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Technology Adoption In and Out of Major Urban Areas: When Do Internal Firm Resources Matter Most?

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  • Chris Forman
  • Avi Goldfarb
  • Shane Greenstein

Abstract

How much do internal firm resources contribute to technology adoption in major urban locations, where the advantages from agglomeration are greatest? The authors address this question in the context of a business's decision to adopt advanced Internet technology. Drawing on a rich data set of adoption decisions by 86,879 U.S. establishments, the authors find that the marginal contribution of internal resources to adoption is greater outside of a major urban area than inside one. Agglomeration is therefore less important for highly capable firms. The authors conclude that firms behave as if resources available in cities are substitutes for both establishment-level and firm-level internal resources.

Suggested Citation

  • Chris Forman & Avi Goldfarb & Shane Greenstein, 2005. "Technology Adoption In and Out of Major Urban Areas: When Do Internal Firm Resources Matter Most?," NBER Working Papers 11642, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:11642
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    References listed on IDEAS

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    1. Thomas J. Holmes & John J. Stevens, 2002. "Geographic Concentration and Establishment Scale," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 682-690, November.
    2. Gilles Duranton & Diego Puga, 2001. "Nursery Cities: Urban Diversity, Process Innovation, and the Life Cycle of Products," American Economic Review, American Economic Association, vol. 91(5), pages 1454-1477, December.
    3. Goolsbee, Austan & Klenow, Peter J, 2002. "Evidence on Learning and Network Externalities in the Diffusion of Home Computers," Journal of Law and Economics, University of Chicago Press, vol. 45(2), pages 317-343, October.
    4. Maryellen Kelley & Susan Helper, 1999. "Firm Size And Capabilities, Regional Agglomeration, And The Adoption Of New Technology," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 8(1-2), pages 79-103.
    5. Rajiv D. Banker & Sandra A. Slaughter, 1997. "A Field Study of Scale Economies in Software Maintenance," Management Science, INFORMS, vol. 43(12), pages 1709-1725, December.
    6. Thomas J. Holmes, 1999. "Localization Of Industry And Vertical Disintegration," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 314-325, May.
    7. Colombo, Massimo G & Mosconi, Rocco, 1995. "Complementarity and Cumulative Learning Effects in the Early Diffusion of Multiple Technologies," Journal of Industrial Economics, Wiley Blackwell, vol. 43(1), pages 13-48, March.
    8. Massoud Karshenas & Paul L. Stoneman, 1993. "Rank, Stock, Order, and Epidemic Effects in the Diffusion of New Process Technologies: An Empirical Model," RAND Journal of Economics, The RAND Corporation, vol. 24(4), pages 503-528, Winter.
    9. Chris Forman & Avi Goldfarb & Shane Greenstein, 2002. "Digital Dispersion: An Industrial and Geographic Census of Commerical Internet Use," NBER Working Papers 9287, National Bureau of Economic Research, Inc.
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    More about this item

    JEL classification:

    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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