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The outbreak of COVID-19 has become a major public health emergency worldwide. How to effectively guide public opinion and implement precise prevention and control is a hot topic in current research. Mining the spatiotemporal coupling between online public opinion and offline epidemics can provide decision support for the precise management and control of future emergencies.

This study focuses on analyzing the spatiotemporal coupling relationship between public opinion and the epidemic. First, based on Weibo information and confirmed case information, a field framework is constructed using field theory. Second, SnowNLP is used for sentiment mining and LDA is utilized for topic extraction to analyze the topic evolution and the sentiment evolution of public opinion in each coupling stage. Finally, the spatial model is used to explore the coupling relationship between public opinion and the epidemic in space.

The findings show that there is a certain coupling between online public opinion sentiment and offline epidemics, with a significant coupling relationship in the time dimension, while there is no remarkable coupling relationship in space. In addition, the core topics of public concern are different at different coupling stages.

This study deeply explores the spatiotemporal coupling relationship between online public opinion and offline epidemics, adding a new research perspective to related research. The result can help the government and relevant departments understand the dynamic development of epidemic events and achieve precise control while mastering the dynamics of online public opinion.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

This study examines the semi-strong market efficiency of the Indian agricultural commodity market in light of market reforms and policies. This study investigates whether the market reforms have boosted the speed of price adjustment and influenced the market quality.

The study used the daily data of nine agricultural commodities. To precisely capture the effects of market microstructure changes, this study split the whole data into pre- and post-ban and pre- and post-reform eras. To ascertain the velocity of price adjustment, the authors used the ARMA (1,1) model, and the ADD VRatio was employed to identify the price movement on a specific day.

This study found that full incorporation of information happens sometimes. The authors noticed no gradual progress in the quickness of price adjustment. Since both methods suggested the same result for the period, the authors confirm that market microstructure changes do not enhance market quality.

This research has implications for academicians, policymakers and market players.

The paper has twofold novelty. First, this is a contemporary topic, and very few studies have been done in the Indian agriculture context. Second, the study has implications for policymakers and government because it highlights the effects of structural changes on market quality and market efficiency.

This study aims to reveal the triggering mechanism and boundary conditions of tourists’ cross-border travel anxiety (CBTA) from different crisis information sources.

Drawing on the heuristic-systematic model (HSM), this study constructs a theoretical formation path of tourists’ CBTA. Based on competence-based and moral-based crises, hypotheses were examined through three situational experiments, targeting Chinese and Malaysian potential tourists.

Organization-released crisis information triggers higher tourists’ CBTA than government ones, with perceived uncertainty mediating it. Crisis communication message appeals (CCMAs) (rational vs emotional) negatively moderate the above relationships. Rational CCMAs work for governmental crisis communication, while emotional CCMAs work for organizational ones.

This study proposes a heuristic cross-border tourism crisis information dissemination strategy for destination management organizations and highlights the advantages of CCMAs in preventing secondary crises.

This study reexamines the cause-and-effect and the intervention mechanisms of tourists’ reactions to crisis information, which expands the cross-border tourism crisis management research and the application of the HSM in such a context.

本研究旨在从不同的危机信息源中揭示游客跨境旅行焦虑的触发机制和边界条件。

本研究借鉴启发式-系统式模型（HSM）, 构建了游客跨境旅游焦虑的理论形成路径。基于能力型和道德型目的地危机事件, 以中国及马来西亚潜在游客为例, 通过三组情境实验验证所提出的假设。

与政府发布的危机信息相比, 组织发布的危机信息会引发更高的游客跨境旅游焦虑, 而感知不确定性会对该路径起到中介作用。危机沟通信息诉求（理性vs.感性）对上述关系起负向调节作用。理性的信息诉求适用于政府危机沟通, 而感性的信息诉求适用于组织危机沟通。

本研究为目的地管理组织提出了启发式跨境旅游危机信息传播策略, 并强调了危机沟通信息诉求在预防二次危机方面的优势。

本研究重新审视了游客对危机信息反应的因果关系和干预机制, 拓展了跨境旅游危机管理研究和HSM在此背景下的应用。

Este estudio pretende revelar el mecanismo desencadenante y las condiciones límite de la ansiedad de los turistas ante los viajes transfronterizos (CBTA) a partir de diferentes fuentes de información sobre crisis (CIS).

Basándose en el modelo heurístico-sistemático (HSM), este estudio construye una vía teórica de formación de la CBTA de los turistas. A partir de las crisis basadas en la competencia y en la moral, se examinaron las hipótesis mediante tres experimentos situacionales, dirigidos a turistas potenciales chinos y malayos.

La información sobre crisis difundida por organizaciones desencadena una mayor CBTA de los turistas que la gubernamental, con la incertidumbre percibida como mediadora. Los recursos de los mensajes de comunicación de crisis (CCMA) (racionales frente a emocionales) moderan negativamente las relaciones anteriores. Los CCMA racionales funcionan para la comunicación de crisis gubernamental, mientras que los CCMA emocionales para las organizativas.

Los resultados proponen que las organizaciones de gestión de destinos (OGD) deberían considerar estrategias heurísticas a la hora de difundir información sobre crisis turísticas transfronterizas. Prestar atención al efecto diferencial de las CCMA ayuda a prevenir crisis secundarias.

Este estudio reexamina la causa-efecto y los mecanismos de intervención de las reacciones de los turistas a la información sobre crisis, lo que amplía la investigación sobre la gestión de crisis turísticas transfronterizas y la aplicación de la HSM en dicho contexto.

The purpose of this study is to examine the effect of extrinsic aspects of the technology acceptance model, namely, information quality, functionality, accessibility, user interface design, system quality, functionality, facilitating conditions and computer playfulness as well as intrinsic aspects, namely, perceived self-efficacy, enjoyment and learning goals. orientation on perceived usefulness and perceived ease of use in the context of the learning management system (LMS) as a system to support employee learning and development. This study also analyzes the effect of perceived ease of use on perceived usefulness and analyzes the effect of these two variables on the intention to adopt a LMS. This study included 3,205 respondents who are employees of banking companies in Indonesia and who used the LMS for their learning and self-development needs during the COVID-19 pandemic.

This research is a quantitative study that uses online surveys to collect data and partial least squares statistical tools to analyze survey data.

The results showed that accessibility alone had no effect on perceived usefulness and perceived ease of use, while enjoyment had no effect on the intention to use LMS and perceived ease of use and functionality had no effect on the intention to use LMS.

This research focuses on the concept of technology acceptance with extrinsic and intrinsic aspects. This research context involves employees working in the banking sector with the adoption of the LMS.

LMS in banking companies can be optimized by providing online training and reducing the operational costs of employee training. By using LMS, companies can offer online courses to employees and track progress in distance learning, become a learning choice and information dissemination during the pandemic and also support future business continuity.

This study focuses on testing the technology adoption model on LMSs in the banking sector by adding extrinsic aspects, namely, system quality, facilitating conditioning, computer playfulness and user interface design, and combining intrinsic aspects, namely, perceived self-efficacy, enjoyment and learning goal orientation.

The pandemic has enhanced the global phenomenon of disinformation. This paper aims to study the false news concerning COVID-19, spread through social media in Spain, by using the LatamChequea database for a duration from 01/22/2020, when the first false information has been detected, up to 03/09/2021.

A quantitative analysis has been conducted with regard to the correlation between fake news stories and the pandemic state, the motive to share them, their dissemination in other countries and the effectiveness of fact checking. This study is complemented by a qualitative method: a focus group conducted with representatives of different groups within the society.

Fake news has been primarily disseminated through several social networks at the same time, with two peaks taking place in over a half of the said false stories. The first took place from March to April of 2020 during complete lockdown, and we were informed of prevention measures, the country’s situation and the origin of the virus, whereas the second was related to news revolving around the coming vaccines, which occurred between October and November. The audience tends to neither cross-check the information received nor report fake news to competent authorities, and fact-checking methods fail to stop their spread. Further awareness and digital literacy campaigns are thus required in addition to more involvement from governments and technological platforms.

The main limitation of the research is the fact that it was only possible to conduct a focus group of five individuals who do not belong to generation Z due to the restrictions imposed by the pandemic, although a clear contribution to the analysis of the impact of fake news on social networks during the COVID-19 pandemic in Spain can be seen from the privileged experiences in each of the fields of work that were identified. In this sense, the results of the study are not generalizable to a larger population. On the other hand, and with a view to future research, it would be advisable to carry out a more specific study of how fake news affects generation Z.

This research is original in nature, and the findings of this study are valuable for business practitioners and scholars, brand marketers, social media platform owners, opinion leaders and policymakers.

The rise of the mobile Internet has accumulated much text information in various online financial forums. Such information often contains the emotional attitudes of investors toward financial technology (fintech) platforms, so extracting the sentimental tendency information has great practical value for the development of fintech platforms. Based on the investor sentiment theory, the paper aims to analyze the relevant social media data and test the influence path of online news evaluation on the stock price fluctuation of fintech platforms.

Taking Oriental Fortune as the research object, this paper selects multiple variables such as stock bar popularity, snowball popularity, news popularity and news sentiment scores collected by UQER and combines the sentiment scores of single daily news into a daily sentiment score. Based on the period from November 1, 2019 to March 31, 2020, during the emergence of the coronavirus disease 2019 (COVID-19) pandemic as the background, the authors conduct the Granger causality test based on the vector autoregressive (VAR) model and analyze the relevant evaluation of Oriental Fortune through the empirical model.

The authors' results show that different online evaluations impact the rise and fall of stock prices differently, while news popularity has the most significant impact. Besides, news sentiment scores on share price fluctuation have a relatively substantial influence. These findings indicate that the authoritative news evaluation can strongly guide investors to make relevant investment behavior operations in the information dissemination process, significantly affecting stock prices.

The research findings of this paper have good inspiration and reference values for investors and financial regulators.

The purpose of this study is to investigate the impact of rapid internationalization by emerging-market multinational enterprises (EMNEs) on their innovation performance. It also seeks to identify any potential moderating factors that could influence this relationship.

By analyzing data from listed Chinese MNEs from 2012 to 2022, this study applies a negative binomial regression model to test the research hypotheses.

This study uncovers an inverted U-shaped relationship between the internationalization speed of EMNEs and their innovation performance. It also suggests that strong absorptive, learning and managerial capacities could play positive moderating roles in the effect of internationalization speed on EMNEs’ innovation performance.

This study highlights rapid global expansion, promoting new knowledge acquisition for EMNEs. However, due to time-compression dilemmas with limited EMNE firm-specific advantages, overly accelerated internationalization hinders learning effectiveness. Additionally, this study reveals the critical importance of three firm-specific capacities in EMNEs – absorptive, learning and managerial capacities – in efficiently assimilating newly acquired knowledge from foreign markets and enhancing their innovation performance through rapid internationalization.

Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications.

This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns.

The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication.

Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.

Microblogs are communication platforms for companies and consumers that challenge companies' brand marketing strategies. This paper provides a theoretical basis for expanding microblog applications and a practical basis for improving the effectiveness of brand marketing.

The authors use factor analysis to extract the factors of microblog user influence and construct a structural equation model to reveal the interaction mechanism of the influencing factors. Additionally, the authors clarify the promotion and enhancement effects of these factors.

Microblog user influence can be converted into richness, interaction and value factors. The richness factor significantly affects the latter two, whereas the interaction factor does not affect the value factor.

First, the sample used is limited to media industry practitioners. To increase generalizability, diverse groups should be included in future studies. Second, this model's theoretical explanatory ability can be further developed by adding other meaningful factors beyond the existing ones.

This study analyzes the factors of microblog user influence in China and validates the relevant elements. As a result, it improves the influence research on social media users and benefits the practice of information recommendation and microblog marketing.