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Specific and General Information Sharing Among Academic Scientists

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  • Carolin Haeussler
  • Lin Jiang
  • Jerry Thursby
  • Marie C. Thursby

Abstract

We provide theoretical and empirical evidence on the factors that influence the willingness of academic scientists to share research results. We distinguish between two types of sharing, specific sharing in which a researcher shares her data or materials with another and general sharing in which scientists report results to the entire community (as in conference presentations). We present two simple games in which scientists research a problem of scientific merit (with an associated prize of academic and/or commercial value). In both cases, the scientists have intermediate research results but none has solved the entire problem.We test these models using a unique survey of bio-scientists in the UK and Germany regarding their willingness to "share." Our results generally support both models. In both, sharing is negatively related to competition and the importance of patents. In other respects they differ markedly. For example, large teams are more likely to share specifically but less likely to share generally. Rank does not matter for general sharing, but it does for specific sharing, where untenured faculty are less likely to share. One important implication is that policies designed to enhance sharing must be tailored to the type of sharing.

Suggested Citation

  • Carolin Haeussler & Lin Jiang & Jerry Thursby & Marie C. Thursby, 2009. "Specific and General Information Sharing Among Academic Scientists," NBER Working Papers 15315, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:15315
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    Cited by:

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    2. Hottenrott, Hanna & Thorwarth, Susanne, 2010. "Industry funding of university research and scientific productivity," ZEW Discussion Papers 10-105, ZEW - Leibniz Centre for European Economic Research.
    3. Xu, Kun & Guan, Zhihua & Xu, Wenli, 2015. "省级财政支出效率空间溢出效应研究:基于超效率dea和gsm模型 [Study on Spatial Spillover Effect of Provincial Fiscal Efficiency: Based on Super-Efficient DEA and GSM Model]," MPRA Paper 71132, University Library of Munich, Germany.
    4. Ali Mohammadi & Chiara Franzoni, 2014. "Inventor's Knowledge Set as the Antecedent of Patent Importance," Industry and Innovation, Taylor & Francis Journals, vol. 21(1), pages 65-87, January.
    5. Haeussler, Carolin & Colyvas, Jeannette A., 2011. "Breaking the Ivory Tower: Academic Entrepreneurship in the Life Sciences in UK and Germany," Research Policy, Elsevier, vol. 40(1), pages 41-54, February.
    6. Holm, Håkan J., 2011. "Double-blind in light of the internet: A note on author anonymity," Information Economics and Policy, Elsevier, vol. 23(1), pages 24-26, March.
    7. Christine Harbring & Bernd Irlenbusch, 2011. "Sabotage in Tournaments: Evidence from a Laboratory Experiment," Management Science, INFORMS, vol. 57(4), pages 611-627, April.
    8. Thomas Hellmann & Enrico Perotti, 2011. "The Circulation of Ideas in Firms and Markets," Management Science, INFORMS, vol. 57(10), pages 1813-1826, October.
    9. Haeussler, Carolin, 2011. "Information-sharing in academia and the industry: A comparative study," Research Policy, Elsevier, vol. 40(1), pages 105-122, February.
    10. Alexander Oettl, 2012. "Reconceptualizing Stars: Scientist Helpfulness and Peer Performance," Management Science, INFORMS, vol. 58(6), pages 1122-1140, June.
    11. Boudreau, Kevin J. & Lakhani, Karim R., 2015. "“Open” disclosure of innovations, incentives and follow-on reuse: Theory on processes of cumulative innovation and a field experiment in computational biology," Research Policy, Elsevier, vol. 44(1), pages 4-19.
    12. Henry Sauermann & Paula Stephan, 2013. "Conflicting Logics? A Multidimensional View of Industrial and Academic Science," Organization Science, INFORMS, vol. 24(3), pages 889-909, June.
    13. Franzoni, Chiara & Sauermann, Henry, 2014. "Crowd science: The organization of scientific research in open collaborative projects," Research Policy, Elsevier, vol. 43(1), pages 1-20.

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    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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