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Human Capital and Institutional Effects in the Compensation of Information Technology Professionals in the United States

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  • Sunil Mithas

    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

  • M. S. Krishnan

    (Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109)

Abstract

This paper studies the influence of supply-side and demand-side factors on the compensation of information technology (IT) professionals and considers the human capital and institutional explanations. We focus on returns to an MBA and the IT-related experience of IT professionals and use the largest data set of IT professionals that has been compiled to date in the United States to answer our research questions. We find that firms pay a significant premium for an MBA. Although firms value the IT experience of IT professionals, they value an MBA significantly more. The results of this study cast doubt on the belief that IT skills have a large firm-specific component. Although IT experience is valued more than non-IT experience for IT professionals, firms value IT experience at other firms much more than they value firm-specific IT experience. Likewise, contrary to popular perception, we do not find evidence for complementarities between an MBA education and IT experience. Among institutional effects, firms in IT and IT-intensive industries pay significantly more to IT professionals than do other firms, and dot-com firms also paid a significant premium in 1999 and 2000. However, these firms do not value an MBA or firm-specific IT experience any more than other firms. We discuss the implications of these findings for further research, for firms' compensation practices, and for individual IT professionals.

Suggested Citation

  • Sunil Mithas & M. S. Krishnan, 2008. "Human Capital and Institutional Effects in the Compensation of Information Technology Professionals in the United States," Management Science, INFORMS, vol. 54(3), pages 415-428, March.
    • Handle: RePEc:inm:ormnsc:v:54:y:2008:i:3:p:415-428
    DOI: 10.1287/mnsc.1070.0778
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    22. Mingfeng Lin & Henry C. Lucas & Galit Shmueli, 2013. "Research Commentary ---Too Big to Fail: Large Samples and the p -Value Problem," Information Systems Research, INFORMS, vol. 24(4), pages 906-917, December.

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