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Unverified information avoidance behavior refers to the conscious effort made by individuals to avoid consuming information that has not been verified by credible sources. This behavior is essential in preventing the spread of misinformation that can hinder effective public health responses. While previous studies have examined information avoidance behavior in general, there is a lack of research specifically focusing on the avoidance of unverified information during health crises. This study aims to fill this gap by exploring factors that lead to social media users’ unverified information avoidance behavior during health crises, providing novel insights into the determinants of this protective behavior.

We based our research model on the health belief model and validated it using data collected from 424 individuals who use social media. The proposed model was tested by using the partial least squares structural equation modeling (PLS-SEM) approach.

Our results indicate that individuals’ government social media participation (following accounts and joining groups) affects their health beliefs (perceived severity and benefits of information avoidance), which in turn trigger their unverified information avoidance behavior.

Our study contributes to the current literature of social media crisis management and information avoidance behavior. The implications of these findings for policymakers, social media platforms and theory are further discussed.

This study aims to use geographical information on social media for public opinion risk identification during a crisis.

This study constructs a double-layer network that associates the online public opinion with geographical information. In the double-layer network, Gaussian process regression is used to train the prediction model for geographical locations. Second, cross-space information flow is described using local government data availability and regional internet development indicators. Finally, the structural characteristics and information flow of the double-layer network are explored to capture public opinion risks in a fine-grained manner. This study used the early stages of the COVID-19 outbreak for validation analyses, and it collected more than 90,000 pieces of public opinion data from microblogs.

In the early stages of the COVID-19 outbreak, the double-layer network exhibited a radiating state, and the information dissemination was more dependent on the nodes with higher in-degree. Moreover, the double-layer network structure showed geographical differences. The risk contagion was more significant in areas where information flow was prominent, but the influence of nodes was reduced.

Public opinion risk identification that incorporates geographical scenarios contributes to enhanced situational awareness. This study not only effectively extends geographical information on social media, but also provides valuable insights for accurately responding to public opinion.

This study examines the effects and driving mechanisms of relational bonds (i.e. financial, social, and structural bonds), live-streaming shopping atmosphere factors (i.e. suspense, entertainment, perceived crowdedness, and vicarious experience), consumer empowerment and customer commitment on consumers’ impulse consumption behavior. Additionally, the study examines the moderating influence of product involvement and collectivism.

An online survey was conducted with 665 valid respondents. The authors empirically validated the collected data through the partial least squares structural equation modeling (PLS-SEM) technique, complemented by the artificial neural network (ANN) analysis.

The results suggest that financial bonds, structural bonds, suspense, entertainment, and vicarious experience promote consumer empowerment, which in turn leads to customer commitment and impulse consumption behavior. Second, collectivism moderates the relationship between customer commitment and impulse consumption behavior.

This study provides empirical evidence that relational bonds and live-streaming shopping atmosphere factors play predictive roles in enhancing consumer empowerment, which further promotes impulse consumption behavior through customer commitment. Also, collectivism is found as a moderator.

This study proposes a theoretical model to explain user intention to continue engaging with Social Commerce (SC) from a habit perspective. The research uses social impact theory, user personal traits, and SC quality to explain how user habits are formed in SC, leading to continued usage.

The study collected data from 868 Indonesian respondents using a cross-sectional field design. SEM analysis confirmed the proposed theoretical model, calculating direct, indirect, and moderating effects.

The results showed that the social aspect is the dominant construct influencing users’ habit of using SC. Further, the outcome indicates that habit significantly predicts Continuity usage. Profoundly, subjective norms are the most significant predictors of habit, followed by self-efficacy, content quality, and herd behavior. Meanwhile, Trust and Social Support only indirectly affect Habit through self-efficacy and content quality, respectively, as mediators. Additionally, the moderating effect analysis revealed that age and gender play a role in habit formation.

This study specifically explores the factors affecting the development of habits in SC usage, leading to repeated behaviors. This area has not been thoroughly examined in previous research. Therefore, this study seeks to address this gap by investigating how habits are formed through social interactions on SC platforms. Understanding habit formation provides an alternative way of comprehending the continued use of SC, as it is considered a significant factor that leads to continued intention.

Middle-aged and elderly users become an important group on short-video platforms, however, the research on determinants of their video-creating intention is limited. Based on lifespan development theories, this study examines the impact of aging experiences on their video-creating intention, considering internal generative motivations as mediators and age as a moderator.

To test this study’s hypotheses, survey data from 321 Chinese middle-aged and elderly short-video users were collected and partial least square-structural equation modelling (PLS-SEM) approach was used to analyze these data.

Middle-aged and elderly users' aging experiences of social loss and personal growth are positively related to their video-creating intention. Aging experiences (i.e. physical loss, social loss, and personal growth) are positively related to internal generative motivations (i.e. need to be needed and symbolic immortality), and need to be needed is positively related to video-creating intention. Via the mediation of need to be needed, physical loss and personal growth are indirectly positively related to video-creating intention. Personal growth strengthens the relationship between physical loss and symbolic immortality, but weakens the associations of social loss with need to be needed and symbolic immortality. Age weakens the relationship between symbolic immortality and video-creating intention.

This study is the first wave to introduce and integrate lifespan theories such as selective optimization with compensation model, socioemotional selectivity theory, and generativity theory to explore the impacts of aging experiences on middle-aged and elderly users' video-creating intention by considering generativity motivations as mediators and age as a moderator.

This research aims to analyse the perceptions of practitioners in three regions regarding the challenges faced by their firms during the pandemic, considered a black-swan event. It examines the strategies implemented to mitigate and recover from risks, evaluates the effectiveness of these strategies and assesses the difficulties encountered in their implementation.

In the summer of 2022, an online survey was conducted among supply chain (SC) practitioners in France, Poland and the St. Louis, Missouri region of the USA. The survey aimed to understand the impact of COVID-19 on their firms and the SC strategies employed to sustain operations. These regions were selected due to their varying levels of SC development, including infrastructure, economic resources and expertise. Moreover, they exhibited different responses in safeguarding the well-being of their citizens during the pandemic.

The study reveals consistent perceptions among practitioners from the three regions regarding the impact of COVID-19 on SCs. Their actions to enhance SC resilience primarily relied on strengthening collaborative efforts within their firms and SCs, thus validating the tenets of the relational view.

COVID-19 is (hopefully) our black-swan pandemic occurrence during our lifetime. Nevertheless, the lessons learned from it can inform future SC risk management practices, particularly in dealing with rare crises. During times of crisis, leveraging existing SC structures may prove more effective and efficient than developing new ones. These findings underscore the significance of relationships in ensuring SC resilience.

Society is critically dependent on an adequate supply of hospital doctors to ensure optimal health care. Voluntary turnover amongst hospital doctors is, however, an increasing problem for hospitals. The aim of this study was to systematically review the extant academic literature to obtain a comprehensive understanding of the current knowledge base on hospital doctor turnover and retention. In addition to this, we synthesise the most common methodological approaches used before then offering an agenda to guide future research.

Adopting the PRISMA methodology, we conducted a systematic literature search of four databases, namely CINAHL, MEDLINE, PsycINFO and Web of Science.

We identified 51 papers that empirically examined hospital doctor turnover and retention. Most of these papers were quantitative, cross-sectional studies focussed on meso-level predictors of doctor turnover.

Selection criteria concentrated on doctors who worked in hospitals, which limited knowledge of one area of the healthcare environment. The review could disregard relevant articles, such as those that discuss the turnover and retention of doctors in other specialities, including general practitioners. Additionally, being limited to peer-reviewed published journals eliminates grey literature such as dissertations, reports and case studies, which may bring impactful results.

Globally, hospital doctor turnover is a prevalent issue that is influenced by a variety of factors. However, a lack of focus on doctors who remain in their job hinders a comprehensive understanding of the issue. Conducting “stay interviews” with doctors could provide valuable insight into what motivates them to remain and what could be done to enhance their work conditions. In addition, hospital management and recruiters should consider aspects of job embeddedness that occur outside of the workplace, such as facilitating connections outside of work. By resolving these concerns, hospitals can retain physicians more effectively and enhance their overall retention efforts.

Focussing on the reasons why employees remain with an organisation can have significant social repercussions. When organisations invest in gaining an understanding of what motivates their employees to stay in the job, they are better able to establish a positive work environment that likely to promote employee well-being and job satisfaction. This can result in enhanced job performance, increased productivity and higher employee retention rates, all of which are advantageous to the organisation and its employees.

The review concludes that there has been little consideration of the retention, as opposed to the turnover, of hospital doctors. We argue that more expansive methodological approaches would be useful, with more qualitative approaches likely to be particularly useful. We also call on future researchers to consider focussing further on why doctors remain in posts when so many are leaving.

Societies depend on interconnected infrastructures that are becoming more complex over the years. Multi-disciplinary knowledge and skills are essential to develop modern infrastructures, requiring close collaboration of various infrastructure owners. To effectively manage and improve inter-organizational collaboration (IOC) in infrastructure construction projects, collaboration status should be assessed continually. This study identifies the assessment criteria, forming the foundation of a tool for assessing the status of IOC in interconnected infrastructure projects.

A systematic literature study and in-depth semi-structured interviews with practitioners in interconnected infrastructure construction projects in the Netherlands are performed to identify the criteria for assessing the status of IOC in infrastructure construction projects, based on which an assessment tool is developed.

The identified assessment criteria through the literature and the practitioner’s perspectives results in the designing and development of a collaboration assessment tool. The assessment tool consists of 12 criteria and 36 sub-criteria from three different categories of collaborative capacity: individual, relational, and organizational.

The assessment tool enables practitioners to monitor the status of IOC between infrastructure owners and assists them in making informed decisions to enhance collaboration. The assessment tool provides the opportunity to assess and analyze the status of collaboration based on three categories (i.e., individual, relational, and organizational).

This paper aims to analyze the direct and indirect effects of investor protection on forced CEO turnover.

The authors investigate 5,175 firm-year observations from 16 European countries over 2012–2018, collect data on four national investor protection indicators, identify 196 forced CEO turnovers and use multiple logistic regression models.

The results show that a reduction in the degree of investor protection significantly increases the probability of a forced change of the company’s CEO. Furthermore, when the degree of investor protection increases, directors are attributed a lower degree of responsibility in the event of a decline in earnings performance. Therefore, the relation between a decrease in profitability and a forced change of CEO is reduced.

The research is focused on countries belonging to the European Economic Area and most of the investor protection indicators are derived from surveys. Concerning policy implications, the findings suggest that regulators should focus on the effective enforcement of investor protection mechanisms.

The results confirm that characteristics at the country level have an impact on corporate decisions, highlighting the importance of increasing the degree of investor protection as a means of mitigating agency conflicts and improving stewardship.

To the best of the authors’ knowledge, this study explores a relatively underinvestigated topic as it uses investor protection indicators to jointly evaluate both direct and indirect effects on forced changes of CEO through cross-national research.

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.