Decision Analytics for Operations Management: An Interval-Valued Spherical Fuzzy Framework for Evaluating Inventory Management Platforms

Purpose: Evaluating inventory management systems is a critical decision-making problem for businesses in almost every industry, as it significantly affects their business models and operational processes. Nevertheless, essential gaps in the relevant literature still need to be addressed. To fill the gaps, the current paper introduces an interval-valued spherical fuzzy (IVSF) decision tool based on preference selection index (PSI) and operational competitiveness ratings analysis (OCRA) methods for evaluating inventory management system platforms. Design/methodology/approach : One of the primary novelties of the work is to develop IVSF-PSI and IVSF-OCRA models, thus proposing IVSF-PSI-OCRA methodology for the first time in the literature for challenging decision-making problems. A case study on inventory management platform evaluation presents the suggested approach's applicability. IVSF-PSI is performed to determine the criteria weights, whereas IVSF-OCRA is employed to decide platforms’ rankings. Findings : The analysis results highlight that the weights of the 24 evaluation criteria are close. The first alternative is the best among the six options, followed by the third and second. The research findings particularly emphasize the complexity of inventory management systems and the multidimensional nature of evaluation criteria. Furthermore, the conclusions of an extensive robustness check confirm the validity and reliability of the suggested model. Originality/value : Developing IVSF-PSI, IVSF-OCRA, and IVSF-PSI-OCRA methodologies is the essential contribution of the study. Another significant contribution is applying the proposed model in evaluating the inventory management system. The research provides an innovative and multidimensional evaluation approach to selecting inventory management systems, valuable contributions for research community members focusing on the relevant literature, and for industry decision-makers. Research implications : The proposed methodology enhances the economic decision-making process in supply chains by facilitating a cost-efficient selection of inventory management platforms, enabling businesses to improve operational performance, minimize procurement and warehousing costs, and better align their supply-demand processes.