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Evaluating the performance of US manufacturing and service operations in the presence of IT: a Bayesian stochastic production frontier approach

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  • Gilwhan Kim
  • Winston T. Lin
  • N.C. Simpson

Abstract

In this paper, we evaluate the performance of US manufacturing and service operations in the presence of information technology (IT) as measured by technical efficiency, using firm-level data from 133 companies over the period from 1999 to 2009. To gain insight into the phenomenon of the ‘IT productivity paradox’, or the history of inconsistent findings in the existing literature, we employ a Bayesian stochastic production frontier approach to model the relationship between performance and technical efficiency at the firm, industry and sector levels. Some results are indicative of a slight advantage of the manufacturing sector over the service sector in terms of technical efficiency and a significant positive contribution of IT-investment to firm output. However, other results do suggest the productivity paradox, because of a lack of any definitive association of high IT investment levels with either high- or low-technical efficiency. Indeed, the findings of this study suggest that the origin of some portion of the IT productivity paradox may exist at the industry level, in that the relationship between extreme levels of IT-investment and extreme levels of technical efficiency appear to work differently in sufficiently different industries.

Suggested Citation

  • Gilwhan Kim & Winston T. Lin & N.C. Simpson, 2015. "Evaluating the performance of US manufacturing and service operations in the presence of IT: a Bayesian stochastic production frontier approach," International Journal of Production Research, Taylor & Francis Journals, vol. 53(18), pages 5500-5523, September.
  • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:18:p:5500-5523
    DOI: 10.1080/00207543.2015.1026616
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    Cited by:

    1. Lin, Winston T. & Chen, Yueh H. & Chou, Chia-Ching, 2021. "Assessing the business values of e-commerce and information technology separately and jointly and their impacts upon US firms' performance as measured by productive efficiency," International Journal of Production Economics, Elsevier, vol. 241(C).
    2. Lin, Winston T. & Chen, Yueh H. & Hung, TingShu, 2019. "A partial adjustment valuation approach with stochastic and dynamic speeds of partial adjustment to measuring and evaluating the business value of information technology," European Journal of Operational Research, Elsevier, vol. 272(2), pages 766-779.
    3. Kovach, Jeremy J. & Swink, Morgan & Rodriguez, Mauricio, 2023. "A novel measure of firm-level production outsourcing," International Journal of Production Economics, Elsevier, vol. 263(C).

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