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While higher education has been encouraging interdisciplinary research, few studies have been conducted to understand how interdisciplinarity shapes the identity construction of scholars, especially doctoral students who may already strive to socialize into academia.

Therefore, this study adopts the approach of autoethnography to analyze my lived experience of developing disciplinary literacy and constructing interdisciplinary identity as a Chinese international doctoral student at a North American university. Communication theory of identity (CTI) is the theoretical framework through which I understand the negotiation among my personal, enacted, relational and communal identities while communicating my research through diverse literacy practices.

This autoethnography reveals that interdisciplinary doctoral students can flexibly use discursive resources from different disciplines and literacy practices in both English and their first language to dynamically create interdisciplinary identities communicable to different discourse communities. Their identities in different disciplines can develop simultaneously, rather than suppressing one for the development of the other as they do interdisciplinary research.

This study first extends current scholarly discussion of disciplinary literacy to a less-investigated setting, i.e. doctoral education in higher education. Second, it adds an additive and current layer of interdisciplinarity to the existing understanding of international doctoral students’ identity construction. Third, it helps to understand how the development of disciplinary literacy can facilitate disciplinary identity construction and how disciplinary identity construction can facilitate the development of disciplinary literacy.

The purpose of this study is to provide better service to hotel customers during the COVID-19 era. Specifically, this study focuses on understanding the changes in hotel customer satisfaction during the epidemic and formulating effective marketing strategies to satisfy and attract guests.

As the first victim of the COVID-19 virus, China’s hotel industry has been profoundly affected and customer satisfaction and needs have also changed. Taking 105,635 hotel reviews obtained from Tripadvisor.com in Beijing and Shanghai as samples, this study explores the changes in consumer satisfaction by using text-mining methods.

The results suggest that there are significant differences in overall ratings, spatial distribution and ratings of different traveller types before and after the epidemic. Generally, customers have higher “tolerance” and are more inclined to give higher ratings and pay more attention to hotel prevention and control measures to reduce health risks after the COVID-19.

This paper proves the changes in customer satisfaction before and after the COVID-19 at the theoretical level and reveals the changes in customer attention through the topic model and provides a basis for guiding hotel managers to reduce the impact of the COVID-19 crisis.

Empirical findings would provide useful insights into tourism management and improve hotel service quality during the COVID-19 epidemic era.

This research explores the hotel customer satisfaction in the field of hotel management before COVID-19 and after COVID-19, by using text mining to analyse mandarin online reviews. The results of this study will suggest that the hotel industry should continuously adjust its products and services based on the effective information obtained from customer reviews, so as to realize the activation and revitalization of the hotel industry in the epidemic era.

The purpose of this paper is to develop a dynamic control method to improve bus schedule adherence under connected bus system.

The authors developed a dynamic programming model that optimally schedules the bus operating speed at road sections and multiple signal timing plans at intersections to improve bus schedule adherence. First, the bus route was partitioned into three types of sections: stop, road and intersection. Then, transit agencies can control buses in real time based on all collected information; i.e. control bus operating speed on road sections and adjust the signal timing plans through signal controllers to improve the schedule adherence in connected bus environment. Finally, bus punctuality at the downstream stop and the saturation degree deviations of intersections were selected as the evaluation criteria in optimizing signal control plans and bus speeds jointly.

An illustrative case study by using a bus rapid transit line in Jinan city was performed to verify the proposed model. It revealed that based on the proposed strategy, the objective value could be reduced by 73.7%, which indicated that the punctuality was highly improved but not to incur excessive congestion for other vehicular traffic.

In this paper, the authors applied speed guidance and the adjustment of the signal control plans for multiple cycles in advance to improve the scheduled stability; furthermore, the proposed control strategy can reduce the effect on private traffics to the utmost extend.

This paper aims to investigate the relation between technological innovation modes and their impact on eco-efficiency of industrial enterprises in China.

This paper first constructs a model to evaluate and measure the eco-efficiency of industrial enterprises in China from 2006 to 2010. Second, this paper compares the role of technological innovation modes – specifically, domestic independent innovation, foreign technology import and domestic technology transfer – in improving eco-efficiency of industrial enterprises in the Eastern, Central and Western regions of China by logarithmic regression.

The study finds that domestic independent innovation has a positive significant influence in improving eco-efficiency of industrial enterprises in the Eastern region; domestic technology transfer has a positive significant role in the Central region; and foreign technology import and domestic technology transfer positively affect the Western region.

This paper is the first to identify the role of technological innovation modes in improving eco-efficiency. The findings can help enterprises in the three regions adopt the most effective technological innovation mode. In addition, the results provide valuable insights into policy development to improve China’s overall eco-efficiency and to balance economic and industrial development among the three regions.

This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.

This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles.

The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results.

This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.

本文旨在分析旅游预测领域的研究重点、演化过程和未来的研究方向。

本研究使用 CiteSpace 软件对 1213 篇旅游预测文章进行了文 献计量学分析。

结果表明, 旅游预测研究经历三个阶段。机构合作包含国际机构合作和 国内机构合作, 需要持续加强国家之间的合作, 作者之间的合作多以校内合作为 主。高引用文章不仅发表在旅游领域的核心期刊还发表在其他专业的核心期刊上。 旅游预测研究的主要内容为旅游需求、收入管理、酒店需求和游客量。新冠疫情 期间的事前预测拓宽了现有的旅游预测研究。未来预测的研究重点在于合理利用 大数据, 提高模型的准确定以及提高预测结果的可信度。

本文使用 CiteSpace 分析旅游预测文章得到未来研究趋势, 既是对 现有研究的补充, 又为今后的研究提供方向。

Este artículo pretende analizar los aspectos más destacados de la investigación, el proceso evolutivo y las futuras orientaciones de la investigación en el campo de la previsión turística.

Este estudio utilizó CiteSpace para realizar un análisis bibliométrico de 1213 artículos sobre previsión turística.

Los resultados muestran que la investigación sobre previsión turística ha experimentado tres etapas. La colaboración institucional incluye la colaboración transnacional y la colaboración institucional nacional. La colaboración entre países aún debe reforzarse. La colaboración entre autores se basa principalmente en la colaboración dentro del campus. Los artículos con una alta cocitación se publican principalmente en las principales revistas de turismo y en otras publicaciones relevantes. El contenido de la investigación se refiere principalmente a la demanda turística, el revenue management, la demanda hotelera y los volúmenes turísticos. La previsión previa y durante la pandemia de la COVID-19 ha ampliado la investigación existente sobre previsión turística. La futura investigación sobre previsiones se centra en el uso racional de los big data, la mejora de la precisión de los modelos y el aumento de la credibilidad de los resultados de las previsiones.

Este artículo utiliza CiteSpace para analizar artículos de previsión turística con el fin de obtener futuras tendencias de investigación, lo que complementa la investigación existente y proporciona orientaciones para futuras investigaciones.