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A hybrid stochastic data envelopment analysis and decision tree for performance prediction in retail industry

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  • Lagzi, Mohammad Dana
  • sajadi, Seyed Mojtaba
  • Taghizadeh-Yazdi, Mohammadreza

Abstract

Assessing the retail industry's efficiency is pivotal for economic growth and corporate productivity. This study employs a novel approach, utilizing a regression-based Stochastic Data Envelopment Analysis (SDEA) model, Balanced Scorecard (BSC), and Decision Tree. The integration of these methods is a pioneering effort in the retail sector. This is a data-driven decision-making framework, aiding managers in predicting efficient and inefficient Decision-Making Units (DMUs). Results from a case study in 44 retail store chains in Iran indicate that the accuracy of the SDEA model is 99%. The Decision Tree highlights low branch efficiency due to a low customer count, a unique finding in comparison to prior studies.

Suggested Citation

  • Lagzi, Mohammad Dana & sajadi, Seyed Mojtaba & Taghizadeh-Yazdi, Mohammadreza, 2024. "A hybrid stochastic data envelopment analysis and decision tree for performance prediction in retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:joreco:v:80:y:2024:i:c:s0969698924002042
    DOI: 10.1016/j.jretconser.2024.103908
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