Air transport provides important transportation services for economic development; meanwhile, its operation requires massive resource inputs into the air transport sector (ATS). In order to ensure sustainable development of air transport industry, improve the utilization efficiency of resources, and coordinate the development of the ATS and the macroeconomy, the operational efficiency of the industry should be evaluated accurately. However, few studies have analyzed the operational performance of ATSs across different regions. This study therefore constructs an index system and applied a three-stage data envelopment analysis (DEA) approach, which considers various regional environmental factors and statistical noise, to evaluate regional ATS operational performance. China’s 30 provincial ATS operational efficiencies in year 2017 are empirically evaluated using the proposed model. The empirical results show that different levels of environmental factors, such as regional GDP, openness, technical markets, technological development, and consumption, pose various influences on provincial ATS operational efficiency in China. Operational performance evaluation results eliminating these environmental effects in the third stage show considerable differences with that stage 1 results. In addition, corresponding development strategy implications in different provinces and regions are put forward according to the evaluation results.

The cultivated land use eco-efficiency (CLUE) is an important indicator to evaluate ecological civilization construction in China. Research on the spatial-temporal pattern and evolution trend of the CLUE can help to assess the level of ecological civilization construction and reveal associated demonstration and driving effects on surrounding areas. Based on the perspective of the CLUE, this paper obtains cultivated land use data pertaining to National Pilot Zones for Ecological Conservation in China and neighboring provinces from 2008 to 2018. In this study, the SBM-undesirable, Moran’s I, and Markov chain models are adopted to quantitatively measure and analyze the CLUE and its temporal and spatial patterns and evolution trend. The research results indicate that the CLUE in the whole study area exhibited the characteristics of one growth, two stable, and two decline stages, with a positive spatial autocorrelation that increased year by year, and a spatial spillover effect was observed. Geographical spatial patterns and spatial spillover effects played a major role in the evolution of the CLUE, and there occurred a higher probability of improvement in the vicinity of cities with high CLUE values. In the future, practical construction experience should be disseminated at the provincial level, and policies and measures should be formulated according to local conditions. In addition, a linkage model between prefecture-level cities should be developed at the municipal level to fully manifest the positive spatial spillover effect. Moreover, we should thoroughly evaluate the risk associated with CLUE transition from high to low levels and establish a low-level early warning mechanism.

The names of tourism types formed by scholars and practitioners reflect the connotations of various tourism types from different aspects and carry a wealth of tourism knowledge. The documents containing the names and connotations of 232 tourism types were sorted from the Springer Encyclopedia of Tourism and 16 major international academic journals. These documents were analyzed using the coding method of grounded theory. A total of 155 naming elements, 22 subcategories, and six categories were extracted. These naming elements, subcategories, and categories constitute the tourism-type ontology, which is the first tourism-type classification framework. Furthermore, the construction of tourism-type ontology enriches the existing research on overall tourism knowledge. The tourism-type ontology can also be used as a preliminary framework for organizing overall tourism knowledge and a foundation for constructing a unified tourism-type naming rule.

Purpose: The purpose of this paper is to investigate how to improve the effectiveness of public participation in public infrastructure megaprojects (PIMs). Conflicts among stakeholders and uncertainty disrupt the success of PIMs when public participation is ineffective.Design/methodology/approach: Secondhand data are collected to study the effectiveness of public participation in the Beijing–Shenyang High-Speed Rail (China) and the California High-Speed Rail (USA). The employed research method is an inductive case study.Findings: Ineffective public participation can cause schedule and cost overruns and increase uncertainty in PIMs. The ambiguity of meaningful public participation, ineffective participatory approaches and overburden of public participation in environmental impact assessment are the causes of ineffective public participation in PIMs.Research limitations/implications: Public participation has become an essential part in PIMs management. This study looks at the understanding of the relationship between public participation and the success of PIMs.Practical implications: Legislative bodies should perfect the laws to guarantee meaningful public participation. Lead agencies should adopt additional effective participatory approaches to solicit public comments and identify critical voices. A dispute solution mechanism is necessary to solve public participation disputes in PIMs in practice.Originality/value: Stakeholder and uncertainty management are important to the success of PIMs. This study reveals methods to improve the effectiveness of public participation to alleviate the conflicts among stakeholders and reduce uncertainty in PIMs.

In China, rural summer health tourism for the urban elderly (RSHTUE) is growing rapidly, but the drivers of RSHTUE development have not been systematically explored. First, this study conducted semi-structured interviews with operators, village leaders, local government staff, and elderly tourists in Zhongyuan Township, Jiangxi Province, China: a typical township for developing RSHTUE. Second, interview data were thematically coded to extract the preliminary drivers. Third, the preliminary drivers supported by the literature or original interview quotes were considered the final drivers. Lastly, subcategories and categories were extracted from the final drivers by thematic coding to form a framework of drivers for RSHTUE development. The results show that the framework driving RSHTUE development includes two categories: demand and supply. Nine demand drivers were clustered into four subcategories: economic, social, cultural, and natural. A total of 21 supply drivers were clustered into five subcategories: economic, social, political, cultural, and natural. This study enriches the knowledge of RSHTUE development drivers. The literature supporting each driver was systematically reviewed. RSHTUE-relevant participants can use these drivers to identify villages’ suitability for developing RSHTUE and to explore countermeasures for the sustainable development of RSHTUE. The literature on each driver can provide support for subsequent studies.