Evaluating the Efficiency in which Risk is Managed in a Portfolio of IT Projects: A Data Envelopment Analysis Approach
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References
[1] F. L. Bauer, “Software engineering,” in Report on the NATO Software Engineering Conference 1968, P. Naur and B. Randell, Eds., North Atlantic Treaty Organization (NATO). Garmisch, Germany: NATO Scientific Affairs Division, 7th to 11th October 1968.
[2] R. Pressman, Software Engineering: A Practitioner’s Approach, 7th ed. McGraw-Hill, 2009.
[3] R. N. Charette, “Why software fails,” IEEE Spectrum On Line, September 2005.
[4] S. P. Masticola, “A simple estimate of the cost of software project failures and the break even effectiveness of project risk management,” in Proceedings of the First International Workshop on The Economics of Software and Computation. Minneapolis, MN, USA: IEEE Computer Society, May 20th, 2007, pp. 6–9.
[5] S. Beer, “IT project failures up sharply according to US report,” ITWire, November 26th 2004.
[6] R. L. Glass, “The standish report: does it really describe a software crisis?” Communications of the ACM, vol. 49, no. 8, pp. 15th–16th, August 2006.
[7] W. Harrison, “Managing uncertainty,” IEEE Software, pp. 8–12, September / October 2005.
[8] K. Moløkken and M. Jørgensen, “A review of software surveys on software effort estimation,” in Proceedings of the International Symposium on Empirical Software Engineering (ISESE). Roman Castles (Rome), Italy: IEEE Press, September 29th - October 4th 2003, pp. 223–230.
[9] Y. H. Kwak and J. Stoddardb, “Project risk management: lessons learned from software development environment,” Technovation, vol. 24, no. 11, pp. 915–920, 2004.
http://dx.doi.org/10.1016/S0166-4972(03)00033-6
[10] P. K. Dey, J. Kinch, and S. O. Ogunlana, “Managing risk in software development projects: a case study,” Industrial Management & Data Systems, vol. 107, no. 2, pp. 284–303, 2007.
http://dx.doi.org/10.1108/02635570710723859
[11] L. Wallace, M. Keil, and A. Rai, “Understanding software project risk: a cluster analysis,” Information & Management, vol. 42, no. 1, pp. 115–125, December 2004.
http://dx.doi.org/10.1016/j.im.2003.12.007
[12] D. Baccarini, G. Salm, and P. E. Love, “Management of risks in information technology projects,” Industrial Management & Data Systems, vol. 104, no. 4, pp. 286–295, 2004.
http://dx.doi.org/10.1108/02635570410530702
[13] L. Jingyue, O. P. N. Slyngstad, M. Torchiano, M. Morisio, and C. Bunse, “A state-of-the-practice survey of risk management in development with off-the-shelf software components,” IEEE Transactions on Software Engineering, vol. 34, no. 2, pp. 271 – 286, 2008.
http://dx.doi.org/10.1109/TSE.2008.14
[14] G. Westerman and R. Hunter, IT Risk: Turning Business Threats into Competitive Advantage. Harvard Business School Press, August 2007.
[15] R. Likert, “A technique for the measurement of attitudes,” Archives of Psychology, vol. 140, pp. 1 – 55, 1932.
[16] R. Xu and D. Wunsch, Clustering. Wiley, 2008.
http://dx.doi.org/10.1002/9780470382776
[17] A. Gemino, B. H. Reich, and C. Sauer, “A temporal model of information technology project performance,” Journal of Management Information Systems, vol. 24, no. 3, pp. 9 – 44, 2007.
http://dx.doi.org/10.2753/MIS0742-1222240301
[18] T. Chena, J. Zhangb, and K.-K. Laic, “An integrated real options evaluating model for information technology projects under multiple risks,” International Journal of Project Managemen, February 2009.
[19] S.-J. Huang and W.-M. Hana, “Exploring the relationship between software project duration and risk exposure: A cluster analysis,” Information & Management, vol. 45, no. 3, pp. 175–182, April 2008.
http://dx.doi.org/10.1016/j.im.2008.02.001
[20] A. J. Alencar, G. G. Rodrigues, E. A. Schmitz, and A. L. Ferreira, “Combining decorated classification trees with RCPS stochastic models to gain new valuable insights into software project management,” in Proceedings of the 19th International Conference on Software Engineering & Knowledge Engineering (SEKE), Boston, MA, USA, July 9th-11th 2007, pp. 151–155.
[21] A. Charnes, W. W. Cooper, and E. Rhodes, “Measuring the efficiency of decision making units,” European Journal of Operational Research, vol. 2, no. 6, pp. 429–444, 1978.
http://dx.doi.org/10.1016/0377-2217(78)90138-8
[22] W. W. Cooper, L. M. Seiford, and K. Tone, Introduction to Data Envelopment Analysis and Its Uses. Springer, 2005.
[23] Y. A. Ozcan, Health Care Benchmarking and Performance Evaluation: An Assessment using Data Envelopment Analysis. Springer, 2007.
[24] R. Ramanathan, An Introduction to Data Envelopment Analysis. Sage Publications, 2003.
[25] D. Israel, Data Analysis in Business Research: A Step-By-Step Nonparametric Approach. Thousand Oaks, CA, USA: Sage Publications, 2009.
[26] S. T. Ziliak and D. N. McCloskey, The Cult of Statistical Significance. Ann Arbor, MI, USA: University of Michigan Press, 2008.
[27] S. El-Sabaa, “The skills and career path of an effective project manager,” International Journal of Project Management, vol. 19, no. 1, pp. 1–7, January 2001.
http://dx.doi.org/10.1016/S0263-7863(99)00034-4
[28] T. DeMarco and T. Lister, Waltzing With Bears: Managing Risk on Software Projects. Dorset House, 2003.
[29] W.-M. Hana and S.-J. Huang, “An empirical analysis of risk components and performance on software projects,” Journal of Systems and Software, vol. 80, no. 1, pp. 42– 50, 2007.
http://dx.doi.org/10.1016/j.jss.2006.04.030
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