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Content analysis of data envelopment analysis literature and its comparison with that of other OR/MS fields

Author

Listed:
  • S Gattoufi

    (Sabanci University)

  • M Oral

    (Sabanci University)

  • A Kumar

    (Grand Valley State University)

  • A Reisman

    (Sabanci University
    Reisman and Associates)

Abstract

Content analysis was performed on the data envelopment analysis (DEA) literature appearing in refereed journals. The extant DEA literature, reported in Gattoufi et al was subdivided into two ways. The first considers all articles appearing during the life cycle of 22 selected major DEA publishing journals. The second considers all post-1995 DEA articles. Content was judged on the basis of a two-point scale representing advancements in theory; a five-point scale indicating contributions to practice; and on seven distinguishable strategies applied by the authors in pursuing their research. Lastly, DEA was compared with similarly obtained results describing the life cycle literatures of flow shop scheduling and of cell manufacturing. This analysis has proven the vitality, robustness, and real-world grounding of DEA on its own and vis-à-vis other OR/MS sub-disciplines. Moreover, the breadth of its diffusion into other disciplines and professions has been shown to be extraordinary.

Suggested Citation

  • S Gattoufi & M Oral & A Kumar & A Reisman, 2004. "Content analysis of data envelopment analysis literature and its comparison with that of other OR/MS fields," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 911-935, September.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:9:d:10.1057_palgrave.jors.2601767
    DOI: 10.1057/palgrave.jors.2601767
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    4. Forsund, Finn R. & Sarafoglou, Nikias, 2005. "The tale of two research communities: The diffusion of research on productive efficiency," International Journal of Production Economics, Elsevier, vol. 98(1), pages 17-40, October.
    5. Timo Kuosmanen & Andrew L. Johnson, 2010. "Data Envelopment Analysis as Nonparametric Least-Squares Regression," Operations Research, INFORMS, vol. 58(1), pages 149-160, February.
    6. Huang, Wencheng & Shuai, Bin & Sun, Yan & Wang, Yang & Antwi, Eric, 2018. "Using entropy-TOPSIS method to evaluate urban rail transit system operation performance: The China case," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 292-303.
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    8. Yao, Di & Xu, Liqun & Li, Jinpei, 2020. "Does technical efficiency play a mediating role between bus facility scale and ridership attraction? Evidence from bus practices in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 77-96.
    9. Zhang, Chunqin & Juan, Zhicai & Luo, Qingyu & Xiao, Guangnian, 2016. "Performance evaluation of public transit systems using a combined evaluation method," Transport Policy, Elsevier, vol. 45(C), pages 156-167.
    10. Zhao, Y. & Triantis, K. & Murray-Tuite, P. & Edara, P., 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, Elsevier, vol. 47(6), pages 1140-1159.
    11. Bhagwan Jagwani, 2012. "Efficiency Measurement in the Indian Banking Industry: An Application of Data Envelopment Analysis," Vision, , vol. 16(4), pages 315-331, December.
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