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Efficient Structures for Innovative Social Networks

Author

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  • William S. Lovejoy

    (Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109)

  • Amitabh Sinha

    (Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109)

Abstract

What lines of communication among members of an organization are most productive in the early, ideation phase of innovation? We investigate this question with a recombination and selection model of knowledge transfer operating through a social network. We find that ideation is accelerated when people in the organization dynamically churn through a large (ideally the entire population) set of conversational partners over time, which naturally begets short path lengths and eliminates information bottlenecks. Group meetings, in which the content of conversations is available to all for consideration, are another way to learn in parallel and accelerate the ideation process, although for complex problems they may not offer significant advantages over the best decentralized networks. The idealized core-periphery graphs emerge as an important family on the time-cost efficient frontier. New sociometrics for the analyses of innovation processes emerge from this investigation.

Suggested Citation

  • William S. Lovejoy & Amitabh Sinha, 2010. "Efficient Structures for Innovative Social Networks," Management Science, INFORMS, vol. 56(7), pages 1127-1145, July.
    • Handle: RePEc:inm:ormnsc:v:56:y:2010:i:7:p:1127-1145
    DOI: 10.1287/mnsc.1100.1168
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    References listed on IDEAS

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    Cited by:

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    2. Tian Heong Chan & Haibo Liu & Steffen Keck & Wenjie Tang, 2023. "When do teams generate valuable inventions? The moderating role of invention integrality on the effects of expertise similarity, network cohesion, and gender diversity," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1760-1777, June.
    3. Ying-Yu Chen & Yi-Long Jaw, 2014. "How do business groups’ small world networks effect diversification, innovation, and internationalization?," Asia Pacific Journal of Management, Springer, vol. 31(4), pages 1019-1044, December.
    4. Wen Zhou & Nikita Koptyug & Shutao Ye & Yifan Jia & Xiaolong Lu, 2016. "An Extended N-Player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-18, January.
    5. Dass, Mayukh & Reddy, Srinivas K. & Iacobucci, Dawn, 2014. "A Network Bidder Behavior Model in Online Auctions: A Case of Fine Art Auctions," Journal of Retailing, Elsevier, vol. 90(4), pages 445-462.
    6. Liang, Liang & Alam, Ashraful & Sorwar, Ghulam & Yazdifar, Hassan & Eskandari, Rasol, 2021. "The combined network effect of sparse and interlocked connections in SMEs’ innovation," Technological Forecasting and Social Change, Elsevier, vol. 163(C).

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