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This study aims to investigate the impacts of pandemic-related media coverage on younger hospitality and tourism employees’ ageist attitudes toward older people by applying the media priming theory and the terror management theory.

This study takes a mixed-method approach through an online survey. A total of 416 usable responses are collected from current US hospitality and tourism employees under 55 years. Qualitative data were analyzed using word cloud. Partial least squares structural equation modeling is then used to test the hypothesized model.

The study’s results show that younger employees' cognitive reaction negatively affects aging anxiety and intergenerational tension, which subsequently influence their willingness to work with older people. Negative media-induced emotions are positively associated with aging anxiety, whereas positive emotions exert no significant impact. Intergenerational contact frequency moderates the effect of intergenerational tension on younger employees’ willingness to work with older people.

This study’s findings contribute to the hospitality and tourism workforce literature by considering the priming effects of media coverage on younger employees’ attitudes toward self-aging and the older group. This study also offers managerial insights on developing effective age-inclusion interventions to reduce workplace ageism in the post-pandemic era.

Existing hospitality and tourism studies on older workers are scant and largely descriptive. To the best of the authors’ knowledge, this study is the first study that assesses the effects of pandemic-related media coverage on workplace ageism toward older people among the current hospitality and tourism workforce.

There is a growing importance of business intelligence systems (BIS) adoption in today’s digital economy age which is characterized by uncertainty and ambiguity considering the magnitude and influence of data-related issues to be solved in contemporary businesses. This study aims to investigate critical success factors that affect business intelligence efficiency based on the DeLone and McLean model in Jordanian banking industry.

A quantitative research method through a questionnaire was used to collect data from actual users who depend on business intelligence tools to make operational and strategic decisions in Jordanian banks. The data obtained were tested using the partial least squares–structural equation modeling approach.

The survey findings attest that system quality, information quality, user quality, user satisfaction and user performance are important factors and contribute to business intelligence efficiency in the Jordanian banking industry.

The findings gained from this work can help policymakers in Jordanian banks to improve the business intelligence success and organizational performance.

To the best of the authors’ knowledge, this study is the first of its kind to propose a theoretical model to assess drivers of BIS efficiency from the Jordanian banks’ perspective.

The existing three-stage network Data Envelopment Analysis (DEA) models with shared input are self-assessment model that are prone to extreme efficiency scores in pursuit of decision-making units (DMUs) efficiency maximization. This study aims to solve the sorting failure problem of the three-stage network DEA model with shared input and applies the proposed model to evaluate innovation resource allocation efficiency of Chinese industrial enterprises.

A three-stage network cross-DEA model considering shared input is proposed by incorporating the cross-efficiency model into the three-stage network DEA model. An application of the proposed model in the innovation resource allocation of industrial enterprise is implemented in 30 provinces of China during 2015–2019.

The efficiency of DMU would be overestimated if the decision-maker preference is overlooked. Moreover, the innovation resource allocation performance of Chinese industrial enterprises had a different spatial distribution, with high in eastern and central China and low in western China. Eastern China was good at knowledge production and technology development but not good at commercial transformation. Northeast China performed well in technology development and commercial conversion but not in knowledge production. The central China did not perform well in terms of technology development.

A three-stage network DEA model with shared input is proposed for the first time, which makes up for the problem of sorting failure of the general three-stage network model.

Building supply chain resilience is increasingly recognized as an effective strategy to deal with supply chain challenges, risks and disruptions. Nevertheless, it remains unclear how to build supply chain resilience and whether supply chain resilience could achieve a competitive advantage.

By analyzing the data collected from 216 firms in China, the current study empirically examines how information technology (IT) capability and supply chain collaboration affect different forms of supply chain resilience (external resilience and internal resilience) and examines the performance implications of these two forms of supply chain resilience.

Results show that IT capability is positively related to external resilience, whereas supply chain collaboration is positively related to internal resilience. The combination of IT capability and supply chain collaboration is positively related to external resilience. In addition, internal resilience is positively related to firm performance.

This study used only cross-sectional data from China for hypothesis testing. Future studies could utilise longitudinal data and research other countries/regions.

The findings systematically assess how IT capability and supply chain collaboration contribute to supply chain resilience and firm performance. The results provide a benchmark of supply chain resilience improvement that can be expected from IT capability and supply chain collaboration.

The study findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

In the context of the digital age, this study aims to investigate the impact of citizens' digital participation on the scientific and democratic decision-making processes of the government. Specifically, the authors focus on the factors influencing citizens' digital participation, with a particular emphasis on their digital skills.

Exploring the influence of citizens' digital skills on their digital participation is of great practical significance for eliminating the digital divide and for promoting a life characterized by enriched digital interactions with the public. This study selected the social consciousness survey database of Chinese netizens in 2017, used ordered Probit and OLS models, and comprehensively used the instrumental variable method (IV), causal stepwise regression method and bootstrap method to empirically verify and construct a mechanism model of the influence of digital skills on citizens' digital participation.

The empirical findings indicate a noteworthy positive association between citizens' proficiency in digital skills and their active engagement in digital activities. This relationship is positively mediated by factors such as political interest and attention to social issues, underscoring their role in encouraging greater digital participation. Conversely, national identity exhibits a counteractive influence on this mechanism, potentially discouraging digital engagement. Notably, the impact of digital skill mastery on digital participation is more pronounced among non-elderly individuals and those residing in metropolitan areas, highlighting the significance of demographic characteristics in this context.

These research results can help the government and other organizations make better decisions and facilitate improvement of citizens' digital participation by promoting their mastery of digital skills.

This study aims to expand tourism knowledge by analysing literature review articles published in English Web of Science (WOS) and Chinese China National Knowledge Infrastructure (CNKI) language journals and reviewing their influence, interconnection and trends.

A three-stage method was designed to understand the tourism research progress. Performance analysis identified the publication timeline, high-yielding journals and authors that published tourism literature reviews and frequently cited papers. Science mapping visualisation examined the intrinsic connections between co-authorship and co-institution. Finally, emerging trend analysis explored the topic modelling and evolution through Latent Dirichlet allocation (LDA) and regression.

The key statistics and collaborations relationships of tourism literature reviews were traced. LDA identified 45 and 22 topics, which narrowed the barriers in tourism studies. The regression analysis divided these topics into “hot”, “fresh”, “bell-shaped” and “stable” patterns. These modes represent the progress of tourism studies. The topic “new emerging technologies and the internet” is the focus of tourism literature reviews published in both databases. Future research could pay more attention to the topics in the “hot” and “fresh” patterns. The results enrich the progress of tourism literature reviews and provide a direction for future research.

To the best of the authors’ knowledge, this study is the first literature analysis for tourism literature reviews published in WOS versus CNKI journals. The proposed three-stage systematic method is used for the first time for the literature review and can guide future research.

本研究旨在通过分析英文WOS和中文CNKI语言期刊上发表的文献综述文章, 回顾其影响、相互联系和趋势, 来扩大旅游知识体系。

本研究设计了一个三阶段方法来了解旅游研究进展。绩效分析确定了出版时间线、发表的旅游文献综述的高产期刊和作者以及经常被引用的文章。科学地图可视化审视了合作作者和合作机构之间的内在联系。最后, 新兴趋势分析通过潜在狄利克雷分配和回归探讨了主题建模和演变。

本文追踪了旅游文献综述的关键统计数据和合作情况。潜在狄利克雷分配确定了45个和22个主题, 这缩小了旅游研究中的研究缺口。回归分析将这些主题分为“热门”、“新鲜”、“钟形”和“稳定”模式。这些模式代表了旅游研究的进展。主题“新兴技术和互联网”是不同数据库中发表的旅游文献综述的焦点。未来的研究可以更多地关注“热门”和“新鲜”模式中的主题。研究结果丰富了旅游文献综述的进展, 为今后的研究提供了方向。

这项研究是首次对WOS与CNKI期刊上发表的旅游文献评论进行文献分析。所提出的三阶段系统方法首次用于文献综述, 可以指导未来的研究。

El objetivo de este estudio es ampliar el conocimiento turístico analizando los artículos de revisión documental publicados en revistas, tanto en la versión WOS en inglés cómo en CNKI China, y revisando sus efectos, interconexiones y tendencias.

Se ha diseñado el método de tres etapas para comprender el progreso de la investigación turística. El análisis del desempeño determinó la línea de tiempo de publicación, las revistas de alto rendimiento y los comentarios de la literatura turística publicados por los autores, así como los artículos citados con frecuencia. La visualización de los mapas científicos, examina los vínculos intrínsecos entre los autores colaboradores y las instituciones colaboradoras. Finalmente, el análisis de tendencias emergentes explora el modelado temático y la evolución a través de posibles asignaciones y regresiones de dilick-ray.

Se han analizado las estadísticas clave y las relaciones de cooperación de la revisión de la literatura turística. La asignación potencial de dilich-ray identifica 45 y 22 temas, lo que reduce las barreras en la investigación turística. El análisis de regresión divide estos temas en patrones “populares”, “novedosos”, “en forma de campana” y “estables”. Estos modelos representan el avance de la investigación turística. El tema “tecnologías emergentes e internet” es el foco de la revisión de la literatura turística publicada en diferentes bases de datos. La investigación futura puede centrarse más en temas en modelos “populares” y “novedosos”. Los resultados de la investigación enriquecen el progreso de la revisión de la literatura turística y proporcionan una dirección para futuras investigaciones.

El estudio es el primer análisis documental de los comentarios de la literatura turística publicados en las revistas WOS y CNKI. El método sistemático de tres etapas propuesto se utiliza por primera vez en la revisión documental y puede guiar futuras investigaciones.

This study investigates whether the visualization of agricultural products influences consumers’ purchase intentions in the context of farmer-assisted livestreaming in China. Moreover, it explores the moderating effect of packaging functionality and the mediating effect of consumer trust.

Consumers in China from multiple social media platforms participated in this survey, which yielded 333 valid responses for analysis.

The results revealed a positive relationship between the video presentation about the agricultural production process and consumers’ purchase intention, which is mediated by consumers’ trust. Meanwhile, packaging functionality moderates the relationship between agricultural product visualization and consumers’ purchase intentions as well as the indirect effect of consumers’ trust.

This study extends the application of the stimulus-organism-response (SOR) model to the field of farmer-assisted livestreaming. By building a more detailed model, this study adds to knowledge on the influencing mechanisms of consumers’ purchase intentions in farmer-assisted livestreaming.

This paper aims to explore the effects of normative and hedonic motivations on continuous knowledge contribution, and how past contribution experience moderates the effects of the motivations on continuous knowledge contribution.

Based on goal-framing theory, the present study proposes a comprehensive theoretical model by integrating normative and hedonic motivations, past contribution experience and continuous knowledge contribution. The data for virtual community members' activities were collected using the Python Scrapy crawler. Logit regression was used to validate the integrative model.

The results show that both normative motivation (reflected by generalized reciprocity and social learning) and hedonic motivation (reflected by peer recognition and online attractiveness) are positively associated with continuous knowledge contribution. Moreover, these effects are found to be significantly influenced by members' past knowledge contribution experience. Specifically, the results suggest that past knowledge contribution experience undermines the influence of generalized reciprocity on continuous knowledge contribution but strengthens the effect of peer recognition and online attractiveness.

Although the emerging literature on continuous knowledge contribution mainly focuses on motivations as antecedents that promote continuous knowledge contribution, most of these studies assume that the relationship between motivating mechanisms and continuous knowledge contribution does not change over time. The study is one of the initial studies to examine whether and how the influence of multiple motivations evolves relative to levels of past contribution experience.

This paper aims to study whether the adoption of an entry mode that fits the social trust level contributes to the improvement of foreign subsidiary performance.

The authors used the Probit model, linear regression, strategic fit approach and instrumental variable regression. The sample was made up of 11,095 observations of Chinese multinational enterprises' foreign subsidiaries in 54 countries from 2005 to 2020.

The results suggest that a host country with a high level of social trust results in fewer difficulties for enterprises in gaining legitimacy, thus foreign subsidiaries are more likely to select the wholly owned entry mode. The results also show that the effect is contingent on the formal institutions of host countries. The results of the mechanism test suggest that social trust influences subsidiaries' entry mode choice by reducing information asymmetry, costs and uncertainty risks. This study further finds that selecting a fit entry mode based on social trust level substantially increases foreign subsidiary performance and this effect is more significant when multinational enterprises (MNEs) are state-owned enterprises (SOEs).

The main limitation of this paper is its only focus on foreign subsidiaries of Chinese MNEs, which may limit the generalizability of research findings.

This paper responds to the call for conducting more research on informal institutions. Findings highlight the critical role of informal institutions in helping foreign subsidiaries in gaining legitimacy in host countries and the essentialness of selecting a fit entry mode based on the informal institutions of host countries for the development of foreign subsidiaries.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.