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Efficiency decomposition with shared inputs and outputs in two-stage DEA

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Abstract

Data envelopment analysis (DEA) is an effective non-parametric method for measuring the relative efficiencies of decision making units (DMUs) with multiple inputs and outputs. In many real situations, the internal structure of DMUs is a two-stage network process with shared inputs used in both stages and common outputs produced by the both stages. For example, hospitals have a two-stage network structure. Stage 1 consumes resources such as information technology system, plant, equipment and admin personnel to generate outputs such as medical records, laundry and housekeeping. Stage 2 consumes the same set of resources used by stage 1 (named shared inputs) and the outputs generated by stage 1 (named intermediate measures) to provide patient services. Besides, some of outputs, for instance, patient satisfaction degrees, are generated by the two individual stages together (named shared outputs). Since some of shared inputs and outputs are hard split up and allocated to each individual stage, it needs to develop two-stage DEA methods for evaluating the performance of two-stage network processes in such problems. This paper extends the centralized model to measure the DEA efficiency of the two-stage process with non splittable shared inputs and outputs. A weighted additive approach is used to combine the two individual stages. Moreover, additive efficiency decomposition models are developed to simultaneously evaluate the maximal and the minimal achievable efficiencies for the individual stages. Finally, an example of 17 city branches of China Construction Bank in Anhui Province is employed to illustrate the proposed approach.

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Author information

Authors and Affiliations

  1. School of Economics and Management, Beihang University, Beijing, 100191, China

    Lin Li & Haijun Huang

  2. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China

    Lin Li & Shouyang Wang

  3. Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Qianzhi Dai

Authors
  1. Lin Li
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  2. Qianzhi Dai
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  3. Haijun Huang
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  4. Shouyang Wang
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Corresponding author

Correspondence to Qianzhi Dai.

Additional information

Lin Li is currently a doctoral student in Beihang Univerisity, China. She received her Master’s degree from Beijing University of Technology and Bachelor degree from Liaocheng University. Her main research interests focus on data analysis, performance evaluation, especially journal evaluation.

Qianzhi Dai is currently a Postdoctor in Institute of Policy and Management, Chinese Academy of Sciences (CAS), China. He received his Ph.D. degree from University of Science and Technology of China in 2014 and Bachelor degree from Anhui University in 2008. His research interests include performance evaluation, data mining and project risk management.

Haijun Huang is currently a professor in Beihang Univerisity, China. He received his Ph.D. degree from Beihang Univerisity in 1992 and Bachelor degree from Nanjing University of Aeronautics and Astronautics in 1984. His research interests include transport network problems and other decision analysis problems.

Shouyang Wang is currently a professor in Academy of Mathematics and Systems Science, CAS, China. He received his Ph.D. degree from Academy of Mathematics and Systems Science, CAS in 1986 and Bachelor degree from Sun Yat-sen University in 1982. His research interests include decision analysis, conflict analysis and system engineering.

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Li, L., Dai, Q., Huang, H. et al. Efficiency decomposition with shared inputs and outputs in two-stage DEA. J. Syst. Sci. Syst. Eng. 25, 23–38 (2016). https://doi.org/10.1007/s11518-016-5298-0

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  • DOI: https://doi.org/10.1007/s11518-016-5298-0

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