Does power sharing matter? The role of power and influence in alliance performance

Journal of Business Research 59 (2006) 811 – 819

Does power sharing matter? The role of power and influence in alliance performance Senthil Kumar Muthusamy a,⁎, Margaret A. White b,1 a

Department of Management, College of Business Administration, Bowling Green State University, Bowling Green, OH 43403, United States b Department of Management, College of Business Administration, Oklahoma State University, Stillwater, OK 74078, United States Received 31 July 2004; accepted 3 January 2006

Abstract Although several scholars have emphasized that a balance in power and control between partners enhances alliance stability, the extant studies have not explicitly addressed the performance implications of relational influence between partners. Drawing on social exchange theory, we examined the effect of mutual influence between partners on perceived alliance performance. An empirical examination of data collected from the alliance managers of 179 strategic alliances revealed that mutual influence between partners is positively related to perceived alliance performance. We also found that the relationship between mutual influence and perceived alliance performance is relatively more salient in international alliances than in domestic alliances. © 2006 Elsevier Inc. All rights reserved. Keywords: Alliance performance; Social exchanges; Mutual influence; Equity control

1. Introduction Strategic alliances are enduring interfirm cooperative agreements or linkages created by two or more autonomous organizations for sharing equity, resources, know-how, expertise or technology to accomplish mutually beneficial objectives (Parkhe, 1993; Yoshino and Rangan, 1995). The formation of strategic alliances is considered a significant strategy for achieving global competitiveness in many industries (Gulati et al., 2000). While alliances are becoming an attractive strategic option, many strategic alliances have been reported to be unstable and poorly performing (Ariño and Doz, 2000). The instability and high failure rate of alliances has kindled new streams of research on the role of various governance, management control and relational aspects in enhancing alliance performance and stability. For example, the significance of whether one partner dominant equity control or equally shared equity control for alliance governance has been a matter ⁎ Corresponding author. Tel.: +1 419 372 8649; fax: +1 419 372 6057. E-mail addresses: [email protected] (S.K. Muthusamy), [email protected] (M.A. White). 1 Tel.: +1 405 744 5064; fax: +1 405 744 5180. 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2006.01.018

of contention among alliance researchers (Killing, 1983; Kogut, 1988). Similarly, the division of management control, whether one partner dominates or management control is shared between partners, has been another subject of much investigation (Choi and Beamish, 2004; MjÖen and Tallman, 1997). Moreover, the relational approaches to alliance coordination and governance are considered imperative for alliance performance by several scholars (Ring and Van de Ven, 1994; Zaheer et al., 1998). The extant studies that advocate a balance in equity and management control between partners, however, have not explicitly addressed the role of relational influence between partners that underlies pooling resources and sharing control. In this article, we argue that mutual influence manifests as forbearance and power sharing, and may be more effective than ownership or formal management controls (Steensma and Lyles, 2000). We extend the social exchange perspective to examine the effect of mutual influence between partners on perceived alliance performance. We specifically argue that the relational influence between partners is a tangible social norm and it not only supplements trust in collaboration (Provan and GassenHeimer, 1994), but also facilitates conflict resolution and joint decision-making (Steensma and Lyles, 2000). In addition to providing support to the view that emphasizes a

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alliance, expertise, technology, knowledge or proximity to the customer, and argued that bargaining power enables partner to gain management control in the alliance. Power-based control, however, has several limitations. Power-based control is an ineffective mechanism for managing an alliance where often the other party cannot be made to yield, because alliances often involve exchange of resources that are critical to each partner (Nord, 1980; Provan and GassenHeimer, 1994). It has been acknowledged that power-centered control is not effective in leveraging the partners' skills, expertise or tacit knowledge that are socially and organizationally embedded (Inkpen and Beamish, 1997). Some scholars have also argued that partners may have to supply the necessary resources to others in exchange for return of resources upon which they are dependent (Blau, 1964). If one partner applies power to gain advantage at the cost of other's interests, the other party may resort to concealing critical information, shielding or defending its position (Frazier et al., 1989), and this may escalate the costs of negotiation (Williamson, 1991) and impede knowledge sharing. From a transaction cost economics view, however, a partner's relative power and control in an alliance is considered significant for enhancing commitment and minimizing other party's opportunistic behavior (Killing, 1983; Pisano, 1989). A stream of research has examined the role of relative control or balance of power that arises from the extent of equity invested in alliance (Blodgett, 1992; Geringer and Hebert, 1989; Killing, 1983; MjÖen and Tallman, 1997). While some studies support the argument that dominant control of one partner is better for alliance performance (Killing, 1983), several studies have emphasized the need for balance in equity share between partners to enhance alliance performance. For example, using event history analysis, Blodgett (1992) found that joint ventures tend to be unstable if partners start out with uneven shares of equity. Similarly, Dhanaraj and Beamish (2004) examined the extent of equity ownership shared by Japanese firms in their international joint ventures and found that the mortality rate of such ventures is higher when their equity commitments were lower. Some researchers raise doubts about the efficacy of equity controls and extend this argument to emphasize sharing management control between partners (Geringer and Hebert, 1989). For example, Choi and Beamish (2004) examined the

balance in management control to enhance alliance stability and performance (Choi and Beamish, 2004; Dhanaraj and Beamish, 2004), our study captures the relational influence process that underlies sharing resources and presents empirical evidence for the effectiveness of relational approach to alliance governance. Although a few pioneering studies have examined the role of relative power and mutual support in enhancing outcomes such as partner learning and alliance survival (Ariño and de la Torre, 1998; Provan and GassenHeimer, 1994), little empirical research examining the performance implications of ongoing relational influence between partners exists. In this study, drawing on dyadic social exchange framework, we argue that alliance performance is related to the extent the partners can mutually influence each other in a relational manner. As in previous studies, we define alliance performance as the alliance manager's assessment of whether the alliance is productive, profitable and contributing to sales or competitive advantage (Parkhe, 1993; Simonin, 1997). Using primary data on 179 strategic alliances, we test whether the perceived alliance performance is related to the extent of mutual influence between partners. We also examine whether this relationship is more salient in international alliances than in domestic alliances as perceived by the focal firm. The sample consisted of both equity and non-equity type alliances and each alliance encompassed one or more of the following activities: joint marketing, joint manufacturing, technology sharing, joint R&D or new product development. A conceptual model of relationships examined in the study is presented in Fig. 1. 2. Power and control in alliances: a literature review Several organizational scholars have argued that interfirm relationships often have a resemblance to political situations in which one party may exert dominance over the other to control the critical resources (Astley and Sachdeva, 1984; Pfeffer and Salanick, 1978). Power asymmetry arises due to differences in resource dependence, competencies, financial strength or size of equity holdings between partners (Frazier et al., 1989; Yan and Gray, 1994). For example, Yan and Gray (1994), in a study of US–China joint ventures (JVs), traced the sources of partners' bargaining power to factors such as strategic importance of

Mutual Influence between Partners (as perceived by focal firm)

(+)

Perceived Alliance Performance (as perceived by focal firm) (+)

International Scope of Alliances

Fig. 1. A model of relationship between alliance performance and mutual influence.

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performance implications of management control over value creation activities in Korean JVs, whether one partner has dominant control, or whether control over specific activities are split or shared between partners, and found that splitting the control is related to alliance performance. The perspectives that advocate a balance in equity and management control, however, have not addressed the role of relational social norms such as the mutual influence between partners that underlies pooling resources and managing the alliance. Regardless of the governance structure or management control, partners' ability to influence each other in a relational manner is critical to effective interaction, learning, knowledge transfer and joint decision-making (Inkpen and Beamish, 1997). Because relational influence manifests as mutual support, forbearance and power sharing, it may be more effective than ownership or formal management controls (Steensma and Lyles, 2000). The relational influence between partners acts as a tangible social norm and it not only supplements trust in collaboration (Provan and GassenHeimer, 1994), but also facilitates conflict resolution and joint decision-making (Steensma and Lyles, 2000). Moreover, it is important to recognize the limitations of formal ownership and management controls in some international alliance contexts. The regulatory controls on equity investments imposed by foreign governments, the risk and uncertainty, managerial discretions and cultural diversity of partners may limit the use of equity to achieve control or balance of power. In addition, equity does not always translate into control in many situations, especially with partners from different socio-political-cultural contexts (Lyles and Salk, 1996). Moreover, the non-equity and minority-equity alliances that are becoming increasingly prevalent in many high-tech industries for pursuing collaborative R&D, joint marketing or manufacturing pose new managerial challenges (Yoshino and Rangan, 1995). Consequently, there is a need to examine the role of ongoing relational dynamics and processes that underlie pooling of complementary resources, sharing management control or joint decision-making. 3. Hypotheses 3.1. Relationship between mutual influence and alliance performance Alliance coordination is considered a social exchange process through which interactions take place between organizations so that the comprehensiveness, accessibility and compatibility among partners are enhanced (Alter and Hage, 1993). When extending the social exchange perspective to alliance relationships, scholars stress that the development process is by no means deterministic (Ring and Van de Ven, 1994). Often unilateral choices cannot be made, because the counterpart must be continuously offered the better reward-cost trade-off in a current relationship compared to its other next-best alternatives (Thibaut and Kelley, 1969). The dyadic relationship will develop and become stronger only if both parties continue to consider it less onerous and more beneficial. Through

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repeated interactions, relationships grow, develop, deteriorate or dissolve as a consequence of an unfolding social exchange of mutually rewarding activities in which the receipt of a needed value is contingent on the supply of a favor in return (Homans, 1976; Thibaut and Kelley, 1969). From this point of view, alliance performance is determined by the quality of relationship that has to be carefully nurtured through ‘mutual give and take’ (Ring and Van de Ven, 1994). From a social exchange perspective, we define the level of mutual influence as the relative degree to which partners can influence each other's decisions about key issues in the specific alliance. Partners gain relational capability for influencing the other party by continually rewarding the other party's cooperation (Astley and Sachdeva, 1984; Blau, 1964). Unlike bargaining power or ownership control, the relational influence is social, mutual and balanced. This relational influence is often derived from the informal mechanisms and social norms that exist between alliance partners and boundary spanning managers (Das and Teng, 1998; Steensma and Lyles, 2000). By supplying tangible and intangible resources (services, technology, expertise or know-how) needed by the other party, one party can enhance its influence over the other (Subramani and Venkatraman, 2003). Through informal relations, partners may be able to exert greater influence on their counterpart and gain more decision-making power than their proportion of equity holdings would suggest (Beamish, 1993). Even if asymmetry arises from differences in dependencies, all potential power is not necessarily enacted (Provan and GassenHeimer, 1994). If the long-term interests and future gains of alliance are taken into consideration, mutual forbearance and restricted use of power may be a fundamental policy shift in managing strategic alliances (Heide and Miner, 1992). Indeed, restraint in the use of power and creating a climate of mutual influence are considered effective norms of alliance governance (Kaufmann and Dant, 1992). In addition, the use of power may inversely vary with the extent of cooperation and commitment in an exchange (Emerson, 1962; Thibaut and Kelley, 1969). If partners take into account each other's concerns, they can confidently partake in joint activities and commit additional resources. This in turn will enhance the knowledge flows and facilitate leveraging of complementary resources. Liker and Choi (2004) have elaborated how Honda is benefiting enormously from its supplier–partners by listening to their ideas, by demonstrating genuine empathy for the partners' problems, by practicing fairness in target pricing and by consulting with partners for setting performance standards. The relative influence a partner carries in a relationship exerts a strong influence on how it views its contributions as well as outcomes. Mutual influence broadens the repertoire of resources and joint activities, and thus facilitates interfirm learning and knowledge transfer. In sum, the mutual influence between partners serves as an effective and tangible norm of alliance governance and thus enhances the efficiency of collaboration. Hypothesis 1. In an alliance relationship, the mutual influence between partners is positively related to perceived alliance performance.

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3.2. Role of mutual influence between partners in international alliances International alliances are becoming an essential feature of many corporations' overall strategy and structure. Nevertheless, international alliances are, in general, more complex and uncertain than domestic alliances. In addition to cultural and linguistic barriers, international alliances may face difficulties due to tariffs, transportation costs, political risks of expropriation and blocking of profit repatriation from foreign markets. Because of the inherent complexities that plague international alliances, partners need to go beyond formal contracts and equity controls to build quality relationships with foreign partners. Moreover, high partner interdependence is a distinctive feature of international alliances. In international alliances, partners become equally interdependent on each other irrespective of the differences in size or technological strength because a partner is likely to possess more information and knowledge about its respective domestic country/market domains than the party from another country. Because of the inherent information asymmetry in international alliances, it is logical to contend that relational influence between partners is very significant in managing the alliance. In situations of high degree of interdependency and information asymmetry, partners should be able to influence each other in a relational manner to tap into each other's resources or expertise (Zaheer and Venkatraman, 1995). In addition, the relational influence partners have on each other reduces conflicts that arise due to socio-culturalpolitical differences between partners and reduces the perception of risk and uncertainty in international alliances (Steensma and Lyles, 2000; Parkhe, 1991). Because of the scope and complexity, and the extent of boundary spanning required to accomplish alliance objectives, we argue that the value and effectiveness of mutual influence between partners may be relatively ‘more salient’ in an international alliance than in a domestic alliance. Hypothesis 2. The positive link between mutual influence and perceived alliance performance is relatively stronger in an international alliance than in a domestic alliance. 4. Research method

allow us to study alliances that had passed the initial phases of alliance building and had been operating for at least 1 year so that we can capture the post-formation interactions effectively. The initial search and identification of target firms and key informants was conducted using ‘LEXIS-NEXIS’ database, Predicast's PROMT business and industry Internet database, Edgar online, F&S index of corporate change and other sources such as journals, industry reports, company annual reports and web page of companies or industry consortiums. Because the business press occasionally refers to mergers, routine buy–sell agreements and subsidiaries as alliances, we used strict criteria to screen and select the sample for this study. Following Parkhe (1993) and Yoshino and Rangan (1995), an alliance was included in the sample only if the business news, corporate reports, company websites or communications to investors disclosed that the particular alliance had become operational and partners exchanged one or more of the following: equity, financial or human resources, expertise, facilities or technology. Consistent with the recommendations to make use of most knowledgeable respondents (Bagozzi and Phillips, 1982), a self-report questionnaire was sent to a key informant in each alliance. These informants were identified from the news reports, Internet business guides, PR Newswire, Edgar online financial database, alliance databases such as Recombinant Capital (www.recap.com), company web pages and Standard and Poor's Register of Corporations, Directors and Executives. The key informants ranged from CEOs, vice presidents of alliances, vice presidents of marketing/business development, chief technology officers, through R&D directors associated with alliances. This study proceeded in two phases. In the first phase, we mailed 610 questionnaires targeting the US firm in each alliance dyad. We collected 156 responses (focal firms). In the second phase, we mailed 250 questionnaires, of which 150 questionnaires were sent to partners of focal firms that responded in the first phase, and 100 questionnaires specifically targeted foreign partners. Following Dillman's (1978) recommendations, we took several steps to increase the response rate: (1) we sent letters or emails, and made phone calls before mailing the first wave of surveys; (2) we mailed the first wave with a detailed letter requesting participation; (3) we mailed the second wave of survey with a reminder letter to all nonrespondents; and (4) we made follow-up phone calls or sent email reminders.

4.1. Data collection 4.2. Respondents Our study targeted strategic alliances formed by publicly owned US businesses (with both domestic as well as foreign partners) between 1994 and 1998. We focused on the following industrial groups: biotech and pharmaceutical (U.S. Standard Industrial Classification [SIC] code 283), computers and office equipment (SIC 357), software (SIC 737), electronics components (SIC 367) and telecommunication (481). Since it was not practical to draw a random sample from a wider population of alliances, we selected firms using a convenience sampling approach. These industries formed the target group, because alliances were most prolific in these industries (Harrigan, 1986). We believe the time-frame used for selecting the alliances would

Of the 610 questionnaires mailed in the first phase, we received 156 responses, of which 144 were usable. Of the 250 questionnaires mailed in the second phase, we received 105 responses, of which 79 were usable. Out of 79, the 44 responses that came from partners of focal firms were not included in the sample nor aggregated with responses of focal firms. We used this data only to test the reliability and validity. However, we included the 35 additional responses (out of 79) that came from other non-US firms, because these represented distinct alliances. Out of 860 firms targeted totally, 223 usable responses (25.93%) were received. A total of 179 usable

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responses (144 + 35) assessing distinct alliances formed the final sample. We tested for non-response bias by comparing the respondent firms' (N = 223) demographic characteristics with those of non-respondents and those returned unusable responses (N = 637). One-way between-groups analysis of variance (ANOVA) of employees, sales and assets suggested that differences were statistically non-significant (for number of employees: F = 1.43, p = 0.23; for sales: F = 1.93, p = 0.17; and for assets: F = 0.55, p = 0.48). Therefore, the responding firms did not structurally differ from the non-responding firms in terms of sales, assets and number of employees. Based on the reporting of 179 firms, 96 (53.6%) were of non-equity type alliances, 46 (25.7%) were of minority-equity alliances and 37 (20.7%) were joint ventures; 95 were domestic partnerships and 84 were international in scope. The number of employees in the firms that responded to survey ranged from 5 to 85,400 and their total sales revenues ranged from $0.58 million to $25.30 billions. 4.3. Measurement instrument This study adapted multi-item measures from the extant alliance research in the fields of management and marketing. Face validity of the constructs was assessed by two business school professors familiar with research in alliances. Scales were pilot tested with 20 senior executives of defense equipment manufacturing firms involved in developing a collaborative consortium in Oklahoma. These executives were directly involved in boundary spanning activities related to building the consortium and had a strong understanding of the significance of relational processes among members in the alliance. Many of the executives had experience in high-tech industries such as electronics and telecommunication, and often consulted with professors pursuing research on alliances. Their insights provided valuable inputs for improving the items. We also conducted in-depth pretest interviews with two senior alliance executives of pharmaceutical firms to refine the items. 4.3.1. Perceived alliance performance Although quantitative financial indicators can be used to measure performance, it is difficult to track and separate the benefits of alliance quantitatively (Gulati, 1998; Kumar et al., 1993). As alliances are often formed between strategic business units (SBUs) or divisions of large corporations, the corporate level financial and market indicators may not reflect the benefits of alliance only. Many alliances are aimed at accomplishing multiple objectives and financial indicators may be less effective in capturing the long-term benefits that accrue to alliance partners (Gulati, 1998). In addition, individual partner's performance and general economic conditions may be reflected in the financial measures (Kumar et al., 1993). Therefore, we measured the performance of alliance from the perspective of focal firms using a generic measure that captured the strategic benefits of the specific alliance. Such a generic measure has been used in several interorganizational studies. Some scholars have suggested that alliance performance can be judged by the extent the relationship is productive, worthwhile or equitable

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(Van de Ven and Walker, 1984; Heide and Miner, 1992). Alliance performance is also captured by the extent it is perceived to contributing for profits, market share or competitive advantage (Harrigan, 1986; Parkhe, 1993; Simonin, 1997). Following the above conceptualizations, we developed a fiveitem measure of seven-point scales ranging from ‘strongly disagree’ to ‘strongly agree’. Two items captured whether the focal firm's relationship with the partner has been productive and worthwhile. The third item captured whether the benefits and returns from the alliance have been fair, and two more items captured whether the alliance has contributed to profits, market share or competitive advantage. The reliability coefficient alpha (Cronbach's α) for this measure was 0.88. 4.3.2. Mutual influence Following the extant research on interfirm influence and flexibility, and joint decision-making (Heide and Miner, 1992; Gaski, 1984; Provan and GassenHeimer, 1994; Zaheer and Venkatraman, 1995), two items were developed to measure the relative extent partners have equal influence on each other in alliance management and the extent of mutual influence between alliance partners in business transactions. The first item captured whether the focal firm and the partner have equal say in all the alliance transactions, and the second item captured whether focal firm and partner can mutually influence each other in making decisions related to the specific alliance. The reliability coefficient alpha (Cronbach's α) for this measure was 0.84. 4.3.3. Control variables The following control variables were included in the analysis: respondent industry, firm size (number of employees), previous experience with partner, alliance age, alliance type (non-equity/minority/JV), international scope, non-US respondents and interfirm trust. To control for industry effects we included four dummy variables to represent five industry groups in the sample. We controlled for firm size because large firms may possess slack resources to manage the boundary spanning activities more effectively than small firms. We controlled for prior business experience between partners because it enables the partners to interact smoothly (Gulati, 1995). A dummy variable was coded “1” if the respondent had past experience with the specific partner and coded “0” otherwise. We controlled for alliance age, because collaborative learning and efficiency may increase as alliance progresses (Simonin, 1997). At the time of data collection, age of alliances in the sample ranged from 2 to 6 years. We controlled for alliance type, because of the possible high integration achieved through equity exchanges. Following the generic classification (Das and Teng, 1998), ‘alliance type’ was coded “1” for non-equity type alliances, “2” for minority-equity alliances and “3” for joint ventures. Joint ventures are independently incorporated entities that are separated from, but jointly run by, parent firms. Minority equity alliances involve one party taking an equity stake in its partner (or equity swap), but do not involve creation of any separate business entity. Non-equity alliances are contractual agreements without any equity arrangements. To

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control variables previous experience, alliance age and alliance type (equity/JV). Alliance performance as perceived by the partner was positively related to ‘mutual influence’ (β = 0.34, p < 0.05) and ‘previous experience between partners’ (β = 0.23, p < 0.10), thus supporting the results of the study. A principal components factor analysis with varimax rotation of all measurement items revealed the items loaded on to their respective constructs without cross loadings (eigenvalues > 1 and factor loadings of 0.50 or higher). The factor structure supported the convergent and discriminant validity of the constructs. The factor analyses and Cronbach's α statistics (Nunnally and Bernstein, 1994) revealed that all variables were unidimensional and reliable. Although data for this study came from knowledgeable respondents, the study did not address the potential problems of common method variance and social desirability bias (Podsakoff and Organ, 1981). The Harman's single-factor test (Harman, 1967), a post hoc test, revealed that neither a single nor a general factor emerged, suggesting that any systematic variance common to the measures was not found.

account for any performance differences due to international scope of the alliance, a dummy variable was coded “1” if the alliance involved international partnership and coded “0” otherwise. An alliance was classified as international in scope if the headquarters or collaborating divisions of the partners were located in two different countries. We also controlled for the responses from non-US firms because the international respondents may differ from US firms in their evaluation of the quality of relationship as well as alliance effectiveness. The non-US responses primarily came from UK, Germany, India, Singapore, China and Malaysia. Our study also controlled for interfirm trust using a comprehensive 17-item measure of respondent's perception of partner's trustworthiness. Adapted from the extant research (Mayer and Davis, 1998), the measure of trust captured three dimensions of partner trustworthiness: ability, benevolence and integrity. 4.3.4. Reliability and validity We assessed the reliability of data by comparing the respondent information and corresponding secondary data on alliance type and scope, task characteristics, equity arrangements and firm characteristics. There was a high degree of agreement between both sources of data and correlation coefficients ranged from 0.74 to 1.00. With objective data for JV sub-sample (n = 37), we assessed the validity of survey measure of alliance performance by comparing it with objective measures such as sales per asset and return on assets (average of 2 years 1999 and 2000). The correlation between perceived alliance performance and sales per asset was 0.52 (p < 0.001), and the correlation between perceived alliance performance and return on assets (ROA) was 0.47 (p < 0.01). These correlations suggest the survey measure of alliance performance captured the important dimensions related to the financial outcomes of the alliance. We examined the correlations between the responses of the focal firms and their respective partners (n = 44). These correlations were significant and ranged from 0.58 to 1.00. We also assessed the validity by cross-regressing the ‘alliance performance as perceived by the partner’ (n = 44) with respective focal firms' responses for mutual influence, and

5. Analyses and results Table 1 shows the means, standard deviations and correlations among all variables. Correlation analysis revealed that the correlation between perceived alliance performance and mutual influence was significant (with p < 0.01). Table 2 summarizes the results of regression analyses with standardized regression coefficients. Tests for multicollinearity revealed that variance inflation factors (VIF) were well below the 10 cutoff for all the variables. Model 1 presents the results of a base regression model with all the control variables. Model 2 presents the results of regression with the main predictor variable ‘mutual influence’ in addition to control variables. Model 3 presents the results of a moderated regression analysis with an interaction term in addition to the predictor and control variables. Hypothesis 1 predicted that mutual influence between partners would be positively related to perceived alliance performance. Models 2 and 3 tested this relationship and were

Table 1 Descriptive statistics and correlations Variables

Mean

S.D.

1

2

3

4

5

6

7

1. Perceived alliance performance 4.56 1.29 1.00 2. Mutual influence 4.69 1.24 0.47 1.00 3. Interfirm trust 4.27 1.22 0.50 0.20 1.00 4. Previous experience with partner 0.33 0.47 0.35 0.12 0.24 1.00 5. Alliance age 3.05 1.06 0.07 0.11 0.13 0.01 1.00 6. Alliance (non-equity/minority/JV) 1.67 0.80 0.44 0.10 0.15 0.21 0.06 1.00 7. International alliance 0.47 0.50 0.39 0.08 0.14 0.10 0.14 0.32 1.00 8. Computers and office equipment 0.17 0.37 0.12 0.09 0.03 −0.06 0.02 0.12 0.08 9. Software 0.26 0.43 −0.06 0.01 0.00 −0.19 −0.01 − 0.06 0.06 10. Electronics 0.16 0.37 0.04 −0.06 0.04 0.07 0.06 − 0.07 0.05 11. Telecommunication 0.16 0.36 −0.01 −0.03 −0.06 0.01 −0.04 − 0.10 − 0.11 12. Respondent firm size (employees) 3901 10,363 0.16 0.08 0.12 0.23 0.08 0.30 0.15 13. Non-US respondents 0.19 0.39 0.09 −0.01 −0.05 −0.06 0.03 0.12 0.52 a

Means, standard deviations and correlations are based on N = 179. All correlations above r ≥ 0.15 are significant at p < 0.05 (two-tailed test).

b

8

9

10

11

12

1.00 − 0.26 1.00 − 0.20 − 0.23 1.00 − 0.19 − 0.26 − 0.19 1.00 − 0.05 0.01 − 0.11 0.11 1.00 0.23 0.07 0.12 − 0.14 − 0.14

S.K. Muthusamy, M.A. White / Journal of Business Research 59 (2006) 811–819 Table 2 Results of regression analysis of perceived alliance performance Variables

Control variables Computers and office equipments Software Electronics Telecommunication Respondent firm size (employees) Previous experience with partner Alliance age Alliance type (non-equity/minority/JV) International alliance Non-US respondents Interfirm trust Predictors Mutual influence Mutual influence ⁎ international R2 Adjusted R2 ΔR2 Model F

6. Discussion

Model 1

Model 2

Model 3

β

β

β

0.13 0.08 0.10 0.03 − 0.03 0.24 ⁎⁎ 0.01 0.18 ⁎ 0.23 ⁎⁎ − 0.06 0.37 ⁎⁎⁎

0.10 0.05 0.10 0.03 − 0.04 0.23 ⁎⁎ 0.02 0.16 ⁎ 0.25 ⁎⁎ − 0.06 0.33 ⁎⁎⁎

0.08 0.06 0.10 0.03 −0.04 0.21 ⁎⁎ 0.01 0.16 ⁎ 0.28 ⁎⁎ −0.07 0.31 ⁎⁎⁎

0.37 ⁎⁎⁎

0.29 ⁎⁎⁎ 0.15 ⁎ 0.63 0.60 0.02 ⁎ 21.60 ⁎⁎⁎

0.48 0.45 14.48 ⁎⁎⁎

0.61 0.58 0.13 ⁎⁎ 22.26 ⁎⁎⁎

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Table reports standardized β coefficients; sample size N = 179. All significance levels are based on two-tailed tests. ⁎ p < 0.05. ⁎⁎ p < 0.01. ⁎⁎⁎ p < 0.001.

significant (Model 2: F = 22.26, adj. R2 = 0.58, p < 0.001; Model 3: F = 21.60, adj. R2 = 0.60, p < 0.001). In addition, ‘mutual influence’ had a significant positive relationship with perceived alliance performance in both models (Model 2: β = 0.37, p < 0.001; Model 3: β = 0.29, p < 0.001). The change in R2 statistics indicates that there was significant improvement in the variance when the predictor was entered in the regression. Model 3 included the proposed moderator in the regression in addition to predictor and control variables. Hypothesis 2 predicted that the link between mutual influence and perceived alliance performance would be relatively stronger in international alliances than in domestic alliances. Results of Model 3 suggest that relationship between mutual influence and perceived alliance performance is stronger in international alliances (with β = 0.15, p < 0.05), lending support for Hypothesis 2. Although Model 3 results revealed only a marginal increase in R2 due to the interaction effect of international dimension, we have to view this result in light of the fact that relational influence is significant in both domestic and international alliance contexts. Given that interdependence is a characteristic feature of most alliances, whether domestic or international, and because our study controlled for both the formal and relational governance factors that explained substantial variance in perceived alliance performance, the modest increase in variance due to interaction effect is satisfactory. Results of Models 1 to 3 suggest that, in addition to predictors, the control variables previous experience between partners, alliance-type (non-equity/minority/JV), interfirm trust and international scope of the alliance were positively related to perceived alliance performance.

This study makes a significant contribution to the understanding of the role of relational exchanges in the performance of strategic alliances. Consistent with the recommendations of several organizational theorists to study behavioral and process issues in firms' strategies and outcomes (Cyert and James, 1963), our study examined the role of relational processes in enhancing interfirm collaborative capabilities. We integrally examined the role of ongoing mutual influence between partners in the post-formation phase of the alliance taking into account other relational exchanges and governance mechanisms. The overall support for the relationship between mutual influence and perceived alliance performance is encouraging given that this study specifically controlled for various alternative explanations of alliance performance such as equity control, alliance age, trust and previous experience between partners. Our study clearly distinguishes the formal and relational forms of governance such as equity control, trust and relational influence between partners and helps us understand their role in alliance management. By capturing the relational influence that underlies sharing resources, our study presents empirical evidence for the effectiveness of relational approach to alliance governance. Because interfirm trust is affected by industry uncertainty and cultural differences, we argued that mutual influence could serve as tangible relational norm of alliance governance. Moreover, it is important to point out the deficiencies of equity controls. Equity control has little weight in transacting vital knowledge embedded in organizational and operational domains of the partners. Although alliance managers may be inclined to exert control over the partner consistent with their equity proportions/contributions, it is highly likely that their counterparts may rebuff such control, especially in foreign operations (Steensma and Lyles, 2000). In many alliances, power balance between partners may also shift due to changes in strategy, performance and management orientation of individual firms; and these changes may render the equity control ineffective. An alliance consultant narrates one such incident where a U.S. company shared its technology with a foreign company: “In the beginning, the equity stake served as a security blanket; the U.S. company was able to exercise some control over the foreign company's strategic direction. A vexing problem developed, however, after a cash crunch forced the U.S. company to sell its equity stake in the foreign company”. (Myers, 1995, p. 31) Managers, however, can gain influence by taking into consideration partner's concerns in their decision process and providing resources in the form of technical support or managerial expertise (MjÖen and Tallman, 1997). Such a relational approach to influence is considered an effective strategy for managing even asymmetric and vertical interfirm relationships (Subramani and Venkatraman, 2003). For example, during the course of survey interviews, one executive from a telecommunication equipment firm pointed out that relational

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power sharing is fundamental to leveraging the skills, expertise and technologies to and from their partners in an alliance. Further, an Executive Director of strategic alliances in a large pharmaceutical company stated, “although our company performs a thorough and careful analysis of partner's skills, assets and other resources during the partner selection for each alliance we enter into, the success of an alliance is very much shaped by the relational chemistry between managers rather than legal contracts or equity stake”. Although our proposition is akin to the point of view that emphasizes balance in power or sharing management control between partners, the notion of mutual influence in our study is drawn from a relational approach to alliance management. Our view is that regardless of the governance structure/mechanism, partners' ability to influence each other in a relational manner is critical to achieving alliance objectives. This study also analyzed how the link between mutual influence and alliance performance becomes more salient in international alliances. We examined the strength of association between mutual influence and perceived alliance performance in international alliances. Since international alliances are complex and uncertain, and demand intense boundary spanning to exchange resources across national boundaries, relational influence between partners is a necessary collaborative process to accomplish objectives. Consistent with the suggestions of several organizational scholars, we argued that mutual influence is an essential relational norm for managing international alliances. Findings of this study support our argument that in contexts involving high interdependence and uncertainty, relational influence becomes more salient. 7. Limitations and future directions There are some theoretical and empirical limitations to this study. First, this study assumes a high degree of autonomy and discretion exists for managers, and neglects the fact that relational norms are influenced by the societal, economical, cultural and institutional contexts in which managerial actions are embedded, and these forces determine the cooperative behavior of firms. Although a few studies have explored these issues (Luo, 2002), there is an opportunity to systematically examine whether any contextual and structural factors determine the nature of relational norms. Specifically, examining the role of organizational and national culture in shaping the relational exchanges will be an interesting research direction. Second, this study does not address the role of socialization and communication between partners that might facilitate relational exchanges. Empirically, this study conjectures that there are clear-cut causal and temporal linkages between the relational influence process and alliance outcomes, even though this research is a cross-sectional examination. Certainly, a longitudinal examination to capture the dynamics of ongoing interaction and alliance outcomes would be a most appropriate way to test and confirm the hypotheses of the study. Another important extension would be to consider the perspectives of both alliance partners with regard to mutual influence and alliance performance.

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