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Past-present-future Intertemporal DEA models

Author

Listed:
  • Tsung-Sheng Chang

    (National Chiao Tung University, Taiwan)

  • Kaoru Tone

    (National Graduate Institute for Policy Studies, Japan)

  • Chen-Hui Wu

    (National Dong Hwa University, Taiwan)

Abstract

It has been well recognized that to thoroughly evaluate a firm’s performance, the evaluator must assess not only its past and present records but also future potential. However, to the best of our knowledge, there are no data envelopment analysis (DEA)-type models proposed in the literature that simultaneously take past, present and, especially, future performance indicators into account. Hence, this research aims at developing a new type of DEA model referred to as Intertemporal DEA models that can be used to fully measure a firm’s efficiency by explicitly considering its key inputs and outputs involving the past-present-future time span. In this research, the proposed Intertemporal DEA models are applied to the performance evaluation of high-tech Integrated Circuit design companies in Taiwan to demonstrate their advantages over other DEA models that ignore intertemporal efficiency.

Suggested Citation

  • Tsung-Sheng Chang & Kaoru Tone & Chen-Hui Wu, 2015. "Past-present-future Intertemporal DEA models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(1), pages 16-32, January.
    • Handle: RePEc:pal:jorsoc:v:66:y:2015:i:1:p:16-32
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    Citations

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    Cited by:

    1. Chang, Tsung-Sheng & Tone, Kaoru & Wu, Chen-Hui, 2021. "Nested dynamic network data envelopment analysis models with infinitely many decision making units for portfolio evaluation," European Journal of Operational Research, Elsevier, vol. 291(2), pages 766-781.
    2. Li, Ying & Chiu, Yung-ho & Lu, Liang Chun, 2018. "Energy and AQI performance of 31 cities in China," Energy Policy, Elsevier, vol. 122(C), pages 194-202.
    3. Chia-Nan Wang & Minh Nhat Nguyen & Anh Luyen Le & Hector Tibo, 2020. "A DEA Resampling Past-Present-Future Comparative Analysis of the Food and Beverage Industry: The Case Study on Thailand vs. Vietnam," Mathematics, MDPI, vol. 8(7), pages 1-24, July.
    4. Dorys Y. Rodríguez-Castro & Juan Aparicio, 2021. "Introducing a functional framework for integrating the empirical evidence about higher education institutions’ functions and capabilities: A literature review," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 17(1), pages 231-267.
    5. Chia-Nan Wang & Phi-Hung Nguyen & Thi-Ly Nguyen & Thi-Giang Nguyen & Duc-Thinh Nguyen & Thi-Hoai Tran & Hong-Cham Le & Huong-Thuy Phung, 2022. "A Two-Stage DEA Approach to Measure Operational Efficiency in Vietnam’s Port Industry," Mathematics, MDPI, vol. 10(9), pages 1-21, April.
    6. Chang, Tsung-Sheng & Tone, Kaoru & Wu, Chen-Hui, 2016. "DEA models incorporating uncertain future performance," European Journal of Operational Research, Elsevier, vol. 254(2), pages 532-549.

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