Volume 53, Number 2, April-June 2019
Fuzzy Data Envelopment Analysis: Recent Developments and Applications
|Page(s)||687 - 703|
|Published online||13 June 2019|
Benchmarking with network dea in a fuzzy environment
Department of Strategic Management and Marketing, Leicester Business School, De Montfort University, Hugh Aston Building, The Gateway, Leicester LE1 9BH, UK
* Corresponding author: email@example.com
Accepted: 6 July 2017
Benchmarking is a powerful and thriving tool to enhance the performance and profitabilities of organizations in business engineering. Though performance benchmarking has been practically and theoretically developed in distinct fields such as banking, education, health, and so on, benchmarking of supply chains with multiple echelons that include certain characteristics such as intermediate measure differs from other practices. In spite of incremental benchmarking activities in practice, there is the dearth of a unified and effective guideline for benchmarking in organizations. Amongst the benchmarking tools, data envelopment analysis (DEA) as a non-parametric technique has been widely used to measure the relative efficiency of firms. However, the conventional DEA models that are bearing out precise input and output data turn out to be incapable of dealing with uncertainty, particularly when the gathered data encompasses natural language expressions and human judgements. In this paper, we present an imprecise network benchmarking for the purpose of reflecting the human judgments with the fuzzy values rather than precise numbers. In doing so, we propose the fuzzy network DEA models to compute the overall system scale and technical efficiency of those organizations whose internal structure is known. A classification scheme is presented based upon their fuzzy efficiencies with the aim of classifying the organizations. We finally provide a case study of the airport and travel sector to elucidate the details of the proposed method in this study.
Mathematics Subject Classification: 90B50 / 90C05 / 90C70 / 90C90
Key words: Internal structure / DEA / fuzzy sets / scale and relative efficiency measure
© EDP Sciences, ROADEF, SMAI 2019
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