The aim of this study is to propose an integrated Analytic Hierarchy Process (AHP) and Weighted Additive Fuzzy Goal Programming (WAFGP) method for the selection of information system projects that can use all types of linear membership functions and offer more flexibility. The proposed methodology includes three steps. First, an expert team was formed to identify the decision criteria and build a hierarchical model for the information system project selection. Then, the AHP was used to estimate the relative weights of the criteria. Finally, a WAFGP model was formulated and used to select the projects. A hypothetical example is given to show how to use this methodology and its advantages. In comparison to other approaches, the AHP-WAFGP hybrid model gives better support for information system project selection by selecting projects that make the best use of available resources and better satisfy the decision goals. Furthermore, the sensitivity analysis reveals that the proposed model is robust, adaptable, and not sensitive to small changes. Nevertheless, the proposed methodology does not include interdependencies among criteria and alternatives.
Information system, project selection, AHP, Weighted Additive Fuzzy Goal Programming
Alava, M. V., Figueroa, S. D., Alcivar, H., & Vazquez, M. (2019). Single valued neutrosophic numbers and analytic hierarchy process for project selection. Neutrosophic Sets and Systems, 21(1), 122-130. doi: https://digitalrepository.unm.edu/nss_journal/vol21/iss1/13
Almajali, D.A., Masa’deh, R., & Tarhini, A. (2016). Antecedents of ERP systems implementation success: a study on Jordanian healthcare sector. Journal of Enterprise Information Management, 29(4), 549-565. doi: https://doi.org/10.1108/JEIM-03-2015-0024
Al-Rafaie, A. (2015). A proposed weighted additive model to optimize multiple quality responses in the Taguchi method with applications. Journal of Process Mechanical Engineering, 229(3), 168-178. doi: https://doi.org/10.1177/0954408913513757
Atkinson, M., Bayazit, O., & Karpak, B. (2015). A case study using the analytic hierarchy process for IT outsourcing decision making. International Journal of Information Systems and Supply Chain Management, 8(1), 60-84. doi: https://doi.org/10.4018/ijisscm.2015010104
Badri, M. A., Davis, D., & Davis, D. (2001). A comprehensive 0-1 goal programming model for project selection. International Journal of Project Management, 19, 243-252. doi: https://doi.org/10.1016/S0263-7863(99)00078-2
Bahurmoz, A.M. (2019). Measuring corporate social responsibility performance: A comprehensive AHP based index. International Journal of the Analytic Hierarchy Process, 11(1), 20-41. doi: https://doi.org/10.13033/ijahp.v11i1.608
Bolat, B., Çebi, F., Temur, G. T., & Otay, ?. (2014). A fuzzy integrated approach for project selection. Journal of Enterprise Information Management, 27(3), 247-260. doi: https://doi.org/10.1108/JEIM-12-2013-0091
Brownsell, S., Blackburn, S., & Hawley, M. (2012). User requirements for an ICT-based system to provide care, support and information access for older people in the community. Journal of Assistive Technologies, 6(1), 5-23. doi: http://dx.doi.org/10.1108/17549451211214328
Burkland, S. & Zachariassen, F. (2014). Developing an ERP technology: handling incompleteness of the system. Scandinavian Journal of Management, 30(4), 409-426. doi: https://doi.org/10.1016/j.scaman.2014.08.009
Buss, M. J. (1983). How to rank computer projects. Harvard Business Review, 61(1), 118–125.
Cabala, P. (2010). Using the analytic hierarchy process in evaluating decisions alternative. Operational Research and Decision, 1, 5-23.
Chang, H. H. & Wong, K. H. (2010). Adoption of e-procurement and participation of e-marketplace on firm performance: Trust as a moderator. Information & Management, 47, 262–270. doi : https://doi.org/10.1016/j.im.2010.05.002
Chen, J., Zhang, W., Li, J., Zhang, W., Liu, Y., Zhao, B., & Zhang, Y. (2018). Optimal sizing for Grid-Tied Microgrids with consideration of joint optimization of planning and operation. IEEE Transactions on Sustainable Energy, 9(1), 237-248. doi: https://doi.org/10.1109/TSTE.2017.2724583
Chena, C. T. & Chengb, H. L. (2009). A comprehensive model for selecting information system project under fuzzy environment. International Journal of Project Management, 27(04), 389–399. doi: https://doi.org/10.1016/j.ijproman.2008.04.001
Chiang, R. H., Grover, V., Liang, T.-P., & Guest, D. Z. (2018). Strategic value of Big Data and business analytics. Journal of Management Information Systems, 35(2), 383-387. doi: http://dx.doi.org/10.1080/07421222.2018.1451950
Chuang, S.-H. & Lin, H.-N. (2017). Performance implications of information-value offering in e-service systems: Examining the resource-based perspective and innovation strategy. Journal of Strategic Information Systems, 26(1), 22-38. doi: https://doi.org/10.1016/j.jsis.2016.09.001
Clegg, C., Axtell, C., Damodaran, L., & Farbey, B. (1997). Information technology: a study of performance and the role of human and organizational factor. Ergonomics, 40(9), 851-872. doi: https://psycnet.apa.org/doi/10.1080/001401397187694
Deng, X., Doll, W. J., Al-Gahtani, S., Larsen, T. J., Pearson, J. M., & Raghunathan, T. S. (2008). A cross-cultural analysis of the end-user computing satisfaction instrument: A multi-group invariance analysis. Information & Management, 45, 211–220. doi : https://doi.org/10.1016/j.im.2008.02.002
Díaz-Madroñero, M., Pérez-Sánchez, M., Satorre-Aznar, J.R., Mula, J., & López-Jiménez, A. (2018). Analysis of a wastewater treatment plant using fuzzy goal programming as a management tool: A case study. Journal of Cleaner Production, 180, 20-33. doi: https://doi.org/10.1016/j.jclepro.2018.01.129
Ebrahimnejad, S., Mousavi, S.M., Tavakkoli-Moghad, R., Hashemi, H., & Vahdani, B. (2012). A novel two-phase group decision making approach for construction project selection in a fuzzy environment. Applied Mathematical Modelling, 36, 4197–4217. doi: https://doi.org/10.1016/j.apm.2011.11.050
Elahi, S., Shamsi, Z., & Ghatari, A. (2016). A hybrid selection method on information system development projects. International Journal of Business Information Systems, 22(4), 495-515. doi: https://doi.org/10.1504/IJBIS.2016.077840
Gerogiannis, V. C., Fitsilis, P., & Kameas, A. D. (2013). Evaluation of project and portfolio management information systems with the use of a hybrid IFS-TOPSIS method. Intelligent Decision Technologies, 7, 91-105. doi: https://doi.org/10.3233/IDT-120153
Islam, R. & Anis, A. (2015). The application of analytic hierarchy process in higher-learning institutions: a literature review. Journal of International Business and Entrepreneurship Development, 8(2), 166-182. doi: https://doi.org/10.1504/JIBED.2015.070446
Kang, Y., O’Brien, W. J., & Mulva, S.P. (2013). Value of IT: Indirect impact of IT on construction project performance via best practices. Automation in Construction, 35, 383–396. doi: http://dx.doi.org/10.1016/j.autcon.2013.05.011
Keeney, R. L. & Raiffa, H. (1978). Decisions with multiple objectives: preferences and value trade-offs. New York: Wiley.
Kim, I., Shin, S., Choi, Y., Thang, N. M., Ramos, E.R., & Hwang, W.J. (2009). Development of a project selection method on information system using ANP and fuzzy logic. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 3(5), 1286-1291.
Kim, J. S. & Whang, K. S. (1998). A tolerance approach to the fuzzy goal programming problems with unbalanced triangular membership function. European Journal of Operational Research, 107(3), 614-624. doi: https://doi.org/10.1016/S0377-2217(96)00363-3
King, J. L. & Schrems, E. L. (1978). Cost-benefit analysis in information systems development and operation. ACM Computing Surveys, 10(1), 19–34. doi: https://doi.org/10.1145/356715.356718
Lee, J. W. & Kim, S. H. (2001). An integrated approach for interdependent information system project selection. International Journal of Project Management, 19, 111-118. doi: https://doi.org/10.1016/S0263-7863(99)00053-8
Leyva-Vazquez, M., Quiroz-Martinez, M. A., Portilla-Castell, Y., Hechavarría-Hernández, J. R., & González-Caballero, E. (2020). A new model for the selection of information technology project in a neutrosophic environment. Neutrosophic Sets and Systems, 32(1), 344-360. doi: https://digitalrepository.unm.edu/nss_journal/vol32/iss1/22
Li, K. W., Wang, Z. J., & Tong, X. (2016). Acceptability analysis and priority weight elicitation for interval multiplicative comparison matrices. European Journal of Operational Research, 250(2), 628-638. doi: https://doi.org/10.1016/j.ejor.2015.09.010
Liang, C. & Li, Q. (2008). Enterprise information system project selection with regard to BOCR. International Journal of Project Management, 26(8), 810-820. doi: https://doi.org/10.1016/j.ijproman.2007.11.001
Liang, T.F. & Cheng, H.F. (2009). Application of fuzzy sets to manufacturing/distribution planning decisions with multi-product and multi-time period in supply chains. Expert Systems with Applications, 36, 3367–3377. doi: https://doi.org/10.1016/j.eswa.2008.01.002
Lootsma, F. A., Mensch, T. A., & Vos, F. D. (1990). Multi-criteria analysis and budget reallocation in long-term research planning. European Journal of Operational Research. 47(3), 293-305. doi: https://doi.org/10.1016/0377-2217(90)90216-x
Lu, X. H., Huang, L. H., & Heng, M. S. (2006). Critical success factors of inter-organizational information systems; A case study of Cisco and Xiao Tong in China. Information & Management (43), 395–408. doi : https://doi.org/10.1016/j.im.2005.06.007
Lu, Y. & Ramamurthy, K. (2011). Understanding the link between information technology capability and organizational agility: An empirical examination. MIS Quarterly, 35(4), 931–954. doi: https://doi.org/10.2307/41409967
Lucas, H. C. & Moore, J. R. (1976). A multiple criterion scoring approach to reformation system project selection. INFOR, 14(1), 1-12. doi: https://doi.org/10.1080/03155986.1976.11731622
Mikalef, P. & Pateli, A. (2017). Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: Findings from PLS-SEM and fsQCA, Journal of Business Research, 70, 1-16. doi: http://dx.doi.org/10.1016/j.jbusres.2016.09.004
Moreno-Jiménez, J. & Vargas, L. (2018). Cognitive multiple criteria decisions making and the legacy of the Analytic Hierarchy Process. Estudios De Economía Aplicada, 36(1), 67-80. doi: https://doi.org/10.25115/eea.v36i1.2516
Muralidhar, K., Santhnanm, R., & Wilson, R. L. (1990). Using the analytic hierarchy process for information system project selection. Information & Management, 18(1), 87-95. doi : https://doi.org/10.1016/0378-7206(90)90055-M
Ohta, R., Salomon, V., & Silva, M.B. (2018). Selection of industrial maintenance strategy: Classical AHP and Fuzzy AHP applications. International Journal of the Analytic Hierarchy Process, 10(2), 254-265. doi: https://doi.org/10.13033/ijahp.v10i2.551
Okumus, F., Bilgihan, A., Ozturk, A.B., & Zhao, X. (2017). Identifying and overcoming barriers to deployment of information technology projects in hotels. Journal of Organizational Change Management, 30(5), 744-766. doi: https://doi.org/10.1108/JOCM-12-2015-0239
OuYang, Y.C. (2017). Information system capabilities and organizational performance: comparing three models. Pacific Asia Journal of the Association for Information Systems, 9(1), 1-28. doi: https://doi.org/10.17705/1pais.09101
Pan, S. L., Pan, G., & Devadoss, P. R. (2008). Managing emerging technology and organizational transformation: An acculturative analysis. Information & Management, 45, 153–163. doi: https://doi.org/10.1016/j.im.2007.11.003
Porter, M. & Millar, V. E. (1985). How information technology gives you competitive advantage. Harvard Business Review, 63(4), 149-161. doi: https://hbr.org/1985/07/how-information-gives-you-competitive-advantage[28/11/2016
Ray, G., Muhanna, W. A., & Barney, J. (2005). Information, technology and the performance of the customer service process: a resource-based analysis. MIS Quarterly, 29(4), 625–651. doi: https://www.jstor.org/stable/25148703.
Rouyendegh, B.D. & Erkan T.E. (2011). ERP system selection by AHP method: Case study from turkey international. Journal of Business and Management Studies, 3(1), 39-48.
Saaty, T. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9-26. doi: https://doi.org/10.1016/0377-2217(90)90057-I
Saaty, T. L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill
Saaty, T. L. (1991). Some mathematical concepts of the analytic hierarchy process. Behaviormetrica, 18(29), 01-09. doi: https://doi.org/10.2333/bhmk.18.29_1
Saaty, T. L. (1996). Decision making with dependence and feedback: The analytic network process. Pittsburgh: RWS Publications.
Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83–98. doi: https://doi.org/10.1504/IJSSCI.2008.017590
Saaty, T. & Vargas, L. (2012). Models, methods, concepts & applications of the analytic hierarchy process. Springer Science and Business Media.
Samvedi, A., Jain., V., Chan, F.T.S., & Chung, S.H. (2018). Information system selection for a supply chain based on current trends: the BRIGS approach. Neural Computing & Applications, 30, 1619–1633. doi: https://link.springer.com/article/10.1007%2Fs00521-016-2776-8
Santhanam, R., Muralidhar, K., & Shniederjans, M. (1989). A zero-one goal programming approach for information system project selection. OMEGA International Journal of Mgmt, 17(6), 583-593. doi: https://doi.org/10.1016/0305-0483(89)90062-5
Santhanam, R. & Kyparisis, G. J. (1995). A multiple criteria decision model for information system project selection. Computers and Operations Research, 22(8), 807-825. doi: https://doi.org/10.1016/0305-0548(94)00069-K
Santhanam, R. & Kyparisis, G. J. (1996). A decision model for interdependent information system project selection. European Journal of Operational Research, 89, 380-399. doi: https://doi.org/10.1016/0377-2217(94)00257-6
Schniederjans, M. J. & Santhanam, R. (1993). A multi-objective constrained resource information system project selection method. European Journal of Operational Research, 70, 244-297. doi: https://doi.org/10.1016/0377-2217(93)90042-L
Schniederjans, M. J. & Wilson, R. L. (1991). Using the analytic hierarchy process and goal programming for information system project selection. Information & Management North-Holland, 20, 333-342. doi: https://doi.org/10.1016/0378-7206(91)90032-W
Sharma, M. J., Moon, I., & Bae, H. (2008). Analytic hierarchy process to assess and optimize distribution network. Applied Mathematics and Computation, 202, 256-265. doi: https://doi.org/10.1016/j.amc.2008.02.008
Strassmann, P. A. (1990). The business value of computer. New Canaan, Connecticut: Information Economics Press.
Strassmann, P. A. (1997). The squandered computer. New Canaan, Connecticut: The Information Economic Press.
Tajudeen, F.P., Jaafar, N.I., & Ainin, S. (2018). Understanding the impact of social media usage among organizations. Information & Management, 55(3), 308-321. doi: https://doi.org/10.1016/j.im.2017.08.004
Tamiz, M. & Yaghoobi, M. (2010). Nurse scheduling by fuzzy goal programming, new developments in multiple objective and goal programming. Lecture Notes in Economics and Mathematical Systems, 638, 151-163. doi: https://doi.org/10.1007/978-3-642-10354-4_11
Tarafdar, M. & Qrunfleh, S. (2017). Agile supply chain strategy and supply chain performance: complementary roles of supply chain practices and information systems capability for agility. International Journal of Production Research, 55(4), 925-938. doi: https://doi.org/10.1080/00207543.2016.1203079
The Standish Group. (2010). CHAOS Summary 2009. Boston: The Standish Group International. https://www.classes.cs.uchicago.edu/archive/2014/fall/51210-1/required.reading/Standish.Group.Chaos.2009.pdf
Toloo, M. & Mirbolouki, M. (2019). A new project selection method using Data Envelopment Analysis. Computers & Industrial Engineering, 138, 1-28. doi: https://doi.org/10.1016/j.cie.2019.106119
Toloo, M., Nalchigar, S., & Sohrabi, B. (2018). Selecting most efficient information system projects in presence of user subjective opinions: a DEA approach. Central European Journal of Operations Research, 26, 1027–1051. doi: https://doi.org/10.1007/s10100-018-0549-4
Torabi, S.A. & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 159, 193–214. doi: https://doi.org/10.1016/j.fss.2007.08.010
Vaidya, O.S. & Kumar, S. (2006). Analytic hierarchy process: An overview of applications. European Journal of Operational Research, 169(1), 1–29. doi: https://doi.org/10.1016/j.ejor.2004.04.028
Wang, E. G., Ju, P. H., Jiang, J. J., & Klein, G. (2008). The effects of change control and management review on software flexibility and project performance. Information & Management, 45, 438–443. doi : https://doi.org/10.1016/j.im.2008.05.003
Weber, Y. & Pliskin, N. (1996). The effects of information systems integration and organizational culture on a firm's effectiveness. Information & Management, 30, 81-90. doi : https://doi.org/10.1016/0378-7206(95)00046-1
Yaghoobi, M. A., Jones, D. F., & Tamiz, M. (2008). Weighted additive models for solving fuzzy goal programming problems. Asia-Pacific Journal of Operational Research, 25, 715-733. doi: https://doi.org/10.1142/S0217595908001973
Yepez, S.L.T. (2017). Decision support based on single valued neutrosophic number for information system project selection. Neutrosophic Sets and Systems, 17(1), 37-41. doi: https://digitalrepository.unm.edu/nss_journal/vol17/iss1/7
Zandi, F. & Tavana, M. (2010). A multi-attribute group decision support system for information technology project selection. International Journal of Business Information Systems, 6(2), 179–199. doi: https://doi.org/10.1504/IJBIS.2010.034353
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