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The Impact of Information Technology on Scientists’ Productivity, Quality and Collaboration Patterns

Author

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  • Ding, Waverly W.
  • Levin, Sharon G.
  • Stephan, Paula E.
  • Winkler, Ann E.

Abstract

This study advances the prior literature concerning the impact of information technology on productivity in academe in two important ways. First, it utilizes a dataset that combines information on the diffusion of two noteworthy and early innovations in IT -- BITNET and the Domain Name System (DNS) -- with career history data on research-active life scientists. This research design allows for proper identification of the availability of access to IT as well as a means to directly identify causal effects. Second, the fine-grained nature of the data set allows for an investigation of three publishing outcomes: counts, quality, and co-authorship. Our analysis of a random sample of 3,771 research-active life scientists from 430 U.S. institutions over a 25-year period supports the hypothesis of a differential return to IT across subgroups of the scientific labor force. Women scientists, early-to-mid-career scientists, and those employed by mid-to-lower-tier institutions benefit from access to IT in terms of overall research output and an increase in the number of new co-authors they work with. Early-career scientists and those in top-tier institutions gain in terms of research quality when IT becomes available at their campuses.

Suggested Citation

  • Ding, Waverly W. & Levin, Sharon G. & Stephan, Paula E. & Winkler, Ann E., 2009. "The Impact of Information Technology on Scientists’ Productivity, Quality and Collaboration Patterns," Institute for Research on Labor and Employment, Working Paper Series qt80n3512q, Institute of Industrial Relations, UC Berkeley.
  • Handle: RePEc:cdl:indrel:qt80n3512q
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    References listed on IDEAS

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    1. Kim, E. Han & Morse, Adair & Zingales, Luigi, 2009. "Are elite universities losing their competitive edge?," Journal of Financial Economics, Elsevier, vol. 93(3), pages 353-381, September.
    2. Winkler Anne E. & Glanzel Wolfang & Levin Sharon & Stephan Paula, 2011. "The Diffusion of Information Technology and the Increased Propensity of Teams to Transcend Institutional and National Borders," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201110, University of Turin.
    3. Ajay Agrawal & Avi Goldfarb, 2008. "Restructuring Research: Communication Costs and the Democratization of University Innovation," American Economic Review, American Economic Association, vol. 98(4), pages 1578-1590, September.
    4. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    5. Tanya S. Rosenblat & Markus M. Mobius, 2004. "Getting Closer or Drifting Apart?," The Quarterly Journal of Economics, Oxford University Press, vol. 119(3), pages 971-1009.
    6. Sanjeev Dewan & Kenneth L. Kraemer, 2000. "Information Technology and Productivity: Evidence from Country-Level Data," Management Science, INFORMS, vol. 46(4), pages 548-562, April.
    7. J. M. C. Santos Silva & Silvana Tenreyro, 2006. "The Log of Gravity," The Review of Economics and Statistics, MIT Press, vol. 88(4), pages 641-658, November.
    8. Adair Morse, 2006. "Are elite universities losing their competitive edge?," Proceedings, Federal Reserve Bank of Cleveland.
    9. Maryellen R. Kelley, 1994. "Productivity and Information Technology: The Elusive Connection," Management Science, INFORMS, vol. 40(11), pages 1406-1425, November.
    10. Anne Winkler & Sharon Levin & Paula Stephan, 2010. "The diffusion of IT in higher education: publishing productivity of academic life scientists," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 19(5), pages 481-503.
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    Cited by:

    1. Beland, Louis-Philippe & Murphy, Richard, 2016. "Ill Communication: Technology, distraction & student performance," Labour Economics, Elsevier, vol. 41(C), pages 61-76.
    2. Malgorzata Wachowska, 2014. "Excessive Accumulation Of Knowledge As A Challenge To Science Policy," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 9(3), pages 29-40, September.
    3. Barham, Bradford L. & Foltz, Jeremy D. & Prager, Daniel L., 2014. "Making time for science," Research Policy, Elsevier, vol. 43(1), pages 21-31.

    More about this item

    Keywords

    JEL O33; J44; J16;

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • J44 - Labor and Demographic Economics - - Particular Labor Markets - - - Professional Labor Markets and Occupations
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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