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Original Articles

Strategic Alliance Networks and Innovation: A Deterministic and Voluntaristic View Combined

, &
Pages 227-249 | Published online: 09 Mar 2011
 

Abstract

Over the past decades we have witnessed a tremendous growth in the number of strategic technology alliances and a growing importance of interfirm collaboration in the high-tech sectors. The literature on these topics has grown accordingly. In this respect, our paper serves two aims. One is to provide an overview of the consensus on key issues in this vast body of literature. Second is to identify some major gaps in this literature that may inform future research. In serving these aims, we first discuss the dominant structuralist perspective that stresses the role of embeddedness, but which also reflects a deterministic stance as if firms are subject to an exogenous structure. In contrast, we also explore a more voluntaristic view of how firms may possibly shape their network in view of achieving their strategic aims. This view also seems better able to capture change and network dynamics, an issue that has been largely ignored by the structuralist view.

Notes

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3. For a more elaborate overview, see e.g. Hagedoorn, op. cit., Ref. 2.

4. See e.g. G. M. Duysters & J. Hagedoorn, Core competences and company performance in the worldwide computer industry, Journal of High Technology Management Research, 11, 2000, pp. 75–91.

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11. Gulati (1995), op. cit., Ref. 10; Gulati & Gargiulo, op. cit., Ref. 10.

12. For example M. Granovetter, Problems of explanation in economic sociology, in: N. Nohria & Robert G. Eccles (Eds) Networks and Organizations: Structure, Form and Action (Boston, MA, Harvard Business School Press, 1992), pp. 25–56; Gulati (1998), op. cit., Ref. 10.

13. Powell et al., op. cit., Ref. 9.

14. Hagedoorn, op. cit., Ref. 2.

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16. T. E. Stuart, Network positions and propensities to collaborate: an investigation of strategic alliance formation in a high-technology industry, Administrative Science Quarterly, 43, 1998, pp. 668–698.

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18. Burt (1992).

19. Coleman, op. cit., Ref. 17.

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22. Ahuja (2000).

23. Walker et al., op. cit., Ref. 9.

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25. Rowley et al., op. cit., Ref. 2; G. M. Duysters & J. Hagedoorn, Learning in dynamic inter-firm networks—the efficacy of multiple contacts, Organization Studies, 23, 2002, pp. 525–548.

26. R. Burt, The network structure of social capital, Paper presented at the ‘Social Network and Social Capital Conference’, Duke University, Durham, NC, 1998; Ahuja, op. cit., Ref. 2; Rowley et al., op. cit., Ref. 2.

27. Here we differentiate between the meaning of hypothesis vs proposition. A hypothesis suggests a causal logic that requires the use of measures in view of empirical testing. A proposition involves concepts and does not necessarily imply/suggest empirical testing (D. A. Whetten, What constitutes a theoretical contribution?, Academy of Management Review, 14, 1989, pp. 490–495). Therefore, we prefer to use ‘proposition’ as it reflects the conceptual nature of this paper and in this way serves as an indicative direction for future research.

28. B. Gomes-Casseres, The Alliance Revolution: The New Shape of Business Rivalry (Cambridge, MA, Harvard University Press, 1996); Y. L. Doz & G. Hamel, Alliance Advantage, The Art of Creating Value through Partnering (Cambridge, MA, Harvard Business School Press, 1998).

29. G. M. Duysters & C. E. A. V. Lemmens, Alliance group formation: enabling and constraining effects of embeddedness and social capital in strategic technology alliance networks, International Studies of Management and Organization, 33, 2003, pp. 49–68.

30. Gulati (1995), op. cit., Ref. 10.

31. D. R. Gnyawali & R. Madhavan, Cooperative networks and competitive dynamics: a structural embeddedness perspective, Academy of Management Review, 26, 2001, pp. 431–445.

32. J. C. Baum, T. Calabrese & B. S. Silverman, Don't go it alone: alliance network composition and start-ups performance in Canadian biotechnology, Strategic Management Journal, 21, 2000, pp. 267–294.

33. Gomes-Casseres, op. cit., Ref. 28; Gnyawali & Madhavan, op. cit., Ref. 31.

34. Gomes-Casseres, op. cit., Ref. 28; R. M. Guidice, A. Vasudevan & G. M. Duysters, From ‘me against you’ to ‘us against them’: alliance formation based on inter-alliance rivalry, Scandinavian Journal of Management, 19, 2003, pp. 135–152.

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36. Gomes-Casseres, op. cit., Ref. 28.

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38. Gomes-Casseres, op. cit., Ref. 28; Das & Teng, op. cit., Ref. 35.

39. Gomes-Casseres, op. cit., Ref. 28.

40. Ibid.; Duysters & Lemmens, op. cit., Ref. 29.

41. Hagedoorn, op. cit., Ref. 2.

42. Gulati (1995, 1998), op. cit., Ref. 10.

43. Baum et al., op. cit., Ref. 32.

44. Ibid.

45. Ibid.

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47. Gomes-Casseres (2001), op. cit., Ref. 46.

48. Baum et al., op. cit., Ref. 32.

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50. Ahuja, op. cit., Ref. 2.

51. Baum et al., op. cit., Ref. 32.

52. Stuart, op. cit., Ref. 16.

53. B. Uzzi, The sources and consequences of embeddedness, for the economic performance of organizations: the network effects, American Sociological Review, 61, 1996, pp. 674–698.

54. Duysters & Hagedoorn, op. cit., Ref. 25.

55. A. Zaheer & G. G. Bell, Benefiting from network position: firm capabilities, structural holes, and performance, Strategic Management Journal, 26, 2005, pp. 809–825.

56. Stuart, op. cit., Ref. 16.

57. Rowley et al., op. cit., Ref. 2.

58. S. Wuyts, M. G. Colombo, S. Dutta & B. Nooteboom, Empirical test of optimal cognitive distance, Journal of Economic Behaviour and Organization, 28, 2005, pp. 277–302.

59. Ahuja, op. cit., Ref. 2.

60. Ibid.

61. Ibid.; Baum et al., op. cit., Ref. 32; McEvily & Zaheer, op. cit., Ref. 21.

62. W. W. Powell, Neither market nor hierarchy: network forms of organization, Research in Organizational Behavior, 12, 1990, pp. 295–336; Gulati & Gargiulo, op. cit., Ref. 10.

63. Gulati (1995, 1998), op. cit., Ref. 10.

64. Chung et al., op. cit., Ref. 10.

65. N. Lin, Building a network theory of social capital, Connections, 22, 1999, pp. 28–51.

66. Walker et al., op. cit., Ref. 9; Gulati (1995), op. cit., Ref. 10; Powell et al., op. cit., Ref. 9.

67. S. Berg, J. Duncan & P. Friedman, Joint Venture Strategies and Corporate Innovation (Cambridge, MA, Oelgeschlager, Gunn and Hain, 1982).

68. Ahuja, op. cit., Ref. 2.

69. C. Freeman, Networks of innovators, a synthesis of research issues, Research Policy, 20, 1991, pp. 499–514.

70. D. Leonard-Barton, Wellsprings of Knowledge (Boston, MA, Harvard Business School Press, 1995).

71. J. Owen-Smith & W.W. Powell, Knowledge networks as channels and conduits: the effects of spillovers in the Boston biotechnology community, Organization Science, 15, 2004, pp. 5–21.

72. Gulati (1998), op. cit., Ref. 10.

73. Ibid.; R. Madhavan, B. R. Koka & J. E. Prescott, Networks in transition: how industry events (re)shape interfirm relationships, Strategic Management Journal, 19, 1998, pp. 439–459; B. R. Koka, R. Madhavan & J. E. Prescott, The evolution of interfirm networks: environmental effects on patterns of network change, Academy of Management Review, 30(4), 2005, pp. 721–737.

74. March, op. cit., Ref. 49

75. D. Teece, Profiting from technological innovation: implications for integration, collaboration, licensing and public policy, Research Policy, 15, 1986, pp. 285–305.

76. M. T. Hansen, J. M. Podolny & J. Pfeffer, So many ties, so little time: a task contingency perspective on corporate social capital, in: S. M. Gabbay, R. T. A. J. Leenders (Eds) Research in the Sociology of Organizations, Vol. 18 (Amsterdam, Elsevier Science, 2001), pp. 21–57.

77. V. A. Gilsing, The Dynamics of Strategic Alliances, Exploration, Exploitation and Co-evolution (Cheltenham, Edward Elgar, 2005).

78. March, op. cit., Ref. 49; B. Nooteboom, Learning and Innovation in Organizations and Economies (Oxford, Oxford University Press, 2000).

79. Rowley et al., op. cit., Ref. 2; Nooteboom, op. cit., Ref. 78.

80. The distinction between exploration and exploitation is related to the distinction between first and second order learning [G. Bateson, Steps to an Ecology of Mind (London, Paladin Book, 1972)], and between single and double loop learning [C. Argyris & D. A. Schon, Organizational Learning (Reading, MA, Addison-Wesley, 1978)].

81. J. Hagedoorn, A. Link & N. Vonartas, Research partnerships, Research Policy, 29, 2000, pp. 567–586; C. Phelps, Technological exploration: a longitudinal study of the role of recombinatory search and social capital in alliance networks, Working Paper, University of Washington, June 2005.

82. J. A. Schumpeter, Business Cycles: A Theoretical, Historical and Statistical Analysis of the Capitalist Process (New York and London, McGraw Hill, 1939).

83. Burt, op. cit., Ref. 17.

84. Ahuja, op. cit., Ref. 2; Rowley et al., op. cit., Ref. 2.

85. W. M. Cohen & D. A. Levinthal, Absorptive capacity: a new perspective on learning and innovation, Administrative Science Quarterly, 35, 1990, pp. 128–152.

86. Hansen et al., op. cit., Ref. 76.

87. Duysters & Hagedoorn, op. cit., Ref. 25.

88. Coleman, op. cit., Ref. 17.

89. Ahuja, op. cit., Ref. 2; Rowley et al., op. cit., Ref. 2.

90. Indirect empirical evidence for this position is found in B. E. Beerkens, External acquisition of technology, exploration and exploitation in international innovation networks, ECIS PhD-thesis, Eindhoven University Press, Eindhoven, 2004: past involvement in alliances, indicative for strong ties in terms of durability is positively associated with exploration, whereas over the same period, also evidence is found for the weak tie argument for exploration.

91. W. J. Abernathy & J. M. Utterback, Patterns of industrial innovation, Technology Review, 81, 1978, pp. 41–47.

92. F. Malerba & S. Breschi, Sectoral innovation systems: technological regimes, Schumpetarian dynamics and spatial boundaries, in: C. Edquist (Ed.) Systems of Innovation, Technologies, Institutions and Organizations (London, Pinter, 1997).

93. Gilsing, op. cit., Ref. 77.

94. Uzzi, op. cit., Ref. 2; Nooteboom, op. cit., Ref. 78.

95. S. Klepper, Industry life cycles, Industrial and Corporate Change, 6, 1996, pp. 145–181.

96. Burt, op. cit., Ref. 17.

97. Gilsing, op. cit., Ref. 77.

98. Rowley et al., op. cit., Ref. 2; Beerkens, op. cit., Ref. 90.

99. Hansen et al., op. cit., Ref. 76; A. H. W. M. Roijakkers, Inter-firm cooperation in high-tech industries: a study of R&D partnerships in pharmaceutical biotechnology, PhD thesis, Datawyse/Universitaire Pers, Maastricht, 2003; V. A. Gilsing & B. Nooteboom, Density and strength of ties, an analysis of multimedia and biotechnology, European Management Journal, 2, 2005, pp. 179–197.

100. Abernathy & Utterback, op. cit., Ref. 91; W. J. Abernathy, The Productivity Dilemma: Roadblock to Innovation in the Automobile Industry (Baltimore, MD,Johns Hopkins University Press, 1978); W. J. Abernathy & K. B. Clark, Innovation: mapping the winds of creative destruction, Research Policy, 14, 1985, pp. 3–22.

101. G. Dosi, R. R. Nelson, G. Silverberg & L. Soete (Eds), Technical Change and Economic Theory (London, Pinter, 1988); G. M. Duysters, The Dynamics of Technical Innovation: The Evolution and Development of Information Technology (Cheltenham, Edward Elgar, 1996).

102. M. L. Tushman & P. Anderson, Technological discontinuities and organizational environments, Administrative Science Quarterly, 31, 1986, pp. 439–465.

103. Ibid.; Madhavan et al., op. cit., Ref. 73.

104. Madhavan et al., op. cit., Ref. 73.

105. P. J. Dimaggio & W. W. Powell, The iron cage revisited: institutional isomorphism and collective rationality in organizational fields, American Sociological Review, 48, 1983, pp. 147–160.

106. M. Granovetter, The strength of weak ties, American Journal of Sociology, 78, 1973, pp. 1360–1380.

107. Ibid.; D. J. Brass, K.D. Butterfield & B.C. Skaggs, Relationships and unethical behavior: a social network perspective, Academy of Management Review, 23, 1998, pp. 14–31.

108. Chung et al., op. cit., Ref. 10.

109. Ibid.

110. Gulati (1995, 1998), op. cit., Ref. 10; Walker et al., op. cit., Ref. 9.

111. D. Knoke & J. H. Kuklinski (Eds), Network Analysis, Series: Quantitative Applications in the Social Sciences (Beverly Hills, CA, Sage, 1982).

112. Brass et al., op. cit., Ref. 107.

113. Walker et al., op. cit., Ref. 9; Gulati (1995), op. cit., Ref. 10; Powell et al., op. cit., Ref. 9.

114. Duysters & Lemmens, op. cit., Ref. 29.

115. Uzzi, op. cit., Ref. 2.

116. For example, R. R. Nelson & S. G. Winter (Eds), An Evolutionary Theory of Economic Change (Cambridge, MA, Belknap Press, 1982); T. E. Stuart & J. M. Podolny, Local search and the evolution of technological capabilities, Strategic Management Journal, 17, 1996, pp. 21–38.

117. Stuart & Podolny, op. cit., Ref. 116; D. J. Teece, G. Pisano & A. Shuen, Dynamic capabilities and strategic management, Strategic Management Journal, 18, 1997, pp. 509–533; L. Rosenkopf & A. Nerkar, Beyond local search: boundary-spanning, exploration, and impact in the optical disk industry, Strategic Management Journal, 22, 2001, pp. 287–306; L. Rosenkopf & P. Almeida, Overcoming local search through alliances and mobility, Management Science, 49, 2003, pp. 751–776; G. Ahuja & R. Katila, Where do resources come from? The role of idiosyncratic situations, Strategic Management Journal, 25, 2004, pp. 887–907.

118. Walker et al., op. cit., Ref. 9; Rowley et al., op. cit., Ref. 2.

119. Rosenkopf & Nerkar, op. cit., Ref. 117; Ahuja & Katila, op. cit., Ref. 117. This connects with the evolutionary notion of ‘diversity’ that is considered to form a crucial condition for learning and innovation (Nelson & Winter, op. cit., Ref. 116). It refers to the heterogeneity of resources or knowledge, which yields the potential for Schumpeterian novel combinations to emerge.

120. Burt, op. cit., Ref. 17.

121. Madhavan et al., op. cit., Ref. 73.

122. N. Eldredge & S. J. Gould, Punctuated equilibria: an alternative to phyletic gradualism, in: T. J. M. Schopf (Ed.) Models in Paleobiology (San Francisco, CA, Freeman, Cooper, 1972), pp. 82–115; Nooteboom, op. cit., Ref. 78.

123. C. M. Christensen & J. L. Bower, Customer power, strategic investment and the failure of leading firms, Strategic Management Journal, 17, 1996, pp. 197–128.

124. Koka et al., op. cit., Ref. 73.

125. J. M. Podolny & T. E. Stuart, A role-based ecology of technological change, American Journal of Sociology, 5, 1995, pp. 1224–1260.

126. Burt, op. cit., Ref. 17.

127. Stuart, op. cit., Ref. 16. This is comparable to what is known as the ‘Matthew-effect’ in science, namely the idea that the work of a high-status member of the scientific community is considered more important, acting as a key guide for future research, than the work of a low(er) status member (R. K. Merton, The Matthew-effect in science, Science, 159, 1968, pp. 56–63; Podolny & Stuart, op. cit., Ref. 125; Stuart, op. cit., Ref. 16).

128. Stuart, op. cit., Ref. 16.

129. J. C. Spender, Industry Recipes (Oxford, Basil Blackwell, 1998).

130. V. A. Gilsing & B. Nooteboom, Exploration and exploitation in innovation systems, Research Policy, 1, 2006, pp. 1–22.

131. Burt, op. cit., Ref. 26; Ahuja, op. cit., Ref. 2; Rowley et al., op. cit., Ref. 2.

132. D. C. Mowery & R. R. Nelson (Eds), Sources of Industrial Leadership, Studies of Seven Industries (New York, Cambridge University Press, 1999).

133. G. R. Salancik, Wanted: a good network theory of organization, Administrative Science Quarterly, 40, 1995, pp. 345–349; W. W. Powell, D. R. White, K. W. Koput & J. Owen-Smith, The growth of interorganizational collaboration in the life sciences, American Journal of Sociology, 110, 2005, pp. 1132–1205.

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