A comparison of chance-constrained data envelopment analysis, stochastic nonparametric envelopment of data and bootstrap method: A case study of cultural regeneration performance of cities

• Published in: European journal of operational research Vol. 316; no. 3; pp. 1179 - 1191
• Main Authors: Lin, Sheng-Wei, Lu, Wen-Min
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.08.2024
• Subjects: Bootstrap method; Chance-constrained data envelopment analysis; Cultural regeneration performance; OR in government; Stochastic nonparametric envelopment of data; Stochastic nonparametric envelopment of data; Bootstrap method; Cultural regeneration performance; Chance-constrained data envelopment analysis; OR in government
• ISSN: 0377-2217
• DOI: 10.1016/j.ejor.2024.03.018

•Comprehensive comparison of CCDEA, StoNED, and bootstrap methods.•Insights into efficiency scores in cultural regeneration.•Reveals regional disparities in management efficiency and value creation.•Provides guidance for choosing efficiency methods in cultural regeneration.•Enriches knowledge in efficiency analysis and policy development. This study comprehensively compares three efficiency measurement methods—chance-constrained data envelopment analysis (CCDEA), stochastic nonparametric envelopment of data (StoNED), and the bootstrap method—in the context of the cultural regeneration performance of cities. The research examines these methods’ methodological differences, advantages, and disadvantages with a focus on uncertainty handling, production function assumptions, and computational requirements. The analysis reveals that CCDEA and the bootstrap method yield similar efficiency scores, while StoNED tends to produce lower efficiency scores. Furthermore, regions exhibit higher value-creation efficiency of cultural and creative industry than operational management efficiency, thus highlighting the untapped potential for improving value creation in cultural regeneration projects. This comprehensive comparison enables researchers and practitioners to further understand the nuances among these methods and select the most suitable method for their specific needs and objectives when evaluating the performance of cultural regeneration projects or other applications.