Restaurants under COVID-19 knife

Purpose: Drawing upon conservation of resources (COR) theory and social exchange theory (SET), this study aims to empirically test a conceptual model in which social loafing (SLof) acts as a mediator in the relationship between fear of COVID-19 (FoC-19) and organizational deviant behaviors (OD). Additionally, the model proposed the moderating effect of servant leadership (SL) in the relation between FoC-19 and SLof. Design/methodology/approach: The relationships were examined using structural equation modeling with LISREL (linear structural relations) 8.30 using data from front-line restaurant employees and their supervisors in India using a time-lag design. Findings: Results suggest that SLof mediates the effects of FoC-19 on OD. Additionally, the results confirm that SL moderates the relation between FoC-19 and SLof. Research limitations/implications: It would be beneficial to increase the knowledge concerning the other potential outcomes of SLof. Moreover, it would be helpful to examine other probable moderators like trust in supervisor and supervisor support to understand whether they can have an interfering role in mitigating and minimizing SLof among restaurant employees. Practical implications: Based on the findings, restaurant managers should pay sufficient attention to and carefully choose the leadership approach they apply in their workplaces. Restaurant managers would try to establish a bond with their employees by showing them empathy and paying attention to their emotional needs. The authors also suggest leaders who are leading people through crises make their employees understand why their job is important, rejuvenate their sense of attachment to their groups and organizations, and set clear directions for their employees. Originality/value: The current study adds to the existing literature by investigating the effects of FoC-19 on front-line employees using data collected in the Indian restaurant industry. This empirical study will enrich the authors' knowledge and understanding of the effect of SL to reduce the positive impact of FoC-19 on SLof. © 2023, Emerald Publishing Limited.

Emerging and reemerging viral infections in globe with special emphasis in India - A review

It has long been recognized that pathogens, such as viruses, parasites, and other microorganisms, emerge and change over time. Viruses are powerful infectious agents that have co-evolved with humans and are responsible for several serious illnesses in people. There is no herd immunity for most humans, making emerging viruses, particularly the RNA viruses, more dangerous. The high mistake rate of the polymerases that copy the RNA viruses' genomes gives them the ability to adapt to the quickly changing local and global environments. Through mutation (as in the case of Dengue viruses), reassortment (as in the case of influenza viruses), and recombination, they can evolve at a rapid rate (polioviruses). The influenza A viruses (such as H1N1 and H5N1), which have caused numerous outbreaks, epidemics, and pandemics around the world, are the finest example of viruses emerging and reemerging. The complex host-pathogen ecology and the co-evolution of microbes with their hosts are linked to the emergence and reemergence of novel diseases. Human viral illness emergence and reemergence is an ongoing problem that affects a nation's social and economic growth.

From Quantity to Quality: Capturing Higher Spending Markets through a Segmentation of Travelers' Expenditure

Many tourism destinations aim at expanding their market share of high spending visitors by shifting from quantity to quality. The COVID-19 pandemic has forced the introduction of social distancing requiring hotspots and mass destinations to reduce their capacity. This paper proposes a two-step approach for identifying top spending European countries over time, distinguishing between leisure and business travelers. The methodology employs the Country Product Dummy index with a hierarchical clusterization, enriched by a convergence analysis. This approach overcomes general shortcomings of descriptive statistics and cluster analyses directly applied to raw expenditure data. The outcomes of this analysis provide a detailed picture of the European travelers' expenditure across time and geographical area. The identified top spending countries of leisure and business travelers can be targeted through ad-hoc marketing campaigns and specific packages for privileging quality tourism and planning economic recovery in the post-COVID-19 reopening phase, while shifting away from mass tourism. © The Author(s) 2021.

Psychological analysis of injuries in a first category softball national championship in Cuba

Introduction: the systematic analysis of the relationships between relevant psychological variables for sports performance and injuries is essential to contribute to their prevention in specific sports. Material and methods: a descriptive-correlational and cross-sectional study was carried out in the first category women's national softball championship in Cuba. 88 athletes participated with an average chronological age of 22.91 (SD=6.13) and a sports experience of 10.83 years (SD=4.92). A specific questionnaire, the Competitive Sport Anxiety Inventory and the Psychological Inventory of Sport Execution was applied. Descriptive statistics and Kendall's Tau_b nonparametric correlation coefficient was used for data analysis. Results: A high injury load was verified with a low perception of the role of psychological factors in its etiology, as well as a notable occurrence of new injuries with negative emotional repercussions. Negative correlations of self-confidence, negative coping control, visual-imaginative control, positive coping control, and attitude control with history of injuries were obtained. The high anxiety showed significant relationships with previous injuries and new injuries during the analyzed competition. Conclusions: the findings are especially congruent with previous results in elite softball players, although new and greater relationships between variables were determined. All this means that stimulating psychological skills to control anxiety in competition could contribute to the prevention of injuries. However, longitudinal analyzes are required to confirm the predictive role of these variables before proposing psychological interventions in this regard.

Understanding the Relation of Psychological/Behavioral Factors and Cycling During the Covid-19 Pandemic: A Case Study in Iran

Previous research on travel behavior has concentrated on the behavior of traveling by cars, especially by private vehicles, while the research on cycling has focused on cycling infrastructure, the built environment, and the natural environment. Furthermore, the studies conducted during pandemics are mostly based on behavioral changes in motorized transportation. The present research tries to identify and evaluate the variables influencing cyclist behavior during covid-19 pandemic. In this research, the sample size retrieved from a survey of 375 participants was checked with Cronbach's alpha standard and estimated using confirmatory factor analysis. Results show that the variables related to health protocols can greatly impact knowing the behavior of cyclists in the time of Covid-19. Furthermore, the results show that the health issues of shared bikes can be an obstacle for people to use them more. © 2023, The Author(s), under exclusive licence to Intelligent Transportation Systems Japan.

Perspectives of non-expert users on cyber security and privacy: An analysis of online discussions on twitter

Many researchers have studied non-expert users' perspectives of cyber security and privacy aspects of computing devices at home, but their studies are mostly small-scale empirical studies based on online surveys and interviews and limited to one or a few specific types of devices, such as smart speakers. This paper reports our work on an online social media analysis of a large-scale Twitter dataset, covering cyber security and privacy aspects of many different types of computing devices discussed by non-expert users in the real world. We developed two new machine learning based classifiers to automatically create the Twitter dataset with 435,207 tweets posted by 337,604 non-expert users in January and February of 2019, 2020 and 2021. We analyzed the dataset using both quantitative (topic modeling and sentiment analysis) and qualitative analysis methods, leading to various previously unknown findings. For instance, we observed a sharp (more than doubled) increase of non-expert users' tweets on cyber security and privacy during the pandemic in 2021, compare to in the pre-COVID years (2019 and 2020). Our analysis revealed a diverse range of topics discussed by non-expert users, including VPNs, Wi-Fi, smartphones, laptops, smart home devices, financial security, help-seeking, and roles of different stakeholders. Overall negative sentiment was observed across almost all topics in all the three years. Our results indicate the multi-faceted nature of non-expert users' perspectives on cyber security and privacy and call for more holistic, comprehensive and nuanced research on their perspectives. © 2022

Adopting new technologies during the crisis: An empirical analysis of agricultural sector

Research and development in agricultural sector are becoming a crucial issue, especially to answer to growing global market needs and, in general, for rural innovation development. The innovation process involves stakeholders of all levels and rural development requires both personal farmers' characteristics along with favourable socio-political and infrastructural environment. Many countries and governments have executed innovation projects for agricultural firms, involving a number of actors from the public and private sectors. However, the literature lacks of studies that investigate the identification of the main factors that determine the agricultural entrepreneurs' probability to adopt new technologies during a crisis context. Thus, through the adoption of the Extended Theory of Planned Behaviour, this study aims at filling this lack. More specifically, the exploratory empirical analysis focuses on a sample of 130 agricultural entrepreneurs operating in a rural developing Italian region, during the historical context of global pandemic crisis of COVID-19. The results provided several insights showing the factors that influence the adoption of technologies, such as the Attitude to Environmental-Economic Sustainability and the Planned Behavioural Control. An important role is also assumed by the past farmer's technological experience. The paper offers implications for entrepreneurs and public government. © 2022 Elsevier Inc.

Global asymptotic stability, extinction and ergodic stationary distribution in a stochastic model for dual variants of SARS-CoV-2

Several mathematical models have been developed to investigate the dynamics SARS-CoV-2 and its different variants. Most of the multi-strain SARS-CoV-2 models do not capture an important and more realistic feature of such models known as randomness. As the dynamical behavior of most epidemics, especially SARS-CoV-2, is unarguably influenced by several random factors, it is appropriate to consider a stochastic vaccination co-infection model for two strains of SARS-CoV-2. In this work, a new stochastic model for two variants of SARS-CoV-2 is presented. The conditions of existence and the uniqueness of a unique global solution of the stochastic model are derived. Constructing an appropriate Lyapunov function, the conditions for the stochastic system to fluctuate around endemic equilibrium of the deterministic system are derived. Stationary distribution and ergodicity for the new co-infection model are also studied. Numerical simulations are carried out to validate theoretical results. It is observed that when the white noise intensities are larger than certain thresholds and the associated stochastic reproduction numbers are less than unity, both strains die out and go into extinction with unit probability. More-over, it is observed that, for weak white noise intensities, the solution of the stochastic system fluctuates around the endemic equilibrium (EE) of the deterministic model. Frequency distributions are also studied to show random fluctuations due to stochastic white noise intensities. The results presented herein also reveal the impact of vaccination in reducing the co-circulation of SARS-CoV-2 variants within a given population. © 2022 International Association for Mathematics and Computers in Simulation (IMACS)

An assessment of tendencies toward teleworking using TAMs: lessons from Covid-19 era for post-pandemic days

Purpose: During the Covid-19 period, when human beings are socially isolated, telework is a viable solution to safeguard employees' health. Because many employees have never experienced such a working system and organizations have not planned for it before the pandemic, imposing employees to telework has adversely affected their productivity and efficiency. This study aims to identify factors affecting individuals' tendency toward teleworking during the pandemic, which can lead to practical solutions for the post-pandemic era. Design/methodology/approach: Through the use of technology acceptance models, a conceptual model was designed. Data used to assess the model were cross-sectional and derived from 229 questionnaires filled out by employees in Tehran. The AMOS24 software processed the corresponding structural equation model. Findings: The results from the cross-sectional data indicated that attitude toward telework and perceived behavioral control over the system were significantly correlated directly with the intention to telework, while perceived usefulness and perceived ease of use of telework were correlated indirectly. Therefore, the integrated model predicts behavioral intentions better than single models performed separately. Originality/value: Psychological and mental health research describing adoption intentions of telework, particularly those focusing on employees, is still lacking. To the best of the authors' knowledge, this is the first study in this regard that has used a conceptual model derived from two technology acceptance models during the Covid-19 outbreak. An era in which the extent of the pandemic has forced employees to experience such working systems and thus the importance and practicality of teleworking have been more evident to nearly every individual. © 2022, Emerald Publishing Limited.

Impulse purchases during emergency situations: exploring permission marketing and the role of blockchain

Purpose: The paper explores how consumer behavior for purchasing impulse products changed in the complex and disruptive (emergency) situation of the COVID-19 pandemic when the customer is shopping in-home and not visiting the offline stores in an emerging economy context. This paper further explores how digital transformations like the use of blockchain technology can aid offline/omnichannel retailers in reviving sales via permission marketing for impulse products. Design/methodology/approach: The authors followed a qualitative research design and conducted 24 personal interviews with millennials and 15 interviews with offline/omnichannel retailers from an emerging economy. The data collected were analyzed using the thematic analysis procedure. Findings: The authors discuss their findings under three themes – customers' conscious impulse buying during the pandemic, customers' unconscious impulse buying during the pandemic, and a viable solution for retailers in response to the pandemic. Practical implications: The authors suggest that marketers primarily from an offline/omnichannel store should adapt to permission marketing and use technologies like blockchain for the digital transformation of their marketing strategies. Doing so can help offline retailers minimize future damages in the retail sector during emergency situations. Originality/value: This paper is one of the first that explores how impulse – pure, suggestion, planned and reminder – purchases got affected during the COVID-19 pandemic disruptions in an emerging economy. This paper is also one of the first to explore the role of permission marketing and digital transformation by the use of blockchain in helping offline retailers in forming swift trust and practice trust-based marketing. © 2022, Emerald Publishing Limited.

Everyday information behavior during the "new normal” of the Covid-19 pandemic: approaching the notions of experiential and local knowledge

Purpose: The purpose of this research is to understand everyday information behavior (IB) during the Covid-19 pandemic at the "new normal” stage, focusing on the notions of experiential knowledge (EK), i.e. knowledge acquired by first-hand experience or in personal interactions, and local knowledge (LK) as perception of local environment. Design/methodology/approach: Seventeen interviews were carried out in February–May 2021, in a district of the city of Madrid (Spain). Interview transcripts were analyzed according to grounded theory, to identify major and complementary themes of EK and LK. Findings: Participants' stories show that EK cooperated with information originating from government, scientific authorities and mainstream media, in patterns of convergence and divergence. While convergence produces "thick knowledge” (knowledge perceived as solid, real and multidimensional), divergence leads to uncertainty and collaboration, but it also supports a critical stance on authorities' information. In addition, participants' perceptions of LK emphasize its human component. LK and EK are exchanged both explicitly and tacitly. Originality/value: The paper presents the first approach to understanding EK and LK and their function during the health crisis, characterizing them as alternative information systems and as topics deserving major attention in research on IB and crisis management. © 2022, Emerald Publishing Limited.

Interacting With COVID-19: How Population Behavior, Feedback and Memory Shaped Recurrent Waves of the Epidemic

Until the approval of vaccines at the end of 2020, societies relied on non-pharmaceutical interventions (NPIs) in order to control the COVID-19 pandemic. Spontaneous changes in individual behavior might have contributed to or counteracted epidemic control due to NPIs. For example, the population compliance to NPIs may have varied over time as people developed 'epidemic fatigue' or altered their perception of the risk and severity of COVID-19. Whereas official measures are well documented, the behavioral response of the citizens is harder to capture. We propose a mathematical model of the societal response, taking into account three main effects: the citizen response dynamics, the authorities' NPIs, and the occurrence of unpreventable events that significantly alter the virus transmission rate. A key assumption is that a society has a waning memory of the epidemic effects, which reflects on both the severity of the authorities' NPIs and on the citizens' compliance to the prescribed rules. This, in turn, feeds back onto the transmission rate of the disease, such that a higher number of hospitalizations decreases the probability of transmission. We show that the model is able to reproduce the COVID-19 dynamics in terms of hospital admissions for several European countries during 2020 over surprisingly long time scales. Also, it is capable of capturing the effects of disturbances (for example the emergence of new virus variants) and can be exploited for implementing control actions to limit such effects. A possible application, illustrated in this letter, consists of exploiting the estimations based on the data of one country, to predict and control the evolution in another country, where the virus spreading is still in an earlier phase. © 2017 IEEE.

Consumers and service robots: Power relationships amid COVID-19 pandemic

Robotics significantly influence retail and consumer services. The COVID-19 pandemic further amplified the rise of service robots (SRs) through social distancing measures. While robots are embraced widely by retailers and service providers, consumers' interaction with SRs remains an intriguing avenue of research across contexts. By taking a relative social power perspective, we report on a series of pre- and intra-COVID-19 studies. Our findings suggest that Gen-Z consumers hold more positive attitudes towards SRs perceived as lower in power vis-à-vis the human user. The longitudinal nature of our study also reveals that while attitudes towards such low-power services turned more negative during the COVID-19 pandemic, attitudes towards SRs that are high in power vis-à-vis the human user remained stable. In practical terms, while Gen-Z consumers hold more positive attitudes towards low-power robots, such service providers also face the challenge of relatively changeable attitudes towards them, especially during crisis times. © 2022 The Author(s)

The relationship between student motivation and academic performance: the mediating role of online learning behavior

Purpose: This paper aims to use a quantitative approach to explore the role of online learning behavior in students' academic performance during the COVID-19 pandemic. Specifically, the authors probe its mediating effect in the relationship between student motivation (extrinsic and intrinsic) and academic performance in a blended learning context. Design/methodology/approach: Survey data were collected from 148 students taking an organizational behavior course at one Chinese university. The data were paired and analyzed through regression analysis. Findings: The results show that students should actively engage in online learning behavior to maximize the effects of blended learning. Extrinsic motivation was found to positively influence academic performance both directly and indirectly through online learning behavior, while intrinsic motivation affected academic performance only indirectly. Originality/value: Through paired data on extrinsic and intrinsic motivation, online learning behavior and academic performance, this study provides a more nuanced understanding of how online learning behavior affects the focal relationship, and it advances research on the mechanisms underlying the focal relationship. Practitioners should enhance students' online learning behavior to boost blended learning effects during the COVID-19 pandemic. © 2022, Emerald Publishing Limited.

Equilibrium social activity during an epidemic

During an infectious-disease epidemic, people make choices that impact transmission, trading off the risk of infection with the social-economic benefits of activity. We investigate how the qualitative features of an epidemic's Nash-equilibrium trajectory depend on the nature of the economic benefits that people get from activity. If economic benefits do not depend on how many others are active, as usually modeled, then there is a unique equilibrium trajectory, the epidemic eventually reaches a steady state, and agents born into the steady state have zero expected lifetime welfare. On the other hand, if the benefit of activity increases as others are more active ("social benefits”) and the disease is sufficiently severe, then there are always multiple equilibrium trajectories, including some that never settle into a steady state and that welfare dominate any given steady-state equilibrium. Within this framework, we analyze the equilibrium impact of a policy that modestly reduces the transmission rate. Such a policy has no long-run effect on society-wide welfare absent social benefits, but can raise long-run welfare if there are social benefits and the epidemic never settles into a steady state. © 2022 Elsevier Inc.

The influence of the ethics of E-retailers on online customer experience and customer satisfaction

The COVID-19 pandemic and the lockdown pushed people to buy more online. With the increase in online shopping, there was also an increase in ethical issues with electronic retailers resulting from problems with products, misleading price practices, lack of customers' personal and financial data protection, non-delivery of goods, and misleading advertising. This study aimed to determine whether consumers' perceptions of e-retailers' ethics influence online customer experience and satisfaction when purchasing products and services. A research model was developed based on the literature on ethics in e-commerce. To fulfill the objective, a research model on consumer perceptions of ethics in online retailing was tested based on answers of 501 Brazilian online shoppers. Data were gathered through an online questionnaire and analyzed using structural equation modeling with an estimation of minimum least squares. The results indicated significant relations between the e-retailer's ethics, the online experience, and customer satisfaction with the mediation of ethical beliefs, suggesting that the e-retailer's ethics can potentially stimulate a good online consumer experience and satisfaction when purchasing on the internet and may contribute to the relationship between the consumer and the e-retailer. Furthermore, ethical beliefs can mediate these relations, collaborating with the effect of e-retailers' ethics on the consumer's experience and satisfaction. These results represent an advance in the study of new ethical dimensions in electronic retail, which currently are reduced to security and privacy issues. In practice, this study resulted in new knowledge about ethical practices that can guide electronic retailers in the adoption of new customer prospecting strategies. It also highlights the importance of improving regulations that prevent certain behaviors from happening. © 2022 Elsevier Ltd

Using Q method to investigate the influence of inclusive water, sanitation and hygiene (WASH) on tourists' hotel choice in Fiji

Consequent to the COVID-19 pandemic and the reopening of international borders, tourists are increasingly concerned about sanitation and hygiene practices in tourism destinations. There is an evident need to investigate how the COVID-19 pandemic has transformed tourist choices. This paper investigates the perceptions of hotel staff and tourists on the influence of inclusive water, sanitation, and hygiene (WASH) practices on tourists' hotel choices in Fiji. This study explores the value of Q-methodology through a case study of Fiji with data collected from 80 hotel staff and 75 tourists. The findings demonstrate that Q-methodology is effective in identifying three tourist types who have a strong interest in WASH impacts and aspects of their safety including concerns about how their visit impacts the local community and environment. Similarly, the Q method was useful in identifying four perspectives of staff understanding on WASH impacts that are significant to tourists' choice of hotel. The findings suggest a significant potential for hotel operators to enact socially inclusive WASH practices to enhance their appeal in the ‘new normal'. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Social workers' adaptation in times of pandemic crisis: A Hong Kong case

Through the lens of the theory of planned behavior, this article explores how social workers adapt to a new situation due to the outbreak of the COVID-19 pandemic. Three focus group sessions were conducted with 23 social workers from child and youth, family, and elderly services in Hong Kong. Three major themes were generated: (1) repositioning the social work profession, (2) renegotiating contracts with funders, and (3) exploring novel intervention methods. Implications of the findings are discussed. To ensure social workers can respond effectively in crises, an evolving nature of the profession is advocated to enshrine its spirit to serve.

Academic performance prediction associated with synchronous online interactive learning behaviors based on the machine learning approach

With long-term impact of COVID-19 on education, online interactive live courses have been an effective method to keep learning and teaching from being interrupted, attracting more and more attention due to their synchronous and real-time interaction. However, there is no suitable method for predicting academic performance for students participating in online class. Five machine learning models are employed to predict academic performance of an engineering mechanics course, taking online learning behaviors, comprehensive performance as input and final exam scores (FESs) as output. The analysis shows the gradient boosting regression model achieves the best performance with the highest correlation coefficient (0.7558), and the lowest RMSE (9.3595). Intellectual education score (IES) is the most important factor of comprehensive performance while the number of completed assignment (NOCA), the live viewing rate (LVR) and the replay viewing rate (RVR) of online learning behaviors are the most important factors influencing FESs. Students with higher IES are more likely to achieve better academic performance, and students with lower IES but higher NOCA tend to perform better. Our study can provide effective evidences for teachers to adjust teaching strategies and provide precise assistance for students at risk of academic failure in advance.