Reexamining the Impact of Information Technology Investments on Productivity Using Regression Tree- and MARS-Based Analyses

  • Myung KoEmail author
  • Kweku-Muata Osei-Bryson
Part of the Integrated Series in Information Systems book series (ISIS, volume 34)


Several studies have investigated the impact of investments in IT on productivity. In this chapter, we revisit this issue and reexamine the impact of investments in IT on hospital productivity using two data mining techniques, which allowed us to explore interactions between the input variables as well as conditional impacts. The results of our study indicated that the relationship between IT investment and productivity is very complex. We found that the impact of IT investment is not uniform and the rate of IT impact varies contingent on the amounts invested in the IT Stock, Non-IT Labor, Non-IT Capital, and possibly time.


Regression Tree Data Mining Technique Multivariate Adaptive Regression Spline Data Mining Approach Multivariate Adaptive Regression Spline Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Material in the chapter previously has appeared in “Reexamining the Impact of Information Technology Investment on Productivity Using Regression Tree and Multivariate Adaptive Regression Splines,” in the Information Technology & Management (9:4, 285–299 (2008)).


  1. Autor D, Katz L, Krueger A (1998) Computing inequality: have computers changed the labor market? Q J Econ 113(4):1169–1213Google Scholar
  2. Barua A, Sophie Lee CH, Whinston AB (1996) The calculus of reengineering. Inf Syst Res 7(4):409–428CrossRefGoogle Scholar
  3. Bergeron F, Raymond L, Rivard S (2001) Fit in strategic information technology management research: an empirical comparison of perspectives. Omega 29:125–142CrossRefGoogle Scholar
  4. Brynjolfsson E, Hitt LM (1996) Paradox lost? Firm-level evidence on the returns to information systems spending. Manage Sci 42(4):541–558CrossRefGoogle Scholar
  5. Deichmann J, Eshghi A, Jaigjtpm D, Sayek S, Teebagy N (2002) Application of multiple adaptive regression splines (MARS) in direct response modeling. J Interact Mark Autumn, 15–27Google Scholar
  6. Dewan S, Min CK (1997) The substitution of information technology for other factors of production: a firm level analysis. Manage Sci 43(12):1660–1675CrossRefGoogle Scholar
  7. Groff ER, Wartell J, McEwen JT (2001) An exploratory analysis of homicides in Washington, DC. In: The 2001 American society of criminology conferenceGoogle Scholar
  8. Hitt LM, Brynjolfsson E (1996) Productivity, business profitability, and consumer surplus: three different measures of information technology value. MIS Q 20(2):121–142CrossRefGoogle Scholar
  9. Kudyba S, Diwan R (2002) Research report: increasing returns to information technology. Inf Syst Res 13(1):104–111Google Scholar
  10. Lichtenberg FR (1995) The output contributions of computer equipment and personnel: a firm-level analysis. Econ Inf New Technol 3(4):201–217CrossRefGoogle Scholar
  11. Menon NM, Lee B (2000) Cost control and production performance enhancement by IT investment and regulation changes: evidence from the healthcare industry. Decis Support Syst 30(2):153–169CrossRefGoogle Scholar
  12. Menon NM, Lee B, Eldenburg L (2000) Productivity of information systems in the healthcare industry. Inf Syst Res 11:83–92CrossRefGoogle Scholar
  13. Mukopadhyay T, Lerch F, Mangal V (1997) Assessing the impact of information technology on labor productivity—a field study. Decis Support Syst 19:109–122CrossRefGoogle Scholar
  14. Selto FH, Renner CJ, Mark Young S (1995) Assessing the organizational fit of a just-in-time manufacturing system: testing selection, interaction and systems models of contingency theory. Acc Organ Soc 20(7–8):665–684CrossRefGoogle Scholar
  15. Shao B, Lin W (2001) Measuring the value of information technology in technical efficiency with stochastic production frontiers. Inf Softw Technol 43:447–456CrossRefGoogle Scholar
  16. Shin H (2006) The impact of information technology on the financial performance of diversified firms. Decis Support Syst 41:698–707CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Information Systems and Cyber Security One UTSA CircleThe University of Texas at San AntonioSan AntonioUSA
  2. 2.Department of Information SystemsVirginia Commonwealth UniversityRichmondUSA

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