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Performance evaluation of NBA teams: A non-homogeneous DEA approach

Author

Listed:
  • Min Yang
  • Yuqi Wei
  • Liang Liang
  • Jingjing Ding
  • Xianmei Wang

Abstract

National Basketball Association (NBA) is one of the four major sports leagues in North America. The performance evaluation of NBA teams is an important reference for team managers. However, non-homogeneity issues exist on both inputs and outputs sides for NBA teams evaluations. For example, some teams do not have “high-level” players as inputs and some teams are not qualified to play in the playoffs with respect to “wins in the playoffs” as an output. The current paper extends the existing non-homogeneous DEA method to address the non-homogeneous structure of NBA teams in performance evaluation by splitting NBA teams into types of homogeneous sub-units. The sub-unit, in this paper, consists of empirical input subset and output subset which satisfies both atomic property and maximum property. In addition, our method yields a unique efficiency decomposition of sub-units of NBA teams in 2018–2019 season without the need for imposing any additional conditions which are needed in some prior relative researches. As a result, detailed performance improvement directions for all teams can be provided.

Suggested Citation

  • Min Yang & Yuqi Wei & Liang Liang & Jingjing Ding & Xianmei Wang, 2021. "Performance evaluation of NBA teams: A non-homogeneous DEA approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(6), pages 1403-1414, June.
    • Handle: RePEc:taf:tjorxx:v:72:y:2021:i:6:p:1403-1414
    DOI: 10.1080/01605682.2020.1718560
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    Cited by:

    1. Josef Jablonsky, 2022. "Individual and team efficiency: a case of the National Hockey League," 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(2), pages 479-494, June.
    2. Yu Zhu & Feng Yang & Bengang Gong & Wei Zeng, 2023. "RETRACTED ARTICLE: Assessing the efficiency of innovation entities in China: evidence from a nonhomogeneous data envelopment analysis and Tobit," Electronic Commerce Research, Springer, vol. 23(1), pages 175-205, March.

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