• Energy Research

Intangible cultural heritage can provide cultural value content for product development and marketing of tourism destinations, enabling these areas to obtain economic benefits. This study selects cultural identity as an antecedent variable, and applies the theory of planned behavior to construct the influence mechanism of cultural identity on tourists’ consumption intention in heritage tourism. In tourism development, visitors and local residents have reached a common cognitive basis for Kunqu Opera through cultural identity, thereby guiding consumer behavior and promoting the continuous development of Kunqu Opera tourism. This study takes Suzhou Kunqu Opera as a research object, designs a questionnaire for local residents and tourists, establishes a structural equation model, and explores the relationship between various impact factors. The results of the study show that cultural identity has a positive effect on consumption intentions in heritage tourism activities, confirming that cultural identity is an effective driving force to promote tourists’ consumption intention. Behavioral attitudes, subjective norms, and perceived behavioral control have a positive effect on consumption intentions. This study supplements the existing knowledge on tourists’ consumption intention in intangible cultural heritage destinations. The study also provides new insights to enhance the consumption intention and achieve long-term sustainable development of the destination.

With the advent of the fifth-generation mobile communication technology era, mobile technology will further change tourism. However, studies on mobile technology in tourism from the perspective of bibliometrics and visualization are limited. This research aimed to systematically, comprehensively, and objectively analyze the current research status and potential future research directions in this field through a visual bibliometric analysis of mobile technology research in tourism. This study used CiteSpace software to analyze 803 related journal papers from the Web of Science Core Collection and provided insights into the research of mobile technology in tourism from the aspects of research trends, research areas, top journals, author/institution/country or region collaboration networks, research keywords, and research foundations. The study can help related personnel in academia and industry to fully understand the research of mobile technology in tourism and provides valuable references for related research fields on bibliometric and visualized analysis.

Urbanization in China is considered an important force for global sustainable development. In particular, China’s urbanization is of great significance to achieve the Millennium Goals of the UN. Hence, an in-depth understanding of China’s urbanization sustainable development process and model of sustainable development is urgently needed. As a result, this study examines the sustainable development of urbanization using China as an example through a survey method. Specifically, sustainable development of urbanization is examined from the following five perspectives: economic development, basic public service quality, ecological environment development, urban–rural heterogeneity, and population urbanization. Differences in the sustainable development quality of different urbanization models and regional urbanization were analyzed. Findings showed that the difference in urbanization quality between different models is not obvious, while the difference in urbanization quality between regions is more obvious. Furthermore, the quality of urbanization development in the eastern region is better than that in the central and western regions, and the level of urbanization development with high administrative levels is superior to regions with low administrative levels.

Identifying the tourist flow of a destination can promote the development of travel-related products and effective destination marketing. Nevertheless, tourist inflows and outflows have only received limited attention from previous studies. Hence, this study visualizes the tourist flow of Tibet through social network analysis to bridge the aforementioned gap. Findings show that the Lhasa prefecture is the transportation hub of Tibet. Tourist flow in the eastern part of Tibet is generally stronger than that in the western part. Moreover, the tourist flow pattern identified mainly includes “(diverse or balanced) diffusion from the main center”, “clustering to the main center”, and “diffusion from a clustered circle”.

The infectious pneumonia caused by the 2019 novel coronavirus (COVID-19) has spread rapidly worldwide, crippling the global tourism industry’s development and operations. In Hong Kong, where tourism is a pillar industry, the hotel industry is essential to maintaining a stable economy. Facing multiple forms of pressure, the industry’s status deserves close attention. More than 200 hotels in Hong Kong were taken as the research set in this study. A Python-based web crawler was used to collect daily hotel prices from various online travel agencies. Repeated-measures analysis of variance (ANOVA), correlation analysis, and descriptive analysis were employed to study hotels’ room rate fluctuations over time. Results indicated that room rates across hotels in Hong Kong were primarily influenced by holidays and festivities prior to COVID-19, whereas rates tended to decline after the outbreak. Data analysis based on hotels’ star ratings revealed that 5-star hotels were relatively less affected by COVID-19 while 4- and 4.5-star hotels were most seriously affected. District-level analysis also showed that hotel room rates were differentially influenced by the virus: Hong Kong’s Islands district was hit hardest, followed by Kowloon. These findings offer valuable implications for hotel managers and relevant government departments in making rational decisions based on the current market state.

Intangible cultural heritage is a natural fit for tourism development due to its extensive cultural and artistic value. Authenticity is important in the development of intangible cultural heritage tourism. This case study considered Celadon Town, a classic scenic spot of intangible cultural heritage in Zhejiang Province, China, to design questionnaires and a research model involving cultural identity, authenticity perception, tourist satisfaction, and traveler loyalty. This model was used to explore the indigenous presentation of authenticity, that is, the “Traditional Firing Technique of Longquan Celadon,” and its impact on tourist satisfaction and loyalty. On the basis of the research model and hypotheses, relevant data were collected through a questionnaire survey, tested, and analyzed using a structural equation model (SEM). Findings indicate that authenticity of intangible cultural heritage has a significant positive effect on destination satisfaction and loyalty, which supplements related research on the authenticity of intangible cultural heritage destinations. This study advocates that building a characteristic town is a unique development mode of intangible cultural heritage tourism. The model integrates the cultural and tourism attributes of intangible cultural heritage. Based on this development model, the study offers related suggestions for the construction of authenticity and the realization of long-term development of tourism destinations.

Given the influence of the financial-economic crisis, hotel room demand in Hong Kong has experienced a significant drop since June 2019. Given that studies on the room rate aspect remains limited, this study considers the demand for hotel rooms from different categories and districts. This study makes forecast attempts for room rates from mid-October of 2019 to mid-June of 2020, which was a difficult period for Hong Kong owing to the onset of the social unrest and novel coronavirus outbreak. This study develops an approach to the short-term forecasting of hotel daily room rates on the basis of the Long Short-Term Memory (LSTM) model by leveraging the key properties of day-of-week to improve accuracy. This study collects a data set containing 235 hotels of the period from various online distribution channels and generates different time series data with the same day-of-week. This study verifies the proposed model through three baseline models, namely, autoregressive integrated moving average (ARIMA), support vector regression (SVR), and Naïve models. Findings shed light on how to lessen the impact of violent fluctuations by combining a rolling procedure with separate day-of-week time series for the hospitality industry. Hence, theoretical and managerial areas for hotel room demand forecasting are enriched on the basis of adjusting room pricing strategies for hoteliers in improving revenue management and making appropriate deals for customers in booking hotel rooms.