A dynamic network data envelopment analysis cross-efficiency evaluation on the benefits of bus transit services in 33 Chinese cities

References

• Aldamak, A., and S. Zolfaghari. 2017. “Review of Efficiency Ranking Methods in Data Envelopment Analysis.” Measurement 106: 161–172. doi:10.1016/j.measurement.2017.04.028.
   Web of Science ®Google Scholar
• Avkiran, N. K. 2015. “An Illustration of dynamic network DEA in commercial banking including robustness tests.” Omega 55: 141–150. doi:10.1016/j.omega.2014.07.002.
   Web of Science ®Google Scholar
• Bang, H. S., H. W. Kang, J. Martin, and S. H. Woo. 2012. “The impact of operational and strategic management on liner shipping efficiency: A two-stage DEA approach.” Maritime Policy & Management 39 (7): 653–672. doi:10.1080/03088839.2012.740165.
   Web of Science ®Google Scholar
• Boame, A. K. 2004. “The technical efficiency of Canadian urban transit systems.” Transportation Research Part E: Logistics and Transportation Review 40 (5): 401–416. doi:10.1016/j.tre.2003.09.002.
   Web of Science ®Google Scholar
• Cai, H., and S. D. Xie. 2010. “determination of emission factors from motor vehicles under different emission standards in China.” Acta Scientiarum Naturalium Universitatis Pekinensis 46 (3): 319–326. in chinese. doi:10.13209/j.0479-8023.2010.046.
   Google Scholar
• Caulfield, B., D. Bailey, and S. Mullarkey. 2013. “Using data envelopment analysis as a public transport project appraisal tool.” Transport Policy 29: 74–85. doi:10.1016/j.tranpol.2013.04.006.
   Web of Science ®Google Scholar
• Chao, S. L., M. M. Yu, and W. F. Hsieh. 2018. “Evaluating the Efficiency of major container shipping companies: a framework of dynamic network DEA with Shared inputs.” Transportation Research Part A: Policy and Practice 117: 44–57. doi:10.1016/j.tra.2018.08.002.
   Web of Science ®Google Scholar
• Charnes, A., W. W. Cooper, and E. Rhodes. 1978. “Measuring the efficiency of decision making units.” European Journal of Operational Research 2 (6): 429–444. doi:10.1016/0377-2217(78)90138-8.
   Web of Science ®Google Scholar
• Cummins, J. D., and X. Y. Xie. 2013. “Efficiency, productivity, and scale economies in the U.S. property-liability insurance industry.” Journal of Productivity Analysis 39 (2): 141–164. doi:10.1007/s11123-012-0302-2.
   Web of Science ®Google Scholar
• Doyle, J., and R. Green. 1994. “Efficiency and cross-efficiency in DEA: derivations, meanings and uses.” The Journal of the Operational Research Society 45 (5): 567–578. doi:10.1057/jors.1994.84.
   Web of Science ®Google Scholar
• Fan, J. L., J. X. Wang, F. Y. Li, H. Yu, and X. Zhang. 2017. “Energy demand and greenhouse gas emissions of urban passenger transport in the internet Era: A Case Study of Beijing.” Journal of Cleaner Production 165: 177–189. doi:10.1016/j.jclepro.2017.07.106.
   Web of Science ®Google Scholar
• Färe, R., and S. Grosskopf. 2000. “Network DEA.” Socio-Economic Planning Sciences 34 (1): 35–49. doi:10.1016/S0038-0121(99)00012-9.
   Google Scholar
• Farrell, M. J. 1957. “The measurement of productive efficiency.” Journal of the Royal Statistical Society 120 (3): 253–290. doi:10.2307/2343100.
   Web of Science ®Google Scholar
• Ferreira, D. C., I. Graziele, R. C. Marques, and J. Gonçalves. 2021. “Investment in drinking water and sanitation infrastructure and its impact on waterborne diseases dissemination: The Brazilian Case.” The Science of the Total Environment 779: 146279. doi:10.1016/j.scitotenv.2021.146279.
   PubMed Web of Science ®Google Scholar
• Ferreira, D. C., R. C. Marques, and M. I. Pedro. 2016. “Comparing efficiency of holding business model and individual management model of airports.” Journal of Air Transport Management 57: 168–183. doi:10.1016/j.jairtraman.2016.07.020.
   Web of Science ®Google Scholar
• Fitzová, H., M. Matulová, and Z. Tomeš. 2018. “Determinants of Urban Public Transport Efficiency: Case Study of the Czech Republic.” European Transport Research Review 10 (2): 42. doi:10.1186/s12544-018-0311-y.
   Web of Science ®Google Scholar
• Fukuyama, H., and W. L. Weber. 2010. “A Slacks-Based Inefficiency Measure for a Two-Stage System with Bad Outputs.” Omega 38 (5): 398–409. doi:10.1016/j.omega.2009.10.006.
   Web of Science ®Google Scholar
• Halkos, G., and K. N. Petrou. 2019. “Treating Undesirable Outputs in DEA: A Critical Review.” Economic Analysis and Policy 62: 97–104. doi:10.1016/j.eap.2019.01.005.
   Web of Science ®Google Scholar
• Huang, W. C., B. Shuai, Y. Sun, Y. Wang, and E. Antwi. 2018. “Using Entropy-TOPSIS Method to Evaluate Urban Rail Transit System Operation Performance: The China Case.” Transportation Research Part A: Policy and Practice 111: 292–303. doi:10.1016/j.tra.2018.03.025.
   Web of Science ®Google Scholar
• Ingvardson, J. B., and O. A. Nielsen. 2019. “The Relationship Between Norms, Satisfaction and Public Transport Use: A Comparison Across Six European Cities Using Structural Equation Modelling.” Transportation Research Part A: Policy and Practice 126 (AUG): 37–57. doi:10.1016/j.tra.2019.05.016.
   Google Scholar
• Kang, C. C., C. M. Feng, B. R. Liao, and H. A. Khan. 2020. “Accounting for Air Pollution Emissions and Transport Policy in the Measurement of the Efficiency and Effectiveness of Bus Transits.” Transportation Letters 12 (5): 349–361. doi:10.1080/19427867.2019.1592369.
   Web of Science ®Google Scholar
• Kao, C. 2009. “Efficiency Decomposition in Network Data Envelopment Analysis: A Relational Model.” European Journal of Operational Research 192 (3): 949–962. doi:10.1016/j.ejor.2007.10.008.
   Web of Science ®Google Scholar
• Kao, C. 2014. “Network Data Envelopment Analysis: A Review.” European Journal of Operational Research 239 (1): 1–16. doi:10.1016/j.ejor.2014.02.039.
   Web of Science ®Google Scholar
• Kao, C., and S. T. Liu. 2018. “Cross Efficiency Measurement and Decomposition in Two Basic Network Systems.” Omega 83 (MAR): 70–79. doi:10.1016/j.omega.2018.02.004.
   Google Scholar
• Karlaftis, M. G., and D. Tsamboulas. 2012. “Efficiency Measurement in Public Transport: Are Findings Specification Sensitive?” Transportation Research Part A: Policy and Practice 46 (2): 392–402. doi:10.1016/j.tra.2011.10.005.
   Web of Science ®Google Scholar
• Khushalani, J., and Y. A. Ozcan. 2017. “Are Hospitals Producing Quality Care Efficiently? An Analysis Using Dynamic Network Data Envelopment Analysis (DEA).” Socio-Economic Planning Sciences 60 (DEC): 15–23. doi:10.1016/j.seps.2017.01.009.
   Google Scholar
• Kiani Mavi, R., R. F. Saen, and M. Goh. 2019. “Joint Analysis of Eco-Efficiency and Eco-Innovation with Common Weights in Two-Stage Network DEA: A Big Data Approach.” Technological Forecasting and Social Change 144 (JUL): 553–562. doi:10.1016/j.techfore.2018.01.035.
   Google Scholar
• Lao, Y., and L. Liu. 2009. “Performance Evaluation of Bus Lines with Data Envelopment Analysis and Geographic Information Systems.” Computers, Environment and Urban Systems 33 (4): 247–255. doi:10.1016/j.compenvurbsys.2009.01.005.
   Web of Science ®Google Scholar
• Li, Q., P. R. Bai, Y. Chen, and X. Wei. 2020. “Efficiency Evaluation of Bus Transport Operations Given Exogenous Environmental Factors.” Journal of Advanced Transportation 2020: 1–13. doi:10.1155/2020/8899782.
   Web of Science ®Google Scholar
• Lin, B. Q., and Z. L. Du. 2018. “A Study of China’s Urban Vehicle Energy Consumption and Public Transport Efficiency.” Economic Research Journal 53 (06): 142–156. in chinese. https://kns.cnki.net/kcms/detail/detail.aspx?FileName=JJYJ201806011&DbName=CJFQ2018.
   Google Scholar
• Link, H. 2019. “The Impact of Including Service Quality into Efficiency Analysis: The Case of Franchising Regional Rail Passenger Serves in Germany.” Transportation Research Part A: Policy and Practice 119: 284–300. doi:10.1016/j.tra.2018.11.019.
   Web of Science ®Google Scholar
• Mahmoudi, R., A. Emrouznejad, S. N. Shetab-Boushehri, and S. R. Hejazi. 2018. “The Origins, Development and Future Directions of Data Envelopment Analysis Approach in Transportation Systems.” Socio-Economic Planning Sciences 69: 100672. doi:10.1016/j.seps.2018.11.009.
   Web of Science ®Google Scholar
• Ministry of Ecology and Environment of the People’s Republic of China, 2018. “Limits and Measurement Methods for Emissions from Light-Duty Vehicles (CHINA 5)”. https://www.mee.gov.cn/ywgz/fgbz/bz/bzwb/dqhjbh/dqydywrwpfbz/201309/t20130917_260352.shtml.
   Google Scholar
• Ministry of Housing and Urban-Rural Development of the People’s Republic of China, 2016-2019. China Urban Construction Statistical Yearbook. China Planning Press.
   Google Scholar
• Ministry of Transport of the People’s Republic of China. 2016-2019. China Transport Statistical Yearbook. Beijing China: China Communications Press.
   Google Scholar
• Ministry of Transport of the People’s Republic of China, 2020. “Passenger Traffic in China’s Central Cities in 2020”. https://xxgk.mot.gov.cn/2020/jigou/zhghs/202101/t20210121_3517380.html.
   Google Scholar
• National Bureau of Statistics of the People’s Republic of China. 2017-2020. China City Statistical Yearbook. Beijing China: China Statistics Press.
   Google Scholar
• Omrani, H., K. Shafaat, and A. Alizadeh. 2019. “Integrated Data Envelopment Analysis and Cooperative Game for Evaluating Energy Efficiency of Transportation Sector: A Case of Iran.” Annals of Operations Research 274 (1–2): 471–499. doi:10.1007/s10479-018-2803-5.
   Web of Science ®Google Scholar
• Orkcu, H. H., V. S. Ozsoy, M. Orkcu, and H. Bal. 2019. “A Neutral Cross Efficiency Approach for Basic Two Stage Production Systems.” Expert Systems with Applications 125: 333–344. doi:10.1016/j.eswa.2019.01.067.
   Web of Science ®Google Scholar
• Park, Y. S., S. H. Lim, G. Egilmez, and J. Szmerekovsky. 2018. “Environmental Efficiency Assessment of US Transport Sector: A Slack-Based Data Envelopment Analysis Approach.” Transportation Research Part D: Transport and Environment 61: 152–164. doi:10.1016/j.trd.2016.09.009.
   Web of Science ®Google Scholar
• Pereira, M. A., D. C. Dinis, D. C. Ferreira, J. R. Figueira, and R. C. Marques. 2022. “A Network Data Envelopment Analysis to Estimate nations’ Efficiency in the Fight Against SARS-CoV-2.” Expert Systems with Applications 210: 118362. doi:10.1016/j.eswa.2022.118362.
   PubMed Web of Science ®Google Scholar
• Pereira, M. A., D. C. Ferreira, J. R. Figueira, and R. C. Marques. 2021. “Measuring the Efficiency of the Portuguese Public Hospitals: A Value Modelled Network Data Envelopment Analysis with Simulation.” Expert Systems with Applications 181 (1): 115169. doi:10.1016/j.eswa.2021.115169.
   Google Scholar
• Ruiz, J. L., and I. Sirvent. 2012. “On the DEA Total Weight Flexibility and the Aggregation in Cross-Efficiency Evaluations.” European Journal of Operational Research 223 (3): 732–738. doi:10.1016/j.ejor.2012.06.011.
   Web of Science ®Google Scholar
• Saeedi, H., B. Behdani, B. Wiegmans, and R. Zuidwijk. 2019. “Assessing the Technical Efficiency of Intermodal Freight Transport Chains Using a Modified Network DEA Approach.” Transportation Research Part E: Logistics and Transportation Review 126 (JUN): 66–86. doi:10.1016/j.tre.2019.04.003.
   Google Scholar
• Seiford, L. M., and J. Zhu. 2002. “Modeling Undesirable Factors in Efficiency Evaluation.” European Journal of Operational Research 142 (1): 16–20. doi:10.1016/S0377-2217(01)00293-4.
   Web of Science ®Google Scholar
• Sexton, T. R., R. H. Silkman, and A. J. Hogan. 1986. “Data Envelopment Analysis: Critique and Extensions.” New Directions for Program Evaluation 1986 (32): 73–105. doi:10.1002/ev.1441.
   Google Scholar
• Sheth, C., K. Triantis, and D. Teodorovic. 2007. “Performance Evaluation of Bus Routes: A Provider and Passenger Perspective.” Transportation Research Part E: Logistics and Transportation Review 43 (4): 453–478. doi:10.1016/j.tre.2005.09.010.
   Web of Science ®Google Scholar
• State Council of the People’s Republic of China, 2014. “Notice of the State Council of China on Adjusting the Criteria for City Size Classification”. https://www.gov.cn/zhengce/content/2014-11/20/content_9225.htm.
   Google Scholar
• Stefaniec, A., K. Hosseini, J. H. Xie, and Y. J. Li. 2020. “Sustainability Assessment of Inland Transportation in China: A Triple Bottom Line-Based Network DEA Approach.” Transportation Research Part D: Transport and Environment 80: 102258. doi:10.1016/j.trd.2020.102258.
   Web of Science ®Google Scholar
• Sun, J., Y. Yuan, R. Yang, X. Ji, and J. Wu. 2017. “Performance Evaluation of Chinese Port Enterprises Under Significant Environmental Concerns: An Extended DEA-Based Analysis.” Transport Policy 60: 75–86. doi:10.1016/j.tranpol.2017.09.001.
   Web of Science ®Google Scholar
• Tian, N., S. S. Tang, A. Che, and P. Wu. 2019. “Measuring Regional Transport Sustainability Using Super-Efficiency SBM-DEA with Weighting Preference.” Journal of Cleaner Production 242: 118474. doi:10.1016/j.jclepro.2019.118474.
   Web of Science ®Google Scholar
• Tone, K., and M. Tsutsui. 2009. “Network DEA: A Slacks-Based Measure Approach.” European Journal of Operational Research 197 (1): 243–252. doi:10.1016/j.ejor.2008.05.027.
   Web of Science ®Google Scholar
• Tone, K., and M. Tsutsui. 2010. “Dynamic DEA: A Slacks-Based Measure Approach.” Omega 38 (3–4): 145–156. doi:10.1016/j.omega.2009.07.003.
   Web of Science ®Google Scholar
• Tone, K., and M. Tsutsui. 2014. “Dynamic DEA with Network Structure: A Slacks-Based Measure Approach.” Omega 42 (1): 124–131. doi:10.1016/j.omega.2013.04.002.
   Web of Science ®Google Scholar
• Van Lierop, D., M. G. Badami, and A. M. El-Geneid. 2018. “What Influences Satisfaction and Loyalty in Public Transport? A Review of the Literature.” Transport Reviews 38 (1): 52–72. doi:10.1080/01441647.2017.1298683.
   Web of Science ®Google Scholar
• Viton, P. A. 1997. “Technical Efficiency in Multi-Mode Bus Transit: A Production Frontier Analysis.” Transportation Research Part B: Methodological 31 (1): 23–39. doi:10.1016/S0191-2615(96)00019-7.
   Web of Science ®Google Scholar
• Wang, H. M. 2015. Research on the Benefit of Public Bus Service Based on Cooperative Governance: A Case Study of Shanghai Public Bus Service. Shanghai China: Tongji University Press.
   Google Scholar
• Wang, Y. M., and K. S. Chin. 2010. “A Neutral DEA Model for Cross-Efficiency Evaluation and Its Extension.” Expert Systems with Applications 37 (5): 3666–3675. doi:10.1016/j.eswa.2009.10.024.
   Web of Science ®Google Scholar
• Wang, Y. M., K. S. Chin, and P. Jiang. 2011. “Weight Determination in the Cross-Efficiency Evaluation.” Computers & Industrial Engineering 61 (3): 497–502. doi:10.1016/j.cie.2011.04.004.
   Web of Science ®Google Scholar
• Wang, Z. H., and W. J. He. 2017. “CO2 Emissions Efficiency and Marginal Abatement Costs of the Regional Transportation Sectors in China.” Transportation Research Part D: Transport and Environment 50: 83–97. doi:10.1016/j.trd.2016.10.004.
   Web of Science ®Google Scholar
• Wei, R., X. Y. Liu, Y. J. Mu, L. M. Wang, A. Golub, and S. Farber. 2017. “Evaluating Public Transit Services for Operational Efficiency and Access Equity.” Journal of Transport Geography 65 (DEC): 70–79. doi:10.1016/j.jtrangeo.2017.10.010.
   Google Scholar
• Wei, F. Q., X. Q. Zhang, J. F. Chu, F. Yang, and Z. Yuan. 2021. “Energy and Environmental Efficiency of China’s Transportation Sectors Considering CO2 Emission Uncertainty.” Transportation Research Part D: Transport and Environment 97 (11): 102955. doi:10.1016/j.trd.2021.102955.
   Google Scholar
• Wu, J., J. S. Sun, and L. Liang. 2012a. “Cross Efficiency Evaluation Method Based on Weight-Balanced Data Envelopment Analysis Model.” Computers & Industrial Engineering 63 (2): 513–519. doi:10.1016/j.cie.2012.04.017.
   Web of Science ®Google Scholar
• Wu, J., J. S. Sun, and L. Liang. 2012b. “DEA Cross-Efficiency Aggregation Method Based Upon Shannon Entropy.” International Journal of Production Research 50 (23): 6726–6736. doi:10.1080/00207543.2011.618150.
   Web of Science ®Google Scholar
• Wu, J., J. S. Sun, L. Liang, and Y. C. Zha. 2011. “Determination of Weights for Ultimate Cross Efficiency Using Shannon Entropy.” Expert Systems with Applications 38 (5): 5162–5165. doi:10.1016/j.eswa.2010.10.046.
   Web of Science ®Google Scholar
• Yu, M. M., L. H. Chen, and B. Hsiao. 2016. “Dynamic Performance Assessment of Bus Transit with the Multi-Activity Network Structure.” Omega 60 (APR): 15–25. doi:10.1016/j.omega.2015.06.003.
   Google Scholar
• Yu, M. M., L. H. Chen, and B. Hsiao. 2018. “A Performance-Based Subsidy Allocation of Ferry Transportation: A Data Envelopment Approach.” Transport Policy 68: 13–19. doi:10.1016/j.tranpol.2018.04.004.
   Web of Science ®Google Scholar
• Zhang, C. Q., Y. T. Hu, and W. T. Lu. 2022. “Evaluating the Comprehensive Benefit of Public Transport Service–The Perspective of Three Stakeholders.” Promet-Traffic & Transportation 34 (2): 179–193. doi:10.7307/ptt.v34i2.3855.
   Web of Science ®Google Scholar
• Zhang, C. Q., Z. C. Juan, Q. Y. Luo, and G. N. Xiao. 2016. “Performance Evaluation of Public Transit Systems Using a Combined Evaluation Method.” Transport Policy 45 (JAN): 156–167. doi:10.1016/j.tranpol.2015.10.001.
   Google Scholar
• Zhang, C. Q., Z. C. Juan, and G. N. Xiao. 2015. “Do Contractual Practices Affect Technical Efficiency? Evidence from Public Transport Operators in China.” Transportation Research Part E: Logistics and Transportation Review 80 (AUG): 39–55. doi:10.1016/j.tre.2015.05.001.
   Google Scholar
• Zhang, C. Q., Y. Liu, W. Lu, and G. Xiao. 2019. “Evaluating Passenger Satisfaction Index Based on PLS-SEM Model: Evidence from Chinese Public Transport Service.” Transportation Research Part A: Policy and Practice 120 (FEB): 149–164. doi:10.1016/j.tra.2018.12.013.
   Google Scholar
• Zhang, C. Q., G. N. Xiao, Y. Liu, and F. Yu. 2018. “The Relationship Between Organizational Forms and the Comprehensive Effectiveness for Public Transport Services in China?” Transportation Research Part A: Policy and Practice 118: 783–802. doi:10.1016/j.tra.2018.10.025.
   Web of Science ®Google Scholar
• Zhao, Y., K. Triantis, P. Murray-Tuite, and P. Edara. 2011. “Performance Measurement of a Transportation Network with a Downtown Space Reservation System: A Network-DEA Approach.” Transportation Research Part E: Logistics and Transportation Review 47 (6): 1140–1159. doi:10.1016/j.tre.2011.02.008.
   Web of Science ®Google Scholar