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A framework for measuring the efficiency of organizational investments in information technology using data envelopment analysis

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  • Shafer, Scott M.
  • Byrd, Terry A.

Abstract

Over the last few decades, organizations have been increasingly investing in information technology (IT). However, despite these substantial investments in IT, empirical studies have not persuasively established corresponding improvements in organazational performance. In fact, to the contrary, many studies investigating investments in IT have found no significant relationship between firm performance and investments in IT. Brynjolfsson and Kaufman and Weill identify shortcomings in past studies. These shortcomings include measurement errors, lags between investments and benefits, redistribution of profits, and mismanagement of IT resources. This paper proposes a framework for measuring the efficiency of investments in IT that addresses these shortcomings. In particular, we demonstrate how a mathematical programming technique called Data Envelopment Analysis (DEA) can be used to evaluate the efficiency of IT investments. Our framework is illustrated using data compiled for over 200 large organizations. The paper illustrates how the shortcomings listed above can be addressed.

Suggested Citation

  • Shafer, Scott M. & Byrd, Terry A., 2000. "A framework for measuring the efficiency of organizational investments in information technology using data envelopment analysis," Omega, Elsevier, vol. 28(2), pages 125-141, April.
  • Handle: RePEc:eee:jomega:v:28:y:2000:i:2:p:125-141
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    References listed on IDEAS

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    1. Peter Weill, 1992. "The Relationship Between Investment in Information Technology and Firm Performance: A Study of the Valve Manufacturing Sector," Information Systems Research, INFORMS, vol. 3(4), pages 307-333, December.
    2. Sirkka L. Jarvenpaa & Blake Ives, 1990. "Information Technology and Corporate Strategy: A View from the Top," Information Systems Research, INFORMS, vol. 1(4), pages 351-376, December.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Sidney E. Harris & Joseph L. Katz, 1991. "Organizational Performance and Information Technology Investment Intensity in the Insurance Industry," Organization Science, INFORMS, vol. 2(3), pages 263-295, August.
    5. J.C. Paradi & D.N. Reese & D. Rosen, 1997. "Applications of DEA to measure the efficiency of software production at two large Canadian banks," Annals of Operations Research, Springer, vol. 73(0), pages 91-115, October.
    6. Scherer, F. M., 1982. "Inter-industry technology flows in the United States," Research Policy, Elsevier, vol. 11(4), pages 227-245, August.
    7. Hammer, Michael & Champy, James, 1993. "Reengineering the corporation: A manifesto for business revolution," Business Horizons, Elsevier, vol. 36(5), pages 90-91.
    8. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    9. Indranil Bardhan & William Cooper & Subal Kumbhakar, 1998. "A Simulation Study of Joint Uses of Data Envelopment Analysis and Statistical Regressions for Production Function Estimation and Efficiency Evaluation," Journal of Productivity Analysis, Springer, vol. 9(3), pages 249-278, March.
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    Cited by:

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    2. Chun-Hsien Wang & Jun-Yen Lee & Yi-Hua Chang, 2012. "Measuring productivity in the biotechnology industry using the global Malmquist index," Applied Economics Letters, Taylor & Francis Journals, vol. 19(9), pages 807-812, June.
    3. Carnero Moya, M. Carmen, 2004. "The control of the setting up of a predictive maintenance programme using a system of indicators," Omega, Elsevier, vol. 32(1), pages 57-75, February.
    4. Madjid Tavana & Salman Nazari-Shirkouhi & Hamidreza Farzaneh Kholghabad, 2021. "An integrated quality and resilience engineering framework in healthcare with Z-number data envelopment analysis," Health Care Management Science, Springer, vol. 24(4), pages 768-785, December.
    5. Zeng, Shihong & Jiang, Chunxia & Ma, Chen & Su, Bin, 2018. "Investment efficiency of the new energy industry in China," Energy Economics, Elsevier, vol. 70(C), pages 536-544.
    6. Barua, Anitesh & Brockett, P. L. & Cooper, W. W. & Deng, Honghui & Parker, Barnett R. & Ruefli, T. W. & Whinston, A., 2004. "DEA evaluations of long- and short-run efficiencies of digital vs. physical product "dot com" companies," Socio-Economic Planning Sciences, Elsevier, vol. 38(4), pages 233-253, December.
    7. van Wessel, R.M., 2008. "Realizing business benefits from company IT standardization : Case study research into the organizational value of IT standards, towards a company IT standardization management framework," Other publications TiSEM 4bdde091-4f3f-4be1-84aa-9, Tilburg University, School of Economics and Management.
    8. Kao, Ta-Wei (Daniel) & Simpson, N.C. & Shao, Benjamin B.M. & Lin, Winston T., 2017. "Relating supply network structure to productive efficiency: A multi-stage empirical investigation," European Journal of Operational Research, Elsevier, vol. 259(2), pages 469-485.
    9. Khallaf, Ashraf, 2012. "Information technology investments and nonfinancial measures: A research framework," Accounting forum, Elsevier, vol. 36(2), pages 109-121.
    10. Fazlollahi, Ariyan & Franke, Ulrik, 2018. "Measuring the impact of enterprise integration on firm performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 200(C), pages 119-129.
    11. H Seol & H Lee & S Kim & Y Park, 2008. "The impact of information technology on organizational efficiency in public services: a DEA-based DT approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(2), pages 231-238, February.
    12. Hokey Min & Hyesung Min & Seong Jong Joo, 2007. "A data envelopment analysis on assessing the competitiveness of Korean hotels," The Service Industries Journal, Taylor & Francis Journals, vol. 29(3), pages 367-385, November.
    13. Mehdi Toloo & Soroosh Nalchigar & Babak Sohrabi, 2018. "Selecting most efficient information system projects in presence of user subjective opinions: a DEA approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 1027-1051, December.

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