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Performance comparison of retailing stores using a Malmquist-type index

Author

Listed:
  • C B Vaz

    (Escola Superior de Tecnologia e Gestão, Instituto Politécnico de Bragança, Portugal)

  • A S Camanho

    (Faculdade de Engenharia, Universidade do Porto, Portugal)

Abstract

This study develops a framework that combines different management science methods to provide insights concerning the performance of retailing stores. First, the framework enables to specify appropriate targets for stores of a retail network using data envelopment analysis. This involves comparing stores within homogenous groups, that is, supermarkets and hypermarkets. Second, the framework compares the overall performance of these two groups. This requires the combined use of a Malmquist-type index and statistical tests. This index is decomposed into sub-indices for comparing the differences between groups in terms of the efficiency spread in each group of stores and the productivity differences between the best-practice frontiers spanned by the benchmark stores from each group. The hypothesis tests are used to verify if the differences between groups captured by the sub-indices are statistically significant.

Suggested Citation

  • C B Vaz & A S Camanho, 2012. "Performance comparison of retailing stores using a Malmquist-type index," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(5), pages 631-645, May.
    • Handle: RePEc:pal:jorsoc:v:63:y:2012:i:5:p:631-645
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    Citations

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    Cited by:

    1. D’Inverno, Giovanna & Smet, Mike & De Witte, Kristof, 2021. "Impact evaluation in a multi-input multi-output setting: Evidence on the effect of additional resources for schools," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1111-1124.
    2. Fang, Lei, 2022. "Measuring and decomposing group performance under centralized management," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1006-1013.
    3. Aparicio, Juan & Santin, Daniel, 2018. "A note on measuring group performance over time with pseudo-panels," European Journal of Operational Research, Elsevier, vol. 267(1), pages 227-235.
    4. Juan Aparicio & Sergio Perelman & Daniel Santín, 2022. "Comparing the evolution of productivity and performance gaps in education systems through DEA: an application to Latin American countries," Operational Research, Springer, vol. 22(2), pages 1443-1477, April.
    5. 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).
    6. Aparicio, Juan & Crespo-Cebada, Eva & Pedraja-Chaparro, Francisco & Santín, Daniel, 2017. "Comparing school ownership performance using a pseudo-panel database: A Malmquist-type index approach," European Journal of Operational Research, Elsevier, vol. 256(2), pages 533-542.
    7. Bojiang Yang & Youliang Zhang & Hongjun Zhang & Rui Zhang & Baoyu Xu, 2016. "Factor-specific Malmquist productivity index based on common weights DEA," Operational Research, Springer, vol. 16(1), pages 51-70, April.
    8. Chen, Xiang & Grifell-Tatjé, Emili & Fu, Tsu-Tan, 2023. "A profit difference decomposition model for measuring group performance: an application to Chinese and Taiwanese commercial banks," Omega, Elsevier, vol. 120(C).
    9. Daniel Feliciano & Laura López-Torres & Daniel Santín, 2021. "One Laptop per Child? Using Production Frontiers for Evaluating the Escuela 2.0 Program in Spain," Mathematics, MDPI, vol. 9(20), pages 1-17, October.

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