 0.73; CRa = 0.73 1. We have gotten new supplier contacts through this supplier. 2. This supplier has ‘opened the doors’ to other suppliers for us. Shared goals Cronbach’s α = 0.76; CR = 0.77

Loadingb 0.750 0.759

1. Both parties in this relationship are enthusiastic about pursuing the collective goals. 2. Both parties are committed to improvements that may benefit the relationship as a whole, and not only the individual parties. 3. The parties share the same ambition and vision. 4. In most aspects of the relationship the parties are jointly responsible for getting things done. Trust Cronbach’s α = 0.86; CR = 0.87 1. This supplier is trustworthy. 2. This supplier has always been evenhanded in its negotiations with us. 3. This supplier never uses opportunities that arise to profit at our expense. 4. We are not hesitant to transact with this supplier when the specifications are vague. Formal contracts Cronbach’s α = 0.89; CR =0.90 1. We have specific, well-detailed agreements with this supplier. 2. We have customized agreements that detail the obligations of both parties. 3. We have detailed contractual aggrements specifically designed with this supplier. Explicit knowledge acquisition Cronbach’s α = 0.92; CR = 0.92

0.761 0.671 0.672 0.728 0.777 0.857 0.885 0.654 0.902 0.887 0.812

To what extent has your firm learned from your relationship with this supplier? 1. Written knowledge about local technology 2. Written knowledge about local operating routines and procedures 3. Written knowledge about management techniques in host country Tacit knowledge acquisition Cronbach’s α = 0.92; CR = 0.93

0.904 0.872 0.827

To what extent has your firm learned from your relationship with this supplier? 1. Local marketing expertise that was difficult to articulate (e.g., tricks of the trade) 2. Knowledge about local culture and tastes that were not well documented 3. Noncodified managerial techniques (e.g., skills of interfirm cooperation and collaborating, skills of managing interfirm relationship in host country) Asset specificity Cronbach’s α = 0.92; CR = 0.93 1. Just for us, this supplier changed its product’s features. 2. Just for us, this supplier changed its personnel. 3. Just for us, this supplier changed its inventory and distribution. 4. Just for us, this supplier changed its capital equipment and tools. Supplier performance Cronbach’s α = 0.91; CR = 0.92

0.882 0.917 0.905

0.854 0.918 0.925 0.858

Please rate this supplier’s performance on the following aspects 1. Product quality 2. Timeliness of delivery 3. Sales, service, and/or technical support

0.928 0.883 0.860

Model fit: χ 2 (271) = 512.23, p < 0.01; GFI = 0.905, CFI = 0.948, IFI = 0.949, RMSEA = 0.063. a Composite reliability. b Standardized loading.



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