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Bounded and discrete data in data envelopment analysis with assurance regions: Application to design performance evaluation of gear shaping machines

Bao Zhang (Office of Academic Affairs, Hefei University of Technology, Hefei, China)
Chenpeng Feng (School of Management, Hefei University of Technology, Hefei, China)
Min Yang (School of Management, Hefei University of Technology, Hefei, China)
Jianhui Xie (International School of Business, Sun Yat-sen University, Zhuhai, China)
Ya Chen (School of Economics and Center for Industrial Information and Economy, Hefei University of Technology, Hefei, China)

Journal of Modelling in Management

ISSN: 1746-5664

Article publication date: 20 February 2020

Issue publication date: 4 August 2020

203

Abstract

Purpose

The purpose of this paper is to evaluate design performance of 51 gear shaping machines by using data envelopment analysis (DEA).

Design/methodology/approach

Existing studies extend traditional DEA by handling bounded and discrete data based on envelopment models. However, value judgment is usually neglected and fail to be incorporated in these envelopment models. In many cases, there is a need for prior preferences. Using existing DEA approaches as a backdrop, the current paper presents a methodology for incorporating assurance region (AR) restrictions into DEA with bounded and discrete data, i.e. the assurance region bounded discrete (AR-BD) DEA model. Then, the AR-BD DEA model is combined with a context-dependent DEA to obtain an efficiency stratification.

Findings

The authors examine different AR restrictions and calculate efficiency scores of five scenarios of AR restrictions by using the proposed AR-BD DEA model. It shows that AR restrictions have a great impact on the efficiency scores. The authors also identify nine efficient frontiers in total. For each decision-making unit, it could set benchmarks and improve its performance based on each higher efficient frontier.

Originality/value

This paper first evaluates efficiency of gear shaping machines by considering different (bounded and discrete) variable types of data and including AR restrictions. The AR-BD DEA model and context-dependent AR-BD DEA model proposed in this paper further enrich the DEA theory. The findings in this paper certainly provide useful information for both producers and consumers to make smart decisions.

Keywords

Acknowledgements

This research was supported by National key research and development program (No. 2017YFB0103200), and National Natural Science Foundation of China (No. 71601064, 71601062, 71601067, 71701220).

Citation

Zhang, B., Feng, C., Yang, M., Xie, J. and Chen, Y. (2020), "Bounded and discrete data in data envelopment analysis with assurance regions: Application to design performance evaluation of gear shaping machines", Journal of Modelling in Management, Vol. 15 No. 3, pp. 1017-1036. https://doi.org/10.1108/JM2-09-2019-0225

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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