Purpose
– The purpose of this paper is to develop a systematic and comprehensive project selection model utilizing fuzzy multi-objective linear programming (FMOLP) that deals with the imprecise data in IS projects and uncertain judgment of decision makers.
Design/methodology/approach
– First, projects are prioritized by considering both quantitative and qualitative factors. A fuzzy analytical hierarchical process (FAHP) is used in order to obtain weights of each project that indicates their priorities. At the second step, project selection decision is completed by using FMOLP. Then, the sensitivity analysis is performed to evaluate the robustness of the proposed integrated model.
Findings
– The result of this study indicates that an integrated approach utilizing FAHP and FMOLP can be used as a supportive tool for project selection in IS context. It decreases the uncertainty caused from uncertain judgment of decision makers.
Research limitations/implications
– Future studies are suggested to design models having fuzzy constraints such as budget and resources. Moreover, for future studies, non-linear membership functions can be used.
Practical implications
– Actual projects are provided from the Turkish IS company for prioritizing process and a hypothetical mathematical model is demonstrated using illustrative data.
Originality/value
– This study contributes to the relevant literature by proposing a comprehensive model considering many conflicting ideas of decision makers on quantitative and qualitative criteria, and evaluating projects in an integrated way including FAHP and FMOLP.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.