Wednesday , December 19 2018

A Portfolio Theory Approach to
Software Vendor Selection

Marius RADULESCU1, Constanţa Zoie RADULESCU2
1
Institute of Mathematical Statistics and Applied Mathematics,
Casa Academiei Române,

13, Calea 13 Septembrie, Bucharest 5, RO-050711, Romania
mradulescu.csmro@yahoo.com
2 I C I Bucharest
(National Institute for R & D in Informatics)

8-10 Averescu Blvd.
011455 Bucharest 1, Romania
radulescucz@yahoo.com

Abstract: The paper presents a minimum risk model, inspired from the financial portfolio theory, for the selection of a software vendor. The performance of the software products offered by potential software vendors is evaluated by several experts regarding several criteria. The minimum risk model has several constraints. One of the constraints is a complementarity constraint. Other constraints are connected with the available budget and the expected performance of the software products. A procedure for solving the minimum risk model is presented and a numerical example is analyzed.

Keywords: Software vendor selection, portfolio theory, minimum risk model, complementarity constraints, decision support.

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CITE THIS PAPER AS:
Marius RADULESCU, Constanţa Zoie RADULESCU, A Portfolio Theory Approach to Software Vendor Selection, Studies in Informatics and Control, ISSN 1220-1766, vol. 24 (4), pp. 379-386, 2015. https://doi.org/10.24846/v24i4y201502

  1. Introduction

The task of selecting project portfolios is an important and recurring activity in many organizations.

Project selection is a process of strategic significance aimed at evaluating individual projects or groups of projects and then choosing to implement a set of them so that the objectives of the organization may be achieved. The project selection is a complex task. Many factors must be taken into account especially in the case of uncertainty or interrelationships among projects. There are many techniques available to assist in this process. The supplier selection problem is a special case of the project portfolio selection problem.

The software vendor selection problem is a special case of the supplier selection problem.

In the second section we present a literature review on the approaches to the project selection problem and to the software vendor selection problem.

In the third section we present an original binary mathematical programming model for the software vendor selection problem under risk and limited resources which is inspired from a previous model presented in Rădulescu and Rădulescu [23]. Our model includes several opinions belonging to a group of evaluator experts. These opinions generate the risk. The project risk is greater if experts’ opinions have a greater degree of dispersion. Since the projects do not have the same impact under every criterion and the relative importance of the criteria is vague definite, at least at the start of the decision process the solution of the real problem is not an easy task. In the fourth section is presented a numerical example for the minimum risk model that aims to find the best software vendor.

REFERENCES

  1. AYHAN, M. B., A Fuzzy AHP Approach for Supplier Selection Problem: A Case Study in a GEARMOTOR Company, International Journal of Managing Value and Supply Chains (IJMVSC) vol. 4(3), 2013, pp. 11-23.
  2. De BOER, L., E. LABRO, P. MORLACCHI, A Review of Methods Supporting Supplier Selection, European Journal of Purchasing & Supply Management, vol. 7, 2001, pp. 75-89.
  3. CABALLERO, R., A. F. CARAZO, T. GÓMEZ, F. M. GUERRERO, A. G. HERNÁNDEZ-DÍAZ, J. MOLINA, Solving a Comprehensive Model for Multiobjective Project Portfolio Selection, Computers & Operations Research, vol. 37, 2010, pp. 630-639.
  4. CHIEN, C., A Portfolio-Evaluation Framework for Selecting R&D Projects. R&D Man., vol. 32(4), 2002, pp. 359-368.
  5. COLDRICK, S., J. HANNIS, P. IVEY, P. LONGHURST, An R&D Options Selection Model for Investment Decisions, Technovation, vol. 25(3), 2005, pp. 185-193.
  6. DEPIANTE, A., A. JENSEN, A Practical R&D Project-Selection Scoring Tool, IEEE Trans. on Engineering Management, vol. 46(2), 1999, pp. 158-170.
  1. DOMINIC P. D. D., O. I. FOONG, G. KANNABIRAN, A. A. WHAB, A New Hybrid Model for the Supplier Selection Decision, J. of Business Information Systems, vol. 5(3), 2010, pp. 230-247.
  2. DUARTE B. P. M., A. REIS, Developing a Project Evaluation System based on Multiple Attribute Value Theory, Computers and Operations Research, vol. 33(5), 2006, pp. 1488-1504.
  3. FRIDGEN, G., H. V. MUELLER, An Approach for Portfolio Selection in Multi-vendor IT Outsourcing, 7, 2011, ICIS 2011 Proceedings. Paper 8. http://aisel.aisnet.org/icis2011/proceedings/projmanagement/8
  4. FULGA C., Convexification Technique and Portfolio Optimization, Studies in Informatics and Control, vol. 22(4), 2013, pp. 285-290.
  5. GHASEMZADEH, F., N. P. ARCHER, P. IYOGUN, A Zero-one Model for Project Portfolio Selection and Scheduling, Journal of Operational Research Society, vol. 50(7), 1999, pp. 745-755.
  6. ARCHER, N. P., F. GHASEMZADEH, Project Portfolio Selection through Decision Support. Decision Suport Systems, vol. 29, 2000, pp. 73-88.
  7. HEIDENBERGER, K., C. STUMMER, Research and Development Project Selection and Resource Allocation: A Review of Quantitative Modelling Approaches, Intl. Journal of Management Reviews, vol. 1, 1999, pp. 197-224.
  8. JADHAV, A. S., R. M. SONAR, Evaluating and Selecting Software Packages: A Review, and Software Technology, vol. 51, 2009, pp. 555-563.
  9. CHEIKHROUHOU, N., S. S. KARA, A Multi-criteria Group Decision Making Approach for Collaborative Software Selection Problem, Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, vol. 26(1), 2014, pp. 37-47.
  10. KARSAK, E. E., C. O. OZOGUL, An Integrated Decision Making Approach for ERP System Selection, Expert Systems with Applications, vol. 36, 2009, pp. 660-667.
  11. AHMAD, R., S. U. KHAN, M. NIAZI, Factors Influencing Clients in the Selection of Offshore Software Outsourcing Vendors: An Exploratory Study using a Systematic Literature Review, Journal of Systems and Software, 84(4), 2011, pp. 686-699.
  12. AHMAD, R., S. U. KHAN, M. NIAZI, Barriers in the Selection of Offshore Software Development Outsourcing Vendors: An Exploratory Study using a Systematic Literature Review, Information and Software Technology, 53(7), 2011, pp. 693-706.
  13. MARKOWITZ, H. M., Portfolio selection, The Journal of Finance, vol. 7, issue 1, 1952, pp. 77-91.
  14. MARKOWITZ, H. M., Portfolio Selection: Efficient Diversification of Investments, New York: John Wiley & Sons, 2nd ed. Basil Blackwell, 1991.
  15. POPESCU, C. C., C. FULGA, Possibilistic Optimization with Application to Portfolio Selection, Proceedings of the Romanian Academy, Series A – Mathematics, Physics, Technical Sciences, Information Science, vol. 12, issue 2, 2011, pp. 88-94.
  16. RĂDULESCU, C. Z., M. RĂDULESCU, Decision Analysis for the Project Selection Problem under Risk, 9-th IFAC/IFORS/ IMACS /IFIP Symposium On Large Scale Systems: Theory And Applications, Bucharest, 2001, 243-248.
  17. RADULESCU, M., C. Z. RADULESCU, Project Portfolio Selection Models and Decision Support, Studies in Informatics and Control, vol. 10(4), 2001, pp. 275-286.
  18. RADULESCU, M., S. RADULESCU, C. Z. RADULESCU, Mathematical Models for Optimal Asset Allocation (ROU), Editura Academiei Române, Bucureşti, 2006.
  19. RADULESCU, C. Z., M. RADULESCU, A Decision Support Tool based on a Portfolio Selection Model for Crop Planning under Risk, Studies in Informatics and Control, 21(4), 2012, pp. 377-382.
  20. RADULESCU, M., C. Z. RADULESCU, Mean-Variance Models with Missing Data, Studies in Informatics and Control, vol. 22 (4), 2013, pp. 299-306.
  21. RADULESCU, M., C. Z. RADULESCU, Gh. ZBAGANU, A Portfolio Theory Approach to Crop Planning under Environmental Constraints, of Op. Res., vol. 219, 2014, pp. 243-264.
  22. BAEK, K., C. SUH, E. SUH, Prioritizing Telecommunications Technologies for Long-range R&D Scheduling to the Year 2006, IEEE Trans. on Eng. Man., vol. 41(3), 1994, pp. 264-275.
  23. WANG, C. H., Using Quality Function Deployment to Conduct Vendor Assessment and Supplier Recommendation for Business-Intelligence Systems, Computers & Industrial Engineering, 84, 2015, pp. 24-31.
  24. WEBER, R., B. WERNERS, H. J. ZIMMERMANN, Scheduling Models for Research and Development, European Journal of Operational Research, 48, 1990, pp.175-188.
  25. YUEN, K. K. F., H. C. W. LAU, Software Vendor Selection using Fuzzy Analytic Hierarchy Process with ISO/IEC 9126, IAENG International Journal of Computer Science, vol. 35(3), 2008, pp. 267-274. Retrieved from http://www.iaeng.org/IJCS/ issues_v35/issue_3/IJCS_35_3_03.pdf.