A hybrid approach for modeling the key performance indicators of information facilitated product recovery system. (3rd February 2020)

• Record Type: Journal Article
• Authors: Dwivedi, Ashish; Madaan, Jitender
• Is Part Of: Journal of modelling in management. Volume 15:Number 3(2020)
• Page Start: 933
• Page End: 965
• Publication Date: 2020-02-03
• Subjects: Information systems -- Product lifecycle -- Modeling -- Supply chain management; Industrial management -- Mathematical models -- Periodicals; Industrial management -- Computer simulation -- Periodicals; Business -- Mathematical models -- Periodicals; Business -- Computer simulation -- Periodicals; 658.4033
• DOI: 10.1108/JM2-01-2019-0003
• Languages: English
• ISSNs: 1746-5664

Abstract

Abstract : Purpose: This study aims to propose a comprehensive framework among Key Performance Indicators (KPIs) for analyzing the Information Facilitated Product Recovery System (IFPRS) on the basis of feedback captured from the industry experts and researchers. Design/methodology/approach: Total Interpretive Structural Modeling (TISM) methodology interspersed with fuzzy MICMAC is used to extract the interrelationships and develop a hierarchical structure among the identified KPIs. Further, the Fuzzy Decision-Making Trial and Evaluation Laboratory (F-DEMATEL) method has been enforced to determine the intensity of these relationships and identify the most influential KPIs among identified KPIs from literature review and expert opinions. The outcome indicates that "information sharing, " "technology capacity" and "technology standards such as EDI, RFID" are the KPIs that have attained highest driving power. Findings: This study has identified 15 KPIs of IFPRS and developed an integrated model using TISM and the fuzzy MICMAC approach, which is helpful to describe and organize the important KPIs and reveal the direct and indirect effects of each KPI on the IFPRS implementation. The integrated approach is developed, as the TISM model provides only binary relationship among KPIs, while fuzzy MICMAC analysis provides explicit analysis related to driving and dependence power of KPIs. Research limitations/implications: Structural Equation Modeling (SEM) analysis can be performed based on the adequate number of responses collected using structured questionnaire. More qualitative techniques like ELECTRE, TOPSIS, etc. can be used to establish the strength of relationship among the KPIs and ranking them to focus on the few critical KPIs. Practical implications: The proposed modeling could empower various governmental and non-governmental regulatory bodies in formulation of policies to effectively tackle the problem related to product recovery systems. This study has strong practical implications, for both practitioners as well as academicians. The practitioners need to concentrate on identified KPIs more cautiously during IFPRS implementation in their organizations and the top management could formulate strategy for implementing these KPIs obtained. Originality value: There is a lack of studies related to the modeling of KPIs of IFPRS. As vast information is essential about the products returned during different product recovery stages, this study bridges the gap in literature by providing a framework for KPIs related to IFPRS. It is expected that the results originated will assist the experts to relevantly identify the significant and drop insignificant KPI for successful product recovery implementation and performance improvement of IFPRS.