Enabling e-business Transformation through Alliances: Integrating Social Exchange and Institutional Perspectives

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1 Enabling e-business Transformation through Alliances: Integrating Social Exchange and Institutional Perspectives Darrin Thomas University of Illinois at Chicago C Ranganathan University of Illinois at Chicago Abstract e-business transformation has become a critical imperative for most organizations today. However these transformations require specific skills, capital, information, technology, access to markets, and core resources that many traditional firms lack. To obtain these resources and capabilities, firms are increasingly turning to external arrangements, such as alliances. Our understanding of why firms choose a particular e- business alliance form over others in such a relationship is limited. Drawing upon social exchange and institutional theories, we examine how partner relatedness and institutional factors drive the choice of e- business alliance form. Results from 1,381 e-business alliances provide a strong first reflection of the impacts of factors on the choice of e-business alliance form. 1. Introduction e-business transformation has become a critical imperative for most organizations today. Since the commercialization of world wide web in 1993, web technologies and the Internet have enabled companies to perform digital business operations better, faster and cheaper than ever before. In fact, web presence and e- business operations have become more of a competitive necessity for most organizations. e-business transformation, i.e., the process of transition from a traditional brick-and-mortar organization to a digital brick-and-click firm has been a daunting task for several firms [1, 12]. e-business transformation requires specific skills, capital, information, technology, access to markets, and core resources that many traditional firms lack [26]. Firms have two broad options for developing specific resources and capabilities required for effective e- business transformation through internal development, or through external sourcing arrangements such as outsourcing and alliance partnerships. The internal development and sustenance of e-business resources requires considerable time and efforts which often deters firms from adopting this route. Further, it is often difficult to develop e-business capabilities internally as they often involve a complex mix of business as well as technology expertise. Therefore, firms are increasingly turning to external governance arrangements such as alliances to this end. There are certain risks inherent, however, to exchanging resources in an alliance, which stem from uncertainties posed by the environment and the alliance partner. Firms need to carefully choose the structure of their alliance form as this choice would determine the basic outcomes of their e-business transformation efforts. The number of e-business alliances is on the rise [9] however, there is little scholarly effort that has focused on understanding e-business alliances and the dynamics underlying the formation of such alliances. Firms use different alliance forms ranging from loosely structured co-marketing and co-promotion contractual agreements, to tighter forms of alliances such as equity investments and joint ventures aimed at enhancing e-business operations. While IS scholars have built a substantial knowledge on IS outsourcing arrangements [16], there is a definite lack of understanding on other forms of partnerships such as bilateral alliances, minority equity partnerships and joint ventures, especially in the context of e-business. Our knowledge on why firms choose a particular e-business alliance form over others is limited. This research seeks to address this important gap. Drawing upon the social exchange and institutional theories, our research objective is to explore the key factors that potentially influence the choice of e-business alliance form. We aim to examine the dynamics underlying a firm s choice of alliance form in an e- Business partnership given their partner and industry characteristics. Specifically, the questions we address are: i) What partner-related and institutional factors drive the choice of e-business alliance form? ii) Why do firms choose a specific alliance form (governance structure) over other alternatives in e- Business alliances? In this paper, we examine these questions using data from 1,381 e-business alliances formed between January 1, 1999 and December 31,

2 2. Literature Review and Conceptual Model In this section, we review extant literature on interfirm alliances and propose an operational definition of e- business alliances. Further, we outline four salient governance forms in e-business alliances and outline their primary characteristics. Then, we elaborate on institutional and social exchange theories and explain the conceptual research model and our conjectures regarding the hypotheses related to the research model. Alliances are voluntary cooperative arrangements between firms involving exchange, transfer, sharing, or co-development of products, technologies or services [13]. Our focus is on e-business alliances, where firms enter into inter-firm partnerships with a goal of enhancing their online business activities and online performance. These alliances can be driven by a variety of motives, take different forms and can transcend across vertical and horizontal boundaries. An example of an e-business alliance is the arrangement between the retailer Target and Amazon.com: Target realized that they lacked the management and technological acumen to create a website that could compete with other online retailers, so they partnered with Amazon.com who agreed to carry Target s products and provide an online channel. This gave Target a best of breed online presence while allowing them to focus on their brick and mortar business operations. The governance form selected by a firm when participating in an alliance is dependent on a variety of factors ranging from the specific objectives to be accomplished through the alliances, the anticipated exchange of resources, and the relative risks involved. Depending on a firm s goals, capabilities sought, resource gaps and the organizational context, a firm could choose a variety of governance forms in e-business alliances. These different arrangements offer a range of risk reduction and varied costs, therefore, careful choice of an alliance and its governance structure becomes paramount. Literature on inter-firm relationships has identified several types of alliance forms that are prevalent in the industry. Some earlier studies viewed alliances as a simply dichotomy: unilateral or bilateral resource exchanges [18], equity-based or non-equity based exchanges [11, 22, 24, 25], or knowledge-based or property-based resources [17]. While these dichotomous options allowed for parsimonious research models, they did not adequately capture the nuances underlying alliances, leading to a significant loss in explanatory power. Recognizing this limitation, less restrictive typologies were developed including the three options of contractual agreements, minority alliances, and joint ventures [15, 27, 31] or the four categories of alliances outlined by Das and Teng: unilateral contract-based alliances, bilateral contract-based alliances, minority equity alliances, and equity joint ventures [4]. This fourpronged typology is appropriate for our research context as it allows a superior level of examination, accommodating simple and complex outsourcing agreements, as well as other kinds of partnerships that require increased levels of interactions, exchanges and commitments among partners. Joint ventures and minority equity investments represent higher levels of equity stakes and managerial controls in the partnership, whereas contractual agreements are usually project-based collaborations that typically revolve around one or a few e-business activities of a firm. The contractual agreements represent lesser hierarchical controls, whereas minority equity investments and joint ventures represents higher degrees of hierarchical control. Further, characteristics of each alliance type are noted below: Unilateral-Contractual: Alliances characterized by well-defined transfer of resources, where individual firms carry out their obligations independently of the other firms. Contracts tend to be specific and complete, and partners have little coordination or integration. Examples include technology licensing, IT infrastructure outsourcing, web hosting and maintenance, application development or software procurement with little customization, and distribution arrangements. Bilateral-Contractual: Both partners engage in sustained resource exchanges and the contracts tend to be more open-ended, less complete and dynamic, and in some cases could unfold as the partnership progresses in time. Due to their bilateral nature and more open contracts, this type of alliance potentially involves far more resource transfer, including knowledge transfer, than a unilateral alliance. Examples include co-marketing and promotion, joint application development, joint R&D, enhanced supply chain partnerships etc. Minority Equity Investments: Exchange agreement where partners share or trade equity. A partner takes an equity interest in the other(s) and gains certain amount of control. Partner could gain the right to access and control certain resources and capabilities, with restricted exposure to the partner, in return for the equity contribution. Joint Ventures: Inter-firm arrangement where a separate entity is created with shared-ownership of partners. Joint ventures are marked by relatively larger equity investments from all partners that lead to creation of new entity. This represents a substantial integration of the resources of all partners and embodies a significant amount of exposure of all partners to each other in the relationship. Two research streams, institutional theory and social exchange perspective, offer useful insights into how firms decide on optimal alliance governance form. These two 2

3 theoretical perspectives, combined, are expected to capture both the partner-related and institutional factors that potentially influence e-business alliance formation. Drawing upon these two theoretical perspectives, we focus on institutional factors and partner relational characteristics which potentially could have an impact on the alliance form. Our research model is shown in Figure. 1. We base our hypotheses off these two theoretical perspectives, and then test them using a fairly large dataset on e-business alliances. Partner Relatedness - Industry - Market Cap - Size - Age Institutional Factors - Prior industry alliances - Prior industry alliance forms Figure 1. Research Model Institutional Theory e-business Alliance Form - Unilateral Contractual - Bilateral Contractual - Minority Equity Investment - Joint Venture Institutional theory focuses on the ceremonial conformity of organizations to the rules and trends of the institutional environment they operate in [7]. It argues that firms adopt and follow certain processes in an effort to conform to similar practices by peers in their industry. Thus, institutional theory provides a non-economic rationale for a firm s actions and behaviors. Arguments arising out of institutional theory suggest that firms could form e-business alliances in response to similar alliances being formed in the industry by its peers and other business partners. Firms could simply mimic the alliance actions by other industry players. Exhibiting and mimicking industry behavior would enable a firm to gain legitimacy and help it stay astride with the prevailing roles, requirements, and norms of their business environment [20, 29, 32]. Moreover, conforming to competitors with a strong web offering is a means of survival [21] as no action on this emergent horizon would no doubt result in a loss of market-share. DiMaggio and Powell [7] referred to this imitating or mimicking of industry actions as mimetic isomorphism, which notes that managers of firms either consciously or unconsciously mimic the strategies of successful organizations. As noted by Barringer and Harrison [2], firms may engage in interorganizational relationships like alliances simply because other successful firms in their same industries have done so. Firms may even go so far as to mimic the governance structure used by other firms in their industry when forming their alliances [6, 10]. Based on these arguments we expect that a firm is likely to enter into e-business alliances, and also choose a particular e-business alliance form based on the dominant pattern exhibited in its operating industry. H1a: The greater the extent of e-business alliances formed by firms in the operating industry of a firm, the higher will be its propensity to form e-business alliances. H1b: The dominant governance form of e-business alliances in a firm s operating industry is likely to influence its choice of e-business alliance form. Social Exchange Perspective Social exchange theory extends economic theory by examining the non-contractual-based reasons for participating in an exchange [3]. The theory was originally derived by sociologists who wished to further explain an individual s behavior when exchanging resources [5]. As defined by Blau, social exchange theory examines the voluntary actions of individuals that are motivated by the returns they are expected to bring and typically in fact bring from others [3]. Social exchanges differ from economic exchanges in that the specific benefits of exchange are not contractually and explicitly fully specified largely because such exchanges do not involve extrinsic benefits. An example is the exchange of tacit knowledge; since the knowledge is tacit, no contract can clearly demark what will be exchanged. In order to participate in such an exchange, partners, be it individuals or firms, must have a social bond borne out of trust and social influence. An alliance is a prime example of a social exchange since it involves an interaction that far exceeds the bounds of a traditional market transaction. Social exchange theory helps to explain alliances with the examination of trust and social influence. While trust can be easily formed through repeated interactions, the first time two firms engage each other an inherent uncertainty exists. Compounding this is a powerdependence, or social influence, as noted by Emerson [8]: 3

4 when one firm (A) needs resources from another firm (B), firm A develops dependence on firm B, and consequently firm B acquires power over firm A. This enables firm B to have some influence over firm A s actions, resulting in an even greater desire for minimized risk. Alliances offer the capability to enable hierarchical controls to control for the type of risk; if greater risk is present, partnering firms can protect themselves by selecting a more hierarchical alliance governance form. While repeated ties may reduce the lack of trust, social influence may still necessitate these controls. In time firms may opt to employ incomplete contracts and take greater risks with each other based on their formed social bond and trust. One factor that may contribute to increased or decreased trust is the level of partner relatedness, which refers to the extent partner firms overlap in their productmarket coverage and primary business operations. Prior studies have shown that related firms tend to prefer more hierarchical forms of alliance governance as it provides a check for opportunistic behavior, enables tighter monitoring of the partnership, and facilitates higher levels of knowledge transfer and organizational learning [14]. H2: The greater the extent of partner relatedness, the higher will be a firm s propensity to form more hierarchical form of e-business alliances. Further affecting the trust in an alliance is the level of perceived uncertainty about a partner firm. In general, partner uncertainty is the ambiguity surrounding the cooperation and performance of a partner in an alliance. When aligning, the individual interests of partners can lead to actions that are individually rational, yet collectively produce suboptimal outcomes. Even just the perception of opportunistic behavior can significantly affect the alliance performance [23]. Different characteristics of a partnering firm can be reflective of the degree of uncertainty; the greater the disparity for reputation, age, and size between two firms, the greater the uncertainty surrounding the alliance. These characteristics and the resultant perceived uncertainty about the partner are likely to influence the choice of alliance form. Confounding this point is the fact that e-business is a relatively new arena characterized by considerable ambiguities surrounding the technologies, standards and the very viability of the business medium. As such, when a firm engages in e-business initiatives through alliances, it becomes all the more important to take adequate measures to mitigate the risks and uncertainty about the partner. If a partner firm is well established with proven capabilities, then that calls for a greater trust towards the partner and reduced need for hierarchical governance mechanisms. Alternatively if perceived uncertainty about a partner is high, a firm might desire to exercise greater control and have tighter monitoring mechanisms, and hence could prefer more hierarchical forms of alliances. H3: The greater the extent of partner uncertainty, the higher will be a firm s propensity to form more hierarchical form of e-business alliances. 3. Data Gathering and Measures In this research study, we examine e-business alliances between two or more publicly-traded partner firms. This limitation was established due to the availability of data, and as such, our data set does not include alliances with international companies (unless they are also traded on a U.S. exchange) or private, nontraded companies. Our sample includes announcements reported through press releases by firms between January 1, 1999 and December 31, Specifically, data was retrieved from Lexis-Nexis Academic Universe, which included sources such as Business Wire and PR Newswire. To root out the most relevant alliances we did a search for all press releases that had terms similar to alliance, partner, tie up, joint venture, cooperate, join forces, relationship, agree, or deal in their text. As a further restriction, we identified a need for terms like Internet, web, online, e-business, e-commerce, or electronic commerce to also be in the text. Our procedure is consistent with Subramani and Walden [30] who used secondary data to examine e-commerce announcements. After extensive sorting, we had data on 1,381 alliances ranging from unilateral contractual alliances to joint ventures. Information about firm characteristics was obtained from the COMPUSTAT database. Our dependent variable is the choice of e-business alliance form. Based on our earlier conceptualization, we classified an e-business alliance as one of four options: a unilateral contractual agreement, a bilateral contractual agreement, a minority-equity investment, or a joint venture. Our independent variables included those pertaining to partner relatedness and industrial factors. Partner relatedness was assessed using NAICS codes, market capitalization, size, and age of the firms. The NAICS measure assessed if the partner firms possessed similar product-market portfolios by comparing the first two digits of their NAICS values; This was effective since the NAICS industry classification scheme groups firms by their primary activity, with successive digits in the code indicating greater specificity. As such, by examining the first two digits, we can determine if two firms are in similar industries. This approach to measuring partner firm relatedness is similar to several studies in strategic management literature and replaces historic approaches using the now-depreciated SIC codes. We used three proxy measures for capturing partner uncertainty, namely market capitalization, size (as 4

5 measured by annual revenues), and age of the firms, with the year prior to the alliance formation being the base year used to capture the data. This approach is consistent with several studies in strategic management that have used age and size to capture firm reputation, level of expertise and potential trust [28]. Market capitalization captures the expectations and assessment of a fairly large number of investors on past, ongoing and potential future performance, and serves as an indicator of a firm s reputation, market standing, and overall expertise. For each of these measures, a relatedness-score was computed by examining the absolute value of the difference between the two firms for each of the three metrics. We used the same approach as Gulati and Singh [13] to capture the institutional factors that could potentially affect e-business alliance formation. We calculated two measures: 1) the percentage of all e-business related ties formed in a firm s operating industry prior to the specific alliance under consideration and 2) the percentage of joint ventures, minority equity alliances, bilateral and unilateral agreements formed in the operating industry as compared to total number of each specific alliance form across all industries. We refer to these as all-ratio and type-ratio, respectively, in our analyses. 4. Analysis and Results To assess our hypotheses, we used multinominal logistic model as our dependent variable was categorical and our independent variables involved a mix of categorical and interval scaled data. Multinomial logistic regression estimates simultaneous logistic regression models with pair-wise comparisons of each functional category with a base category. In our case, the base category was formation of unilateral alliance while the other categories represented varied alliance forms. The model estimates the parameters of given independent variables for the likelihood of formation of bilateral, minority-equity and joint venture based e-business alliances. Therefore, we considered multinomial logistic regression as an appropriate analytical technique for performing our analysis. Our basic model for predicting alliance form (FORM) is: FORM = f (NAICS_diff, market_cap_diff, size_diff, age_diff, all-ratio, type-ratio) equation. The probability of a particular e-business governance form choice, e.g. joint venture, with respect to the probability of all other choices could be computed as: [ Pr (Form = 3 / x) / 1 Pr (Form = 3 / x) ] = exp ( 1 + x ) As the above equation indicates, the probability of choosing a joint venture, as compared to any other forms, will be higher when the coefficient associated with a particular independent variable in vector x is positive and vice versa. After deleting alliances with missing values from the consideration set, data from 1,381 were available for analysis, and of those, 863 were unilateral contractual alliances, 162 were bilateral contractual alliances, 46 were minority-equity alliances and 310 were joint ventures. Table 1 presents the results of the analysis as estimated with SPSS for bilateral alliances, minority equity alliances, and joint ventures as compared to the base category of unilateral alliances. The results partially support H1a which stated that the greater the extent of e- Business alliances formed by firms in the operating industry of a firm (all-ratio), the higher will be its propensity to form e-business alliances. Specifically, the hypothesis held true for all but joint ventures, for which the inverse held true. H1b indicated that the dominant governance form of e-business alliances in a firm s operating industry (type-ratio) is likely to influence its choice of e-business alliance form. This hypothesis received mixed support as minority equities were the only alliance type with a significant difference from contractual alliances for the influence of governance form. We expected this to be true for all three alliance forms tested. H2, the greater the extent of partner relatedness, the higher will be a firm s propensity to form more hierarchical form of e-business alliances, had mixed support as it was supported for minority equities and joint ventures but not bilateral alliances. Similarly, H3, which stated that the greater the extent of partner uncertainty, the higher will be a firm s propensity to form more hierarchical form of e-business alliances, was only partially supported over two of the three measures for minority equity alliances and joint ventures, and was not supported at all for bilateral alliances. The specification of the multinomial logistic regression takes the form log [ Pr (Form i / x) / 1 Pr (Form i / x) ] = i + x where i represents different alliance form outcomes such as unilateral agreement (i = 0), bilateral agreement (i = 1), minority-equity investment (i = 2) and joint venture (i = 3). The i value represents intercept parameters, represents a vector of coefficients, and x is a vector of independent variables shown in earlier basic model 5

6 Table 1. Multinomial Logistic Regression Results Bilateral Minority Equity Joint Venture Intercept *** (2.924) *** (0.490) (0.457) Prior industry alliances (all-ratio) *** (7.480) 9.553*** (1.726) *** (3.396) Prior industry alliance form (type-ratio) (19.561) *** (1.556) (2.033) Age (0.015) *** (0.003) (0.005) Market Cap ** Size Industryrelatedness (Difference in NAICS code) (1.505) Log likelihood: Chi-square: Significance: * 2.388*** (0.285) 0.000** 1.381*** (0.378) Coefficients show effects of covariates for each alliance type relative to effects that the covariates have for the base category, unilateral contractual alliances. Values provided are the un-standardized coefficient, followed by the standard error in parentheses. N = 1,381. Significance is noted as follows: *p <.10, **p <.05, ***p < Discussion, Contributions and Conclusions For all but one measure, there was no significant difference between unilateral contractual alliances and bilateral contractual alliances. This lends credibility to the assertion that there is no significant difference between contractual alliance forms, and that they can be examined together [15, 27, 31]. We found strong support for association between institutional factors and alliance formation. The overall number of alliances formed in a firm s operating industry seem to influence subsequent formation of e-business alliances in an industry. However, when we examined if prevalence of a specific alliance form in an operating industry was associated with a choice of specific alliance form chosen by firms in our sample, we did not find any significant results, except in the case of minority equity investments. Our results imply that though firms might tend to mimic the alliance-route for effecting e-business transformation, the specific choice of alliance form need not be influenced by the alliance form prevalent in the operating industry. A firm could choose to distinguish itself from peers by opting for different alliance forms, though its objective of building e-business via alliance networks might remain the same as those of its peers. Further, as noted by Barringer and Harrison [2], interorganizational relationships are far more pervasive in some industries, e.g. biotechnology, computer, telecommunication, pharmaceutical, chemical, and electronics industries. Use of institutional mimicking on the individual industry level may thus vary greatly, resulting in statistically insignificant results in the composite. We also found strong support for the influence of partner-related factors on alliance formation, and the choice of specific alliance form. Partner relatedness was found to influence the type of alliance used, as was partner uncertainty. Given the prior discussion on the relationship between trust and partner relatedness and uncertainty, these findings are consistent with expectations and prior studies of the relationship between trust and alliance forms [13, 19]. An examination of the coefficients for NAICS differences further supports our second hypothesis and suggests that greater partner relatedness likely results in a more hierarchical form of alliance between the partner firms in an e-business alliance. Due to mixed support of the third hypothesis, the coefficients for the partner uncertainty measures cannot provide the same level of additional support. Overall, however, the results provide a strong first reflection of the impacts of factors on the choice of e-business alliance form. This contribution can be regarded as a first step towards shedding light on an alliance driver, e-business transformation, and its primary antecedents. We believe this study has made several significant contributions to research and practice. First, this study is one of the first few studies that have examined varied external governance arrangements for building e-business resources and capabilities. Extant literature has largely focused on outsourcing, which represents an arms-length relationship between a firm and its partners. However, our research throws light on a variety of e-business partnerships that are being pursued in the industry. Second, we have combined institutional and social exchange perspectives to identify salient factors affecting e-business alliance formation. Identification of these factors help us understand the non-economic drivers that potentially affect e-business alliance formation. Third, our study also contributes to emergent research on e-business transformation which has largely ignored the issue of alliances as an enabler of e-business transition. For practitioners, our study throws light on a contemporary phenomenon and a highly prevalent business practice. Our findings suggest a strong tendency of firms to mimic 6

7 industry practices and trends. An implicit assumption is that the mimicking would enable firms to achieve a similar degree of effectiveness in e-business transformation like the successful firms However, it should noted that the partner-related factors also play a key role in determining alliance forms. Choice of alliance form cannot be solely based on industry trends, but a variety of firm-level factors need to be taken into account before making a decision on the partnertship form and the alliance partner. This research has several limitations that should be noted. First, we examined only two broad set of factors belonging to the partnership and institutional sets. A firm s choice of alliance forms is dependent on a host of factors available resource levels, type of resources sought through alliance, broader trust between the partners, complementarity, anticipated interdependence, etc. It should be noted that our research sought to empirically examine a restricted set of two broad constructs rather than perform an exhaustive examination of all potential factors affecting e-business alliance formation. Second, we used several surrogate measures that were available through secondary data sources. Future researchers could seek to assess alliance formation through surveys or in-depth case studies. 6. References [1] Andal-Ancion, A., Cartwright, P. A. & Yip, G. S. The Digital Transformation of Traditional Businesses, Sloan Management Review, 44(4), Summer 2003, pp [2] Barringer, B. R. & Harrison, J. S. Walking a Tightrope: Creating Value Through Interorganizational Relationships, Journal of Management, 26(3), 2000, pp [3] Blau, P. M. Exchange and Power in Social Life, Wiley, New York, [4] Das, T. K. & Teng, B-S. A Resource-Based Theory of Strategic Alliances, Journal of Management, 26(1), 2000, pp [5] Das, T. K., & Teng, B. A Social Exchange Theory of Strategic Alliances, In Contractor, F. J. & Lorange, P. (Eds.), Cooperative Strategies and Alliances, Elsevier Science, Oxford, UK, 2002, pp [6] Davis, Gerald F. Agents Without Principles? The Spread of the Poison Pill through the Intercorporate Network, Administrative Science Quarterly, 36, 1991, pp [7] DiMaggio, P. & Powell, W. The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields, American Sociological Review, 48, 1983, pp [8] Emerson, R. M. Power-Dependence Relations, American Sociological Review, 27, 1962, pp [9] Ernst, D., Halevy, T., Monier, J. & Sarrazin, H. A Future For e-alliances, McKinsey Quarterly, 2, 2001, pp [10] Fligstein, N. The Spread of the Multidivisional Form among Large Firms, , American Sociological Review, 50, 1985, pp [11] Gulati, R. Does Familiarity Breed Trust? The Implications of Repeated Ties for Contractual Choice in Alliances, The Academy of Management Journal, 38(1), February 1995, pp [12] Gulati, R. & Garino, J. Get the Right Mix of Bricks and Clicks, Harvard Business Review, May/June 2000, pp [13] Gulati, R. & Singh, H. The Architecture of Cooperation: Managing Coordination Costs and Appropriation Concerns in Strategic Alliances, Administrative Science Quarterly, 43(4), 1998, pp [14] Khanna, T., Gulati, R., & Nohria, N. The Dynamics of Learning Alliances: Competition, Cooperation, and Relative Scope, Strategic Management Journal, 19(3), March 1998, pp [15] Killing, J. P. Understanding Alliances: The Role of Task and Organizational Complexity, In Contractor, F. J. & Lorange, P. (Eds.), Co-operative Strategies and International Business, Lexington Books, Lexington, MA, 1988, pp [16] Lacity, M. C. & Willcocks, L. P. An Empirical Investigation of Information Technology Sourcing Practices: Lessons from Experience, MIS Quarterly, 22(3), September 1998, pp [17] Miller, D., & Shamsie, J. The Resource-Based View of the Firm in Two Environments: The Hollywood Film Studios from 1936 to 1965, Academy of Management Journal, 39, 1996, pp [18] Mowery, D. C., Oxley, J. E., & Silverman, B. S. Strategic Alliances and Interfirm Knowledge Transfer, Strategic Management Journal, 17, 1996, pp [19] Norman, P. M. Protecting Knowledge in Strategic Alliances: Resource and Relational Characteristics, The Journal of High Technology Management Research, 13(2), 2002, pp [20] Oliver, C. Determinants of Interorganizational Relationships: Integration and Future Directions, Academy of Management Review, 15, 1990, pp [21] Oliver, C. Strategic Responses to Institutional Processes, Academy of Management Review, 16, 1991, pp [22] Osborn, R. N. & Baughn, C. C. Forms of Interorganizational Governance for Multinational Alliances, The Academy of Management Journal, 33(3), September 1990, pp

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