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Efficiency analysis of chain stores: a case study

  • Case-oriented Paper
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Journal of the Operational Research Society

Abstract

An efficiency analysis problem of a hairdressing company is addressed in this paper. The service system has the characteristics of different trade area types, multiple workers with different levels, crisp facilities and expenses and customer relationship orientations. A specialized imprecise data envelopment analysis (IDEA) model is proposed so that the efficiencies of stores from different trade areas can be compared and all workers in different ranks are included. The analysis results exhibit that the inefficiency in resource utilization is largely caused by inefficient operation. Based on the measurement results, eight stores and two stores are aimed with high priority for improving the efficiencies in operation and scale, respectively. The regional manager agrees that IDEA is helpful in evaluating relative efficiency and detecting the reasons caused inefficiency.

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Acknowledgements

The author deeply appreciates the editors and anonymous referees whose comments and suggestions added significantly to the clarity of this paper. The author is also grateful to Miss Hsieh for the help in collecting and processing data of the case company.

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Authors and Affiliations

  1. National Chin-Yi University of Technology, Taiwan, Republic of China

    H-T Lin

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  1. H-T Lin
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Correspondence to H-T Lin.

Appendix

Appendix

In Example 2 of Wang et al (2005), there are eight DMUs joining in the performance rating. The inputs include purchase cost (PC) and the number of employees (NOE), whose data are known exactly. The gross output value (GOV) and the product quality (PQ) are considered as output factors 1 and 2, respectively. The data of GOVs are imprecise and some of them are given as interval numbers and some as TFNs. The PQ is a qualitative index and is given as strong ordinal preference information, where ordinal scale 1 stands for the best and 8 stands for the worst. The data of DMUs 6 and 7, for example, in their Table 3 are presented as follows:

By using their transformation technique, the interval estimates of DMUs 6 and 7 are as follows (shown in their Table 4):

As PQ is output factor 2 and it is ranked in position 5 for DMU 7, hence the lower bound of PQ for DMU 7 is rendered and expressed as ŷ 25 L=0.1404928; meanwhile the upper bound of PQ for DMU 6 (ranked in position 6) as ŷ 26 U=0.567427. The relation of ŷ 25 L=0.1404928<ŷ 26 U=0.567427 violates the relation of ŷ 25 U⩾ŷ 25 L>ŷ 26 U⩾ŷ 26 L inherent in ŷ 25>ŷ 26, where the value of rank 5 is greater than that of rank 6 in their study.

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Lin, HT. Efficiency analysis of chain stores: a case study. J Oper Res Soc 62, 1268–1281 (2011). https://doi.org/10.1057/jors.2010.97

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