Measuring supply chain knowledge management (SCKM) performance based on double/triple loop learning principle

Abstract

Purpose– The purpose of this paper is to propose performance measures for supply chain knowledge management (SCKM) performance.Design/methodology/approach– This is a conceptual study. State of performance measurement has been analyzed on the basis of a comprehensive review of literature in field of SCKM. Based on principles of double and triple loop learning, performance measures have been identified for measuring the success of KM practices in SCs.Findings– Principles of double and triple loop learning have been utilized to suggest KPI’s for SCKM performance, i.e. supply chain identity and knowledge supply chain stratum. The relevance and justification of these KPI’s is also discussed.Research limitations/implications– This study is limited to conceptualized measures for SCKM only. Further research is required to test the benefits of these performance measures based on industry applications.Practical implications– These proposed KPI’s will facilitate the development of the new processes through re-engineering, i.e. problem identification and then rectification. Further, these KPI’s will provide some essential insights as to how supply chains can develop their performance evaluation systems to become more effective and learning oriented.Originality/value– This study aims to not only identify the gaps present in the SCKM performance measurement literature but also aims to fill the knowledge gap by suggesting suitable performance metrics.