A hybrid approach for modeling the key performance indicators of information facilitated product recovery system

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.

Business Process Linguistic Modeling: Theory and Practice Part I: BPLM Strategy Creator

“…Then an organization effectively tracks the performance of a company's goal and delivers analytic recommendations for future strategies [30].…”

“…The KPI indicators postulated for strategic management level are represented by formulas (25,26,28,29) and (30) create basis for their further decomposition related to tactic management level, where we are operating with main business processes subordinated to appropriate core processes implemented and operated at strategic management level. However, at that level should be the BSC perspectives respected as well.…”

“…At the strategic management level, the Production main process might be quantified via {[PROD (i, j 1 )]} linguistic set and two KPI indicators could be postulated, which indicate that process functionality (performance) (see also formulas (28) and (29) and (30 In order to create a complex set of KPI indicators related to business processes implemented and operated at tactic and operational management level, an appropriate decomposition of primary KPI indicators related to performance of those processes to should be done. However, the KPI indicator decomposition for tactic level will be explained based on Consideration 3 and the KPI indicator decomposition for operational level will be explained based on Consideration 4 as well, while the Consideration no.…”

“…At the strategic management level, the Production main process might be quantified via {[PROD (i, j 1 )]} linguistic set and two KPI indicators could be postulated, which indicate that process functionality (performance) (see also formulas (28) and (29) and (30).…”

“…The KPI indicators postulated for strategic management level are represented by formulas (25, 26, (28, 29) and (30)…”