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Analysis of Sustainable Procurement in SMEs in Developing Countries

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  • MUKHERJEE, KRISHNENDU

Abstract

The purpose of the paper is to integrate supply base consolidation, rationalization, and buyer’s perspective about its suppliers to reveal more insight to implement sustainable procurement in small and medium enterprises (SMEs) in developing countries like India. In this paper an attempt has been made to integrate Constrained Optimization of Frobenius Norm by Genetic Algorithm (COFGA) with traditional spend, and value risk analysis to consolidate and rationalize supply base w.r.t fifteen triple bottom line indicators (TBL). This paper shows that spend analysis is justified in crisp domain and becomes myopic in limited data environment. Spend analysis becomes more ineffective to deal imprecise and vague qualitative data. Integrated approach of multiple criteria decision analysis,spend analysis, and value risk analysis, thus, an alternative approach to give better insight to sustainable procurement in fuzzy environment. Finally, a case study is discussed to use proposed method.

Suggested Citation

  • Mukherjee, Krishnendu, 2019. "Analysis of Sustainable Procurement in SMEs in Developing Countries," MPRA Paper 93277, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:93277
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    File URL: https://mpra.ub.uni-muenchen.de/93277/1/MPRA_paper_93277.pdf
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    References listed on IDEAS

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    1. Handfield, Robert & Walton, Steven V. & Sroufe, Robert & Melnyk, Steven A., 2002. "Applying environmental criteria to supplier assessment: A study in the application of the Analytical Hierarchy Process," European Journal of Operational Research, Elsevier, vol. 141(1), pages 70-87, August.
    2. Lutz Preuss, 2007. "Buying into our future: sustainability initiatives in local government procurement," Business Strategy and the Environment, Wiley Blackwell, vol. 16(5), pages 354-365, July.
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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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