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The purpose of this paper is to identify the themes that emerged from retail supply chain (RSC) literature during the coronavirus disease 2019 (COVID-19) pandemic that inform future mitigation and recovery strategies.

This study analyses contributions in the RSC literature using four databases: Emerald, Elsevier (Science Direct), Wiley and Taylor & Francis. The systematic review approach resulted in identifying 74 articles covering 2020 to 2022.

Four themes emerged from the RSC literature on COVID-19. The first theme highlighted the factors that exacerbated the effects of the COVID-19 pandemic on the RSC. The second theme focussed on the types of disruptions that occurred in the RSC during the pandemic. The third theme demonstrated the recovery strategies used to reduce the impact of COVID-19 on the RSC. The fourth theme identified proposed mitigation strategies for the RSC post-COVID-19 outbreak.

The study provides a deeper understanding of how RSC managers could successfully reduce the effects of the COVID-19 pandemic by dealing with interruptions. Based on the reviewed studies and the four themes that evolved from RSC literature on COVID-19 throughout 2020–2022, 11 key RSC strategies and lessons have been recommended to decision-makers in the retail industry.

This is the first study to identify the themes that emerged from RSC literature during the COVID-19 pandemic to inform future mitigation and recovery strategies. The resulting themes add to the existing body of knowledge and establish the need for further research into other sectors that might be affected by future pandemics.

Construction industry (CI) has great prominence for the world economy, and it is expected that, with the use of the innovative technologies and approaches of Industry 4.0 (I4.0), the new industrial paradigm, construction can reach higher levels of productivity. This study aims to develop a model (readiness model) to assess the level of use of I4.0 technologies by the construction sector in Brazil and its most relevant applications.

The methodology used was bibliographic research, design-science research and a survey to validate the model, carried out with 162 companies, considered among the main ones in the sector in Brazil. The literature review revealed 13 technologies of I4.0 applied to construction; hence, the views of industry experts were based on these technologies.

The Digital Advancement Within CoNstruction (DAWN) readiness model was proposed, showing that among the 13 evaluated technologies of I4.0 and their applications, the Brazilian construction companies had a low level of utilization; both high and middle-income companies presented this low level of use; some technologies with a greater number of scientific publications were less used in practice in the Brazilian construction.

The originality and theoretical contribution are to present a readiness model to assess the level of use of I4.0 technologies and their most relevant applications in the CI in countries with an economy similar to Brazil’s, making it possible to measure the level of adoption of these technologies.

This study, a narrative literature review, aims to examine the combined benefits of the active and passive use of social media (SM) for well-being (WB), physical and mental health during the COVID-19 pandemic.

A search strategy has been carried out in the databases: Riss, PubMed, Medline, Scopus and Google Scholar, including all the articles published until 19 October 2023.

SM offers various benefits, including global risk awareness, health information, social connections and support. With the natural increase in physical inactivity due to COVID-19 social restrictions, SM has been identified as an appropriate tool for promoting physical activity (PA) at home to improve health.

It suggests that the combined use of active and passive benefits of SM could potentially play an important role in public health by increasing individuals’ health behaviours. In addition, dissemination, sharing and social interaction of information provided by YouTube can encourage healthy behaviours, contribute to WB, physical and mental health and raise public health awareness.

The findings presented in this study highlight the combined benefits of differentiating the features of SM use. Compared to other SM platforms, YouTube can be used as a useful tool for home-based PA that promotes health by enabling people to remain active and avoid barriers to PA due to social restrictions during the global crisis. In addition, some recommendations from the findings may help protect against potential risks and improve public health outcomes during global crises, such as the COVID-19 pandemic, among the general public using SM.

The purpose of this paper is to develop an appropriate machine learning model for predicting soil compaction degree while also examining the contribution rates of three influential factors: moisture content, electrical conductivity and temperature, towards the prediction of soil compaction degree.

Taking fine-grained soil A and B as the research object, this paper utilized the laboratory test data, including compaction parameter (moisture content), electrical parameter (electrical conductivity) and temperature, to predict soil degree of compaction based on five types of commonly used machine learning models (19 models in total). According to the prediction results, these models were preliminarily compared and further evaluated.

The Gaussian process regression model has a good effect on the prediction of degree of compaction of the two kinds of soils: the error rates of the prediction of degree of compaction for fine-grained soil A and B are within 6 and 8%, respectively. As per the order, the contribution rates manifest as: moisture content > electrical conductivity >> temperature.

By using moisture content, electrical conductivity, temperature to predict the compaction degree directly, the predicted value of the compaction degree can be obtained with higher accuracy and the detection efficiency of the compaction degree can be improved.

In the digital era individuals are overwhelmed by huge amount of readily available information. The information provided at the time of COVID-19 crisis is increasingly available. The purpose of this paper was to investigate individuals’ perceived feelings due to the plethora of information during COVID-19 pandemic in Greece in Spring 2020.

This study was conducted through a Web-based questionnaire survey posted on the Google Forms platform. The questionnaire consisted of closed-ended, seven-point Likert-scale questions. The data collected were subjected to a principal component analysis. The retained principal components (PCs) were subjected to statistical analysis between genders and among age groups and professional status with the nonparametric criteria Mann–Whitney U and Kruskal–Wallis.

Responses by 776 individuals were obtained. Seventeen original variables from the questionnaire were summarized into three PCs that explained the 71.7% of total variance: “affective disorders,” “uncertainty issues and inaccurate information worries” and “satisfaction and optimism.” Participants partly agree that the received amount of information on the disease caused them feelings of uncertainty about the future and worries about relatives’ lives, but also satisfaction with developments in the country. Females seem to experience stronger perceived feelings of “affective disorders” (p < 0.001) and reported higher degree of agreement about “uncertainty issues and inaccurate information worries.”

The recorded feelings caused by the volume of available information may have forced people accept the necessary precautionary behavioral changes that had contributed to the Greek success in preventing spread of the disease in Spring 2020.

The gender composition of teams remains an important yet complex element in unlocking the success of collaboration and performance in the metaverse. In this study, the authors examined the collaborations of same- and mixed-gender dyads to investigate how gender composition influences perceptions of the dyadic collaboration process and outcomes at both the individual and team levels in the metaverse.

Drawing on expectation states theory and social role theory, the authors hypothesized differences between dyads of different gender compositions. A blocked design was utilized where 432 subjects were randomly assigned to teams of different gender compositions: 101 male dyads, 59 female dyads and 56 mixed-gender dyads. Survey responses were collected after the experiment.

Multilevel multigroup analyses reveal that at the team level, male dyads took on the we-impress manifestation to increase satisfaction with the team solution. In contrast, female and mixed-gender dyads adopted the we-work-hard-on-task philosophy to increase satisfaction with the team solution. At the individual level, impression management is the key factor associated with trust in same-gender dyads but not in mixed-gender dyads.

As one of the pioneering works on gender effects in the metaverse, our findings shed light on two fronts in virtual dyadic collaborations. First, the authors offer a theoretically grounded and gendered perspective by investigating male, female and mixed-gender dyads in the metaverse. Second, the study advances team-based theory and deepens the understanding of gender effects at both the individual and team levels (multilevel) in a virtual collaboration environment.

Extant research shows mixed results on the impact of expressed negative emotions on donations in online charitable crowdfunding. This study solves the puzzle by examining how different types of negative emotions (i.e. sadness, anxiety and fear) expressed in crowdfunding project descriptions affect donations.

Data on 15,653 projects across four categories (medical assistance, education assistance, disaster assistance and poverty assistance) from September 2013 to May 2019 come from a leading online crowdfunding platform in China. Text analysis and regression models serve to test the hypotheses.

In the medical assistance category, the expression of sadness has an inverted U-shaped effect on donations, while the expression of anxiety has a negative effect. An appropriate number of sadness words is helpful but should not exceed five times. In the education assistance and disaster assistance categories, the expression of sadness has a positive effect on donations, but disclosure of anxiety and fear has no influence on donations. Expressions of sadness, anxiety and fear have no impact on donations in the poverty assistance category.

This work has important implications for fundraisers on how to regulate the fundraisers' expressions of negative emotions in a project's description to attract donations. These insights are also relevant for online crowdfunding platforms.

Online crowdfunding research often studies negative emotions as a whole and does not differentiate project types. The current work contributes by empirically testing the impact of three types of negative emotions on donations across four major online crowdfunding categories.

In the face of increasing political polarization worldwide, this study explores whether people create biased perceptions of political knowledge and how this affects their selection and evaluation of political content on YouTube.

For this study, an online experiment was conducted with 441 panels of South Korean respondents. In the first phase, participants answered 10 questions designed to capture their level of objective political knowledge, and for each question, they indicated whether they had responded to that question correctly as a means of measuring their subjective political knowledge. In the second phase, two types of YouTube thumbnails were presented to represent progressive and conservative claims on two controversial political issues, and participants rated and selected the content they would like to see.

Participants with low political knowledge perceived their knowledge as more than it really was. In contrast, participants with high political knowledge perceived their political knowledge as less than it really was. This biased perception of political knowledge influences respondents' choice and evaluation of political YouTube channel videos.

At a time when political polarization is increasing around the world, this study sought to explore how perceptions of political knowledge differ from actual political knowledge by applying the Dunning-Kruger effect. The authors also used political YouTube channels, whose role in forming public opinion and political influence is rapidly growing, to study the behavior and attitudes of a group of Korean respondents in the media according to their actual and perceived level of political literacy.