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<p>This paper provides a comprehensive analysis of Professor Rajiv Banker’s significant impact on the field of Data Envelopment Analysis (DEA). Through an extensive review of his scholarly contributions, we explore three major clusters within DEA research: (1) Returns-to-Scale (RTS) and Most Productive Scale Size (MPSS), (2) Statistical Inference in DEA, and (3) Contextual Analysis. Banker’s pioneering research has significantly advanced DEA methodologies, addressing fundamental challenges related to scale efficiency, statistical robustness, and the influence of contextual variables on performance. His work has bridged theoretical developments and practical applications, influencing diverse fields such as economics, finance, and management science. By examining citation trends and bibliometric data, we trace the evolution and enduring relevance of his contributions, highlighting key papers that have shaped the trajectory of DEA research. This paper also discusses the evolution of DEA models and approaches, including the integration of stochastic elements and second-stage analyses. In recognising Banker’s lifetime dedication to DEA, we celebrate his lasting legacy and his transformative influence on both the academic community and practical implementations of DEA worldwide.</p>

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Rajiv Banker’s lasting impact on data envelopment analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月24日

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  • Ali Emrouznejad,
  • Victor Podinovski,
  • Vincent Charles,
  • Chixiao Lu,
  • Amir Moradi-Motlagh

摘要

This paper provides a comprehensive analysis of Professor Rajiv Banker’s significant impact on the field of Data Envelopment Analysis (DEA). Through an extensive review of his scholarly contributions, we explore three major clusters within DEA research: (1) Returns-to-Scale (RTS) and Most Productive Scale Size (MPSS), (2) Statistical Inference in DEA, and (3) Contextual Analysis. Banker’s pioneering research has significantly advanced DEA methodologies, addressing fundamental challenges related to scale efficiency, statistical robustness, and the influence of contextual variables on performance. His work has bridged theoretical developments and practical applications, influencing diverse fields such as economics, finance, and management science. By examining citation trends and bibliometric data, we trace the evolution and enduring relevance of his contributions, highlighting key papers that have shaped the trajectory of DEA research. This paper also discusses the evolution of DEA models and approaches, including the integration of stochastic elements and second-stage analyses. In recognising Banker’s lifetime dedication to DEA, we celebrate his lasting legacy and his transformative influence on both the academic community and practical implementations of DEA worldwide.