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Development of Multi-Stage Supplier Performance Evaluation using DEA and Econometrics

Author Affiliations

  • 1Dept. of Management Studies, M.S. Ramaiah School of Adv. Studies, Bengaluru, Karnataka, INDIA
  • 2 Dept. of Automotive and Aeronautical Engg, M.S. Ramaiah School of Adv. Studies, Bengaluru, Karnataka, INDIA
  • 3 Department of Engineering Management, Coventry University, Coventry, UNITED KINGDOM

Res. J. Management Sci., Volume 1, Issue (2), Pages 8-14, September,6 (2012)


Many supply chain research schools believe “competition is no longer between companies; it is between supply chains”. In order to create agile supply chains, dynamic (time-dependent) performance evaluation system for assessing trading partners has become necessary. This has led to multi-stage development of mathematical models using inter-disciplinary approaches. In this study, Gear suppliers of a tiller and tractor manufacturing company have been considered. The proposed performance evaluation framework has been synthesized under five stages of model development using data envelopment analysis (DEA) and econometrics. Further, the multi-stage evaluation incorporates non-controllable and categorical formulation, which makes the model realistic from buyers’ perspective. Nonetheless, in the last stage of model development, an attempt to convert static to dynamic DEA model has been made considering inter-temporal effects between input-outputs. This effect has been captured as the lagged effect using Vector Auto Regression (VAR) model. Lastly, the proposed framework has been validated using system efficiency DEA model and Wilcoxon-Mann-Whitney rank sum test. Results have revealed that static evaluation overestimates dynamic evaluation by 4 to 5%. In addition, proposed dynamic evaluation system yielded better DEA results in terms of efficient Decision Making Units (DMUs) in numbers, average efficiency (~23%) and standard deviation (~38%). Therefore, multi-stage supplier performance evaluation methodology considering lagged effect has been considered as the original contribution in this study. In summary, combining DEA and econometric models, offer wide scope for the buyer to carry out performance evaluation under Multi Criteria Decision Making (MCDM) environment.


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