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The 2019 novel coronavirus (COVID-19) outbreak is projected to have adverse consequences on the global tourism and hospitality industry. This paper aims to examine how the outbreak may alter Chinese tourists’ lifestyle choices, travel behaviour and tourism preferences in the short and long term.

This paper is based on the synthesis of news broadcasted by several media outlets to be supported by an overview of the related literature on tourism marketing, tourism management and tourist behaviour. The authors’ experiences investigating trends in tourism and hospitality at the local and international level have also contributed to the study.

This paper predicts that COVID-19 will likely affect Chinese travellers’ consumption patterns, such as the growing popularity of free and independent travel, luxury trips and health and wellness tourism. New forms of tourism including slow tourism and smart tourism may also drive future tourism activities. Such changes are likely to force businesses to reconsider their service designs and distribution channels.

While Chinese and other potential visitors rethink how they travel, professionals, too, should reflect upon how to bring positive or negative changes to the tourism industry following this pandemic. Subsequent research should also consider how to mitigate the effects of similar public health crises in the future.

Recommendations for industry practitioners and policymakers focus on tailoring travel arrangements to tourists’ backgrounds. The suggestions may help to alleviate outbreak-related stress, offer travellers newly enriching experiences and partially mitigate the effects of COVID-19 on the tourism and hospitality industry. These recommendations can also apply more broadly to global tourist markets.

The COVID-19 outbreak has already brought significant impacts to nearly every society and industry. Tourism scholars and practitioners should carefully consider this tragedy and how it may inform industry and social practices. This and other public health crises represent sterling opportunities to view the industry holistically in terms of its effects on the environment, climate and travellers themselves.

This paper presumably represents a frontier study, critically examining the possible impacts of COVID-19 on Chinese travellers’ consumption patterns and how the tourism and hospitality industry may respond to such changes in the future.

预计2019年新型冠状病毒（COVID-19）爆发将对全球旅游和酒店业产生不利影响。本文预测, COVID-19可能会影响中国旅客的消费方式, 例如自由行, 豪华旅行以及健康与养生旅游的普及。包括慢速旅游和智能旅游在内的新型旅游形式也可能推动未来的旅游活动。这种变化可能促使企业重新考虑其服务设计和分销渠道。针对行业从业者和政策制定者的建议着重于根据游客的背景和需求量身定制旅行安排。我们的建议可能有助于减轻与疫情暴发导致的压力, 为旅行者提供全新的丰富体验, 并从一定程度减轻COVID-19对旅游业和酒店业的影响。这些建议还可以更广泛地应用于全球旅游市场。

COVID-19, 生活方式 旅游行为 灾后 集体主义倾向 中国

El impacto del COVID-19 se prevé importante en la actividad turística global y en la industria de la hostelería. Este artículo predice que el COVID-19 afectará con probabilidad alta los patrones de consumo de los viajeros chinos, incluyendo los cada vez más populares viajes comprados directamente por los consumidores chinos, en el segmento del lujo, y el turismo de salud y belleza. Nuevas formas de turismo, incluyendo el slow tourism, y el turismo responsable pueden convertirse en importantes tendencias de futuro igualmente. Dichos cambios llevarán con cierta seguridad a la industria a reconsiderar y adaptar su oferta de servicios en este sector, en particular su diseño y los canales de distribución utilizados. Las recomendaciones para la industria y los responsables de la política turística se alinean con una mayor proximidad de la oferta a los gustos cambiantes del consumidor. Dichas acciones ayudarán a reducir fricciones y fallos en la definición del negocio turístico, ofreciendo a los viajeros nuevas y enriquecedoras experiencias, así como podrán mitigar en parte los efectos adversos estimados del COVID-19, los cuales son relevantes a día de hoy. Así mismo, dichas recomendaciones son aplicables de una manera más global a la industria del turismo y la hospitalidad en el mercado mundial.

COVID-19, Estilo de vida, Conducta del viajero, Post-desastre, Orientacion collectivista, China

The purpose of this paper is to interview Mr. Jingbang Zhang, EVP of Yagao Meihua Hotel Management Co., Ltd & CEO of Madison Brand based in Shanghai, China, regarding the impact of COVID-19 on China’s hotel industry and potential post-COVID-19 trends.

Interview with hotel group CEO and industry leader in China.

Several effects of COVID-19 and potential trends are discussed from a hotel CEO’s perspective.

Tourism and hospitality stakeholders will acquire a better understanding of the impacts of COVID-19 on China’s hotel industry and possible post-COVID-19 adjustments

Currently, environmental and social concerns have made green innovation more popular among researchers and practitioners around the globe. Developed countries tend to focus more on this issue, compared to developing countries. However, the reality shows that small- to medium-sized enterprises (SMEs) are considered as high contributors to environmental pollution. This study is designed for, and conducted on, SMEs in a developing country, Pakistan. The purpose of this paper is to highlight the main determinants of green innovation adoption in SMEs in Pakistan.

A data sample of 288 SMEs from five different sectors was collected and analyzed using the partial least squares structural equation modeling technique.

The results of the study indicate that organizational and human resource factors, market and customer factors, and government support and technological factors have a positive and significant impact, whereas external partnership and cooperation, and rules and regulatory factors have an insignificant impact on green innovation adoption in SMEs in Pakistan.

The outcomes of the study have important implications for managers as well as for government policy makers regarding framing better policies to promote green practices in SMEs.

This paper aims to discuss the effects of COVID-19 on hotel marketing and management practices and outlines a three-pronged research agenda to stimulate knowledge development in the hotel sector.

This paper is based on an overview of the relevant literature on hotel marketing and management and the hotel guest behavior. The authors also investigated hospitality service trends to propose a research agenda.

This paper presents a research agenda from three dimensions – artificial intelligence (AI) and robotics, hygiene and cleanliness and health and health care. First, different types of AI (mechanical, thinking and feeling) might open up distinct research streams at the intersection of health crises and hotel management, in light of the COVID-19 pandemic. Additionally, this paper recommends that researchers move beyond typical perspectives on the antecedents and outcomes of hotel hygiene and cleanliness to delve into guests’ perceptions of the cleanliness of specific hotel surfaces. Furthermore, a more in-depth analysis is warranted about the evolving relationship between hotels and the health-care sector.

The recommended research areas are intended to advance the knowledge base to help hotels recover from the COVID-19 pandemic. The suggested research streams are expected to provide actionable insights to promote the development and sustainability of the hotel sector.

This paper appears to be a frontier study, critically examining possible effects of the COVID-19 pandemic on hotel marketing and management practices and how hoteliers may respond to such challenges to recover after this pandemic.

This paper seeks to discuss the genealogical sources for Chinese immigrants as well as the settlement of Chinese in the USA and the historical evolution of Chinese names, their origins, arrangement and development. It aims to cover the origins of various classes of Chinese surnames, followed by the content description of a traditional genealogical book for jiapu.

The paper researches the various ways that a Chinese person can find out about their ancestry.

The paper reveals the roles of libraries, including serving the needs of patrons interested in genealogical research, preserving and interpreting information through oral and family history projects and collaborating with other libraries through interlibrary loan, document delivery, library consortia, collection management and international resource‐sharing.

The study provides information on where and how to locate the genealogical resources for researching the genealogy of a Chinese family.

The paper analyzes the value of genealogical research as a documentary source for population history, life expectancy in a clan, marriages and family connections, as well as lineage organizations and inter‐lineage relations.

Reports on the first of two joint symposia to be held in South China during 1998. The Zhongshan University Symposium focused on library automation and networking, with six sessions on specific subthemes and 47 papers on such topics as information resources development and digital libraries, Internet information applications and services, resource sharing and regional cooperation. Participants at the symposium concluded that the standardisation of a Chinese encoding system to cater for all Chinese characters from China, Taiwan, Japan and Korea is a prerequisite for future cooperation and resource sharing. In addition, the panellists agreed that it is important to concentrate on developing library and information networks, especially using Internet technology and related resources.

The purpose of this paper is to develop a simplified optimization calculation method to assess cable force of self-anchored suspension bridge based on optimization theories.

A simplified analysis method construction using Matlab is developed, which is then compared with the optimization method that considers the main cable’s geometric nonlinearity with software ANSYS in an actual bridge calculation.

This contrast proves the weak coherence and the adjacently interaction theory unreasonable and its limitation.

This paper analyzes the calculation method to assess cable force of a self-anchored suspension bridge and its application effect.

The purpose of this paper is to investigate the influence of two dimensions of relational risks, namely, opportunism behavior and interest conflict, on knowledge flow and to explore the moderating effect of network power among these untested relationships and to examine the positive effect of opportunism behavior and interest conflict.

This paper adopts survey data collected from 180 enterprises in China's high-technology industry and examines the relationship between relational risks, network power and knowledge flow.

This research empirically shows that opportunism behavior and interest conflict significantly and negatively impact on knowledge flow. Those relationships are positively moderated by network power.

To be more generalized to the high-technology industry, future research should adopt the quantitative research, which can obtain more comprehensive information to explore the nature of phenomenon. The future research can also combine with other variables. In addition, this research extends the current literature by investigating the relationship of so far understudied theorized antecedents.

This research enriches the related network perspective literature by providing new insight combining relational risks and knowledge flow. Especially, the moderating effect of network power is empirically examined.

With the advent of the web computing era, the transmission mode of the Internet of Everything has caused an explosion in data volume, which has brought severe challenges to traditional routing protocols. The limitations of the existing routing protocols under the condition of rapid data growth are elaborated, and the routing problem is remodeled as a Markov decision process. this paper aims to solve the problem of high blocking probability due to the increase in data volume by combining deep reinforcement learning. Finally, the correctness of the proposed algorithm in this paper is verified by simulation.

The limitations of the existing routing protocols under the condition of rapid data growth are elaborated and the routing problem is remodeled as a Markov decision process. Based on this, a deep reinforcement learning method is used to select the next-hop router for each data transmission task, thereby minimizing the length of the data transmission path while avoiding data congestion.

Simulation results show that the proposed method can significantly reduce the probability of data congestion and increase network throughput.

This paper proposes an intelligent routing algorithm for the network congestion caused by the explosive growth of data volume in the future of the big data era. With the help of deep reinforcement learning, it is possible to dynamically select the transmission jump router according to the current network state, thereby reducing the probability of congestion and improving network throughput.