The release of the Planning Outline for the Protection, Inheritance, and Utilization of Grand Canal Culture has created opportunities for the high-quality development of tourism economy in cities along the Grand Canal. To assess the policy’s effects, this study employs the entropy method to construct an evaluation system for high-quality tourism economic development, using panel data from 2010 to 2021 to measure the tourism economic development levels of cities along the Grand Canal. Based on the measurement results, the synthetic control method is applied to empirically test the impact of the Outline on high-quality tourism economic development. The findings show that: (1) divided by the Huai River, cities in southern provinces exhibit greater internal disparities in development levels than those in northern provinces. Hangzhou, Suzhou, and Ningbo demonstrate relatively high overall development levels, with scores of 0.724, 0.685, and 0.522, respectively, while Suzhou (Anhui) and Cangzhou show lower levels, at 0.204 and 0.211, respectively. (2) Within the high-quality development framework, Luoyang and Ningbo have achieved rapid progress in green development, exceeding 40%, while Luoyang, Zhengzhou, and Hangzhou show the most significant improvements in shared development. (3) At the provincial and municipal levels, the policy’s impact on high-quality tourism economic development is not significant overall. No policy effect is observed in treatment provinces/municipalities of Anhui, Beijing, Shandong, or Jiangsu, while Hebei and Tianjin show positive effects in coordinated development, Henan in green development, and Zhejiang in shared development. This study provides a quantitative and objective understanding of the actual impacts of policy implementation on various dimensions of urban tourism economic development, offering valuable insights for governments to formulate targeted measures, adjust implementation strategies in a timely manner, and promote the high-quality development of tourism economies in cities along the Grand Canal.

As an essential link connecting human subjective perceptions with objective environmental characteristics, landscape value serves as a major criterion for evaluating the recreational potential of natural landscapes and cultural heritages. This study constructs a recreational potential evaluation system dominated by multiple landscape values from dimensions of ecology, culture, and recreation. The study adopts Public Participation Geographic Information System (PPGIS) technology, a three-dimensional coordination model, and the multivariate clustering method to study the recreational potential of the Tonghui River, a section of the Grand Canal. Key findings include: (1) the recreational potential along the Tonghui River exhibits significant spatial heterogeneity, with high-potential areas mainly being distributed along both banks of the river and in parks, museums, and other locations that are along the river; (2) Concerning landscape value clustering, five compound types of landscape values have been identified and they are culture, history, and education values-dominated, recreation, tourism, and mind-body healing values-dominated, education, aesthetics, and history values-dominated, nature, mind-body healing, and biodiversity values-dominated, and biodiversity, nature, and mind-body healing values-dominated; (3) High-potential areas show a trend of low degree of multifunctional coordination, manifesting prominent single dimension of recreation or education and relatively insufficient ecological or natural support. (4) Six measures have been proposed by the public to optimize the recreational space along the Tonghui River, including improving the ecological environment, protecting cultural resources, increasing recreational facilities, enhancing infrastructure, expanding cultural activity spaces, and regulating recreational behaviors. The study enriches the theories and methodologies for recreational potential evaluation and provides empirical references for promoting community-engaged spatial optimization and heritage revitalization.

Digital transformation has become a crucial pathway and inevitable trend driving innovative development in tourism enterprises. As an important policy instrument, government subsidies exert significant signaling effects and play guiding roles in promoting the digital transformation of tourism enterprises. From a signaling perspective, this study examines. listed tourism companies on China’s A-share market from 2001 to 2022 and investigates the impact of government subsidies on tourism enterprises’ digital transformation through keyword screening and manual verification methods. The findings indicate: (1) government subsidies actively promote digital transformation in tourism enterprises; (2) These subsidies effectively reduce information asymmetry and enhance innovation capabilities, thereby facilitating digital transformation; (3) The transformative effects demonstrate regional and corporate heterogeneity, showing more pronounced impacts in private enterprises, small-scale firms, and regions with superior governance environments. This research not only expands theoretical perspectives on corporate digital transformation but also provides valuable decision-making references for governments to optimize tourism industry policies and improve subsidy mechanisms.

With the comprehensive implementation of the policy allowing tour guides to practice independently, online-hiring tour guide services have emerged as a novel model to meet tourists' personalized demands while posing challenges to service quality supervision. This study focuses on the regulatory issues of online-hiring tour guide service quality, constructing a tripartite evolutionary game model involving government regulators, online platforms, and tour guides. System dynamics simulations were employed to analyze the evolutionary stable strategies of stakeholders and the influence mechanisms of key parameters. The findings reveal: (1) the system exhibits three potential stable strategy combinations, converging toward an ideal equilibrium where governments enforce strict supervision, platforms exercise self-regulation, and guides provide high-quality services under specific parameter conditions. (2) Government regulators’ strategy choices are influenced jointly by platforms and guides, with stricter supervision adopted when platforms lack self-regulation or guides deliver low-quality services. (3) Platforms’ self-regulation probability increases with stricter government supervision but decreases as guides improve service quality. (4) Moderately enhancing governmental rewards to platforms or strengthening penalties for low-quality services proves effective in elevating service standards. These findings provide theoretical and practical significance for establishing a collaborative regulatory framework combining government leadership, platform collaboration, and guide self-discipline in online-hiring tour guide service quality management.