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General Two-Stage Systems

In: Network Data Envelopment Analysis

Author

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  • Chiang Kao

    (National Cheng Kung University)

Abstract

The basic two-stage system discussed in the preceding chapter describes a production type where all intermediate products produced by the first division are consumed by the second division for production. Specifically, no intermediate products flow out of the system, and the second division does not consume other inputs supplied from outside, except for the intermediate products. However, it should be noted that real world cases are usually more complicated than this basic two-stage system. For example, some intermediate products may flow out of the system to be sold as spare parts, and the second division may need workers to work on the intermediate products to become the final products. Taking these situations into account, we then have a general two-stage system, which allows the first division to have final outputs and the second division to have exogenous inputs. Several models have been proposed for measuring the efficiency of this type of system, and many applications have been reported in the literature (Kao 2014a).

Suggested Citation

  • Chiang Kao, 2017. "General Two-Stage Systems," International Series in Operations Research & Management Science, in: Network Data Envelopment Analysis, chapter 0, pages 237-273, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-31718-2_11
    DOI: 10.1007/978-3-319-31718-2_11
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    Citations

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    Cited by:

    1. Yi Ji & Hechang Cai & Zilong Wang, 2023. "Impact of Industrial Synergy on the Efficiency of Innovation Resource Allocation: Evidence from Chinese Metropolitan Areas," Land, MDPI, vol. 12(1), pages 1-16, January.
    2. K. Hafsal & Anandarao Suvvari & S. Raja Sethu Durai, 2020. "Efficiency of Indian banks with non-performing assets: evidence from two-stage network DEA," Future Business Journal, Springer, vol. 6(1), pages 1-9, December.
    3. Xiaohong Liu & Jiasen Sun & Feng Yang & Jie Wu, 2020. "How ownership structure affects bank deposits and loan efficiencies: an empirical analysis of Chinese commercial banks," Annals of Operations Research, Springer, vol. 290(1), pages 983-1008, July.
    4. Riju Chaudhary & H. D. Arora, 2022. "Efficiency evaluation of public and nationalized Indian banks using data envelopment analysis," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 469-478, February.
    5. Kao, Chiang, 2019. "Inefficiency identification for closed series production systems," European Journal of Operational Research, Elsevier, vol. 275(2), pages 599-607.
    6. Xiong, Xi & Yang, Guo-liang & Guan, Zhong-cheng, 2018. "Assessing R&D efficiency using a two-stage dynamic DEA model: A case study of research institutes in the Chinese Academy of Sciences," Journal of Informetrics, Elsevier, vol. 12(3), pages 784-805.
    7. Jiawei Yang, 2023. "Disentangling the sources of bank inefficiency: a two-stage network multi-directional efficiency analysis approach," Annals of Operations Research, Springer, vol. 326(1), pages 369-410, July.
    8. Zhang, Linyan & Chen, Kun, 2019. "Hierarchical network systems: An application to high-technology industry in China," Omega, Elsevier, vol. 82(C), pages 118-131.
    9. Meiqiang Wang & Yingwen Chen & Zhixiang Zhou, 2020. "A Novel Stochastic Two-Stage DEA Model for Evaluating Industrial Production and Waste Gas Treatment Systems," Sustainability, MDPI, vol. 12(6), pages 1-17, March.
    10. Jiawei Yang & Lei Fang, 2022. "Average lexicographic efficiency decomposition in two-stage data envelopment analysis: an application to China’s regional high-tech innovation systems," Annals of Operations Research, Springer, vol. 312(2), pages 1051-1093, May.
    11. Kao, Chiang, 2018. "Multiplicative aggregation of division efficiencies in network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 270(1), pages 328-336.
    12. Zhu, Qingyuan & Xu, Shuqi & Sun, Jiasen & Li, Xingchen & Zhou, Dequn, 2022. "Energy efficiency evaluation of power supply system: A data-driven approach based on shared resources," Applied Energy, Elsevier, vol. 312(C).
    13. Fang, Lei, 2020. "Stage efficiency evaluation in a two-stage network data envelopment analysis model with weight priority," Omega, Elsevier, vol. 97(C).

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