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Nurses' turnover intention has become a major issue in developing countries with high power distance cultures. Therefore, the authors attempt to investigate how turnover intention among nurses' can be reduced through paternalistic leadership (PL). The authors further investigate the mediating role of job satisfaction between the associations of benevolent, moral and authoritarian dimensions of PL with turnover intention. Finally, the authors examined perceived organizational support (POS) as a conditional variable between job satisfaction and turnover intention.

The authors collected data from 374 nurses working in public and private hospitals of high power distance culture using a questionnaire-based survey on convenience basis.

Structural equation modeling confirms that benevolent and moral dimensions of PL positively affect nurses' job satisfaction which helps them reduce their turnover intention. While the authoritarian dimension of PL negatively affects job satisfaction to further enhance their turnover intention. In addition, the authors noted POS as a conditional variable to trigger the negative effect of job satisfaction on turnover intention.

The authors used a cross-sectional design to collect responses and ensured the absence of common method variance through Harman's Single factor test.

This study identified the mechanism (job satisfaction and POS) through which benevolent, moral and authoritative dimensions of PL predict turnover intention among nurses working in high power distance culture.

護士有離職意向，在擁有高權力距離文化的發展中國家，已成為一個重大的問題。因此，我們擬探討如何可以透過採用家長式領導、把護士離職的意欲減低，繼而研究工作滿足感，在離職意向與家長式領導中仁慈、道德和獨裁這三個層面的關係中所起的中介作用。最後，我們就組織支持感，作為是工作滿足感與離職意向之間的一個條件變數，進行了研究。

本研究透過採用在便利的基礎上進行的問卷調查，從374名在高權力距離文化的公營和私營醫院內工作的護士取得數據，進行分析。

結構方程模型證實了家長式領導中的仁慈和道德這兩個層面，會對可減低護士離職意欲的工作滿足感，產生積極的影響。家長式領導中的獨裁層面、則會對護士的工作滿足程度產生負面的影響，繼而增強其離職意欲。而且，我們確認了組織支持感是一個會增強工作滿足感與離職意向之間負相聯的條件變數。

我們以橫斷面的設計法來收集回應，並透過採用哈曼 (Harman) 的單因素檢定法，來確保共同方法變異不會存在。

本研究確定了一個 (工作滿足感與組織支持感) 機制，透過這機制，家長式領導中的仁慈、道德和獨裁這三個層面可預測於高權力距離文化工作的護士的離職意向。

Mobile shopping is the current trend for firms to conduct business, having great advantages over electronic shopping as well as traditional shopping. The purpose of this paper is to discuss not only the driving forces of mobile shopping behaviors from the theory of reasoned action (TRA) perspective, but also the additional promotion and barrier sides of the mobile business.

A structural equation modeling approach with latent constructs is applied on a self-administered survey data of 208 Vietnamese consumers to test the hypotheses.

The results of this study have proved the predictive power of TRA in exploring consumer behavior in the context of mobile shopping. Also, both promotion and barrier variables have significantly strong impacts on the intention to adopt mobile shopping.

Future studies would benefit from investigating other variables (e.g. specific aspects of trust and risk) and using actual behavior (e.g. online purchases).

Business managers should pay attention to both promotion and barrier factors to understand how and why Vietnamese consumers adopt mobile shopping.

This pioneering study adapts the TRA model with extended promotion and barrier variables to explain mobile shopping in the context of Vietnam.

Metaverse is a virtual application spawned by digital technology that is becoming increasingly relevant to our lives. However, for the opportunities created and challenges posed by the metaverse, its important elements and future evolution trend remain largely unknown. Thus, this paper aims to understand the current status of metaverse research and its future research directions.

Based on the analysis of the literature data on the metaverse both in English and Chinese using Latent Dirichlet allocation (LDA) topic modeling and bibliometrics, this study discussed the related research and development trend of the metaverse. The authors first defined the concept of the metaverse and analyzed 1,378 English articles from seven publishers and 590 Chinese articles from the CNKI database. Following that, the authors summarized three important themes from the current studies: virtual world, metaverse technologies and metaverse applications. Finally, a framework of future directions on metaverse research was proposed.

The review found that during the rapid development of the metaverse, opportunities and challenges coexisted. In the virtual world, metaverse technologies drive the implementation of application scenarios, and in turn, applications promote the improvement of technologies. The interrelationship between technology and application lays the foundation for the development of the metaverse. Future metaverse research will generate different research directions.

This review provides a valuable, systematic perspective for individuals who want to understand the metaverse. The conceptual framework on metaverse research proposed in this paper offers a comparison of literature analysis from domestic and international perspectives and brings new insights into the development of the metaverse.

The purpose of this study is to analyze the current situation of the competitiveness development of China’s marine industrial clusters, reveal the existing problems and challenges, provide theoretical support and practical guidance for improving the competitiveness of China’s marine industrial clusters so as to promote industrial upgrading and high-quality development and help China realize the strategic transformation from a marine power to a marine power.

This report first provides a detailed review of the current development status and existing issues of marine industry clusters in China. Second, it constructs an evaluation index system for the competitiveness development of China’s marine industry clusters and conducts competitiveness analysis and evaluation of typical marine industry clusters in China. Third, it explores the development trends and prospects of typical marine industry clusters in China. Finally, the report proposes countermeasures and suggestions for enhancing the competitiveness of marine industry clusters in China, focusing on resource optimization, cluster structure and cluster efficiency.

(1) Significant competitiveness of marine shipbuilding and ocean engineering equipment clusters: Through technological innovation and policy support, the marine shipbuilding and ocean engineering equipment clusters have shown a marked improvement in competitiveness, advancing toward high-quality development despite facing macroeconomic fluctuations. (2) Continuous improvement in marine energy and offshore wind power clusters: The competitiveness of marine energy and offshore wind power clusters has been continuously enhanced under supportive policies. However, there is still a need to optimize resource allocation and strengthen innovation stability to meet market challenges. (3) Strong growth potential of desalination and comprehensive utilization clusters: The desalination and comprehensive utilization clusters demonstrate robust growth potential in technological innovation and regional collaborative development. Future efforts should focus on the application of environmentally friendly and energy-saving technologies to ensure a balance between economic and ecological benefits.

By strengthening the competitiveness of industrial clusters, China can effectively respond to international competition, accelerate the transformation and upgrading of the marine industry and support its transition from a maritime power to a strong maritime nation. Hence, this study will focus on analyzing the competitiveness development of China’s marine industry clusters, identifying existing problems and challenges and providing theoretical support and practical guidance for enhancing the competitiveness of China’s marine industry clusters.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

As publishers and academia swiftly head towards e-textbooks, it is important to understand how students feel about using e-textbooks as a primary learning tool. This paper discusses results of a small-scale study looking into how a group of language learners view and use e-textbooks as learning tools in ESL classrooms. The paper concludes by offering teaching implications that could ease integrating e-textbooks in language classrooms in a more effective and efficient manner.

The main objective of this article is to visualize the structure and trends of pro-environmental behavior (PEB) between 1999 and 2023 through mapping and in-depth analysis. The aim is to analyze PEB, which has received considerable academic attention in recent years due to its key role in the conservation of the environment and the protection of local communities in tourist destinations. This paper provides an important summary of the recent research that has explored the role that tourists have in protecting the environment through PEB.

This study presents a visual analysis of 2005 scholarly articles between the years 1999 and 2023 related to PEB. Using the knowledge mapping based on VOSviewer it presents the current status of research, which includes the analysis of citation analysis, co-citation analysis, co-citation network and longitudinal analysis.

PEB is an emerging topic due to its relevance to protecting the environment in the context of travel. The citation and co-citation analysis show the relevance of the behavior of tourists with regard to protecting the environment. The co-word analysis highlights the current significance of research concerning green hotels and the destination image of environmentally responsible destinations.

This study sheds light on the current research progress of PEB in the context of tourism through a comprehensive analysis (citation, co-citation and co-word). In addition, we provide theories and factors that have been previously used to study PEB in the context of tourism. The findings contribute to a broad and diverse understanding of the concept of PEB, which can provide important insights for policymakers in formulating management strategies and policies aimed at reducing environmental impacts in destinations.

This study aims to inform prospective listing firms, investors and regulators of the unique drivers of Chinese initial public offering (IPO) pricing on the Hong Kong Exchange.

Using a hand-collected IPO dataset, we investigate whether information uncertainty or investor exuberance drives underpricing and Chinese IPOs’ performance from 2002 to 2015, including 114 state-owned enterprises (SOEs).

Contrasting with the “listing bubble” in the China domestic stock market, generated by the overoptimism of retail investors, we highlight a “placing bubble” among Chinese firms listed in Hong Kong. This is driven by institutional investors’ buoyant demand for Chinese IPO shares, particularly those of SOEs. Chinese listing firms employ discreet earnings management strategies with their working capital accounts to smooth pre-IPO earnings, which becomes apparent to the market only in the long term.

This study is the first to examine the pricing of sought-after Chinese IPOs among international investors, who face various restrictions when investing in the Chinese domestic stock market. Additionally, it is the first study to measure earnings management using hand-collected pre-IPO data in IPO underpricing studies.

The COVID-19 pandemic, which appeared in China in late 2019, has affected the world psychologically, socially and economically in 2020. Tourism is one of the areas where the effects of COVID-19 have been felt most clearly. The study aims to determine the effect of negative problem orientation (NPO) and perceived risk related to the COVID-19 pandemic on travel and destination visit intention.

This study employed a convenience and probabilistic sampling method for collecting data from 531 respondents using an online questionnaire. Partial least square structural equation modeling (PLS-SEM) was used for testing research model.

According to the findings, NPO and perceived risk related to the pandemic were found to have direct and indirect effects on the travel behavior of tourists. The results of this research provide theoretical and practical implications for hospitality and travel businesses on topics such as the psychological effects of the pandemic and the travel behaviors of tourists.

It is estimated that the pandemic will also affect tourist behavior due to its effects on human psychology. For this reason, a study conducted in the context of tourist behavior theories is expected to contribute to the literature, managers and future of the tourism.

The precast concrete slab track (PST) has advantages of fewer maintenance frequencies, better smooth rides and structural stability, which has been widely applied in urban rail transit. Precise positioning of precast concrete slab (PCS) is vital for keeping the initial track regularity. However, the cast-in-place process of the self-compacting concrete (SCC) filling layer generally causes a large deformation of PCS due to the water-hammer effect of flowing SCC, even cracking of PCS. Currently, the buoyancy characteristic and influencing factors of PCS during the SCC casting process have not been thoroughly studied in urban rail transit.

In this work, a Computational Fluid Dynamics (CFD) model is established to calculate the buoyancy of PCS caused by the flowing SCC. The main influencing factors, including the inlet speed and flowability of SCC, have been analyzed and discussed. A new structural optimization scheme has been proposed for PST to reduce the buoyancy caused by the flowing SCC.

The simulation and field test results showed that the buoyancy and deformation of PCS decreased obviously after adopting the new scheme.

The findings of this study can provide guidance for the control of the deformation of PCS during the SCC construction process.