Modeling Supply Chain Performance: A Structural Equation Approach

Rajwinder Singh, Harpinder Sandhu, B Metri, Rajinder Kaur

    Research output: Contribution to journalArticle

    2 Citations (Scopus)

    Abstract

    Supply chain management (SCM) has become an effective tool now a day to survive in this competitive world. Organizations do their best to improve performance by adopting better supply chain (SC) performance indicators. In this paper 19 key performance indicators (KPI) were identified based on strong literature support in consultation of practitioners and consultants in the field of non-livestock retailing (NLR). NLR is the retailing of agriculture and horticulture products. The technique of factor analysis using principal component analysis with Varimax rotation has classified KPI into four factors as; inventory metrics, customer metrics, flexibility metrics and growth and learning metrics. Structural Equation Modelling (SEM) approach was used to develop and validate a model for measuring SC performance of organized NLR industry based on KPI. The data for analysis was collected from top 10 organized NLR players operating in Punjab, Chandigarh, New Delhi and Gurgaon in India. The results were subjected to rigorous statistical tests for reliability and validity. Finally, these classified KPI were presented in the form of a model to measure SC performance of organized NLR industry using SEM.

    Original languageEnglish
    Pages (from-to)18-41
    Number of pages24
    JournalSUPPLY CHAIN MANAGEMENT-AN INTERNATIONAL JOURNAL
    Volume6
    Issue number4
    DOIs
    Publication statusPublished - 2013

    Fingerprint Dive into the research topics of 'Modeling Supply Chain Performance: A Structural Equation Approach'. Together they form a unique fingerprint.

  • Cite this