The productivity impact of information technology in the healthcare industry: An empirical study using a regression spline-based approach

Information and Software Technology

Volumn 46, Issue 1, 2004, Pages 65-73

  Ko, Myung ^a   Osei Bryson, Kweku Muata ^b  

^a UNIVERSITY OF TEXAS AT SAN ANTONIO   (United States)

^b VIRGINIA COMMONWEALTH UNIVERSITY   (United States)

Author keywords

Data mining; Information technology investments; Multivariate adaptive regression splines; Productivity; Regression splines

Indexed keywords

COST BENEFIT ANALYSIS; DATA MINING; HEALTH CARE; INVESTMENTS; PRODUCTIVITY; REGRESSION ANALYSIS; SOCIETIES AND INSTITUTIONS; STRATEGIC PLANNING;

MULTIVARIATE ADAPTIVE REGRESSION SPLINES (MARS); STOCKS;

INFORMATION TECHNOLOGY;

EID: 0346266068     PISSN: 09505849     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0950-5849(03)00110-1     Document Type: Article

References (32)

1. Dewan S., Min C.-K. The substitution of information technology for other factors of production: a firm level analysis. Management Science. 43:(12):1997;1660-1675.
2. Farbey B., Land F., Targett D. Targett evaluating investments in IT: findings and a framework. Wilcocks L.P., Lester S. Beyond the IT Productivity Paradox. 1999;Wiley.
3. Brynjolfsson E. The productivity paradox of information technology. Communications of the ACM. 36:(12):1993;66-76.
4. Brynjolfsson E., Hitt L.M. Paradox lost? Firm-level evidence on the returns to information systems spending. Management Science. 42:(4):1996;541-558.
5. Hitt L.M., Brynjolfsson E. Productivity, business profitability, and consumer surplus: three different measures of information technology value. MIS Quarterly. 20:(2):1996;121-142.
6. B. Prasad, P. Harker, Examining the contribution of information technology toward productivity and profitability in US retail banking, Working paper no. 97-09, Financial Institutions Center, The Wharton School, 1997.
7. Sircar S., Turnbow J.L., Bordoloi B. A framework for assessing the relationship between information technology investments and firm performance. Journal of Management Information Systems. 16:(4):2000;69-97.
8. Garretson R. Greenspan hails technology spending. InfoWorld. 21:(21):1999;32.
9. Shao B., Lin W. Examining the determinants of productive efficiency with IT as a production factor. Journal of Computer Information Systems. 41:(1):2000;25-30.
10. Shao B., Lin W. Measuring the value of information technology in technical efficiency with stochastic production frontiers. Information and Software Technology. (43):2001;447-456.
11. Ward S. Companies squander billions on tech. USA Today. May 20:2002.
12. Menon N., Lee B., Eldenburg L. Productivity of information systems in the healthcare industry. Information Systems Research. 11:(1):2000;83-92.
13. Loveman G.W. An assessment of the productivity impact of information technologies. Allen T.J., Scott Morton M.S. Information Technology and the Corporation of the 1990s: Research Studies. 1994;84-110 Oxford University Press.
14. Weill P. The relationship between investment in information technology and firm performance: a study of the valve manufacturing sector. Information Systems Research. 3:(4):1992;307-333.
15. Lee B., Menon N. Information technology value through different normative lenses. Journal of Management Information Systems. 16:(4):2000;99-119.
16. Henderson J., Quandt R. Microeconomic Theory: A Mathematical Approach. 1980;McGraw-Hill.
17. B. Shao, Investigating the value of information technology in productive efficiency: an analytic and empirical study, PhD Dissertation, State University of New York, Buffalo, 2000.
18. Evans D., Green C., Murinde V. The importance of human capital and financial development in economic growth: new evidence using the translog production function. Finance and Development Research Programme Working Paper Series, Paper No. 22. November:2000;1-31.
19. Hastie T.J., Tibshirani R.J. Generalized Additive Model. 1990;Chapman and Hall.
20. Hastie T.J., Tibshirani R.J., Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2001;Springer, New York.
21. Eubank R. Spline Smoothing and Nonparametric Regression. 1988;Marcel Dekker, Inc.
22. Steinberg D., Colla P.L., Martin K. MARS User Guide. 1999;Salford Systems, San Diego, CA.
23. Breiman L., Friedman J., Olshen R., Charles S. Classification and Regression Trees. 1984;Wadsworth International Group.
24. Friedman J.H. Multivariate adaptive regression splines. The Annals of Statistics. 19:(1):1991;1-141.
25. Barua A., Mukhopadhyay T. Information technologies and business performance: past, present, and future. Zmud R. Framing the Domains of IT Management Projecting the Future through the Past. 2000;Pinnaflex Education Resources, Inc.
26. McKeen J.D., Smith H.A. The relationship between information technology use and organizational performance. Banker R., Kaufman R.J., Mahmood M.A. Strategic and Economic Impacts of Information Technology Investment. 1993;405-444 Idea Publishing, Middletown.
27. Hoogeveen D., Oppelland H.J. A socio political model of the relationship between IT investments and business performance. Proceedings of the 35th Hawaii International Conference on Systems Sciences. 2002.
28. Li M., Ye L.R. Information technology and firm performance: linking with environmental, strategic and managerial contexts. Information and Management. (35):1999;43-51.
29. Teo T.S.H., Wong P.K., Chia E.H. Information Technology (IT) investment and the role of a firm: an exploratory study. International Journal of Information Management. 20:2000;269-286.
30. Soh C., Markus M.L. How IT creates business value: a process theory synthesis. Proceedings of the 16th International Conference on Information Systems, Amsterdam, The Netherlands. 1995;29-41.
31. Markus L., Soh C. Banking on information technology: converting IT spending into firm performance. Banker R., Kaufmann R., Mahmood M. Strategic Information Technology Management: Perspectives on Organizational Growth and Competitive Advantage. 1993;375-404 Idea Group Publishing.
32. Sumner A.T., Moreland C.C. The potential impact of diagnosis related group medical management on hospital utilization and profitability. Health Care Management Review. 20:(2):1995;92-100.