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Modeling Supply Chain Performance: A Structural Equation Approach

Author

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  • Rajwinder Singh

    (School of Management Studies, Punjabi University, Patiala, Punjab, India)

  • H. S. Sandhu

    (Department of Commerce and Business Management, Guru Nanak Dev University, Amritsar, Punjab, India)

  • B. A. Metri

    (Management Development Institute, Gurgaon, Haryana, India)

  • Rajinder Kaur

    (Department of Management Studies, Malout Institute of Management and Information Technology, Malout, Punjab, India)

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.

Suggested Citation

  • Rajwinder Singh & H. S. Sandhu & B. A. Metri & Rajinder Kaur, 2013. "Modeling Supply Chain Performance: A Structural Equation Approach," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 6(4), pages 18-41, October.
    • Handle: RePEc:igg:jisscm:v:6:y:2013:i:4:p:18-41
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