an integrative model of trust on it outsourcing - Semantic Scholar

AN INTEGRATIVE MODEL OF TRUST ON IT OUTSOURCING: EXAMINING A BILATERAL PERSPECTIVE 1 Jae-Nam Lee 2 Korea University Business School Anam-Dong 5 Ga, Seongbuk-Gu, Seoul 136-701, Korea Tel: 82-2-3290-2812, Fax: 82-2-922-7220 [email protected]

Minh Q. Huynh Management Department, Southeastern Louisiana University, SLU 10350, Hammond, LA 70402 USA Tel: 1-985-549-3949, Fax: 1-985-549-2019 [email protected]

Rudy Hirschheim Department of Information Systems and Decision Sciences, E. J. Ourso College of Business Administration, Louisiana State University Baton Rouge, LA 7080, USA Tel: 1-225-578-2514; Fax: 1-225-578-2511 [email protected]

Jae-Nam Lee, Minh Q. Huynh, and Rudy Hirschheim

ABSTRACT Trust has been considered a central aspect of successful IT outsourcing from the beginning of the outsourcing relationship to the end. A great deal of interest in trust has been described, but there has been little in the way of strong theoretical models to aid in understanding the role of trust, the antecedents of trust, and the consequences of trust in outsourcing relationship. Further, very limited research has been done on the outsourcing relationships from the service receiver and provider’s perspectives simultaneously. This study suggests an integrative model of trust in the context of outsourcing and then attempts to empirically explore the role of initial trust and initial distrust, and trust with knowledge management as mechanisms for a successful outsourcing project from both service receiver and provider perspectives. The results show that trust between the service receiver and provider is very important for knowledge sharing and outsourcing success, and is affected by the initial perception to each other’s partner at the beginning of the outsourcing process. Interestingly, this study also shows that initial trust is considered as a significant factor in its perception of trust from the service receiver’s perspective, but not from the service provider’s viewpoint. The results help extend our understanding of critical success factors in outsourcing success and of different standpoints between the service receiver and provider.

KEYWORDS IT outsourcing, Trust, Initial trust, Initial distrust, Knowledge sharing, Mutual dependency, Outsourcing success, Bilateral perspective, PLS 1 2

An earlier version of this manuscript was presented at PACIS 2005 Author for correspondence

1. INTRODUCTION During the last decade, outsourcing has emerged as a major strategic alternative in information systems management. According to the International Data Corporation, the worldwide outsourcing market size is estimated to rise from $100 billion in 1998 to $152 billion by 2005, with an annual growth rate of 12.2%. With this kind of growth, IT outsourcing warrants top-level attention. This is evident in the recent wave of billion dollars outsourcing deals [Dibbern et al., 2004]. Despite a new wave of billion dollars contracts, few report successful returns on their outsourcing investments. The major issue facing both the service provider and client organizations is the increasing pressure to exhibit the value of outsourcing [Diromualdo et al., 1998]. Therefore, improving the quality of the relationship, based on trust, between the service provider and client organizations has been suggested as the best way to meet this challenge [Lee et al., 2003]. Because today’s outsourcing contracts are often very complex, it is not possible to spell out every rule and agreement in a contract. Moreover, the interactions between the clients and their service providers often go beyond rules, agreements, and exceptions. They also rest on intangible factors that could not be easily captured in the contract such as trust and interdependency [cf. Goles, 2001]. As increasing attention has been paid to building a flexible relationship between the customer and the provider of IT outsourcing services [McFarlan and Nolan, 1995; Willcocks and Kern, 1998], the notion of trust is emerging as a potentially central aspect leading to successful outsourcing. Trust, which has been studied widely in social exchange literature, is one of the most desired qualities in any close relationship [Mayer and Davis, 1995; Moorman et al., 1993]. Accordingly, trust plays a critical role in developing a long-term relationship and facilitating exchange relationship. Without trust, organizations will cooperate with their service providers only under a system of formal and legal rules. Although there has been some interest in trust in past outsourcing research, the previous studies of trust in outsourcing reported conflicting results with no clear theoretical explanation [Grover et al. 1996; Lacity and Willcocks 1995; McLellan et al., 1995; Sabherwal, 1999]. In other words, there has been little in the way of strong theoretical models to aid in understanding the role of trust, the antecedents of trust, and the consequences of trust in an outsourcing relationship. This deficiency in the outsourcing literature needs to be addressed and a more detailed comprehension of the notion of trust is required. Furthermore, very limited research has been done on the outsourcing relationship from the service receiver and provider’s perspectives simultaneously. Usually outsourcing research concentrates on the organizations that choose to outsource. However, an understanding of both parties in an outsourcing relationship is important because a successful outcome is determined not by the service provider or the client organizations alone but by both. This paper attempts to conceptualise and validate a theoretical model of trust in the context of outsourcing relationships. The proposed model in this study is synthesized from a body of literature related to inter-organizational relation management, organizational learning and trust in conjunction with relevant empirical findings from previous outsourcing studies. The hypothesized model is then tested empirically using data collected from both customer organizations and service providers in Korea. Research questions addressed in this study include: (1) what is the role of trust in an outsourcing relationship?; (2) how can trust be nurtured?; (3) what are the consequences of trust? By focusing on the bilateral perception of the outsourcing relationship from the service receiver and provider perspectives, this study tries to answer the above three questions. Our paper is organized into six sections. Following the introduction is a section on theoretical background. In this section, we develop an integrated trust model in the outsourcing context based on the past literature and propose our research hypotheses. In section three, we describe our research methodology. Section four presents our analysis and results. We then highlight our implications as well as the future research direction in the section of discussion. The last section summarizes the study’s contributions

2. THEORETICAL DEVELOPMENT 2.1 Integrative Model of Inter-organizational Trust Trust is undoubtedly an important component of many social and business relationships, determining the nature of the interactions and expectations between parties. Since trust enables one organization to form appropriate and favorable expectation about other organizations they are going business with, it has been considered essential in many business activities [Anderson and Narus, 1990; Gefen, 2002; Mohr and Spekman, 1994]. The previous studies have shown that trust indeed determines the nature of many buyer-seller relationships [Dwyer et al., 1987; Heide and John, 1990], working partnerships in marketing area [Moorman et al., 1993; Morgan and Hunt, 1994], and strategic alliances in management area [Krishnan, et al., 2006; Lewis, 1985; Yoshino and Rangan, 1995; Zaheer, et al., 1998]. Although trust is regarded as one of the fundamental and relevant factor in IT outsourcing, especially in a long-term outsourcing relationship [McFarlan and Nolan, 1995; Sabherwal, 1999], its role and impact in IT outsourcing remain fragmented. A number of studies have tried to explain trust in outsourcing relationship through correlation analysis among trust-related variables [e.g., Klepper, 1994] or correlation analysis between trust-related variables and outsourcing success [e.g., Lee and Kim, 1999]. However, these studies drew multiple, sometimes conflicting conclusions with little business implications. Part of the problem is because these studies could not distinguish trust from other similar constructs such as cooperation and confidence. Despite the various theories related to trust such as social exchange theory and social network theory, there has been a lack of an integrated view to provide an in-depth analysis of trust on outsourcing relationship. As a result of no prior trustbased relationship model available, there has been a lack of obvious differentiation among factors that contribute to trust, trust itself, and outcomes of trust in outsourcing literature. Finally, it is true that the studies of the relationship truly require an understanding of both parties to reap greater outsourcing benefits, but, to our knowledge, very limited academic research has been done on the outsourcing research from both the service receiver and provider’s perspectives. With above motivations, this study proposes an outsourcing relationship trust model based on concepts existed in literature on interorganizational relations, outsourcing, and organizational learning. To provide a conceptual foundation for outsourcing research involved trust-based relationship, this paper attempts to introduce an integrative model of inter-organizational trust and its impact on knowledge sharing and outsourcing success as shown in figure 1. Initial Trust Cognition-based Calculative-based

Mutual Dependency

H4 (+) and H6 (+)

H2 (+)

Knowledge Sharing

Interorganizatonal Trust H1 (+)

Initial Distrust Psychology-based

Outsourcing Success

Explicit KS Implicit KS

H3 (+)

H5 (-) and H7 (-)

Economics-based

Figure 1: A research model on Inter-organizational trust in outsourcing context. (+) denotes positive relation; (-) denotes negative relation between variables

2.2 The importance of trust in outsourcing relationships Outsourcing is a form of relationship that is some ways similar to strategic alliances, especially when outsourcing involves knowledge exchange and sharing. The organizational boundaries may become blurred and hence give rise to mutual dependence among partners in the relation [McEvily et al., 2003]. As indicated from prior studies of inter-organizational relations [Harrigan, 1985; Powell, 1990], partners in an outsourcing relation like any other relations have to deal with not only uncertainly arising from each other’s behavior as well as from external factors. Among the most important relational mechanism that has been studied widely is trust [Gambetta, 1988; Mayer et al., 1995; McEvely et al., 2003; Sako, 1991; Zaheer et al., 1998, Zand, 1972]. Accordingly, inter-organizational trust has been identified to be a key factor contributing to alliance success as well as alliance performance [e.g., Dyer and Chu, 2003; Mohr and Spekman, 1994; Zaheer et al., 1998] Krishnam et al. [2006], defined inter-organizational trust as the expectation held by one firm that another will not exploit its vulnerabilities when faced with the opportunity to do so. This definition bases on three related components: reliability, fairness, and goodwill [Dyer and Chu, 2003]. According Zaheer et al. [1998], inter-organizational trust is defined in the context of supplier and buyer relationship. Unlike interpersonal trust which is the trust placed by the individual boundary spanner in her individual opposite member, the term inter-organizational trust refers to the extent of trust placed in the partner organization by the members of a focal organization. This definition clearly indicates the intrinsically complex and multifaceted nature of trust as well as the variety of units and levels of analysis to which trust can be applied [Zaheer, et al., 1998]. We adopt Zaheer et al. [1998]’s conceptualization of trust in our study because of the following reasons. One, it clearly distinguishes between relational trust vs. dispositional trust. Relational forms of trust pertain specifically to the counterpart not an individual in the dyad while dispositional trust is an individual trait reflecting expectancies about the trustworthiness of others. An important implication here is that relational trust is likely to be based on experience and interaction with a particular exchange partner rather than an individual trait [Ring and Van de Ven 1992]. Another important implication is that inter-organizational trust describes the extent to which organizational members have a collectively held trust orientation toward the partner [Zaheer, et al. 1998]. This collective held trust is the key that helps explain how inter-organizational trust can persist even under the turnover of different personnel in the firms. Also, it is this collective held trust that makes it possible to analyze trust at the organizational level. Trust in an outsourcing relation is very similar to those of other relations because it often involves interaction between a client and a service provider that often goes beyond the rules, agreements, and exceptions specified in a legal contract. Although most of outsourcing arrangements are based on contractual agreements among partners, yet quite often when partners commit themselves and make contributions to their relationship that go beyond what was specified in the contract, then interorganizational trust stands to be relevant. Hence, there are always trust-related elements that are intangible and not easily captured in a contract. Relationships based on a formal contract and rooted in mutual trust give rise to stronger bonds between clients and their service providers [Klepper, 1994; Sabherwal, 1999]. In many cases, organizations seek to create flexible relationships with their service providers after they have identified the limitations of legal contracts. There is also evidence that outsourcing projects in the 1990s increasingly shifted from contractual to trust-based relationships [Willcocks and Kern, 1998]. Consequently, forming effective relationships based on interorganizational trust might be a key predictor of future outsourcing success [Lee et al., 2003]. The role of inter-organizational trust in IT outsourcing was highlighted by Sabherwal [1999] and Lee and Kim [1999]. According to Sabherwal [1999], trust leads participants to work together rather than seek ways to deflect blame, and the balance between trust (i.e., psychological contract which consists of unwritten and largely unspoken sets of congruent expectations) and formal written contract is critical. Lee and Kim [1999] emphasize that trust is a basic component to classify a relationship type

into transaction style and partnership style, and evolving through mutually satisfying interactions and increasing confidence in relationship. So, trust is considered as a major component of relationship quality, which directly affects the degree of outsourcing success. However, it is not assumed that the trust-based relationship always leads to the best results in outsourcing relationships. Instead, we believe that inter-organizational trust is a necessary but not necessarily a sufficient condition for outsourcing success. For instance, when the outsourcing objective is cost reduction but the vendor cannot meet this objective, the outcome of such outsourcing cannot be called a success even if their relationship is trust-based. Despite the importance of understanding trust-based relationship, considerable ambiguity is evident in the literature about the antecedents, roles, consequents, and impacts of trust in outsourcing. Therefore, a better understanding of inter-organizational trust in outsourcing relationship is crucial to have a successful outsourcing project. This is the reason why we explore the source, role, and outcome of inter-organizational trust in outsourcing relationship, as shown in figure 1. 2.3 Trust consequences Knowledge sharing as risk taking in relationship Knowledge, which is information whose validity has been established through tests of proof, has emerged as a strategically significant resource of the firm. This is because an organization itself is considered as a knowledge system where knowledge is created, shared, and utilized for organizational objectives. Daft and Weick [1984] viewed an organization as an inquiry system that they make sense of the information they deem necessary. Organizations usually scan their environment and interpret possible problems or opportunities. Argyris and Schon [1978] echoed a similar view in their notion of “organizational learning”. In a simple term, it is a process of putting cognitive theories into actions through the single and double loop. In this context, organizations are capable of learning by carrying out their actions and learning from the results. Spender [1996] extended the view of organization as a system of knowing further by treating organizational learning as the process of experiencing and analyzing. In other words, it is the process for an organization to communicate the knowledge previously generated by others. At the core of an organizational learning is knowledge. Since organizational knowledge is inherently created and resides with individuals [Nonaka and Takeuchi, 1995], one major management issue is how to change individual knowledge into organizational knowledge. Another issue is how to integrate and manage organizational knowledge so that it results in successful performance. Since organizational knowledge is usually distributed within an organization and organizational products or services generally require multiple knowledge (or collective knowledge), organizations need to integrate the knowledge to produce new products or services, or to improve business performance [Brown, 1998]. The key to solve these two issues rests on knowledge sharing, which is included as one of the major constructs in our proposed outsourcing relationship trust model, as shown in figure 1. Individual knowledge should be shared among organizational members. Many organizational managers focus their managerial efforts on this organizational sharing of individual knowledge. Though organizational knowledge is created within an organization, it can also be acquired externally [Badaracco, 1991]. Recently, increasing attention has been paid to how organizations learn from their partners and develop new competencies through strategic alliances. Many scholars have discussed the introduction of alliances to acquire new capabilities from partners through the extension of organizational learning in a relationship [e.g., Simonin, 1999]. According Nelson and Cooprider [1996], trust exerts a major impact in relationships between organizational groups. Their study identifies mutual trust among the determinants of shared knowledge. The development of mutual trust leading to shared knowledge is an ongoing phenomenon. Repeated intergroup exchanges of information generate trust, which lead to increased communications and eventually facilitate sharing of knowledge [Anderson and Narus, 1984]. Extrapolating the importance of organizational trust to the outsourcing context, it is clear that knowledge sharing is not

just a simple shared reality between groups in the case of IS performance. Because of the interorganizational nature an outsourcing relationship, both the client organization and the service provider are coupled in an intimate interaction where high interdependence requires both to share valuable knowledge-intensive resources, exposing these to each other. Thus, there is a high degree of interdependency and vulnerability. Knowledge sharing involves an element of risk taking. The effectiveness of knowledge sharing is related to the willingness for parties involved to take risks by opening up to each other. Thus, the higher level of perceived inter-organizational trust between the client and the service provider organizations are in their relationship, the more willingness for risk taking the client and the service provider organizations have in their knowledge sharing. Here, we define knowledge sharing as activities of transferring or disseminating knowledge from one person, group or organization to another. This definition broadly includes both tacit and explicit knowledge. However, as defined by Nonaka and Takeuchi [1995], tacit knowledge is personal, context-specific, and so hard to formalize and communicate, and explicit knowledge can be described as knowledge that is transmittable in formal, systematic language. To make more concrete and new definitions of tacit and explicit knowledge, we introduce the concept of knowledge representativeness [Polanyi, 1996] - the degree to which knowledge can be expressed in verbal, symbolic or written form. That is, we consider the representativeness of knowledge to be a continuum. According to this rationale, tacit knowledge is defined as knowledge that cannot be expressed in verbal, symbolic and written form while explicit knowledge is knowledge that exists in symbolic or written form. Then, implicit knowledge is knowledge that can be expressed in verbal, symbolic or written form, but not yet expressed. Since tacit knowledge is hard to formalize and communicate, this study focuses mainly on explicit and implicit knowledge sharing between the service receiver and provider. Based on above premise, we propose the following hypothesis. H1: Trust will be positively related to the extent of knowledge sharing. Mutual dependency as perceived risk In an alliance, organizations are often dependent upon each other. As the degree of interdependence in an alliance increase, the importance and the extent of the resources shared between partners also increase. Hence, these alliances are characterized by substantial overlap between the partners’ responsibilities and involved ongoing mutual adjustment between partners [Gulati and Singh, 1998; Krishnan, et al., 2006]. Similarly, in an outsourcing relationship, both client and provider have to work together to achieve the inter-organizational goals. This interdependence creates the sphere of mutual dependency. As a result, inter-organizational trust is therefore essential for outsourcing success, as it facilitates mutual adjustment and allows the mother synchronization of critical tasks [Krishnan, et al., 2006]. While a strong inter-organizational trust limits the need for formally written contract or structure by reducing the perceived need to guard against opportunistic behavior, exclusive mutual dependency is risky [Sabherwal, 1999]. Even if the parties may be confident in each other’s trustworthiness, they also may be uncertainty how much they rely on each other. This is why we introduce another construct - mutual dependency as perceived risk in our proposed model of outsourcing relationship trust. Mutual dependency between organizations results from a relationship in which participating parties perceive mutual benefits and share the risks from their interactions [Bensaou and Venkatraman, 1995; Mohr and Spekman, 1994]. Such dependency is determined by the organization’s perception of its dependency on its partner in relation to the partner’s dependency on it [Anderson and Narus, 1984]. When the size of the exchange increases and the importance of the exchange is recognized, the level of mutual dependency is high [Heide and John, 1990]. In such a case, participating parties usually see their partners as the best alternative for sources of exchange. According to Lee and Kim [1999], the higher the degree of mutual dependency is likely to result in the higher quality of relationship. Therefore, it is true that, in the context of outsourcing, the mutual dependency contributes to the degree of knowledge sharing (i.e., the level of risk taking), but it depends on the degree of mutual trust between the service receiver and provider. The higher the mutual dependency between the service provider and client organizations, the more likely they would

share their knowledge. Subsequently, the stronger the level of mutual dependency, the stronger the relationship between mutual trust and knowledge sharing. We hypothesize that: H2: The relationship between trust and knowledge sharing will be moderated by the degree of mutual dependency. Outsourcing Success The success of outsourcing can manifest in several different ways. Generally, success may be reflected by the degree to which predefined objectives are realized. In most outsourcing cases, outsourcing objectives relate to the strategic, economic and technological benefits. Then the success of outsourcing should be assessed in terms of attainment of these benefits [Loh and Venkatraman, 1992]. Such objectives include outsourced system’s efficiency, user and business satisfaction for outsourced systems, service quality, cost reduction, and so on [Arnett and Jones, 1994; Grover et al., 1996; Lacity and Hirschhein, 1993]. Outsourcing relationship based on inter-organizational trust can create a competitive advantage through the strategic sharing of organizations’ key information and knowledge [Konsynski and McFarlan, 1990]. Closer relationships result from more frequent and more relevant information and knowledge exchanges among high performance partners [Lam, 1997]. By sharing knowledge between the client and the service provider organizations, they are able to sustain a more effective outsourcing relationship over time. Therefore, the absence of knowledge sharing is a critical factor in the dysfunctional inter-organizational dynamics, whereas the presence of such a shared perception may lead to better outsourcing performance. Based on this premise, we hypothesize that: H3: Knowledge sharing will be positively related to the outcome of outsourcing. 2.4 Antecedents of trust Distinction between trust and initial trust Trust is one of the widely studied constructs in the social exchange literature. It represents one of the most desired qualities in any close relationship. Morgan and Hunt [1994] describe it as existing when one party has confidence in an exchange partner’s reliability and integrity. As shown in literature, trust plays a critical role in the development of long-term relationship and in facilitating exchange relationship. This type of committed and long-term relationship is perceived as a dynamic process as the parties mutually demonstrate their trustworthiness through specific sequential interactions. An interesting revelation is that if trust is indeed a dynamic process then it should be considered as a process-oriented concept rather than an outcome-oriented concept or an input-oriented concept [Lee and Kim, 1999]. However, the previous outsourcing studies have overlooked the dynamic nature of trust, which in part might have contributed to multiple and conflicting conclusions. According to Zaheer, et al. [1998] and Krishnan, et al. [2006], inter-organizational trust is relational and is collectively oriented. Such form of trust is likely to be based on experience and interaction with partner influenced by an organizational culture and value. Hence, it is dynamic because there is a time factor and historical element here. The issue is the missing of a dynamics that happens at the beginning when the parties come together with neither experience nor history of interaction to draw on. This is where we suggest the relevance and necessity of the construct “initial trust.” While at the organizational level, trust is a set of expectations shared by all those in an exchange [Zucker, 1986], we posit that initial trust is the general willingness to trust others prior to data on that particular party being available. Initial trust between parties is not based on any kind of prior experience with each other. Rather, it is based on an institutional cue that enables one party to trust another without firsthand knowledge. Thus, this study examines initial trust in the outsourcing relationship as an antecedent to interorganizational trust. We define our notion of initial trust as one party's willingness to believe the other

party based on the economic and cognitive cues that the other party would fulfill the commitment and behave in a predictable way. In outsourcing relationship, interaction between the client and its service provider organizations is commonplace. Such a situation involves initial trust. Since they have not worked together enough to develop an interaction history, initial trust situations occur naturally. Initial trust excludes experiential processes (e.g., observing actual behavior through interactions between parties), but it includes cognitive processes (e.g., having perception from some cues such as reputation). To work together well, two organizations need some level of initial trust so that they come to trust each other quickly [Meyerson et al., 1996]. Burt and Knez [1996] describe that high level of initial trust tends to be maintained as people interact in cooperative ways. If people have positive feeling about each other, they are not apt to reduce interactions between them. For instance, one who trusts another will tend to express that trust in actions toward the other. Since initial extended trust is usually reciprocated, the other party will also express trust [Burt and Knez, 1996]. This confirms the first party’s trusting beliefs, which in turn supports continued high levels of trusting intention. Social interaction also supports initial trust because of reputation effects [Wrightsman, 1991]. Generally, since the reputation of a person spreads gradually through social interaction, one party remembers the other party’s previous encounters. This international history accumulates with information about the person’s background and is transmitted to others. Therefore, when many people perceive that an individual has a good reputation, it is harder for a negative event to significantly decrease a high level of trusting beliefs in that individual. According to McKnight, Cummings and Chervany [1998], there are five research streams to explain how initial trust forms: (1) calculative-based; (2) knowledge-based; (3) personality-based; (4) institution-based; and (5) cognition-based. Calculative-based trust researchers theorize that individuals make trust choices based on rationally derived costs and benefits [Lewick and Bunker, 1995]. The second stream, knowledge-based trust theorists describe that trust develops over time as one accumulates trust-relevant knowledge through experiences with the other person [Lewicki and Bunker, 1995]. According to personality-based trust stream, trust develops during childhood as an infant seeks and receives help from his or her benevolent caregiver [Erikson, 1968]. Institution-based trust researchers maintain that trust reflects the security one feels about a situation because of guarantees, safety nets, or other structures [Zucker, 1986]. Finally, cognition-based trust researchers propose that trust relies on rapid, cognitive cues or first impressions, as opposed to personal interactions [Meyerson et al., 1996]. In this study, two research streams – calculative-based and cognition-based – among five can be used to conceptualize initial trust, even though each of other three streams can be adopted for initial trust. Knowledge-based trust assumes that the parties have firsthand knowledge of each other. However, the concept of initial trust in this study does not include any interaction history and focuses on second-hand knowledge such as reputation as a categorization process [McKnight et al., 1998]. Also, personality and institution-based trust are not appropriate for this study because of their totally different point of view. While personality-based trust exhibits an individual disposition to trust to the extent that she or he demonstrates a consistent tendency to be willing to depend on others [Erickson, 1968], institution-based trust is the psychological status originated from the appearance that things are normal regardless of actual outside environment [Zucker, 1986]. As a result, we only view the initial trust strictly from cognitive-based trust and calculative-based trust perspective. Based on above explanation and classification, we formulate the following hypothesis. H4: Initial trust will be positively related to the level of trust in an outsourcing arrangement. Distinction between trust and initial distrust The distinction between trust and distrust is less complicated than that of trust and initial trust. Our justification is drawn from Lewicki et al’s and McAllister’s works. Going back to the context of Rotter’s definition of trust, trust is characterized as confident positive expectations from one partner toward the other partners. According to Lewicki and his associate, distrust can be viewed as confident negative expectations toward other partners. This is consistent with Lewicki et al. [1998]’s view of distrust. That is distrust is simply as the opposite of trust or lack of trust.

Like the case of initial trust, the lack of trust has its source even at the time when there is no history or experience between the parties. This source is the construct “initial distrust” that we included in our proposed model. We can think of initial distrust in terms of initial trust. While initial trust is the general willingness to trust others prior to any history, initial distrust refers to the unwillingness of one party to trust other parties. Like initial trust, such unwillingness is based on an institutional cue for doubts and suspicions about other parties. In the context of our study, we define the notion of initial distrust as one party's unwillingness to believe other parties because of the economic and cognitive cues that the other parties may not fulfill the commitment or behavior in a predictable way. Similar to initial trust, we posit that initial distrust is an important construct in IT outsourcing. We based our conceptualization of initial distrust from McKnight et al. [1998]’s five research streams to explain how initial distrust forms. The two streams of research relevant to initial distrust are psychology-based trust and economic-based trust perspectives. The first one based on the psychology perspective is the suspicion of humanity by which one assumes others are not usually honest, benevolent, competent, and predictable [Wrightsman, 1991], and the second one related to the economic perspective is the distrusting stance by which one assumes that he/she will achieve better outcomes by dealing with people even though these people are not well-meaning and reliable [Riker, 1971]. Because the suspicions and doubts that inherently affect the extent of trust among parties, we propose that initial distrust is negatively influence an organization’s perceptions of new or existing environments, its relationships with specific partners, intentions and beliefs, and finally actual behaviors with others [Fishbein and Ajzen, 1975; Worchel, 1979]. We can also apply the evidence from Ajzen [1988]’s study to the situation of initial distrust between organizations – consistent intentions and beliefs from the beginning to the end of relationship. The basic assumption is that initial trust can be considered as the presence of safeguards against risks of bad relationship whereas initial distrust as the absence of such safeguards. Thus, if a party’s prior beliefs are negative, cognitive biases that prefer conservatism generally will sustain negative intensions and behaviors [Fazio and Zanna, 1981]. Consequently, over time, the negative belief will compound and adversely affect the interorganizational trust. Based on this premise, we posit that the attainment of initial distrust should lead to negative expectations toward other parties. Thus, our next hypothesis is the following. H5: Initial distrust will be negatively related to the level of trust in an outsourcing arrangement. Different Perspectives between the Service Receiver and Provider It has been pointed out that the perception of outsourcing relationships is different from the service receiver and provider. From the beginning of the outsourcing process, the service receiver generally has concerns about whether the current service provider is the best choice, the perceived replaceability of the service provider, and the perceived switching costs and risks [Lindskold, 1978; Ruyer et al., 2001]. It is truism that once a service provider is selected, it is very difficult for the service receiver to replace the selected provider with others because of the costs and risks of switching. Therefore, the degree of initial trust and initial distrust influences the perception of the service receiver to estimate the potential credibility and risks in the relationship with the service provider. On the other hand, although the service provider has similar feelings with initial trust and initial distrust, the service provider’s perception of risks and costs in the future relationship is lower than that of the service receiver, since the service provider’s interest is mainly driven by the future business opportunity and potential profit rather than a good or bad impression on a potential client at the beginning of the relationship. Thus, initial perception is more important for the service receiver than for the service provider. We hypothesize that: H6: The positive relationship between initial trust and trust will be stronger from the service receiver’s perspective than from the service provider’s perspective. H7: The negative relationship between initial distrust and trust will be stronger from the service receiver’s perspective than from the service provider’s perspective.

3. RESEARCH METHODOLOGY In this study, a field survey method was adopted with a confirmatory analysis approach. The unit of analysis was the outsourcing relationship between a customer and a service provider. This study focuses on the bilateral perception of the outsourcing relationship from both the service receiver and provider’s perspectives. 3.1 Development of Measures All measures used in the study are shown in Appendix A. After developing the research framework, we conducted a series of personal interviews with IT outsourcing professionals to assess the external validity of the model. We then developed a questionnaire based on the previous literature and the comments gathered from the interviews. When developing the measurement instrument, the multipleitem method was used and each item was measured on a five-point Likert scale from ‘strongly disagree’ to ‘strongly agree’. The survey instrument was developed either by adapting existing measures to the research context (7[e.g., knowledge sharing [Lee and Kim, 1999] and outsourcing success [Grover et al., 1996]] or by converting the definitions of the constructs into a questionnaire format (e.g., initial trust and initial distrust). In the model, initial trust, initial distrust, and knowledge sharing are measured as second-order factors, while the rest of the constructs are assessed as firstorder factors. For knowledge sharing, as described earlier, we introduced the concept of knowledge representativeness to classify knowledge into either implicit or explicit [Polanyi, 1966]. By reviewing the previous literature on knowledge sharing, we decided that the knowledge that exists in symbolic or written form as explicit knowledge (business proposals, reports, manuals, and models). Implicit knowledge, on the other hand, was defined as that material expressed verbally, symbolically, or in written form but not yet expressed as know-how, know-where, and know-whom from work experience. There is little empirical research on initial trust and initial distrust, and most such work emphasizes conceptual studies or small-scale surveys. These gaps reflect the lack of reliable measures of initial trust and initial distrust between organizations. Thus, we developed these measures based on their conceptual definitions and perspectives from the existing literature. In this study, two research streams – calculative-based and cognition-based – were used to conceptualize initial trust, while both psychology and economics perspectives were adopted to develop the measure of initial distrust. According to the calculative-based and cognition-based streams, initial trust can be measured by rationally derived costs and benefits [Lewicki and Bunker, 1995] and cognitive cues such as first impression and reputation [Meyerson et al., 1996]. For initial distrust, two major dimensions – suspicion of humanity and distrusting stance - from a psychology and economics perspectives were adopted. The suspicion of humanity refers to the assumption that parties are not usually honest, benevolent, competent, and predictable, while a distrusting stance indicates that parties have to be handled as if they are not well-meaning and reliable. An initial version of the survey instrument was subsequently refined through extensive pretesting with seven academics who have significant expertise in the study of outsourcing. The instrument was further pilot tested with ten service receivers and five service providers in Korea. We interviewed a CIO or a representative in charge of the firm’s IT function in each service receiver, and a manager who has control in operating outsourcing projects, teams, or divisions in each service provider. The multiple phases of instrument development resulted in a significant degree of refinement and restructuring of the survey instrument as well as establishing the initial face validity and internal validity of the measures.

3.2 Sample and Data Collection The data were obtained in two separate surveys. In the first survey, data was collected from the service receiver using a self-administered questionnaire. The primary source of the sampling frame for service receivers was a list of the 1,000 large firms reported in the Maeil Business Newspaper in Korea as of year 2003. We removed 30 IT service providers from the sample. Then, these firms were checked in the Book of Listed Firms published by the Korea Stock Exchange to obtain the name of the IS executive in each firm. Finally, the survey questionnaire was mailed to 970 corporate-level top IS executives of the service receiver’s firms. In this survey, service receivers were asked to select the most important service provider and answer questions dealing with that specific service provider. To avoid the same subject bias, the IS executives were asked not only to directly answer questions for trust, mutual dependency and outsourcing success, but also to indirectly get answers of questions for other constructs from their subordinates. Once responses were obtained from service receivers, a second questionnaire was sent to the service provider selected by the service receiver. The survey sent to the service provider focused on the same antecedents and characteristics as the service receiver questionnaire. Table 1. Characteristics of the sample [a] Industry type Service Industry Type receiver Freq % Banking and Finance 33 20.2 Manufacturing 41 25.2 Transport and Comm. 19 11.7 Retail and Wholesale 33 20.2 Construction 37 22.7 Information Tech. 0 0 Others 0 0 Unanswered 0 0 Total 163 100

Service provider Freq % 0 0 0 0 0 0 0 0 0 0 45 100 0 0 0 0 45 100

[b] Number of total employees Service Service Range receiver provider Freq % Freq % Less than 100 25 15.3 7 15.6 101 – 500 36 22.1 5 11.1 501 – 1,000 42 25.8 14 31.1 1,001 – 5,000 39 23.9 9 20.0 5,001 – 10,000 12 7.4 5 11.1 10,001 and above 7 4.3 0 0 Unanswered 2 1.2 5 11.1 Total 163 100 45 100

Range Less than $50 mil. $50 - $100 mil. $100 - $500 mil. $500 - $1 bil. $1 - $5 bil. $5 - $10 bil. $10 bil. and above Unanswered Total

[c] Total sales revenue Service receiver Freq % 30 18.4 17 10.4 42 25.8 21 12.9 19 11.7 20 12.3 10 6.1 4 2.4 163 100

Service provider Freq % 8 17.8 6 13.3 12 26.7 7 15.6 5 11.1 2 4.4 0 0 5 11.1 45 100

[d] Period of outsourcing relationship Service Service Year receiver provider Freq % Freq % Less than 2 32 19.6 7 15.6 2–4 54 33.1 15 33.3 4–6 38 23.3 9 20.0 6–8 14 8.6 6 13.3 8 – 10 7 4.3 3 6.7 10 and above 5 3.1 1 2.2 Unanswered 13 8.0 4 8.9 Total 163 100 45 100

In order to increase the response rate, Schaefer and Dillman [1998]’s Total Design Method had been applied to the two surveys. A total of 285 service receivers responded to the first survey representing a response rate of about 29 percent. Most of the respondents provided the name and address of the vendor representative who was most knowledgeable about the relationship. 86 out of 285 responses did not provide their vendor information, while 36 responses were discarded due to incomplete data. Finally, 163 responses could be used for the second survey for the service provider. Then, the questionnaire of the service provider was addressed to each representative of 163 service providers. As did in the first survey, we asked each vendor’s representative to directly answer questions for trust, mutual dependency and outsourcing success, and to indirectly get answers of other constructs from a person who has experience with a particular customer described in a cover letter. Following the Total Design Method, 59 responses out of 163 distributed questionnaires were received from vendor

representatives, providing a response rate of about 36 percent. Out of 59 responses, 14 responses were eliminated from analysis because of missing data. Thus, 45 responses could be used for the final analysis from the service provider’s standpoint. The respondent characteristics of both the service receiver and provider in terms of industry type, number of employees, total sales revenue, and the period of outsourcing are summarized in Table 1. Before the final data analysis, to test for non-response bias, we used guidelines suggested by Armstrong and Overton [1977]. First, the respondents and non-respondents were compared with regard to two key organization features: total sales volume and number of employees. Second, we compared early-returned questionnaires to late-returned questionnaires in terms of their total sales and number of employees. Analyses indicated that no significant mean differences existed between respondents and non-respondents and between early and late respondents. Thus, there was no evidence of obvious response bias in the sample, except the under-representation of manufacturing companies. Further, we applied the same procedure to examine a potential response bias for the service providers’ sample through a comparison between respondents and non-respondents in terms of total sales volume and number of employees. The result also showed no mean difference from the comparison of respondents to non-respondents of service providers at the significance level of 0.05.

4. ANALYSIS AND RESULTS 4.1 Analysis Method Instead of exploratory approaches like regression analysis, this study selected a confirmatory approach using Partial Least Squares (PLS). The PLS method was chosen to examine the proposed model and its hypotheses because of the following reasons: First, PLS is suitable for assessing theories in the early stages of development [Fornell and Bookstein, 1982]. Thus, it can be used to analyze the data because this study is a first attempt to advance a theoretical model by introducing new concepts knowledge sharing, initial trust, and initial distrust – to outsourcing research, even though this study tried to deduce the research model from an existing theory; Second, PLS requires minimal demands on sample size in order to validate a model compared to other SEM techniques [Chin, 1998]. Due to the scale of the survey and the complex data collection process of eliciting participation of the service receivers and providers, the size of the sample for the final analysis seems to be acceptable at the minimum level, especially with the data collected from the service provider. This makes PLS appropriate for testing the proposed model using the gathered data. This study used PLS-Graph version 3.00 for analyzing measurement and structural models. 4.2 Measurement Model Following the recommended two-stage analytical procedures [Anderson and Gerbing, 1988; Hair et al., 1998], a confirmatory factor analysis is first conducted to assess the measurement model, and then the structural relationship is examined. The rationale for this approach is to ensure that our results on the structural relationship come from accurate and desirable representation of the reliability of the indicators in the measurement model. To validate our measurement model, three types of validity were assessed: content validity, convergent validity and discriminant validity of the instrument. First, content validity refers to the representativeness and comprehensiveness of the items used to create a scale. It is assessed by examining the process by which scale items were generated [Straub, 1989]. Content validity is established by ensuring the consistency between the measurement items and extant literature, by interviewing senior practitioners and pilot-testing the instrument. Second, convergent validity was assessed by looking at the composite reliability and the average variance extracted from the measures [Hair et al, 1995]. Although many studies employing PLS use 0.5 as the threshold reliability of the

measures, 0.7 is the recommended value for a reliable construct [Chin, 1998]. As shown in Table 2, our composite reliability values of the measures for the service receiver range from 0.863 to 0.957, and from 0.871 to 0.945 for the service provider. For the average variance extracted by a measure, a score of 0.5 indicates its acceptable level [Fornell and Larcker, 1981]. Table 2 shows that the average variances extracted by our measures were very satisfactory at 0.632 or above for the service receiver and at 0.600 or above for the service provider. Table 2 also exhibits the loadings and t-values of the measures for both the service receiver and providers in our research model. All measures are significant on their path loadings at the level of 0.01, as expected. Finally, the discriminant validity of our instrument was verified by looking at the square root of the average variance extracted, as recommended by Fornell and Larcker [1981]. As shown in Table 3, the result revealed that the square root of the average variance extracted for each construct on models of the service receiver and provider is greater than the correlations between it and all other constructs. Also, the results of the inter-construct correlations exhibited that each construct shared larger variance with its own measures than with other measures. Overall, these results suggest that the measurement models for the service receiver and provider are strongly supported by the gathered data and ready for further analysis. In addition to the validity assessment, we checked multicollinearity of the measurement model. Multicollinearity may potentially exist among the independent variables. Table 3 displays the correlations among all variables. The highest correlations exist between mutual dependency and implicit knowledge sharing for the service receiver (0.610) as well as the service provider (0.674). The remaining correlations among constructs ranged from -0.091 to 0.584 in the measurement model of the service receiver, while -0.007 to 0.673 in the service provider’s measurement model. The multicollinearity for all variables was examined with the Variance Inflation Factor (VIF). The results show that the values of VIF for constructs are acceptable: 1.142~1.827 for the service receiver; and 1.085~1.863 for the service provider. These correlations plus the result from the VIF suggest that multicollinearity is not a serious problem for the proposed model from both the service receiver’s and provider’s perspectives, particularly when the purpose of the analysis is to make inferences on the response function or the prediction of new observations [Neter et al., 1985], which is the case in this study. Table 2. Results of PLS Confirmatory Factor Analysis Construct Cognition-based Initial Trust Calculative-based Initial Trust Psychology-based Initial Distrust Economics-based Initial Distrust

Trust

Explicit knowledge sharing

Item COIT1 COIT2 COIT3 COIT4 CAIT1 CAIT2 CAIT3 PSID1 PSID2 PSID3 PSID4 ECID1 ECID2 ECID3 TR1 TR2 TR3 TR4 TR5 TR6 EKS1 EKS2 EKS3

Service Receiver Loading 0.887 0.964 0.949/0.823 0.805 0.964 0.771 0.884/0.718 0.889 0.877 0.895 0.882 0.906/0.707 0.743 0.834 0.773 0.863/0.677 0.882 0.810 0.702 0.763 0.758 0.871/0.632 0.620 0.764 0.758 0.932/0.775 0.888 0.862 0.856 CR / AVE*

t-value 51.069 214.440 24.273 214.439 8.375 9.718 9.736 9.876 9.775 8.015 9.614 8.963 9.818 9.183 12.815 17.294 14.188 9.053 17.294 14.188 9.837 9.710 9.690

Service Provider CR / AVE** Loading 0.949 0.911 0.936/0.786 0.715 0.949 0.718 0.871/0.693 0.898 0.871 0.807 0.955 0.942/0.805 0.861 0.956 0.898 0.880/0.711 0.729 0.892 0.717 0.776 0.840 0.900/0.600 0.685 0.776 0.840 0.914/0.728 0.897 0.878 0.729

t-value 61.96 31.016 6.132 61.962 3.790 8.602 8.660 13.806 56.419 14.664 56.420 19.226 5.621 30.066 4.509 9.226 16.171 6.506 9.226 16.171 23.167 25.023 12.431

EKS4 0.913 IKS1 0.767 Implicit knowledge 0.866/0.684 IKS2 0.881 sharing IKS3 0.829 MD1 0.920 MD2 0.879 Mutual 0.957/0.816 MD3 0.919 Dependency MD4 0.879 MD5 0.920 OS1 0.692 OS2 0.771 OS3 0.750 OS4 0.738 Outsourcing Success 0.920/0.664 OS5 0.735 OS6 0.780 OS7 0.812 OS8 0.756 OS9 0.807 * CR stands for Composite Reliability and AVE is Average Variance Extracted

9.881 8.699 9.734 9.401 11.525 15.834 11.524 15.834 11.522 14.944 23.003 20.423 10.183 15.458 25.210 31.741 20.263 30.827

0.897 0.775 0.915 0.852 0.918 0.856 0.854 0.918 0.856 0.753 0.756 0.737 0.800 0.872 0.830 0.763 0.603 0.860

0.886/0.722

0.945/0.776

0.932/0.606

23.167 8.385 22.354 23.308 24.041 14.694 23.444 24.041 14.694 13.533 13.184 13.570 9.501 17.063 22.631 7.648 4.700 19.270

Table 3. Correlations between Constructs 1 2 3 4 5 6 7 8 9

Construct Cognition-based Initial Trust Calculative-based Initial Trust Psychology-based Initial Distrust Economics-based Initial Distrust Trust Explicit knowledge sharing Implicit knowledge sharing Mutual Dependency Outsourcing Success

(a) Correlations for service receivers 1 2 3 4 0.907 0.333 0.847 0.237 0.092 0.841 0.265 0.206 0.366 0.823 0.317 0.055 0.306 0.375 0.389 0.344 0.155 0.501 0.281 0.291 -0.091 0.334 0.314 0.135 0.157 0.122 0.363 0.300 0.183 0.391

5

6

7

8

9

0.795 0.553 0.610 0.236 0.477

0.880 0.584 0.201 0.462

0.827 0.147 0.423

0.903 0.242

0.815

6

7

8

9

0.853 0.673 0.424 0.574

0.850 0.400 0.450

0.881 0.303

0.778

(b) Correlations for service providers Construct 1 2 3 4 5 1 Cognition-based Initial Trust 0.886 2 Calculative-based Initial Trust 0.152 0.832 3 Psychology-based Initial Distrust 0.475 0.234 0.897 4 Economics-based Initial Distrust 0.129 0.431 0.334 0.843 5 Trust 0.452 0.146 0.439 0.182 0.775 6 Explicit knowledge sharing 0.483 0.288 0.478 0.279 0.650 7 Implicit knowledge sharing 0.261 0.117 0.306 -0.007 0.674 8 Mutual Dependency 0.544 0.053 0.211 0.151 0.393 9 Outsourcing Success 0.329 -0.052 0.418 0.197 0.572 . The shade numbers in the diagonal row are square roots of the average variance extracted.

4.3 Structural Model With adequate measurement models and an acceptable level of multicollinearity, the proposed hypotheses are tested with PLS. The results of the analysis of the structural models for the service receiver and provider are summarized with the path coefficients and t-values in Figures 2 and 3, respectively. Tests of significance of all paths in each model were performed using the bootstrap resampling procedure. Service receiver’s perspective Figure 2 shows the results of the PLS analysis from the service receiver’s perspective including the path loadings, t-values of the paths, and R-square. As shown in the Figure, among five hypothesized paths, three are found significant at the level of 0.01.

A service receiver’s perception of initial trust was found to be significantly related to the service receiver’s perception of trust (β=0.418; t=6.127; p