Managing creativity in small worlds

California Management Review

Volumn 48, Issue 4, 2006, Pages 6-27

  Fleming, Lee ^a   Marx, Matt ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33748418886     PISSN: 00081256     EISSN: None     Source Type: Journal    
DOI: 10.2307/41166358     Document Type: Article

References (88)

1. H. Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology (Boston, MA: Harvard Business School Press, 2003).
2. For entry points into the psychology and social-psychology literatures, see T. Amabile, Creativity in Context (Boulder, CO: Westview Press, 1996);
3. D. Simonton, Origins of Genius: Darwinian Perspectives on Creativity (New York, NY: Oxford University Press, 1999);
4. P. Paulus and B. Nijstad, Group Creativity (Oxford: Oxford University Press, 2003).
5. For structural perspectives, see R. Burt, "Structural Holes and Good Ideas," American Journal of Sociology, 110 (September 2004): 349-399;
6. B. Uzzi and J. Spiro, "Collaboration and Creativity: The Small World Problem," American Journal of Sociology, 111 (September 2005): 447-504.
7. L. Fleming, C. King, and A. Juda, "Small Worlds and Regional Innovation," Organization Science, under revision.
8. Saxenian made the original argument for denser networks in Silicon Valley and was the first to identify and document many of the phenomena we studied. See A. Saxenian, Regional Advantage (Cambridge, MA: Harvard University Press, 1994).
9. See L. Fleming, S. Mingo, and D. Chen, "Brokerage and Collaborative Creativity," Harvard Business School working paper, 2005. While the regional analyses revealed a positive though inconsistently significant small world interaction, the individual-level analyses demonstrated a robust positive interaction. Though the two results are consistent, we rely much more heavily upon the latter research, because it was randomly sampled to avoid network auto-correlation and instrumented to control for endogeneity.
10. J. Singh, "Collaborative Networks as Determinants of Knowledge Diffusion Patterns," Management Science, 51/5 (May 2005): 756-770.
11. J. Travers and S. Milgram, "An Experimental Study of the Small World Problem," Sociometry, 32 (1969): 425-443.
12. D.J. Watts and S.H. Strogatz, "Collective Dynamics of 'Small-World' Networks," Nature, 393 (1998): 440-442;
13. D.J. Watts, Small Worlds: The Dynamics of Networks between Order and Randomness (Princeton, NJ: Princeton University Press, 1999);
14. M.E.J. Newman, A.L. Barabasi, and D.J. Watts, eds., The Structure and Dynamics of Complex Networks (Princeton, NJ: Princeton University Press, 2003).
15. See T. Allen, Managing the Flow of Technology (Cambridge, MA: MIT Press, 1977).
16. Robert Stewart, interview by first author, Cambridge, MA, June 17, 2004.
17. The idea thai small worlds improve creativity has recently been an area of intense research activity, though our research proposes and demonstrates novel mechanisms that are contrary to some of those previously argued. For example, see A. Hargadon, How Breakthroughs Happen: The Surprising Truth About How Companies Innovate (Boston, MA: Harvard Business School Press, 2003);
18. Uzzi and Spiro, How Breakthroughs Happen: The Surprising Truth about How Companies Innovate, op. cit.;
19. Melissa A. Schilling and Corey C. Phelps, "Interfirm Collaboration Networks: The Impact of Small World Connectivity on Firm Innovation," December 2005, 〈http://ssrn.com/abstract=564422〉.
20. See D. Obstfeld, "Social Networks, the Tertius lungens Orientation, and Involvement in Innovation," Administrative Science Quarterly, 50/1 (March 2005): 100-130;
21. Uzzi and Spiro, Administrative Science Quarterly, op. cit.;
22. Burt, Administrative Science Quarterly, op. cit.
23. Fleming, Mingo, and Chen, Administrative Science Quarterly, op. cit.
24. J.S. Coleman, "Social Capital in the Creation of Human Capital," American Journal of Sociology, 94 (1988): S95-S120.
25. Michael Porter has written extensively about the benefits to regional competitiveness of clustering specialists in a field. Porter's theory of clusters was introduced in Michael Porter, The Competitive Advantage of Nations (New York, NY: Free Press, 1990)
26. and later developed in several articles including Michael Porter, "Clusters and the New Economics of Competition," Harvard Business Review, 76/6 (November/December 1998): 77-90;
27. Michael Porter, "Location, Clusters, and Company Strategy," in G. Clark, M. Gertler, and M. Feldman, eds., Oxford Handbook of Economic Geography (Oxford: Oxford University Press, 2000).
28. See Burt, Oxford Handbook of Economic Geography, op. cit.;
29. Obstfeld, Oxford Handbook of Economic Geography, op. cit.
30. Fleming, King, and Juda, Oxford Handbook of Economic Geography, op. cit.
31. See Saxenian, Oxford Handbook of Economic Geography, op. cit.;
32. P. Almeida and B. Kogut, "Localization of Knowledge and the Mobility of Engineers in Regional Networks," Management Science, 45 (1999): 905-917.
33. In both regions, in the years before the small worlds grew to encompass more than one predominant organization, the dominant organization in the largest cluster changed several times. In Silicon Valley, dominance alternated between Raychem and IBM; in Boston, between DEC and MIT.
34. For greater detail, see L. Fleming, L. Colfer, A. Marin, and J. McPhie, "Why the Valley Went First: Agglomeration and Emergence in Regional Inventor Networks," in W. Powell and J. Padgett, eds., Market Emergence and Transformation (Santa Fe, NM: Santa Fe Institute, forthcoming);
35. L. Fleming and K. Frenken, "The Evolution of Inventor Networks in the Silicon Valley and Boston Regions," Advances in Complex Systems (forthcoming).
36. For a description of a similar postdoc program at Syntex (coincidentally, the predominant firm on the other side of the IBM-pharmaceutical bridge depicted in Figure 3), see A. Kornberg. The Golden Helix: Inside Biotech Ventures (Sausalito, CA: University Science Books, 1995).
37. John Campbell Scott, interview by first author, Santa Clara, CA, May 12, 2003.
38. We define regions using the conventional Metropolitan Statistical Area designation. Boston is region 1120 and Silicon Valley is region 7400. See U.S. Census Bureau, "Reference Resources for Understanding Census Bureau Geography," 〈www.census.gov/geo/www/reference.html〉, accessed April 13, 2004. Different regional definitions and window sizes did not substantively influence the observed processes of network aggregation.
39. While our focus is upon regional differences in small worlds, we strongly suspect variance across industries as well. For example, industries with stronger academic ties are probably more small world, and different academic fields probably have different clustering and small world properties. See M. Newman, "The Structure of Scientific Collaboration Networks," Proceedings of the National Academy of Sciences, 98 (January 16, 2001): 404-409. Current research attempts to describe the industrial differences in collaborative structure and inventor mobility.
40. R.J. Gilson, "The Legal Infrastructure of High Technology Industrial Districts: Silicon Valley, Route 128. and Covenants Not to Compete," New York University Law Review, 74 (1999): 575-629.
41. We suspect this happened due to the weakening of mutual loyalty (the "psychological contract") between employers and employees and are developing more direct tests of this hypothesis.
42. "Centrifugal Forces: Americans Are Still Restless in the Midst of Plenty," Economist, July 16, 2005. pp. 4-7.
43. T. Gura, "Joining a Trend, Scientists Increasingly Say 'Call My Agent," Science, 303 (2004): 303-305.
44. R. Gulati and M. Gargiulo, "Where Do Interorganizational Networks Come From?" American Journal of Sociology, 104 (1999): 1439-1493.
45. L. Fleming and A. Juda, "A Network of Invention," Harvard Business Review, 82/4 (April 2004): 22.
46. S. Barley and G. Kunda, Gurus, Hired Guns, and Warm Bodies: Itinerant Experts in a Knowledge Economy (Princeton, NJ: Princeton University Press, 2004).
47. For an entertaining story of subterfuge, obsession, and ultimate victory for the geeks, see R. Avitzur, "The Graphing Calculator Story," 〈www.pacifia.com/Story/〉, accessed July 4, 2005;
48. S. Levy, "They Hacked Real Good, for Free," Newsweek, January 10, 2005.
49. See 〈http://news.com.com/Where+are+Netscapes+pioneers+today/2100- 1032_35406730.html〉 and 〈http://ex-mozilla.org〉 for biographies of more than 900 ex-Netscape employees.
50. The bursting of the technology bubble aside, we believe (though we lack systematic evidence) that power remains with high-powered inventors, as evidenced by Microsoft's inability to retain Kai-Fu Lee after he announced plans to defect to Google.
51. Though we cannot directly cite the firm involved, we fictionalized the true story in L. Fleming and M. Marx, "Barry Riceman at NetD," Harvard Business School Case Study No. 606-090. Whether or not the inventor was justified remains unclear; engineers can leave a firm with their ideas "before an inventive concept has taken on a concrete, tangible form,'
52. according to R. Merges, "The Law and Economics of Employee Inventions," Harvard Journal of Law and Technology, 13/1(Fall 1999), pg. 3.
53. Fleming, Colfer, Marin, and McPhie, Harvard Journal of Law and Technology, op. cit.
54. Amabile, Harvard Journal of Law and Technology, op. cit.
55. Michael Souza, interview by second author, March 21, 2005, Cambridge, Mass.
56. Intel provides a counterexample - a successful firm that has pursued an aggressive litigation strategy. Hyde describes the hiring problems that accompany this strategy. See A. Hyde, Working in Silicon Valley: Economic and Legal Analysis of a High Velocity Labor Market (Armonk, NY: M.E. Sharp, 2003).
57. Formal economic models that demonstrate the benefits to firms of greater mobility include B. Anand, A. Galetovic, and A. Stein, "Incentives versus Synergies in the Markets for Talent," Harvard Business School working paper, 2004;
58. R. Lewis and D. Yao, "Innovation, Knowledge Flow, and Worker Mobility," Fuqua School of Business working paper, 2003.
59. A. Tversky and D. Kahneman, "The Framing of Decisions and Psychology of Choice," Science, 211 (1981): 453-458.
60. See M. T. Hansen, "The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits," Administrative Science Quarterly, 44/1 (March 1999); 82-111;
61. Singh, Administrative Science Quarterly, op. cit.
62. For particular emphasis on the development of business models in an open and increasingly connected environment, see H. Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology (Boston, MA: Harvard Business School Press, 2003);
63. M. lansiti and R. Levien, The Keystone Advantage: What the New Dynamics of Business Ecosystems Mean for Strategy, Innovation, and Sustainability (Boston, MA: Harvard Business School Press, 2004). For more general works on technology and strategy,
64. see S. Wheelwright and K. Clark, Revolutionizing Product Development: Quantum Leaps in Speed, Efficiency, and Quality (Boston, MA: Harvard Business School Press, 1992);
65. S. Thomke, Experimentation Matters (Boston, MA: Harvard Business School Press, 2003).
66. Although bridging inventors can connect firms internally as well (as illustrated by Stewan in Figure 2), this article is concerned with the more important, challenging, and increasingly common problem of managing across firm boundaries.
67. Allen, op. cit.;
68. M. Tushman, "Special Boundary Roles in the Innovation Process," Administration Science Quarterly, 22/4 (December 1977): 587-605.
69. Allen, Administration Science Quarterly, op. cit.
70. Pyare Khanna, interview by first author, Fremont, Calif., July 10, 2003. 47.
71. See Obstfeld, Administration Science Quarterly, op. cit.
72. For the first stage of idea generation, 60% of the effect remained after controlling for the inventor with fixed-effects models (such models assume that the inventor's innate intelligence or creativity remains fixed over his or her lifetime). For the second stage of idea diffusion, between 70% and 80% of the effect remained after estimating fixed-effects models. An instrumented version of the structural variable also returned similar results. Hence we inferred that most of the effects are due to differences in collaborative structure.
73. See C. Christensen, The Innovator's Dilemma (Boston, MA: Harvard Business School Press, 1997);
74. M. Tushman and C. O'Reilly, Winning through Innovation: A Practical Guide to Leading Organizational Change and Renewal (Boston, MA: Harvard Business School Press, 1997).
75. See S. Klepper and P. Thompson, "Spin-Off Entry in High Tech Industries: Motives and Consequences,' Carnegie Mellon University working paper, 2006.
76. This has become more common lately. See J. Lerner and Paul Gompers, "The Determinants of Corporate Venture Capital Success: Organizational Structure, Incentives, and Complementarities," in Randall Morck, ed., Concentrated Ownership (Chicago, IL: University of Chicago Press for the National Bureau of Economic Research, 2000), pp. 17-50.
77. See Anand, Galetovic, and Stein, Concentrated Ownership, op. cit.;
78. Merges, Concentrated Ownership, op. cit.
79. Trade secret law remains enforceable, to varying degrees, in all states. See Hyde, Concentrated Ownership, op. cit.
80. Hoover's online database.
81. K.R. Lakhani and R. Wolf, "Why Hackers Do What They Do: Understanding Motivation and Effort in Free/Open Source Software Projects," in J. Feller, B. Fitzgerald, S. Hissa, and K. R. Lakhani, eds., Perspectives on Free and Open Source Software (Cambridge, MA: MIT Press, 2005).
82. See 〈http://dbpubs.stanford.edu:8090/pub/showDoc.Fulltext?lang= en&doc=1999-66&format=pdf&compression=〉, among other sites.
83. Scott Stem, "Do Scientists Pay to Be Scientists?' Management Science, 50 (2004): 835-853.
84. W. Cohen and D. Levinthal, "Absorptive Capacity: A New Perspective on Learning and Innovation," Administrative Science Quarterly, 35/1 (March 1990): 128-152.
85. Chuck Morehouse, director of Hewlett-Packard's Information Access Laboratory, interview by first author, Palo Alto, CA, June 18, 2005.
86. We do not specify the particular inventors in these cases out of respect for their privacy.
87. D. Teece, "Profiting from Technological Innovation," Research Policy, 15 (1986): 285-305.
88. Stan Williams, director of Hewlett-Packard's Quantum Science Research Group, interview by first author, Palo Alto, Calif., June 18, 2005.