Students' psychological perceptions toward online learning engagement and outcomes during the COVID-19 pandemic: a comparative analysis of students in three different countries

Due to COVID-19, universities have shifted to offer online learning for their students from traditional face-to-face learning. Despite various efforts made by university administrators for their students' online learning during the COVID-19 pandemic, not much has been identified about how students perceived online learning and what factors affected their online learning engagement and outcomes. Examining students' motivation, self-efficacy, and anxiety as key factors for their online learning engagement and outcomes, this study conducted a self-administered online survey with college students in three countries: the U.S., South Korea, and Colombia. This study used SEM to test hypotheses and conducted a multi-group analysis to find differences among students. The findings indicated that students' self-efficacy and anxiety significantly impacted their online learning engagement, influencing online learning outcomes. Although students were highly engaged in online learning, their perceived online learning was not so effective and rigorous compared to face-to-face learning.

Effects of customers' perceived risks of sharing economy on self-protective behavior toward COVID-19. (Special Issue: The sharing economy in a post-pandemic world.)

Purpose: This study aims to investigate how customers' perceived risks of sharing economy (SE) affect their self-protective behaviors when using SE, leading to their future behavioral intention. Additionally, this study looks into whether there are any differences between accommodation-sharing and ride-sharing customers in the aforementioned relationships. Design/methodology/approach: An online survey targeting two groups of SE customers (i.e. accommodation sharing and ride sharing) was used. Using partial least squares structural equation modeling, the mechanism of how SE customers' perceived risks of SE affect their self-protective behaviors, which in turn influence their future behavior intention. A multigroup analysis was performed to assess the difference between the two groups of SE customers. Finally, a multivariate analysis of variance (MANOVA) was conducted to see the potential differences between the five classifications of self-protective behaviors in their perceived risks. Findings: SE customers' psychological risks positively affected their hygiene protective behaviors and social protective behaviors, influencing their behavior intention and relative intention (compared with traditional services). Social risk had a negative impact on SE customers' hygiene protective behaviors. There was a significant difference between accommodation sharing and ride sharing customers in their psychological mechanism of how perceived risks influence their self-protective behaviors. Practical implications: The findings of this study help SE platforms and service providers better understand their customers' perceived risks of their services and suggest them to promote their customers' self-protective behaviors so that perceived risks can be mitigated, thereby generating strong behavior intentions. As the results indicated that there is a significant difference between the two major forms of SE (i.e. accommodation sharing and ride sharing) in their customers' perceived risks and self-protective behavior, SE platforms can further refine their operational and marketing efforts based on the findings. Originality/value: This study offers a comprehensive understanding of SE customers' self-protective behaviors by examining the effects of SE customers' different perceived risks on their self-protective behaviors during the unprecedented pandemic. Furthermore, the comparison of the two most popular forms of SE (i.e. accommodation sharing and ride sharing) provides new perspectives to understand customers' behavior in the SE context.

Effects of customers' perceived risks of sharing economy on self-protective behavior toward COVID-19

PurposeThis study aims to investigate how customers' perceived risks of sharing economy (SE) affect their self-protective behaviors when using SE, leading to their future behavioral intention. Additionally, this study looks into whether there are any differences between accommodation-sharing and ride-sharing customers in the aforementioned relationships.Design/methodology/approachAn online survey targeting two groups of SE customers (i.e. accommodation sharing and ride sharing) was used. Using partial least squares structural equation modeling, the mechanism of how SE customers' perceived risks of SE affect their self-protective behaviors, which in turn influence their future behavior intention. A multigroup analysis was performed to assess the difference between the two groups of SE customers. Finally, a multivariate analysis of variance (MANOVA) was conducted to see the potential differences between the five classifications of self-protective behaviors in their perceived risks.FindingsSE customers' psychological risks positively affected their hygiene protective behaviors and social protective behaviors, influencing their behavior intention and relative intention (compared with traditional services). Social risk had a negative impact on SE customers' hygiene protective behaviors. There was a significant difference between accommodation sharing and ride sharing customers in their psychological mechanism of how perceived risks influence their self-protective behaviors.Practical implicationsThe findings of this study help SE platforms and service providers better understand their customers' perceived risks of their services and suggest them to promote their customers' self-protective behaviors so that perceived risks can be mitigated, thereby generating strong behavior intentions. As the results indicated that there is a significant difference between the two major forms of SE (i.e. accommodation sharing and ride sharing) in their customers' perceived risks and self-protective behavior, SE platforms can further refine their operational and marketing efforts based on the findings.Originality/valueThis study offers a comprehensive understanding of SE customers' self-protective behaviors by examining the effects of SE customers' different perceived risks on their self-protective behaviors during the unprecedented pandemic. Furthermore, the comparison of the two most popular forms of SE (i.e. accommodation sharing and ride sharing) provides new perspectives to understand customers' behavior in the SE context.

How do restaurants respond to the COVID-19 pandemic? Lessons from Colombian restauranteurs and their survival strategies

This study attempted to identify the overall impact of COVID-19 on the restaurant industry in Colombia through the interviews with ten restaurant owners or chefs (e.g., fine-dining, family-dining, casual dining, and quick-service restaurants). Adopting the three phase post-pandemic planning framework, this study examined how the restaurants responded, recovered, and renewed their businesses and what survival strategies they have been implementing to respond to the new normal after the COVID-19 outbreaks. Findings of the study indicated the restaurants in Colombia focused on and developed four operational survival strategies: operational transformation and challenges, government support, social responsibility, and precautionary measurement practices, focusing on their core value and assets such as employees and menus.

Effects of customers’ perceived risks of sharing economy on self-protective behavior toward COVID-19

Purpose This study aims to investigate how customers' perceived risks of sharing economy (SE) affect their self-protective behaviors when using SE, leading to their future behavioral intention. Additionally, this study looks into whether there are any differences between accommodation-sharing and ride-sharing customers in the aforementioned relationships. Design/methodology/approach An online survey targeting two groups of SE customers (i.e. accommodation sharing and ride sharing) was used. Using partial least squares structural equation modeling, the mechanism of how SE customers' perceived risks of SE affect their self-protective behaviors, which in turn influence their future behavior intention. A multigroup analysis was performed to assess the difference between the two groups of SE customers. Finally, a multivariate analysis of variance (MANOVA) was conducted to see the potential differences between the five classifications of self-protective behaviors in their perceived risks. Findings SE customers' psychological risks positively affected their hygiene protective behaviors and social protective behaviors, influencing their behavior intention and relative intention (compared with traditional services). Social risk had a negative impact on SE customers' hygiene protective behaviors. There was a significant difference between accommodation sharing and ride sharing customers in their psychological mechanism of how perceived risks influence their self-protective behaviors. Practical implications The findings of this study help SE platforms and service providers better understand their customers' perceived risks of their services and suggest them to promote their customers' self-protective behaviors so that perceived risks can be mitigated, thereby generating strong behavior intentions. As the results indicated that there is a significant difference between the two major forms of SE (i.e. accommodation sharing and ride sharing) in their customers' perceived risks and self-protective behavior, SE platforms can further refine their operational and marketing efforts based on the findings. Originality/value This study offers a comprehensive understanding of SE customers' self-protective behaviors by examining the effects of SE customers' different perceived risks on their self-protective behaviors during the unprecedented pandemic. Furthermore, the comparison of the two most popular forms of SE (i.e. accommodation sharing and ride sharing) provides new perspectives to understand customers' behavior in the SE context.

Key factors driving customers’ restaurant dining behavior during the COVID-19 pandemic

PurposeThis study aims to identify key factors that affected US respondents’ dining behavior at restaurants during the midst of the COVID-19 pandemic.Design/methodology/approachDue to the lack of a prior framework or model to test customers’ perceptions of dining-out behavior during this unprecedented time, this study used a mixed-methods approach, conducting two focus group discussions to generate potential restaurant attributes, followed by a US-based survey using an online panel. Using structural equation modeling, this study tested eight developed propositions.FindingsThe findings of this study indicated that the three key factors (i.e. restaurant dining environment, communication and hygiene and contactless features) made customers feel comfortable dining in the restaurant during the pandemic. Out of these three factors, only the restaurant dining environment and communication and hygiene were essential predictors for customers’ perceived trust toward the restaurant, leading to their willingness to pay more. This study used two moderators, customers’ perceived risk and support for restaurants to examine how they affected customers’ perceived trust and willingness to pay, respectively.Practical implicationsThis study provides both theoretical and practical implications to the current body of knowledge in customers’ dining-out behavior and the development of operational strategies for restaurants to accommodate customers’ changing dining-out behavior due to the COVID-19 pandemic. To develop a holistic conceptual framework, this study incorporates two COVID-19-focused measurement items, perceived risk and support of the restaurant, to identify their moderating roles in the relationships among the five proposed measurement items. This study provides restaurant operators with insights into the altered dining-out behavior of their customers due to the COVID-19 pandemic and prepares them for the post pandemic environment.Originality/valueDuring the unprecedented pandemic situation, few customers are willing to dine in restaurants. As local and national governments lifted the mandated COVID-19 protocols, restaurants opened their business slowly to cater to customers in compliance with the centers for disease control’s health and safety regulations. It is of utmost importance for restaurant operators to accommodate their customers’ needs when they dine in the middle of the COVID-19 pandemic. There is a paucity of research that has examined customers’ comfort level when dining in restaurants and customers’ preferred dining environment during the pandemic.

How do restaurants respond to the COVID-19 pandemic? Lessons from Colombian restauranteurs and their survival strategies

This study attempted to identify the overall impact of COVID-19 on the restaurant industry in Colombia through the interviews with ten restaurant owners or chefs (e.g., fine-dining, family-dining, casual dining, and quick-service restaurants). Adopting the three phase post-pandemic planning framework, this study examined how the restaurants responded, recovered, and renewed their businesses and what survival strategies they have been implementing to respond to the new normal after the COVID-19 outbreaks. Findings of the study indicated the restaurants in Colombia focused on and developed four operational survival strategies: operational transformation and challenges, government support, social responsibility, and precautionary measurement practices, focusing on their core value and assets such as employees and menus. [ FROM AUTHOR] Copyright of Journal of Foodservice Business Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)