Journal of Information Systems Vol. 16, No. 2 Fall 2002 pp. 209–222
Impact of Information Technology on Public Accounting Firm Productivity Rajiv D. Banker Hsihui Chang The University of Texas at Dallas Yi-ching Kao University of Wisconsin–Milwaukee ABSTRACT: In recent years, information technology (IT) has played a critical role in the services provided by the public accounting industry. However, no empirical research has evaluated the impact of IT on public accounting firms. This study focuses on five offices of an international public accounting firm that recently made large IT investments, primarily in audit software and knowledge-sharing applications. Both qualitative and quantitative information from the research site are analyzed to estimate the change in productivity following the implementation of IT. The results from both regression analysis and Data Envelopment Analysis (DEA) indicate significant productivity gains following IT implementation, documenting the value impact of IT in a public accounting firm. Keywords: public accounting; information technology (IT); IT productivity; IT adoption; data envelopment analysis. Data Availability: The confidentiality agreement with the firm that provided the data for this study precludes revealing its identity and disseminating detailed data without its written consent. I. INTRODUCTION dvances in information technology (IT) have transformed many firms in professional services industries, but perhaps none as much as those in the public accounting industry. Once a slowpaced and conservative industry, public accounting underwent tremendous changes at the turn of the millennium, sparked largely by the rapid changes in its IT environment (Elliott 2000). Audit software and knowledge-sharing applications are two crucial components of these changes. Automation of audit tasks and use of specialized audit software has substituted IT for labor and changed the structure of audit teams. Equally important is the use of advanced systems to share knowledge bases across different parts of the organization that has enabled professional services firms to leverage their human resources more effectively (Gogan et al. 1995). With rapid advances in IT, numerous articles have appeared in practitioner-oriented accounting journals that discuss how to invest in IT to keep up with the current technology (Smith 1997; Zarowin 1998). To justify an IT investment, managers need to understand the potential benefits resulting from the investment. Although there is a general perception that IT investments by public accounting firms can improve firms’ productivity (Lee and Arentzoff 1991), the impact of IT on firm performance is not directly observable. Public accounting firms need to understand how the technology can transform their work and whether such transformation will ultimately lead to productivity gain. While the recent IT research literature documents a positive marginal contribution of incremental IT expenditure using cross-sectional
Journal of Information Systems, Fall 2002
analysis across several firms (e.g., Brynjolfsson and Hitt 1995; Lichtenberg 1995), empirical evidence at the firm level has not been reported. Longitudinal analysis before and after IT implementation is important to support a causality argument leading from IT deployment to improvement in the firm’s productivity. This is especially of interest in a public accounting firm where information utilization is the core competence. The objective of this study is to evaluate whether IT implementation has an impact on the productivity of a public accounting firm. We identified a large international public accounting firm as our research site. Our research site has recently made a large investment in IT, focusing primarily on audit software and knowledge-sharing applications. With access to the firm’s senior management, we obtained both qualitative and quantitative data from five offices of the firm for our...
References: Abbe, S. C., and R. King, Jr. 1998. Aid for the audit. Baylor Business Review 6 (2): 14–18. Auditing Concepts Committee (ACC). 1972. Report of the Committee on Basic Auditing Concepts. The Accounting Review 47: 18. Bamber, E. M., R. T. Watson, and M. C. Hill. 1996. The effects of group support system technology on audit group decision making. Auditing: A Journal of Practice & Theory 15 (1): 122–134. Banker, R. D., A. Charnes, and W. W. Cooper. 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30 (9): 1078–1092. ———, S. M. Datar, and M. V. Rajan. 1989. Measurement of productivity improvements: An empirical analysis. Journal of Accounting, Auditing & Finance 4 (4): 528–554. ———, R. J. Kauffman, and R. C. Morey. 1990. Measuring gains in operational efficiency from information technology: A study of the Positran deployment at Hardee’s Inc. Journal of Management Information Systems 7 (2): 29–54. ———. 1993. Maximum likelihood, consistency and data envelopment analysis: A statistical foundation. Management Science 39 (10): 1265–1273. ———, and H. Chang. 1995. A simulation study of hypothesis tests for differences in efficiencies. International Journal of Production Economics 39: 37–54. ———, and R. Natarajan. 2001. Evaluating contextual variables affecting productivity using data envelopment analysis. Working paper, The University of Texas at Dallas. Barua, A., C. Kriebel, and T. Mukhopadhyay. 1995. Information technologies and business value: An analytic and empirical investigation. Information Systems Research 6 (1): 3–23. ———, and B. Lee. 1997. The IT productivity paradox revisited: A theoretical and empirical investigation in the manufacturing sector. The International Journal of Flexible Manufacturing Systems 9: 245–266. ———, and T. Mukhopadhyay. 2000. Information technology and business performance: Past, present, and future. In Framing the Domains of IT Management—Projecting the Future Through the Past, edited by R. W. Zmud, Chapter 5. Cincinnati, OH: Pinnaflex Education Resources, Inc. Bell, T. B., W. R. Knechel, J. L. Payne, and J. J. Willingham. 1998. An empirical investigation of the relationship between the computerization of accounting systems and the incidence of size of audit differences. Auditing: A Journal of Practice & Theory 17 (1): 13–38. Belsley, D., E. Kuh, and R. Welsch. 1980. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York, NY: John Wiley & Sons. Bergeron, F., and L. Raymond. 1997. Managing EDI for corporate advantage: A longitudinal study. Information & Management 31: 319–333. Brynjolfsson, E., and L. Hitt. 1995. Information technology as a factor of production: The role of differences among firms. Economics of Innovation and New Technology 3: 183–200. ———, and ———. 1996. Paradox lost? Firm-level evidence on the returns to information systems spending. Management Science 42 (4): 541–558. Carmichael D. R., and J. J. Willingham. 1989. Auditing Concepts and Methods. Fifth edition. New York, NY: McGraw-Hill Book Company. Cochran, W. G., and G. M. Cox. 1950. Experimental Designs. New York, NY: John Wiley & Sons, Inc. Cohen, J. R., G. Krishnamoorthy, and A. M. Wright. 2000. Evidence on the effect of financial and nonfinancial trends on analytical review. Auditing: A Journal of Practice & Theory 19 (1): 27–48. Davern, M. J., and R. J. Kauffman. 2000. Discovering potential and realizing value from information technology investments. Journal of Management Information Systems 16 (4): 121–143. Davis, F. D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly (Sept): 319–340 . DeLurgio, S. A. 1998. Forecasting Principles and Applications . First edition. New York, NY: Irwin McGraw-Hill. Ellis, C. A., S. J. Gibbs, and G. L. Rein. 1991. Groupware—Some issues and experiences. Communications of the ACM 34 (1): 38–58. Elliott, R. K. 1998. Who are we as a profession—And what must we become? Journal of Accountancy (February): 81–85. Francalanci, C., and H. Galal. 1998. Information technology and worker composition: Determinants of productivity in the life insurance industry. MIS Quarterly (June): 227–241. Freund, J. E. 1992. Mathematical Statistics. Fifth edition. Englewood Cliffs, NJ: Prentice Hall. Giuliano, V. 1982. The mechanization of office work. Scientific American 247 (3): 146–165. Gogan, J., L. M. Applegate, and R. Nolan. 1995. KPMG Peat Marwick: The shadow partner. Harvard Business School Teaching Note 5-196-066. (Dec. 1). Cambridge, MA: Harvard Business School. Goodhue, D. L. 1995. Understanding user evaluations of information systems. Management Science 41 (12): 1827–1845. ———, and R. L. Thompson. 1995. Task-technology fit and individual performance. MIS Quarterly (June): 213–236.
Journal of Information Systems, Fall 2002
Greene, W. H. 1997. Econometric Analysis. Third edition. Englewood Cliffs, NJ: Prentice Hall. Ho, J. L. 1999. Technology and group decision process in going-concern judgment. Group Decision and Negotiation 8: 33–49. Hunton, J. E. 1994. Setting up a paperless office. Journal of Accountancy (November): 77–85. Igbaria, M. 1990. End-user computing effectiveness—A structural equation model. Omega—International Journal of Management Science 18 (6): 637–652. Jones, J. W., C. Saunders, and R. McLeod. 1993. Media usage and velocity in executive information acquisition: An exploratory study. European Journal of Information systems (October). Kraemer, K. L., J. N. Danziger, D. E. Dunkle, and J. King. 1993. The usefulness of computer-based information to public managers. MIS Quarterly (June): 129–148. Lee, J. Y., and S. Arentzoff. 1991. The productivity factor—Justifying your computer purchase. The National Public Accountant (May): 22–24. Lichtenberg, F. R. 1995. The output contributions of computer equipment and personnel: A firm-level analysis. Economics of Innovation and New Technology 3: 201–207. Loveman, G. W. 1994. An assessment of the productivity impact of information technologies. In Information Technology and the Corporation of the 1990s, edited by T. J. Allen, and M. S. Morton. Oxford, U.K.: Oxford University Press. Lucas, H. C., D. J. Berndt, and G. Truman. 1996. A reengineering framework for evaluating a financial imaging system. Communications of the ACM 39 (5): 86–96. Menon, N., M. B. Lee, and L. Eldenburg. 2000. Productivity of information systems in the healthcare industry. Information Systems Research 11 (1): 83–92. Meyer, B. D. 1995. Natural and quasi-experiments in economics. Journal of Business & Economic Statistics 13 (2): 151–161. Millman Z., and J. Hartwick. 1987. The impact of automated office systems on middle managers and their work. MIS Quarterly (December). Orlikowski, W. 1993. Learning from NOTES: Organization issues in groupware implementation. Information Society (July-September): 237–250. ———. 1997. An improvisational model for change management: The case of Groupware Technologies. Sloan Management Review (Winter): 11–21. Parsons, D., C. C. Gotlieb, and M. Denny. 1993. Productivity and computers in Canadian banking. The Journal of Productivity Analysis 4: 95–113. Pennings, J. M. 1995. Information technology and organizational effectiveness. In Service Productivity and Quality Challenge, edited by P. T. Harker, Chapter 9. Dordrecht, The Netherlands: Kluwer Academic Publishers. Pinsonneault, A., and S. Rivard 1998. Information technology and the nature of managerial work: From the productivity paradox to the Icarus paradox. MIS Quarterly (September): 287–311. Reardon, J., R. Hasty, and B. Coe. 1996. The effect of information technology on productivity in retailing. Journal of Retailing 72 (4). Reimers, J. L., and M. G. Fennema. 1999. The audit review process and sensitivity to information source objectivity. Auditing: A Journal of Practice & Theory 18 (1). Ricchiute, D. N. 1992. Working-paper order effects and auditors’ going-concern decisions. The Accounting Review 67 (1): 46–58. Salamasick, M., W. Fraczkowski, and R. Walley. 1995. Using groupware for audit automation. Internal Auditor (April): 18–21. Shafer, S. M., and T. A. Byrd. 2000. A framework for measuring the efficiency of organizational investments in information technology using data envelopment analysis. Omega 28: 125–141. Shapiro, S. S., and M. B. Wilk. 1965. An analysis of variance test for normality (complete samples). Biometrika 52: 591–611. Smith, S. 1997. The smart way to invest in computers. Journal of Accountancy (May): 63–65. Soh, C., and M. L. Markus. 1995. How IT creates business value: A process theory synthesis. Proceedings of the 16th International Conference of Information Systems, 29–41. Amsterdam, The Netherlands. Vandenbosch, B., and M. J. Ginzberg. 1996-1997. Lotus Notes and collaboration. Journal of Management Information Systems 13 (3): 65–81. Venkatesh, V., and F. D. Davis. 2000. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science 46 (2): 186–204. Wang, C. H., R. D. Gopal, and S. Zionts. 1997. Use of data envelopment analysis in assessing information technology impact on firm performance. Annals of Operations Research 73: 191–213. White, H. 1980. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 4: 817–838. Zarowin, S. 1994. The computer as communicator. Journal of Accountancy (April): 37–42. ———. 1998. Top office technology tools. Journal of Accountancy (April): 22–26.
Please join StudyMode to read the full document