IDEAS home Printed from https://ideas.repec.org/r/eee/ejores/v203y2010i3p749-760.html
   My bibliography  Save this item

Measuring dynamic efficiency: Theories and an integrated methodology

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
  2. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
  3. Tsionas, Mike G. & Malikov, Emir & Kumbhakar, Subal C., 2020. "Endogenous dynamic efficiency in the intertemporal optimization models of firm behavior," European Journal of Operational Research, Elsevier, vol. 284(1), pages 313-324.
  4. Kao, Chiang, 2014. "Efficiency decomposition for general multi-stage systems in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 232(1), pages 117-124.
  5. Li-Ting Yeh, 2021. "Integrating corporate image of corporate social responsibility, stock price crash risk and profitability into a dynamic corporate sustainability performance measurement," Annals of Operations Research, Springer, vol. 305(1), pages 325-345, October.
  6. Cherchye, Laurens & De Rock, Bram & Kerstens, Pieter Jan, 2018. "Production with storable and durable inputs: Nonparametric analysis of intertemporal efficiency," European Journal of Operational Research, Elsevier, vol. 270(2), pages 498-513.
  7. Alperovych, Yan & Amess, Kevin & Wright, Mike, 2013. "Private equity firm experience and buyout vendor source: What is their impact on efficiency?," European Journal of Operational Research, Elsevier, vol. 228(3), pages 601-611.
  8. Chen, Kaihua & Kou, Mingting & Fu, Xiaolan, 2018. "Evaluation of multi-period regional R&D efficiency: An application of dynamic DEA to China's regional R&D systems," Omega, Elsevier, vol. 74(C), pages 103-114.
  9. Chen, Kuan-Chen & Lin, Sun-Yuan & Yu, Ming-Miin, 2022. "Exploring the efficiency of hospital and pharmacy utilizations in Taiwan: An application of dynamic network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
  10. Cave, Joshua & Chaudhuri, Kausik & Kumbhakar, Subal C., 2023. "Dynamic firm performance and estimator choice: A comparison of dynamic panel data estimators," European Journal of Operational Research, Elsevier, vol. 307(1), pages 447-467.
  11. Guo, Xiaoying & Lu, Ching-Cheng & Lee, Jen-Hui & Chiu, Yung-Ho, 2017. "Applying the dynamic DEA model to evaluate the energy efficiency of OECD countries and China," Energy, Elsevier, vol. 134(C), pages 392-399.
  12. Ching-Cheng Lu & Liang-Chun Lu, 2019. "Evaluating the energy efficiency of European Union countries: The dynamic data envelopment analysis," Energy & Environment, , vol. 30(1), pages 27-43, February.
  13. Saeideh Fallah-Fini & Konstantinos Triantis & Andrew Johnson, 2014. "Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art," Journal of Productivity Analysis, Springer, vol. 41(1), pages 51-67, February.
  14. Frederic Ang & Alfons Oude Lansink, 2018. "Decomposing dynamic profit inefficiency of Belgian dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 81-99.
  15. Silva, Elvira & Magalhães, Manuela, 2023. "Environmental efficiency, irreversibility and the shadow price of emissions," European Journal of Operational Research, Elsevier, vol. 306(2), pages 955-967.
  16. Kapelko, Magdalena & Oude Lansink, Alfons & Stefanou, Spiro E., 2014. "Assessing dynamic inefficiency of the Spanish construction sector pre- and post-financial crisis," European Journal of Operational Research, Elsevier, vol. 237(1), pages 349-357.
  17. Li, Ying & Chiu, Yung-ho & Lin, Tai-Yu, 2019. "Coal production efficiency and land destruction in China's coal mining industry," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
  18. Yu Mao & Yonglin Li & Deyi Xu & Yaqi Wu & Jinhua Cheng, 2022. "Spatial-Temporal Evolution of Total Factor Productivity in Logistics Industry of the Yangtze River Economic Belt, China," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
  19. Samira Foladi & Maghsud Solimanpur & Mustafa Jahangoshai Rezaee, 2020. "Inverse Dynamic Data Envelopment Analysis for Evaluating Faculties of University with Quasi-Fixed Inputs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(1), pages 323-347, February.
  20. Víctor Giménez & Claudio Thieme & Diego Prior & Emili Tortosa-Ausina, 2019. "Comparing the Performance of National Educational Systems: Inequality Versus Achievement?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(2), pages 581-609, January.
  21. Magdalena Kapelko, 2017. "Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis," Agribusiness, John Wiley & Sons, Ltd., vol. 33(4), pages 505-521, September.
  22. Kao, Chiang, 2013. "Dynamic data envelopment analysis: A relational analysis," European Journal of Operational Research, Elsevier, vol. 227(2), pages 325-330.
  23. Aparicio, Juan & Kapelko, Magdalena, 2019. "Accounting for slacks to measure dynamic inefficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 278(2), pages 463-471.
  24. Wu, Yueh-Cheng & Lin, Sheng-Wei, 2022. "Efficiency evaluation of Asia's cultural tourism using a dynamic DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
  25. Teirlinck, Peter & Khoshnevis, Pegah, 2020. "Within-cluster determinants of output efficiency of R&D in the space industry," Omega, Elsevier, vol. 94(C).
  26. Encarna Guillamon-Saorin & Magdalena Kapelko & Spiro E. Stefanou, 2018. "Corporate Social Responsibility and Operational Inefficiency: A Dynamic Approach," Sustainability, MDPI, vol. 10(7), pages 1-26, July.
  27. Ronggang Zhang & Ching-Cheng Lu & Jen-Hui Lee & Ying Feng & Yung-Ho Chiu, 2019. "Dynamic Environmental Efficiency Assessment of Industrial Water Pollution," Sustainability, MDPI, vol. 11(11), pages 1-12, May.
  28. Lim, Dong-Joon & Kim, Moon-Su, 2022. "Measuring dynamic efficiency with variable time lag effects," Omega, Elsevier, vol. 108(C).
  29. Nelson Amowine & Zhiqiang Ma & Mingxing Li & Zhixiang Zhou & Benjamin Azembila Asunka & James Amowine, 2019. "Energy Efficiency Improvement Assessment in Africa: An Integrated Dynamic DEA Approach," Energies, MDPI, vol. 12(20), pages 1-17, October.
  30. Skevas, Theodoros & Lansink, Alfons Oude & Stefanou, Spiro E., 2012. "Measuring technical efficiency in the presence of pesticide spillovers and production uncertainty: The case of Dutch arable farms," European Journal of Operational Research, Elsevier, vol. 223(2), pages 550-559.
  31. Zha, Yong & Liang, Nannan & Wu, Maoguo & Bian, Yiwen, 2016. "Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach," Omega, Elsevier, vol. 60(C), pages 60-72.
  32. 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.
  33. Hirofumi Fukuyama & William Weber, 2015. "Measuring Japanese bank performance: a dynamic network DEA approach," Journal of Productivity Analysis, Springer, vol. 44(3), pages 249-264, December.
  34. Dan Wu & Ching-Cheng Lu & Xiang Chen & Pei-Chieh Tu & An-Chi Yang & Chih-Yu Yang, 2021. "Evaluating the Dynamic Energy Production Efficiency in APEC Economies," Energies, MDPI, vol. 14(14), pages 1-20, July.
  35. Hirofumi Fukuyama & Atsuo Hashimoto & Kaoru Tone & William L. Weber, 2018. "Does human capital or physical capital constrain output in Japanese prefectures?," Empirical Economics, Springer, vol. 54(2), pages 379-393, March.
  36. Qingxian An & Fanyong Meng & Beibei Xiong & Zongrun Wang & Xiaohong Chen, 2020. "Assessing the relative efficiency of Chinese high-tech industries: a dynamic network data envelopment analysis approach," Annals of Operations Research, Springer, vol. 290(1), pages 707-729, July.
  37. Hsiao-Yin Chen & Chin-wei Huang & Yung-Ho Chiu, 2017. "An intertemporal efficiency and technology measurement for tourist hotel," Journal of Productivity Analysis, Springer, vol. 48(1), pages 85-96, August.
  38. Li, Hongkuan & He, Haiyan & Shan, Jiefei & Cai, Jingjing, 2019. "Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 136-148.
  39. Li, Lan-bing & Liu, Bing-lian & Liu, Wei-lin & Chiu, Yung-Ho, 2017. "Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 24-33.
  40. Samoilenko, Sergey & Osei-Bryson, Kweku-Muata, 2010. "Determining sources of relative inefficiency in heterogeneous samples: Methodology using Cluster Analysis, DEA and Neural Networks," European Journal of Operational Research, Elsevier, vol. 206(2), pages 479-487, October.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.