城市创造力:结合DEA与SFA模型的效率评估

Urban Creativity: An Efficiency Evaluation Combining DEA With SFA Models

Journal of Regional Science · 2026
被引 0 · 同刊同年前 10%
人大 A-ABS 3

中文导读

提出城市创造力概念,将其操作化为文化遗产与创意经济的联合领域,并利用DEA和SFA模型评估107个意大利城市的效率,发现文化遗产是主要贡献者,小城市资源利用更高效,政治行动可带来高达14%的提升。

Abstract

ABSTRACT Technical efficiency analysis is widely applied in the cultural and creative sectors. However, little research uses this notion to understand how these economic activities perform at the urban level. In this paper, conceptually, we operationalize urban creativity (UC) as the joint realm of cultural heritage and creative economy; empirically, we measure UC by combining their respective technical‐efficiency scores via entropy‐weighted aggregation. Our research focuses on 107 Italian cities at NUTS‐3 levels and tests the diverse contributions made by the activities mentioned above in the period from 2014 to 2019. Data envelopment analysis and stochastic frontier analysis, both considered in two‐stages approach and output‐oriented, were combined through weighted entropy. The first results show that cultural heritage is the most efficient and decisive contributor to the UC index. In the entropy‑weighted composite, a high CH efficiency score carries greater weight and thus contributes more strongly to overall UC. Conversely, where CH efficiency is weaker, a high CE score can partially compensate, reflecting a synergy mechanism in the composite index. Moreover, we found that small cities tend to make careful and efficient use of resources, while most of the large cities, even when well‐endowed, struggle to govern their CCIs efficiently. This work also examines the contribution of external factors to UC, finding that the influence of GDP, crime, unemployment, educational level, and geographical location (South‐North or West‐East) on UC is limited to specific clusters or peripheral cities. Political faith, understood as local political action, has a generally positive effect and can result in up to +14% improvement, with less equipped cities more likely to benefit from it.

城市创意技术效率数据包络分析随机前沿分析熵权法