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A new multi-component DEA approach using common set of weights methodology and imprecise data: an application to public sector banks in India with undesirable and shared resources

Author

Listed:
  • Jolly Puri

    (Thapar University)

  • Shiv Prasad Yadav

    (Indian Institute of Technology Roorkee)

  • Harish Garg

    (Thapar University)

Abstract

Owing to the importance of internal structure of decision making units (DMUs) and data uncertainties in real situations, the present paper focuses on multi-component data envelopment analysis (MC-DEA) approach with imprecise data. The undesirable outputs and shared resources are also incorporated in the production process of multi-component DMUs to validate real problems. The interval efficiencies of DMUs and their components in MC-DEA are often challenging with imprecise data. In many practical situations, different set of weights may be resulted into valid efficiency intervals for DMUs but invalid interval efficiencies for their components. Therefore, the present study proposes a new common set of weights methodology, based on interval arithmetic and unified production frontier, to determine unique weights for measuring these interval efficiencies. It is a two-level mathematical programming approach that preserves linearity of DEA and exhibits stronger discrimination power among the DMUs as compared to some existing approaches. Theoretically, the aggregate efficiency interval of each DMU lies between the components’ interval efficiencies. Further, the proposed approach is also applied to banks in India for proving its acceptability in practical applications. The performance of each bank is investigated in terms of two components: general business and bancassurance business for the years 2011–2013. The present study emphasized expanding pattern of bancassurance business in current market scenario with more percentage increase as contrasted to general business.

Suggested Citation

  • Jolly Puri & Shiv Prasad Yadav & Harish Garg, 2017. "A new multi-component DEA approach using common set of weights methodology and imprecise data: an application to public sector banks in India with undesirable and shared resources," Annals of Operations Research, Springer, vol. 259(1), pages 351-388, December.
    • Handle: RePEc:spr:annopr:v:259:y:2017:i:1:d:10.1007_s10479-017-2540-1
    DOI: 10.1007/s10479-017-2540-1
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    References listed on IDEAS

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    1. Jolly Puri & Shiv Prasad Yadav, 2013. "Performance evaluation of public and private sector banks in India using DEA approach," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 18(1), pages 91-121.
    2. Tyagi, Preeti & Yadav, Shiv Prasad & Singh, S.P., 2009. "Relative performance of academic departments using DEA with sensitivity analysis," Evaluation and Program Planning, Elsevier, vol. 32(2), pages 168-177, May.
    3. Kao, Chiang, 2009. "Efficiency decomposition in network data envelopment analysis: A relational model," European Journal of Operational Research, Elsevier, vol. 192(3), pages 949-962, February.
    4. Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity and intermediate products: A frontier approach," Economics Letters, Elsevier, vol. 50(1), pages 65-70, January.
    5. Zhu, Joe, 2003. "Imprecise data envelopment analysis (IDEA): A review and improvement with an application," European Journal of Operational Research, Elsevier, vol. 144(3), pages 513-529, February.
    6. Roll, Yaakov & Cook, Wade D., 1993. "Partial efficiencies in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 27(3), pages 171-179, September.
    7. 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.
    8. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    9. Wade Cook & Moez Hababou & Hans Tuenter, 2000. "Multicomponent Efficiency Measurement and Shared Inputs in Data Envelopment Analysis: An Application to Sales and Service Performance in Bank Branches," Journal of Productivity Analysis, Springer, vol. 14(3), pages 209-224, November.
    10. Chen, Yao & Du, Juan & David Sherman, H. & Zhu, Joe, 2010. "DEA model with shared resources and efficiency decomposition," European Journal of Operational Research, Elsevier, vol. 207(1), pages 339-349, November.
    11. Fare, R. & Grabowski, R. & Grosskopf, S. & Kraft, S., 1997. "Efficiency of a fixed but allocatable input: A non-parametric approach," Economics Letters, Elsevier, vol. 56(2), pages 187-193, October.
    12. William W. Cooper & Kyung Sam Park & Gang Yu, 1999. "IDEA and AR-IDEA: Models for Dealing with Imprecise Data in DEA," Management Science, INFORMS, vol. 45(4), pages 597-607, April.
    13. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    14. Cook, Wade D. & Zhu, Joe & Bi, Gongbing & Yang, Feng, 2010. "Network DEA: Additive efficiency decomposition," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1122-1129, December.
    15. Ali Emrouznejad, 2014. "Advances in data envelopment analysis," Annals of Operations Research, Springer, vol. 214(1), pages 1-4, March.
    16. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    17. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    18. Lorenzo Castelli & Raffaele Pesenti & Walter Ukovich, 2010. "A classification of DEA models when the internal structure of the Decision Making Units is considered," Annals of Operations Research, Springer, vol. 173(1), pages 207-235, January.
    19. 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.
    20. Korhonen, Pekka J. & Luptacik, Mikulas, 2004. "Eco-efficiency analysis of power plants: An extension of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 437-446, April.
    21. Kao, Chiang, 2009. "Efficiency measurement for parallel production systems," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1107-1112, August.
    22. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    23. C Kao, 2012. "Efficiency decomposition for parallel production systems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(1), pages 64-71, January.
    24. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
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    3. Zhujia Yin & Yantuan Yu & Jianhuan Huang, 2018. "Evaluation and evolution of bank efficiency considering heterogeneity technology: An empirical study from China," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-19, October.
    4. Hamid Kiaei & Reza Kazemi Matin, 2022. "New common set of weights method in black-box and two-stage data envelopment analysis," Annals of Operations Research, Springer, vol. 309(1), pages 143-162, February.
    5. I. Contreras & S. Lozano & M. A. Hinojosa, 2021. "A bargaining approach to determine common weights in DEA," Operational Research, Springer, vol. 21(3), pages 2181-2201, September.
    6. Wasi Ul Hassan Shah & Gang Hao & Nan Zhu & Rizwana Yasmeen & Ihtsham Ul Haq Padda & Muhammad Abdul Kamal, 2022. "A cross-country efficiency and productivity evaluation of commercial banks in South Asia: A meta-frontier and Malmquist productivity index approach," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-17, April.
    7. 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.
    8. Pankaj Dutta & Aayush Jain & Asish Gupta, 2020. "Performance analysis of non-banking finance companies using two-stage data envelopment analysis," Annals of Operations Research, Springer, vol. 295(1), pages 91-116, December.
    9. Shabani, Amir & Visani, Franco & Barbieri, Paolo & Dullaert, Wout & Vigo, Daniele, 2019. "Reliable estimation of suppliers’ total cost of ownership: An imprecise data envelopment analysis model with common weights," Omega, Elsevier, vol. 87(C), pages 57-70.
    10. Xinlin Zhang, 2020. "Estimation of eco‐efficiency and identification of its influencing factors in China's Yangtze River Delta urban agglomerations," Growth and Change, Wiley Blackwell, vol. 51(2), pages 792-808, June.

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