عنوان مقاله [English]
Regarding the complexity of IT service management (ITSM), the purpose of this study is to provide a mathematical model for evaluating and selecting ITSM solution In this research, a new classification of functional and non-functional requirements as well as a fuzzy multi-objective model is presented. The functional requirements derived from the ITIL processes generally include: strategic requirements, design, transfer, operation, and continuous service improvement. In addition, three requirements for availability, capacity and occurrence were carefully examined. a total of 64 criteria for assessing ITSM systems are provided. The developed models with fuzzy approach also include 5 objective and 7 constraints that were implemented with fuzzy multi-objective Techniques. The proposed model was used to evaluate and select the software in the IT service provider company. The proposed model not only helps the organization to choose the best supplier, but also helps identify the supplier's weaknesses, reduce decision-making time, and increase the accuracy and ease of decision-making. The results of the methods that used to solved the model show that the MOPSO algorithm has the best result than the other three ones. Respectively NSGA2, Goal programming and epsilon constraint were ranked in the following order.
Andrews, A. A., Beaver, P., & Lucente, J. 2016. Towards better help desk planning: Predicting incidents and required effort. Journal of Systems and Software, 117: 426-449.
A.CharnesandW.W.Cooper. 1961. Management Models and Industrial Applications of Linear Programming, volume 1. New York: John Wiley & Sons.
Black, J, Draper, C, Lococo, T, Matar, F & Ward, C. 2007, An integration model for organizing IT service management, IBM Systems Journal, 46, )3(: 405-22..
Bosse, S., Splieth, M., & Turowski, K. 2016. Multi-objective optimization of IT service availability and costs. Reliability Engineering & System Safety, 147: 142-155.
Cochran, J. K., & Chen, H.-N. 2005. Fuzzy multi-criteria selection of object-oriented simulation software for production system analysis. Computers & operations research, 32(1): 153-168.
Collier, K., Carey, B., Sautter, D., & Marjaniemi, C. 1999. A methodology for evaluating and selecting data mining software. Paper presented at the Systems Sciences, 1999. HICSS-32. Proceedings of the 32nd Annual Hawaii International Conference on.
Colombo, E., & Francalanci, C. 2004. Selecting CRM packages based on architectural, functional, and cost requirements: Empirical validation of a hierarchical ranking model. Requirements Engineering, 9(3): 186-203.
Cooper, H., 2010. Applied social research methods series: Vol. 2. Research synthesis and meta-analysis: A step-by-step approach . Thousand Oaks, CA, US.
Davis, L., & Williams, G. 1994. Evaluating and selecting simulation software using the analytic hierarchy process. Integrated manufacturing systems, 5(1): 23-32.
Deb, K., 2014. Multi-objective optimization. In Search methodologies (pp. 403-449). Springer, Boston, MA.
Denyer, D., & Tranfield, D. 2006. Using qualitative research synthesis to build an actionable knowledge base. Management Decision, 44(2): 213-227.
Grönroo. 2008. Service logic revisited: who creates value? And who co-creates?,
European Business Review, 20 (4): 298-314
Jarke, M., & Vassiliou, Y. 1985. A framework for choosing a database query language. ACM Computing Surveys (CSUR), 17(3): 313-340.
Kara, S. S., & Cheikhrouhou, N. 2014. A multi criteria group decision making approach for collaborative software selection problem. Journal of Intelligent & Fuzzy Systems, 26(1): 37-47.
Kannan, D., Khodaverdi, R., Olfat, L., Jafarian, A., & Diabat, A. 2013. Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain. Journal of Cleaner Production, 47: 355-367.
Keel, AJ, Orr, MA, Hernandez, RR, Patrocinio, EA & Bouchard, J. 2007. From a technology-oriented to a service-oriented approach to IT management, IBM Systems Journal, vol. 46, no. 3: 549-64
Kilic, H. S., Zaim, S., & Delen, D. 2014. Development of a hybrid methodology for ERP system selection: The case of Turkish Airlines. Decision Support Systems, 66: 82-92.
Konak, A., Coit, D. W., & Smith, A. E. 2006. Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering & System Safety, 91(9): 992-1007.
L. Hunnebeck. 2010. ITIL Service Design 2011 Edition, The Stationery Office, Norwich, UK,
Le Blanc, L. A., & Jelassi, M. T. 1989. DSS software selection: a multiple criteria decision methodology. Information & Management, 17(1): 49-65.
Lovelock, Christopher .1991. Services Marketing. Englewood Cliffs, NJ: Prentice Hall
McKibbon, A. 2006. Systematic reviews and librarians. Library Trends, 55(1): 202-215.
Morera, D. 2002. COTS evaluation using DESMET methodology & analytic hierarchy process (AHP). Paper presented at the International Conference on Product Focused Software Process Improvement.
Mostaghim, S., & Teich, J. 2003. Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO). In Swarm Intelligence Symposium, 2003. SIS'03. Proceedings of the 2003 IEEE (pp. 26-33). IEEE.
Ngai, E. W., & Chan, E. 2005. Evaluation of knowledge management tools using AHP. Expert systems with applications, 29(4): 889-899.
Office of Government Commerce (OGC). 2011. ITIL® Service Design.
Oh, K. S., Lee, N. Y., & Rhew, S. Y. 2003. A selection process of COTS components based on the quality of software in a special attention to internet. Paper presented at the International Conference Human Society@ Internet.
Orta, E., Ruiz, M., Hurtado, N., & Gawn, D. 2014. Decision-making in IT service management: a simulation based approach. Decision Support Systems, 66: 36-51.
Ossadnik, W., & Lange, O. 1999. AHP-based evaluation of AHP-Software. European journal of operational research, 118(3): 578-588.
Perez, M., & Rojas, T. 2000. Evaluation of Workflow-type software products: a case study. Information and software technology, 42(7): 489-503.
Pultorak, D, Henry, C & Leenards, P 2008, MOF 4.0: Microsoft operations framework 4.0, Van Haren Publishing, Zaltbommel.
Rouhani, S., & Ravasan, A. Z. 2014. A Fuzzy TOPSIS based Approach for ITSM Software Selection. International Journal of IT/Business Alignment and Governance (IJITBAG), 5(2): 1-26.
Rouhani, S., & Ravasan, A. Z. 2015. Multi-objective model for intelligence evaluation and selection of enterprise systems.International Journal of Business Information Systems, 20(4): 397-426.
Rouhani, S. and Zare Ravasan, A., 2017. Fuzzy TOPSIS evaluation approach for business process management software acquisition. Intelligent Automation & Soft Computing, 23(3): 459-468.
Rouhani, S. 2017. A fuzzy superiority and inferiority ranking based approach for IT service management software selection. Kybernetes, 46(4): 728-746.
Sanders, G. L., Ghandforoush, P., & Austin, L. M. 1983. A model for the evaluation of computer software packages. Computers & Industrial Engineering, 7(4): 309-315.
Sarkis, J., & Talluri, S. 2004. Evaluating and selecting e-commerce software and communication systems for a supply chain. European journal of operational research, 159(2): 318-329.
Shtub, A., Spiegler, I., & Kapeliuk, A. 1988. Using DSS methods in selecting operations management software. Computer Integrated Manufacturing Systems, 1(4): 211-220.
Siewiorek, D. P., & Swarz, R. S. 1982. The theory and practice of reliable system design. Digital press.
Solomon, M. R., Surprenant, C., Czepiel, J. A., & Gutman, E. G. 1985. A role theory perspective on dyadic interactions: the service encounter. The Journal of Marketing: 99-111.
Teltumbde, A. 2000. A framework for evaluating ERP projects. International journal of production research, 38(17): 4507-4520.
Tewoldeberhan, T. W., Verbraeck, A., Valentin, E., & Bardonnet, G. 2002. Software evaluation and selection: an evaluation and selection methodology for discrete-event simulation software. Paper presented at the Proceedings of the 34th conference on winter simulation: exploring new frontiers.
Tranfield, D., Denyer, D., & Smart, P. 2003. Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. British journal of management, 14(3): 207-222
Van Bon, J. 2007. Foundations of IT service management based on ITIL v3, 1st edn, Van Haren Publishing, Zaltbommel, Netherlands.
Vargo, S. L., & Lusch, R. F. 2004. The four service marketing myths remnants of a goods-based, manufacturing model. Journal of service research, 6(4): 324-335.
Tweney, D. 2013. 5-minute outage costs Google $545,000 in revenue. http://venturebeat. Com/2013/08/16/3-minute-outage-costs-google-545000-in-revenue..
Winniford, M, Conger, S & Erickson-Harris, L. 2009. Confusion in the Ranks: IT Service Management Practice and Terminology, Information Systems Management, 26( 2): 153-63
Hossein Razavi Hajiagha, S., Amoozad Mahdiraji, H., & Sadat Hashemi, S. 2013. Multi-objective linear programming with interval coefficients: A fuzzy set based approach. Kybernetes, 42(3): 482-496
Oliveira, C., & Antunes, C. H. 2007. Multiple objective linear programming models with interval coefficients–an illustrated overview. European journal of operational Research, 181(3): 1434-1463.