Abstract
Information technology (IT) is defined as the obtainment, procedure, storage and propagation of sounding, drawing, and textual information by combining microelectronics-based computing and telecommunications. Nowadays, IT is starting to spread further from the conventional personal computer and network technologies to integrations of other fields of technology such as the use of cell phones, televisions, automobiles, etc. In other words, IT has penetrated in daily life of human beings and become one part of the whole society. The importance of IT has become momentous. Therefore, to understand the performance of efficiency and productivity of the IT firms is critical for managers as well as for personal investors. Until now, there are very few researches tried to analyze final performance of the IT firms. As a result, this research intends to use traditional Data Envelopment Analysis (DEA) CCR or BCC models to evaluate the performance of IT firms. The Decision Making Units (DMUs) on this research are chosen from IT firms in S&P 500. However, the traditional DEA models are not fair models from the aspect of improper weight derivations. Thus, this paper intends to analyze the efficiency of IT firms in S&P 500 efficiencies by using multiple objective programming (MOP) based Data Envelopment Analysis (DEA). In a MOP based DEA approach, DMUs will be evaluated based on an equal standard and the results will be evaluated more fairly. The world’s leading IT firms in S&P 500 will be evaluated based on publicly available financial reports of the fiscal year 2010. In addition, the newly developed MOP can improve the traditional DEA’s unfair weights problems and benchmark the efficiency of IT firms in S&P 500 correctly. In the empirical study, the MOP based DEA demonstrated that F5 Networks should be the communications equipment companies of IT worthwhile to be invested. In the future, performance evaluation results can be served as foundations for investment strategies definition.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jorgenson, D.W.: Information Technology and the U.S. Economy. The American Economic Review 91(1), 1–32 (2001)
Phillips, P.A.: Performance measurement systems and hotels: a new conceptual framework. International Journal of Hospitality Management 18(2), 171–182 (1999)
Lewin, A.Y., Minton, J.W.: Determining organizational effectiveness: another look, and an agenda for research. Management Science 32(5), 514–538 (1986)
Charnes, A., Cooper, W., Rhodes, E.: Measuring the efficiency of decision making units. European Journal of Operational Research 2(6), 429–444 (1978)
Fare, R., Hunsaker, W.: Notions of efficiency and their reference sets. Management Science 32(2), 237–243 (1986)
Chiang, C.I., Tzeng, G.H.: A new efficiency measure for DEA: efficiency achievement measure established on fuzzy multiple objectives programming. Journal of Management 17(2), 369–388 (2003)
Chiang, C.I., Tzeng, G.H.: A multiple objective programming approach to data envelopment analysis. In: Shi, Y. (ed.) New Frontiers of Decision Making for the Information Technology Era. World Science, Hong Kong (2000)
Helms, M.M.: Encyclopaedia of Management, 5th edn. Thomson Gale (2006)
Sumanth, D.J.: Productivity engineering and management. McGraw-Hill, New York (1994)
Tangen, S.: Demystifying productivity and performance. International Journal of Productivity and Performance Management 54(1), 34–46 (2005)
Coelli, T., Prasada Rao, D.S., O’Donnell, C.J., Battese, G.E.: An introduction to efficiency and productivity analysis. Springer, New York (2005)
Emrouznejad, A.: Data Envelopment Analysis Homepage (1995), http://www.DEAzone.com
Harbour, J.L.: The performance Paradox: understanding the real drivers that critically affect outcomes. Productivity Press Taylor & Francis Group (2009)
Collin, S.M.H.: Dictionary of ICT, 4th edn. Bloomsbury Publishing Plc. (2004)
Bruton, N.: Managing the IT services process, p. 95. Butterworth Heinemann (2004)
Harry, P.: Performance Measurement Principles and Techniques: An Overview for Local Government. Public Productivity Review 4(4), 312–339 (1980)
Grinstein, A., Goldman, A.: Characterizing the technology firm: An exploratory study. Research Policy 35, 121–143 (2006)
Park, S., Hartley, J., Wilson, D.: Quality management practices and their relationship to buyers’ supplier ratings: A study in the Korean automotive industry. Journal of Operations Management 268, 1–18 (2001)
Cardy, R.L., Dobbins, R.H.: Human resources, high technology, and a quality organizational environment: Research agendas. The Journal of High Technology Management Research 6(2), 261–279 (1995)
Bowonder, B.Y., Yadav, S.: R&D spending patterns of global firms. Research Technology Management 42(6), 44–55 (1999)
Deeds, D.L.: The role of R&D intensity, technical development and absorptive capacity in creating entrepreneurial wealth in high technology startups. Journal of Engineering and Technology Management 18(1), 29–47 (2001)
Fare, R., Grabowaski, R., Grosskopf, S.: Technical efficiency of Philippine agriculture. Applied Economics 17(2), 205–214 (1985)
Chiang, C.I., Tzeng, G.H.: A New Efficiency Measure for DEA: Efficiency Achievement Measure Established on Fuzzy Multiple Objectives Programming. Journal of Management 17(2), 369–388 (2000a)
Chiang, C.I., Tzeng, G.H.: A multiple objective programming approach to data envelopment analysis. In: Shi, Y., Zeleny, M. (eds.) New Frontiers of Decision Making for the Information Technology Era, pp. 270–285. World Science Publishing Company, Singapore (2000b)
Farrell, M.J.: The measurement of productive efficiency. Journal of the Royal Statistical Society 120(3), 253–291 (1957)
Banker, R.D., Charnes, A., Cooper, W.W.: Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30(9), 1078–1092 (1984)
Charnes, A., Clark, T., Cooper, W.W., Golany, B.: A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the US Air Force. Annals of Operations Research 2(1), 95–112 (1985)
Yu, J.R., Tzeng, Y.C., Tzeng, G.H., Yu, Z.Y., Sheu, H.J.: A fuzzy multiple objective programming to DEA with imprecise data. International Journal of Uncertainty, Fuzziness & Knowledge-Based Systems 12(5), 591–600 (2004)
Sakawa, M., Yumine, T.: Interactive fuzzy decision-making for multi-objective linear fractional programming problems. Large Scale Systems 5, 105–114 (1983)
Sakawa, M., Yano, H.: Interactive decision making for multi- objective linear fractional programming problems with parameters. Cybernetics and Systems: An International Journal 16, 377–394 (1985)
Ohta, H., Yamaguchi, T.: Multi-goal programming including fractional goal in consideration of fuzzy solutions. Journal of Japan Society for Fuzzy Theory and System 7, 1221–1228 (1995)
Zimmermann, H.J.: Fuzzy programming and linear programming with several objective functions. Fuzzy. Sets and Systems 1(1), 45–55 (1978)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Huang, CY., Wang, PY., Tzeng, GH. (2012). Evaluating Top Information Technology Firms in Standard and Poor’s 500 Index by Using a Multiple Objective Programming Based Data Envelopment Analysis. In: Jiang, H., Ding, W., Ali, M., Wu, X. (eds) Advanced Research in Applied Artificial Intelligence. IEA/AIE 2012. Lecture Notes in Computer Science(), vol 7345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31087-4_73
Download citation
DOI: https://doi.org/10.1007/978-3-642-31087-4_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31086-7
Online ISBN: 978-3-642-31087-4
eBook Packages: Computer ScienceComputer Science (R0)