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How Does Information Technology Really Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement and Worker Skills

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  • Ann P. Bartel
  • Casey Ichniowski
  • Kathryn L. Shaw

Abstract

This study presents new empirical evidence on the relationship between investments in new computer-based information technology (IT) and productivity by investigating several plant-level mechanisms through which IT could promote productivity growth. We have assembled a data set on plants with a common production technology in a narrowly defined industry - valve manufacturing - to study the effects of new IT on product innovation, production process improvements, employee skills and work practices. The homogeneity of the plants' production processes within this narrowly defined industry together with the estimation of longitudinal models eliminate many sources of unmeasured heterogeneity that could confound productivity comparisons in more aggregate data and in broader samples. The three main results of this study highlight how the adoption of new IT-enhanced machinery involves much more than just the installation of new equipment on the factory floor. We find that adoption of new IT-enhanced equipment (1)alters business strategies, moving valve manufacturers away from commodity production based on long production runs to customized production in smaller batches; (2)improves the efficiency of all stages of the production process with reductions in setup times supporting the change in business strategy and (3)increases the skill requirements of workers while promoting the adoption of new human resource practices.

Suggested Citation

  • Ann P. Bartel & Casey Ichniowski & Kathryn L. Shaw, 2005. "How Does Information Technology Really Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement and Worker Skills," NBER Working Papers 11773, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:11773
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    Cited by:

    1. Garicano, Luis & Heaton, Paul, 2006. "Computing Crime: Information Technology, Police Effectiveness and the Organization of Policing," CEPR Discussion Papers 5837, C.E.P.R. Discussion Papers.
    2. Javitt, Jonathan C. & Rebitzer, James B. & Reisman, Lonny, 2008. "Information technology and medical missteps: Evidence from a randomized trial," Journal of Health Economics, Elsevier, vol. 27(3), pages 585-602, May.
    3. K. Sudhir & Debabrata Talukdar, 2015. "The “Peter Pan Syndrome” in Emerging Markets: The Productivity-Transparency Tradeoff in IT Adoption," Cowles Foundation Discussion Papers 1980, Cowles Foundation for Research in Economics, Yale University.
    4. repec:eee:eecrev:v:100:y:2017:i:c:p:50-71 is not listed on IDEAS
    5. Saint-Paul, Gilles, 2017. "A “quantized” approach to rational inattention," European Economic Review, Elsevier, vol. 100(C), pages 50-71.
    6. Luis Garicano & Paul Heaton, 2010. "Information Technology, Organization, and Productivity in the Public Sector: Evidence from Police Departments," Journal of Labor Economics, University of Chicago Press, vol. 28(1), pages 167-201, January.
    7. Young Hoon Lee, 2010. "The Effects of Management Practices on Productivity: Evidence from Baseball Team Production," Working Papers 1005, Research Institute for Market Economy, Sogang University, revised 2010.
    8. Andrea Tokman, 2010. "Productivity: The Management Enhancement Strategy for Chile," Working Papers 12, Facultad de Economía y Empresa, Universidad Diego Portales.

    More about this item

    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
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

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