Understanding the Evolution of Regional Tourism Efficiency: Through the Lens of Evolutionary Economic Geography

Abstract

To further understand the evolution of regional tourism efficiency, a more systematic and theoretical analysis is required. Taking the urban agglomeration in the middle reaches of the Yangtze River as a case, this study applied evolutionary economic geography to analyze the evolutionary process of regional tourism efficiency. Data envelopment analysis (DEA) and the Malmquist index were used to measure the regional tourism efficiency and total factors productivity changes. Moreover, this paper employed the semi-variogram, Kriging interpolation, and Markov chain to explore the spatiotemporal evolution and transition characteristics of regional tourism efficiency. Finally, based on the test results of Geo-detector, the driving mechanism of the spatiotemporal evolution of regional tourism efficiency was constructed. The results show that the overall tourism development was inefficient, and the leading sources of inefficiency were primarily embedded in pure technology inefficiency, while the main contributor to the growth of total factor productivity was the positive technical change. Over time, the spatial spillover effect of regional tourism continued to increase, and the spatial pattern changed from divergence to convergence, resulting in co-evolution. The inertial trajectory of the evolution of regional tourism efficiency reveals a significant path dependence. Factors such as traffic accessibility, tourism resource endowments, tourism specialization, industrial structure, informatization, and openness can reasonably explain the evolution of regional tourism efficiency.

Analysis on the Spatial Structure and Interaction of Aviation Network and Tourism Efficiency Network in Major Cities in China

“…Following the studies of existing scholars [40][41][42], this research considers the cross-attributes of the tourism industry and data availability, and selects the number of A-class scenic spots, the number of employees in accommodation and catering above the quota, and the number of travel agencies in each city as resource input factors (i.e., tourism resource endowment), labor input factors (i.e., tourism labor advantage), and capital input factors (i.e., tourism capital advantage), respectively. The total tourism revenue (i.e., tourism revenue capacity) and the total number of tourist arrivals (i.e., tourism market scale) of each city are chosen as output evaluation indicators.…”

Spatiotemporal evolution and mechanisms of tourism efficiency and its decomposition: Evidence from 63 counties in Zhejiang, China

“…Applying these methods, some scholars have explored the evolutionary characteristics, spatial network structure, and influencing factors of provincial level tourism efficiency, proposing valuable suggestions for advancing high-quality tourism development in China [23][24][25][26]. In addition, the evolution of regional tourism efficiency and its mechanisms have been analyzed by measuring tourism efficiency [27]. Previous research has improved the input-output index system for evaluating tourism efficiency and analyzed its spatial spillover effects [28].…”

The relationship of tourism and geography for the development of sports activities: a bibliometric analysis

“…También se han analizado las características naturales y su relación con el turismo deportivo a través de la evaluación de indicadores de potenciales geográficos, económicos y de uso del recurso hídrico para identificar los impactos que se relacionan con estas actividades (Lewandowicz, 2022). Otros estudios se enfocan en elementos de accesibilidad del tráfico, la dotación de recursos turísticos, la especialización turística, la estructura industrial y la informatización para el fortalecimiento del turismo deportivo regional (Zhao et al, 2022). La sostenibilidad es un elemento vital en estudios del turismo deportivo desde asuntos de calidad y como instrumento de desarrollo local (Mateos, 2018).…”