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Ya Chen

Personal Details

First Name:Ya
Middle Name:
Last Name:Chen
Suffix:
RePEc Short-ID:pch2079
[This author has chosen not to make the email address public]

Affiliation

School of Economics
Hefei University of Technology

Hefei, China
http://jjxy.hfut.edu.cn/
RePEc:edi:sehftcn (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP092020, School of Economics, University of Queensland, Australia.

Articles

  1. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
  2. Zhao, Tianyi & Xu, Xiaoping & Chen, Ya & Liang, Liang & Yu, Yugang & Wang, Ke, 2020. "Coordination of a fashion supply chain with demand disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
  3. Ya Chen & Wei Xu & Qian Zhou & Zhixiang Zhou, 2020. "Total Factor Energy Efficiency, Carbon Emission Efficiency, and Technology Gap: Evidence from Sub-Industries of Anhui Province in China," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
  4. Ya Chen & Xiaoli Fan & Qian Zhou, 2020. "An Inverted-U Impact of Environmental Regulations on Carbon Emissions in China’s Iron and Steel Industry: Mechanisms of Synergy and Innovation Effects," Sustainability, MDPI, vol. 12(3), pages 1-19, February.
  5. Ya Chen & Justin Wang & Joe Zhu & H. David Sherman & Shin-Yi Chou, 2019. "How the Great Recession affects performance: a case of Pennsylvania hospitals using DEA," Annals of Operations Research, Springer, vol. 278(1), pages 77-99, July.
  6. Ya Chen & Yongjun Li & Liang Liang & Huaqing Wu, 2019. "An extension on super slacks-based measure DEA approach," Annals of Operations Research, Springer, vol. 278(1), pages 101-121, July.
  7. Yande Gong & Joe Zhu & Ya Chen & Wade D. Cook, 2018. "DEA as a tool for auditing: application to Chinese manufacturing industry with parallel network structures," Annals of Operations Research, Springer, vol. 263(1), pages 247-269, April.
  8. Tao Ding & Ya Chen & Huaqing Wu & Yuqi Wei, 2018. "Centralized fixed cost and resource allocation considering technology heterogeneity: a DEA approach," Annals of Operations Research, Springer, vol. 268(1), pages 497-511, September.
  9. Fabienne Miller & Justin Wang & Joe Zhu & Ya Chen & Jason Hockenberry, 2017. "Investigation of the Impact of the Massachusetts Health Care Reform on Hospital Costs and Quality of Care," Annals of Operations Research, Springer, vol. 250(1), pages 129-146, March.
  10. Ya Chen & Wade D. Cook & Juan Du & Hanhui Hu & Joe Zhu, 2017. "Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China," Annals of Operations Research, Springer, vol. 255(1), pages 347-366, August.
  11. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.
  12. Yang, Min & Li, Yongjun & Chen, Ya & Liang, Liang, 2014. "An equilibrium efficiency frontier data envelopment analysis approach for evaluating decision-making units with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 239(2), pages 479-489.
  13. Wu, Jie & An, Qingxian & Xiong, Beibei & Chen, Ya, 2013. "Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs," Energy Policy, Elsevier, vol. 57(C), pages 7-13.
  14. Li, Yongjun & Yang, Min & Chen, Ya & Dai, Qianzhi & Liang, Liang, 2013. "Allocating a fixed cost based on data envelopment analysis and satisfaction degree," Omega, Elsevier, vol. 41(1), pages 55-60.

Chapters

  1. Ya Chen & Mengyuan Wang & Jingyu Yang, 2021. "Measuring Chinese Bank Performance with Undesirable Outputs: A Slack-Based Two-Stage Network DEA Approach," International Series in Operations Research & Management Science, in: Joe Zhu & Vincent Charles (ed.), Data-Enabled Analytics, pages 299-326, Springer.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

    Sorry, no citations of working papers recorded.

Articles

  1. Zhao, Tianyi & Xu, Xiaoping & Chen, Ya & Liang, Liang & Yu, Yugang & Wang, Ke, 2020. "Coordination of a fashion supply chain with demand disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).

    Cited by:

    1. Nana Wan & Li Li & Xiaozhi Wu & Jianchang Fan, 2021. "Coordination of a fresh agricultural product supply chain with option contract under cost and loss disruptions," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-15, June.
    2. Tseng, Ming-Lang & Bui, Tat-Dat & Lim, Ming K. & Fujii, Minoru & Mishra, Umakanta, 2022. "Assessing data-driven sustainable supply chain management indicators for the textile industry under industrial disruption and ambidexterity," International Journal of Production Economics, Elsevier, vol. 245(C).
    3. Govindan, Kannan & Mina, Hassan & Alavi, Behrouz, 2020. "A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    4. Shuangsheng Wu & Qi Li, 2021. "Emergency Quantity Discount Contract with Suppliers Risk Aversion under Stochastic Price," Mathematics, MDPI, vol. 9(15), pages 1-12, July.
    5. Ponte, Borja & Puche, Julio & Rosillo, Rafael & de la Fuente, David, 2020. "The effects of quantity discounts on supply chain performance: Looking through the Bullwhip lens," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    6. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    7. Shou, Yongyi & Zhao, Xinyu & Dai, Jing & Xu, Dong, 2021. "Matching traceability and supply chain coordination: Achieving operational innovation for superior performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    8. Zhao, Yujie & Zhou, Hong & Leus, Roel, 2022. "Recovery from demand disruption: Two-stage financing strategy for a capital-constrained supply chain under uncertainty," European Journal of Operational Research, Elsevier, vol. 303(2), pages 699-718.

  2. Ya Chen & Wei Xu & Qian Zhou & Zhixiang Zhou, 2020. "Total Factor Energy Efficiency, Carbon Emission Efficiency, and Technology Gap: Evidence from Sub-Industries of Anhui Province in China," Sustainability, MDPI, vol. 12(4), pages 1-21, February.

    Cited by:

    1. Yu, Ming-Miin & See, Kok Fong & Hsiao, Bo, 2022. "Integrating group frontier and metafrontier directional distance functions to evaluate the efficiency of production units," European Journal of Operational Research, Elsevier, vol. 301(1), pages 254-276.
    2. Yuanxin Peng & Zhuo Chen & Jay Lee, 2020. "Dynamic Convergence of Green Total Factor Productivity in Chinese Cities," Sustainability, MDPI, vol. 12(12), pages 1-18, June.
    3. Ying Chen & Suran Li & Long Cheng, 2020. "Evaluation of Cultivated Land Use Efficiency with Environmental Constraints in the Dongting Lake Eco-Economic Zone of Hunan Province, China," Land, MDPI, vol. 9(11), pages 1-15, November.

  3. Ya Chen & Xiaoli Fan & Qian Zhou, 2020. "An Inverted-U Impact of Environmental Regulations on Carbon Emissions in China’s Iron and Steel Industry: Mechanisms of Synergy and Innovation Effects," Sustainability, MDPI, vol. 12(3), pages 1-19, February.

    Cited by:

    1. Desheng Xu & Encui Liu & Wei Duan & Ke Yang, 2022. "Consumption-Driven Carbon Emission Reduction Path and Simulation Research in Steel Industry: A Case Study of China," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    2. Wang, Zhuo & Yen-Ku, Kuo & Li, Zeyun & An, Nguyen Binh & Abdul-Samad, Zulkiflee, 2022. "The transition of renewable energy and ecological sustainability through environmental policy stringency: Estimations from advance panel estimators," Renewable Energy, Elsevier, vol. 188(C), pages 70-80.
    3. Neves, Sónia Almeida & Marques, António Cardoso & Patrício, Margarida, 2020. "Determinants of CO2 emissions in European Union countries: Does environmental regulation reduce environmental pollution?," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 114-125.

  4. Ya Chen & Justin Wang & Joe Zhu & H. David Sherman & Shin-Yi Chou, 2019. "How the Great Recession affects performance: a case of Pennsylvania hospitals using DEA," Annals of Operations Research, Springer, vol. 278(1), pages 77-99, July.

    Cited by:

    1. Zhang, Wenwen & Chiu, Yi-Bin & Hsiao, Cody Yu-Ling, 2022. "Effects of country risks and government subsidies on renewable energy firms’ performance: Evidence from China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    2. Marwa Hasni & Safa Bhar Layeb & Najla Omrane Aissaoui & Aymen Mannai, 2022. "Hybrid model for a cross‐department efficiency evaluation in healthcare systems," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(5), pages 1311-1329, July.
    3. Wen-Min Lu & Qian Long Kweh & Kai-Chu Yang, 2022. "Multiplicative efficiency aggregation to evaluate Taiwanese local auditing institutions performance," Annals of Operations Research, Springer, vol. 315(2), pages 1243-1262, August.
    4. Cinaroglu, Songul, 2021. "Changes in hospital efficiency and size: An integrated propensity score matching with data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).

  5. Ya Chen & Yongjun Li & Liang Liang & Huaqing Wu, 2019. "An extension on super slacks-based measure DEA approach," Annals of Operations Research, Springer, vol. 278(1), pages 101-121, July.

    Cited by:

    1. Lee, Hsuan-Shih, 2022. "Integrating SBM model and Super-SBM model: a one-model approach," Omega, Elsevier, vol. 113(C).
    2. Lin, Shuguang & Shi, Hai-Liu & Wang, Ying-Ming, 2022. "An integrated slacks-based super-efficiency measure in the presence of nonpositive data," Omega, Elsevier, vol. 111(C).

  6. Yande Gong & Joe Zhu & Ya Chen & Wade D. Cook, 2018. "DEA as a tool for auditing: application to Chinese manufacturing industry with parallel network structures," Annals of Operations Research, Springer, vol. 263(1), pages 247-269, April.

    Cited by:

    1. Xiyang Lei & Yongjun Li & Alec Morton, 2022. "Dominance and ranking interval in DEA parallel production systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 649-675, June.
    2. Qingfeng Tian & Shuo Zhang & Huimin Yu & Guangming Cao, 2019. "Exploring the Factors Influencing Business Model Innovation Using Grounded Theory: The Case of a Chinese High-End Equipment Manufacturer," Sustainability, MDPI, vol. 11(5), pages 1-16, March.
    3. Volkan Soner Özsoy & Mediha Örkcü & H. Hasan Örkcü, 2021. "A minimax approach for selecting the overall and stage-level most efficient unit in two stage production processes," Annals of Operations Research, Springer, vol. 300(1), pages 137-169, May.
    4. Saeed Assani & Jianlin Jiang & Ahmad Assani & Feng Yang, 2019. "Estimating and decomposing most productive scale size in parallel DEA networks with shared inputs: A case of China's Five-Year Plans," Papers 1910.03421, arXiv.org, revised Oct 2019.
    5. Ming-Fu Hsu & Ying-Shao Hsin & Fu-Jiing Shiue, 2022. "Business analytics for corporate risk management and performance improvement," Annals of Operations Research, Springer, vol. 315(2), pages 629-669, August.
    6. Yiru Guo & Yan Hu & Ke Shi & Yuriy Bilan, 2020. "Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    7. Xie, Qiwei & Xu, Qifan & Zhu, Da & Rao, Kaifeng & Dai, Qianzhi, 2020. "Fair allocation of wastewater discharge permits based on satisfaction criteria using data envelopment analysis," Utilities Policy, Elsevier, vol. 66(C).

  7. Tao Ding & Ya Chen & Huaqing Wu & Yuqi Wei, 2018. "Centralized fixed cost and resource allocation considering technology heterogeneity: a DEA approach," Annals of Operations Research, Springer, vol. 268(1), pages 497-511, September.

    Cited by:

    1. Menghan Chen & Sheng Ang & Lijing Jiang & Feng Yang, 2020. "Centralized resource allocation based on cross-evaluation considering organizational objective and individual preferences," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(2), pages 529-565, June.
    2. Mohsen Afsharian, 2020. "A metafrontier-based yardstick competition mechanism for incentivising units in centrally managed multi-group organisations," Annals of Operations Research, Springer, vol. 288(2), pages 681-700, May.
    3. Elizabeth Ahikiriza & Jef Meensel & Xavier Gellynck & Ludwig Lauwers, 2021. "Heterogeneity in frontier analysis: does it matter for benchmarking farms?," Journal of Productivity Analysis, Springer, vol. 56(2), pages 69-84, December.
    4. Li, Yongjun & Lin, Lin & Dai, Qianzhi & Zhang, Linda, 2020. "Allocating common costs of multinational companies based on arm's length principle and Nash non-cooperative game," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1002-1010.
    5. Xie, Qiwei & Xu, Qifan & Zhu, Da & Rao, Kaifeng & Dai, Qianzhi, 2020. "Fair allocation of wastewater discharge permits based on satisfaction criteria using data envelopment analysis," Utilities Policy, Elsevier, vol. 66(C).
    6. Jiasen Sun & Guo Li, 2022. "Optimizing emission reduction task sharing: technology and performance perspectives," Annals of Operations Research, Springer, vol. 316(1), pages 581-602, September.
    7. Mehdi Soltanifar & Farhad Hosseinzadeh Lotfi & Hamid Sharafi & Sebastián Lozano, 2022. "Resource allocation and target setting: a CSW–DEA based approach," Annals of Operations Research, Springer, vol. 318(1), pages 557-589, November.
    8. Qingxian An & Ping Wang & Honglin Yang & Zongrun Wang, 2021. "Fixed cost allocation in two-stage system using DEA from a noncooperative view," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 1077-1102, December.
    9. Ding, Tao & Yang, Jie & Wu, Huaqing & Liang, Liang, 2022. "Land use efficiency and technology gaps of urban agglomerations in China: An extended non-radial meta-frontier approach," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    10. An, Qingxian & Wang, Ping & Emrouznejad, Ali & Hu, Junhua, 2020. "Fixed cost allocation based on the principle of efficiency invariance in two-stage systems," European Journal of Operational Research, Elsevier, vol. 283(2), pages 662-675.
    11. Tao Xu & Jianxin You & Yilei Shao, 2020. "Efficiency of China’s Listed Securities Companies: Estimation through a DEA-Based Method," Mathematics, MDPI, vol. 8(4), pages 1-16, April.

  8. Fabienne Miller & Justin Wang & Joe Zhu & Ya Chen & Jason Hockenberry, 2017. "Investigation of the Impact of the Massachusetts Health Care Reform on Hospital Costs and Quality of Care," Annals of Operations Research, Springer, vol. 250(1), pages 129-146, March.

    Cited by:

    1. Margit Sommersguter-Reichmann, 2022. "Health care quality in nonparametric efficiency studies: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(1), pages 67-131, March.

  9. Ya Chen & Wade D. Cook & Juan Du & Hanhui Hu & Joe Zhu, 2017. "Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China," Annals of Operations Research, Springer, vol. 255(1), pages 347-366, August.

    Cited by:

    1. Yande Gong & Joe Zhu & Ya Chen & Wade D. Cook, 2018. "DEA as a tool for auditing: application to Chinese manufacturing industry with parallel network structures," Annals of Operations Research, Springer, vol. 263(1), pages 247-269, April.
    2. Kang, Jijun & Yu, Chenyang & Xue, Rui & Yang, Dong & Shan, Yuli, 2022. "Can regional integration narrow city-level energy efficiency gap in China?," Energy Policy, Elsevier, vol. 163(C).
    3. Sidhoum, Amer Ait & Serra, Teresa, 2018. "Measuring Sustainability Efficiency At Farm Level: A Data Envelopment Analysis Approach," 166th Seminar, August 30-31, 2018, Galway, West of Ireland 276184, European Association of Agricultural Economists.
    4. De Witte, Kristof & Schiltz, Fritz, 2018. "Measuring and explaining organizational effectiveness of school districts: Evidence from a robust and conditional Benefit-of-the-Doubt approach," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1172-1181.
    5. Guo, Wen & Liu, Xiaorui, 2022. "Market fragmentation of energy resource prices and green total factor energy efficiency in China," Resources Policy, Elsevier, vol. 76(C).
    6. Xiang Ji & Jie Wu & Qingyuan Zhu & Jiasen Sun, 2019. "Using a hybrid heterogeneous DEA method to benchmark China’s sustainable urbanization: an empirical study," Annals of Operations Research, Springer, vol. 278(1), pages 281-335, July.
    7. Sun Meng & Wei Zhou & Jin Chen & Cheng Zhang, 2018. "A synthesized data envelopment analysis model and its application in resource efficiency evaluation and dynamic trend analysis," Energy & Environment, , vol. 29(2), pages 260-280, March.
    8. Monireh Jahani Sayyad Noveiri & Sohrab Kordrostami & Alireza Amirteimoori, 2022. "Performance analysis of sustainable supply networks with bounded, discrete, and joint factors," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 238-270, January.
    9. Kalinichenko, Olena & Amado, Carla A.F. & Santos, Sérgio P., 2022. "Exploring the potential of Data Envelopment Analysis for enhancing pay-for-performance programme design in primary health care," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1084-1100.
    10. Fritz Schiltz & Kristof Witte & Deni Mazrekaj, 2020. "Managerial efficiency and efficiency differentials in adult education: a conditional and bias-corrected efficiency analysis," Annals of Operations Research, Springer, vol. 288(2), pages 529-546, May.
    11. Shuanglian Chen & Gaoke Liao & Benjamin M. Drakeford & Pierre Failler, 2019. "The Non-Linear Effect of Financial Support on Energy Efficiency: Evidence from China," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    12. Ghimire, Sarad & Amin, Saman Hassanzadeh & Wardley, Leslie J., 2021. "Developing new data envelopment analysis models to evaluate the efficiency in Ontario Universities," Journal of Informetrics, Elsevier, vol. 15(3).
    13. Milad Kolagar & Seyed Mohammad Hassan Hosseini & Ramin Felegari & Parviz Fattahi, 2020. "Policy-making for renewable energy sources in search of sustainable development: a hybrid DEA-FBWM approach," Environment Systems and Decisions, Springer, vol. 40(4), pages 485-509, December.
    14. Utsav Pandey & Sanjeet Singh, 2022. "Data envelopment analysis in hierarchical category structure with fuzzy boundaries," Annals of Operations Research, Springer, vol. 315(2), pages 1517-1549, August.
    15. Zhao, Linlin & Zha, Yong & Zhuang, Yuliang & Liang, Liang, 2019. "Data envelopment analysis for sustainability evaluation in China: Tackling the economic, environmental, and social dimensions," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1083-1095.

  10. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.

    Cited by:

    1. Tatiana Bencova & Andrea Bohacikova, 2022. "DEA in Performance Measurement of Two-Stage Processes: Comparative Overview of the Literature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 111-129.
    2. Tsionas, Mike G. & Izzeldin, Marwan, 2018. "A novel model of costly technical efficiency," European Journal of Operational Research, Elsevier, vol. 268(2), pages 653-664.
    3. Li, Yongjun & Liu, Jin & Ang, Sheng & Yang, Feng, 2021. "Performance evaluation of two-stage network structures with fixed-sum outputs: An application to the 2018winter Olympic Games," Omega, Elsevier, vol. 102(C).
    4. Ang, Sheng & Liu, Pei & Yang, Feng, 2020. "Intra-Organizational and inter-organizational resource allocation in two-stage network systems," Omega, Elsevier, vol. 91(C).
    5. Kao, Chiang, 2019. "Inefficiency identification for closed series production systems," European Journal of Operational Research, Elsevier, vol. 275(2), pages 599-607.
    6. Kao, Chiang, 2017. "Efficiency measurement and frontier projection identification for general two-stage systems in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 261(2), pages 679-689.
    7. Kottas, Angelos T. & Bozoudis, Michail N. & Madas, Michael A., 2020. "Turbofan aero-engine efficiency evaluation: An integrated approach using VSBM two-stage network DEA," Omega, Elsevier, vol. 92(C).
    8. Victor John M. Cantor & Kim Leng Poh, 2020. "Efficiency measurement for general network systems: a slacks-based measure model," Journal of Productivity Analysis, Springer, vol. 54(1), pages 43-57, August.
    9. Xiaohong Liu & Feng Yang & Jie Wu, 2020. "DEA considering technological heterogeneity and intermediate output target setting: the performance analysis of Chinese commercial banks," Annals of Operations Research, Springer, vol. 291(1), pages 605-626, August.
    10. Lim, Dong-Joon & Kim, Moon-Su, 2022. "Measuring dynamic efficiency with variable time lag effects," Omega, Elsevier, vol. 108(C).
    11. Ya Chen & Justin Wang & Joe Zhu & H. David Sherman & Shin-Yi Chou, 2019. "How the Great Recession affects performance: a case of Pennsylvania hospitals using DEA," Annals of Operations Research, Springer, vol. 278(1), pages 77-99, July.
    12. 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.
    13. Jomthanachai, Suriyan & Wong, Wai-Peng & Soh, Keng-Lin & Lim, Chee-Peng, 2022. "A global trade supply chain vulnerability in COVID-19 pandemic: An assessment metric of risk and resilience-based efficiency of CoDEA method," Research in Transportation Economics, Elsevier, vol. 93(C).
    14. Kao, Chiang, 2020. "Decomposition of slacks-based efficiency measures in network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 283(2), pages 588-600.
    15. Patrizii, Vincenzo, 2020. "On network two stages variable returns to scale Dea models," Omega, Elsevier, vol. 97(C).
    16. Mahdiloo, Mahdi & Toloo, Mehdi & Duong, Thach-Thao & Farzipoor Saen, Reza & Tatham, Peter, 2018. "Integrated data envelopment analysis: Linear vs. nonlinear model," European Journal of Operational Research, Elsevier, vol. 268(1), pages 255-267.
    17. Chen, Kun & Zhu, Joe, 2020. "Additive slacks-based measure: Computational strategy and extension to network DEA," Omega, Elsevier, vol. 91(C).

  11. Yang, Min & Li, Yongjun & Chen, Ya & Liang, Liang, 2014. "An equilibrium efficiency frontier data envelopment analysis approach for evaluating decision-making units with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 239(2), pages 479-489.

    Cited by:

    1. Lucas Assunção & Andréa Cynthia Santos & Thiago F. Noronha & Rafael Andrade, 2021. "Improving logic-based Benders' algorithms for solving min-max regret problems," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(2), pages 23-57.
    2. Jiao, Hong-Wei & Liu, San-Yang, 2015. "A practicable branch and bound algorithm for sum of linear ratios problem," European Journal of Operational Research, Elsevier, vol. 243(3), pages 723-730.
    3. Alireza Amirteimoori & Simin Masrouri & Feng Yang & Sohrab Kordrostami, 2017. "Context-based competition strategy and performance analysis with fixed-sum outputs: an application to banking sector," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1461-1469, November.
    4. Li, Yongjun & Liu, Jin & Ang, Sheng & Yang, Feng, 2021. "Performance evaluation of two-stage network structures with fixed-sum outputs: An application to the 2018winter Olympic Games," Omega, Elsevier, vol. 102(C).
    5. Jie Wu & Panpan Xia & Qingyuan Zhu & Junfei Chu, 2019. "Measuring environmental efficiency of thermoelectric power plants: a common equilibrium efficient frontier DEA approach with fixed-sum undesirable output," Annals of Operations Research, Springer, vol. 275(2), pages 731-749, April.
    6. Wu, Jie & Chu, Junfei & Sun, Jiasen & Zhu, Qingyuan, 2016. "DEA cross-efficiency evaluation based on Pareto improvement," European Journal of Operational Research, Elsevier, vol. 248(2), pages 571-579.
    7. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.
    8. Xi Xiong & Guo-liang Yang & Kai-di Liu & De-qun Zhou, 2022. "A proposed fixed-sum carryovers reallocation DEA approach for social scientific resources of Chinese public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4097-4121, July.
    9. Zhu, Qingyuan & Li, Xingchen & Li, Feng & Wu, Jie & Zhou, Dequn, 2020. "Energy and environmental efficiency of China's transportation sectors under the constraints of energy consumption and environmental pollutions," Energy Economics, Elsevier, vol. 89(C).
    10. Bouzidis, Thanasis & Karagiannis, Giannis, 2022. "An alternative ranking of DMUs performance for the ZSG-DEA model," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    11. Shen, Peiping & Zhu, Zeyi & Chen, Xiao, 2019. "A practicable contraction approach for the sum of the generalized polynomial ratios problem," European Journal of Operational Research, Elsevier, vol. 278(1), pages 36-48.
    12. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.
    13. Jingrong Xu & Dechun Huang & Zhengqi He & Yun Zhu, 2020. "Research on the Structural Features and Influential Factors of the Spatial Network of China’s Regional Ecological Efficiency Spillover," Sustainability, MDPI, vol. 12(8), pages 1-22, April.
    14. Yang, Min & Li, Yong Jun & Liang, Liang, 2015. "A generalized equilibrium efficient frontier data envelopment analysis approach for evaluating DMUs with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 246(1), pages 209-217.
    15. Jiasen Sun & Guo Li, 2022. "Optimizing emission reduction task sharing: technology and performance perspectives," Annals of Operations Research, Springer, vol. 316(1), pages 581-602, September.
    16. Qingyuan Zhu & Jie Wu & Malin Song & Liang Liang, 2017. "A unique equilibrium efficient frontier with fixed-sum outputs in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(12), pages 1483-1490, December.
    17. Li, Feng & Zhang, Danlu & Zhang, Jinyu & Kou, Gang, 2022. "Measuring the energy production and utilization efficiency of Chinese thermal power industry with the fixed-sum carbon emission constraint," International Journal of Production Economics, Elsevier, vol. 252(C).
    18. Junfei Chu & Jie Wu & Qingyuan Zhu & Qingxian An & Beibei Xiong, 2019. "Analysis of China’s Regional Eco-efficiency: A DEA Two-stage Network Approach with Equitable Efficiency Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1263-1285, December.
    19. Thanasis Bouzidis & Giannis Karagiannis, 2021. "An Alternative Ranking of DMUs Performance for the ZGS-DEA Model," Discussion Paper Series 2021_12, Department of Economics, University of Macedonia, revised Oct 2021.

  12. Wu, Jie & An, Qingxian & Xiong, Beibei & Chen, Ya, 2013. "Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs," Energy Policy, Elsevier, vol. 57(C), pages 7-13.

    Cited by:

    1. Jie Wu & Qingyuan Zhu & Junfei Chu & Liang Liang, 2015. "Two-Stage Network Structures with Undesirable Intermediate Outputs Reused: A DEA Based Approach," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 455-477, October.
    2. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    3. Noor Ramli & Susila Munisamy & Behrouz Arabi, 2013. "Scale directional distance function and its application to the measurement of eco-efficiency in the manufacturing sector," Annals of Operations Research, Springer, vol. 211(1), pages 381-398, December.
    4. He, Weijun & Yang, Yi & Wang, Zhaohua & Zhu, Joe, 2018. "Estimation and allocation of cost savings from collaborative CO2 abatement in China," Energy Economics, Elsevier, vol. 72(C), pages 62-74.
    5. Yang, Zhuofan & Shi, Yong & Yan, Hong, 2017. "Analysis on pure e-commerce congestion effect, productivity effect and profitability in China," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 35-49.
    6. Ren, Xian-tong & Fukuyama, Hirofumi & Yang, Guo-liang, 2022. "Eliminating congestion by increasing inputs in R&D activities of Chinese universities," Omega, Elsevier, vol. 110(C).
    7. Rabab Mudakkar, Syeda & Zaman, Khalid & Shakir, Huma & Arif, Mariam & Naseem, Imran & Naz, Lubna, 2013. "Determinants of energy consumption function in SAARC countries: Balancing the odds," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 566-574.
    8. Chen, Zhenling & Li, Jinkai & Zhao, Weigang & Yuan, Xiao-Chen & Yang, Guo-liang, 2019. "Undesirable and desirable energy congestion measurements for regional coal-fired power generation industry in China," Energy Policy, Elsevier, vol. 125(C), pages 122-134.
    9. Zhiyang Shen & Jean-Philippe Boussemart & Hervé Leleu, 2015. "Aggregate green productivity growth in OECD’s countries," Working Papers 2016-EQM-03, IESEG School of Management.
    10. Xiaohong Zhuang & Zhuyuan Li & Run Zheng & Sanggyun Na & Yulin Zhou, 2021. "Research on the Efficiency and Improvement of Rural Development in China: Based on Two-Stage Network SBM Model," Sustainability, MDPI, vol. 13(5), pages 1-21, March.
    11. Boussemart, Jean-Philippe & Leleu, Hervé & Shen, Zhiyang, 2017. "Worldwide carbon shadow prices during 1990–2011," Energy Policy, Elsevier, vol. 109(C), pages 288-296.
    12. Zhang, Lin & Zhao, Linlin & Zha, Yong, 2021. "Efficiency evaluation of Chinese regional industrial systems using a dynamic two-stage DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    13. Jun Wang & Yong Zha, 2014. "Distinguishing Technical Inefficiency from Desirable and Undesirable Congestion with an Application to Regional Industries in China," Sustainability, MDPI, vol. 6(12), pages 1-19, December.
    14. Shiying Hou & Liangrong Song & Jiaqi Wang & Shujahat Ali, 2021. "How Land Finance Affects Green Economic Growth in Chinese Cities," Land, MDPI, vol. 10(8), pages 1-16, August.
    15. F. Wu & P. Zhou & D. Zhou, 2015. "Measuring Energy Congestion in Chinese Industrial Sectors: A Slacks-Based DEA Approach," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 479-494, October.
    16. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    17. Liu, Yunqiang & Zhu, Jialing & Li, Eldon Y. & Meng, Zhiyi & Song, Yan, 2020. "Environmental regulation, green technological innovation, and eco-efficiency: The case of Yangtze river economic belt in China," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    18. Yin, Pengzhen & Sun, Jiasen & Chu, Junfei & Liang, Liang, 2016. "Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspectiveAuthor-Name: Wu, Jie," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1047-1062.
    19. Lei Chen & Fei-Mei Wu & Feng Feng & Fujun Lai & Ying-Ming Wang, 2018. "A Common Set of Weights for Ranking Decision-Making Units with Undesirable Outputs: A Double Frontiers Data Envelopment Analysis Approach," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(06), pages 1-25, December.
    20. Hu, Jin-Li & Chang, Ming-Chung & Tsay, Hui-Wen, 2017. "The congestion total-factor energy efficiency of regions in Taiwan," Energy Policy, Elsevier, vol. 110(C), pages 710-718.
    21. Zhang, Yue-Jun & Liu, Jing-Yue & Su, Bin, 2020. "Carbon congestion effects in China's industry: Evidence from provincial and sectoral levels," Energy Economics, Elsevier, vol. 86(C).

  13. Li, Yongjun & Yang, Min & Chen, Ya & Dai, Qianzhi & Liang, Liang, 2013. "Allocating a fixed cost based on data envelopment analysis and satisfaction degree," Omega, Elsevier, vol. 41(1), pages 55-60.

    Cited by:

    1. Chu, Junfei & Wu, Jie & Chu, Chengbin & Zhang, Tinglong, 2020. "DEA-based fixed cost allocation in two-stage systems: Leader-follower and satisfaction degree bargaining game approaches," Omega, Elsevier, vol. 94(C).
    2. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    3. Yang, Zhihua & Zhang, Qianwei, 2015. "Resource allocation based on DEA and modified Shapley value," Applied Mathematics and Computation, Elsevier, vol. 263(C), pages 280-286.
    4. Li, Feng & Zhu, Qingyuan & Chen, Zhi, 2019. "Allocating a fixed cost across the decision making units with two-stage network structures," Omega, Elsevier, vol. 83(C), pages 139-154.
    5. Xie, Qiwei & Hu, Ping & Jiang, An & Li, Yongjun, 2019. "Carbon emissions allocation based on satisfaction perspective and data envelopment analysis," Energy Policy, Elsevier, vol. 132(C), pages 254-264.
    6. Yu, Ming-Miin & Chen, Li-Hsueh & Hsiao, Bo, 2018. "A performance-based subsidy allocation of ferry transportation: A data envelopment approach," Transport Policy, Elsevier, vol. 68(C), pages 13-19.
    7. Lin, Ruiyue & Liu, Yue, 2019. "Super-efficiency based on the directional distance function in the presence of negative data," Omega, Elsevier, vol. 85(C), pages 26-34.
    8. Mahdiloo, Mahdi & Ngwenyama, Ojelanki & Scheepers, Rens & Tamaddoni, Ali, 2018. "Managing emissions allowances of electricity producers to maximize CO2 abatement: DEA models for analyzing emissions and allocating emissions allowances," International Journal of Production Economics, Elsevier, vol. 205(C), pages 244-255.
    9. Yu, Ming-Miin & Chen, Li-Hsueh & Hsiao, Bo, 2016. "A fixed cost allocation based on the two-stage network data envelopment approach," Journal of Business Research, Elsevier, vol. 69(5), pages 1817-1822.
    10. Sun, Jiasen & Li, Guo & Wang, Zhaohua, 2018. "Optimizing China’s energy consumption structure under energy and carbon constraints," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 57-72.
    11. Zhu, Qingyuan & Li, Xingchen & Li, Feng & Wu, Jie & Zhou, Dequn, 2020. "Energy and environmental efficiency of China's transportation sectors under the constraints of energy consumption and environmental pollutions," Energy Economics, Elsevier, vol. 89(C).
    12. Dai, Qianzhi & Li, Yongjun & Lei, Xiyang & Wu, Dengsheng, 2021. "A DEA-based incentive approach for allocating common revenues or fixed costs," European Journal of Operational Research, Elsevier, vol. 292(2), pages 675-686.
    13. Yang, Min & Li, Yongjun & Chen, Ya & Liang, Liang, 2014. "An equilibrium efficiency frontier data envelopment analysis approach for evaluating decision-making units with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 239(2), pages 479-489.
    14. Yang, Min & Li, Yong Jun & Liang, Liang, 2015. "A generalized equilibrium efficient frontier data envelopment analysis approach for evaluating DMUs with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 246(1), pages 209-217.
    15. Li, Yongjun & Lin, Lin & Dai, Qianzhi & Zhang, Linda, 2020. "Allocating common costs of multinational companies based on arm's length principle and Nash non-cooperative game," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1002-1010.
    16. Xie, Qiwei & Xu, Qifan & Zhu, Da & Rao, Kaifeng & Dai, Qianzhi, 2020. "Fair allocation of wastewater discharge permits based on satisfaction criteria using data envelopment analysis," Utilities Policy, Elsevier, vol. 66(C).
    17. Chao, Shih-Liang & Yu, Ming-Miin, 2022. "Applying data envelopment analysis to allocate incentive bonuses for container terminal operators," Transport Policy, Elsevier, vol. 125(C), pages 231-240.
    18. Ma, Gang & Li, Xu & Zheng, Jianping, 2020. "Efficiency and equity in regional coal de-capacity allocation in China: A multiple objective programming model based on Gini coefficient and Data Envelopment Analysis," Resources Policy, Elsevier, vol. 66(C).
    19. An, Qingxian & Wang, Ping & Emrouznejad, Ali & Hu, Junhua, 2020. "Fixed cost allocation based on the principle of efficiency invariance in two-stage systems," European Journal of Operational Research, Elsevier, vol. 283(2), pages 662-675.
    20. An, Qingxian & Tao, Xiangyang & Xiong, Beibei & Chen, Xiaohong, 2022. "Frontier-based incentive mechanisms for allocating common revenues or fixed costs," European Journal of Operational Research, Elsevier, vol. 302(1), pages 294-308.

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 2 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-BIG: Big Data (2) 2020-02-03 2020-10-26
  2. NEP-EFF: Efficiency & Productivity (2) 2020-02-03 2020-10-26
  3. NEP-CMP: Computational Economics (1) 2020-10-26
  4. NEP-ECM: Econometrics (1) 2020-02-03

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