The measurement of stores efficiency in a retail chain using fuzzy data envelopment analysis

Konyalıoğlu, Aziz Kemal and Çayır, Sibel and Yiğit, Nehir and Özcan, Tuncay; Durakbasa, Numan M. and Gençyılmaz, M. Güneş, eds. (2024) The measurement of stores efficiency in a retail chain using fuzzy data envelopment analysis. In: Industrial Engineering in the Industry 4.0 Era. Lecture Notes in Mechanical Engineering . Springer, TUR, pp. 85-94. ISBN 9783031539916 (https://doi.org/10.1007/978-3-031-53991-6_7)

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Abstract

The efficiency analysis of retail stores is critical to identify possible areas of improvement. At this point, data envelopment analysis (DEA) is widely used for efficiency measurement of service and production units. On the other hand, the values of input and output variables must be deterministic and precise in the conventional DEA models such as CCR and BCR. However, the input and output values are usually imprecise for real world problems. In order to overcome this shortcoming, fuzzy data envelopment analysis models have been developed. This study aims to use the fuzzy data envelopment analysis for measuring and ranking the efficiency of stores in a grocery retailer in Turkey. In this study, total floor area, average inventory at cost, total number of customers that visited the store and average number of employees in the store are considered as the input variables while GMROI (gross margin return on investment), net sales, inventory turnover and stock-out rate are considered as output variables in the fuzzy DEA. The proposed model is solved by using LINGO 17.0 optimization software. According to the model results, the inefficient stores are ranked and compared using a minimax regret approach.

ORCID iDs

Konyalıoğlu, Aziz Kemal ORCID logoORCID: https://orcid.org/0000-0002-2443-5063, Çayır, Sibel, Yiğit, Nehir and Özcan, Tuncay; Durakbasa, Numan M. and Gençyılmaz, M. Güneş
  • Item type:Book Section
    ID code:89672
    Dates:
    Date
    Event
    2 March 2024
    Published
    31 August 2023
    Accepted
    Subjects:Social Sciences > Commerce
    Science > Mathematics > Analysis
    Department:UNSPECIFIED
    Depositing user: Pure Administrator
    Date deposited:19 Jun 2024 15:45
    Last modified:11 Nov 2024 15:35
    URI:https://strathprints.strath.ac.uk/id/eprint/89672
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