Evaluation and Prioritization of Sustainable Enterprise Resource Planning in SMEs Using q-Rung Orthopair Fuzzy Rough Set-Based Decision Support Model

Abstract

The firm requires multidisciplinary services, incorporated efforts and appropriate information to utilize effective sustainable enterprise resource planning systems (S-ERPSs). With the suitable S-ERPS, it is easy to give coordination between the items, reduce waste and take quicker and better decisions. Implementation of an effective S-ERPS is one of the major investment decisions for any firm, thus, the selection of suitable S-ERPS requires major attention from the experts. Due to involvement of several aspects of sustainability, the S-ERPS selection process can be considered as a complex uncertain multicriteria decision making problem. The aim of this article is to develop a four-stage hybrid decision support system (DSS) by integrating the symmetry point of criterion (SPC), ranking comparison (RANCOM) and multiattribute multiobjective optimization based on ratio assessment (MULTIMOORA) approaches with q-rung orthopair fuzzy rough set (q-ROFRS), named as q-ROFR-SPC-RANCOM-MULTIMOORA. The underlying DSS consists of four main stages: new q-ROFR-Hamacher aggregation operators are developed to aggregate the q-ROFRSs; q-ROFR-score rating and rank sum model is given to find the significance weights of decision experts; an integrated q-ROFR-SPC-RANCOM model is developed to determine the weights of sustainability dimensions and criteria for S-ERPSs; and a hybrid q-ROFR-MULTIMOORA model is presented to evaluate and rank the S-ERPSs. To exhibit the feasibility of developed DSS, a case study is discussed to evaluate the S-ERPS in small and medium sized enterprises (SMEs). The developed DSS effectively prioritized the S-ERPS options and recognized the suitable S-ERPS using the information obtained from various SMEs. In this article, the evaluation criteria are categorized into social, environmental and economic dimensions with the expert's opinions. The results indicate that cost, environmental grievance mechanisms and technical requirements are the most effective sustainable factors and SAP ERP is the most suitable alternative among others. The robustness and superiority of the developed DSS is evaluated by means of sensitivity and comparative analyses. It provides us a very useful approach for MADM in q-rung orthopair fuzzy rough environment.

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