Benchmarking with data envelopment analysis: An agency perspective
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DOI: 10.1016/j.omega.2020.102235
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Cited by:
- An, Qingxian & Tao, Xiangyang & Chen, Xiaohong, 2023. "Nested frontier-based best practice regulation under asymmetric information in a principal–agent framework," European Journal of Operational Research, Elsevier, vol. 306(1), pages 269-285.
- Jarmila Horváthová & Martina Mokrišová & Mária Vrábliková, 2021. "Benchmarking—A Way of Finding Risk Factors in Business Performance," JRFM, MDPI, vol. 14(5), pages 1-17, May.
- An, Qingxian & Zhang, Qiaoyu & Tao, Xiangyang, 2023. "Pay-for-performance incentives in benchmarking with quasi S-shaped technology," Omega, Elsevier, vol. 118(C).
- Zeng, Ximei & Zhou, Zhongbao & Gong, Yeming & Liu, Wenbin, 2022. "A data envelopment analysis model integrated with portfolio theory for energy mix adjustment: Evidence in the power industry," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
- Tzuping Chiang, 2021. "Estimating the Artificial Intelligence Learning Efficiency for Civil Engineer Education: A Case Study in Taiwan," Sustainability, MDPI, vol. 13(21), pages 1-11, October.
- Chatzistamoulou, Nikos & Kounetas, Kostas & Tsekouras, Kostas, 2022. "Technological hierarchies and learning: Spillovers, complexity, relatedness, and the moderating role of absorptive capacity," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
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Keywords
Data envelopment analysis; Benchmarking; Agency theory; Yardstick competition theory; Nash equilibrium;All these keywords.
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