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The purpose of this study is to examine the factors that affect managers’ ethical decision-making in export-oriented readymade garments in Bangladesh.

This is an empirical study based on the quantitative approach undertaking a cross-sectional survey method where a convenience sampling technique was applied. The analysis was done using partial least square structural equation model applying Smart-PLS version 3.0.

This study confirmed that all the components of cognitive appraisal processes, including perceived severity, perceived vulnerability, response efficacy and self-efficacy, have a significant influence on attitude. Attitude, in turn, mediates the relationship between these variables and the behavioural intention of ethical practice, except for perceived vulnerability. Besides, moral obligation is found to mediate the relationship between attitude, self-efficacy and the behavioural intention of ethical decision-making. The study also found that ethical climate and subjective norms have a direct influence on behavioural intention. Furthermore, behavioural intention, ethical climate and self-efficacy are positively related to actual decision-making behaviour. However, this study did not find any direct effect of subjective norms on moral obligation.

The organization should include an emphasis on building ethical culture and setting an ethical code of conduct within the organization to sustain ethical practice within employees. However, the practitioner should work on enhancing self-efficacy to curb unethical practices by individuals.

This research contributes to the management of garments manufacturers by a practical and theoretical understanding of what influences the ethical behavioural decision-making process. Valuable guidelines are provided on the ethical decision-making process in the garments manufacturing companies for future researchers.

The current advancements in technologies and the internet industry provide users with many innovative digital devices for entertainment, communication and trade. However, simultaneous development and the rising sophistication of cybercrimes bring new challenges. Micro businesses use technology like how people use it at home, but face higher cyber risks during riskier transactions, with human error playing a significant role. Moreover, information security researchers have often studied individuals’ adherence to compliance behaviour in response to cyber threats. The study aims to examine the protection motivation theory (PMT)-based model to understand individuals’ tendency to adopt secure behaviours.

The study focuses on Australian micro businesses since they are more susceptible to cyberattacks due to the least security measures in place. Out of 877 questionnaires distributed online to Australian micro business owners through survey panel provider “Dynata,” 502 (N = 502) complete responses were included. Structural equational modelling was used to analyse the relationships among the variables.

The results indicate that all constructs of the protection motivation, except threat susceptibility, successfully predict the user protective behaviours. Also, increased cybersecurity costs negatively impact users’ safe cyber practices.

The study has critical implications for understanding micro business owners’ cyber security behaviours. The study contributes to the current knowledge of cyber security in micro businesses through the lens of PMT.

This study aims to explore the role of frontline service employees’ (FSEs) awareness that their job can be substituted by smart technology, artificial intelligence, robotics and algorithms (STARA) in their job autonomy and proactive service performance and when these relationships can be buffered. Drawing on the cognitive appraisal theory of stress, the study examined the mediating relationship between FSEs’ STARA awareness, job autonomy and proactive service performance and the moderating effects of self-efficacy and resilience on this relationship.

The authors administered two-wave online surveys to 301 South Korean FSEs working in various service sectors (e.g. retailing, food/beverage, hospitality/tourism and banking). The Time 1 survey measured respondents’ STARA awareness, self-efficacy, resilience and job autonomy, and the Time 2 survey assessed their proactive service performance.

FSEs’ STARA awareness negatively affected their subsequent proactive service performance through decreased job autonomy. The negative association between STARA awareness and job autonomy was weaker when FSEs’ self-efficacy was high than when it was low. While the authors observed no significant moderation of resilience, the author found a marginally significant three-way interaction between STARA awareness, self-efficacy and resilience. Specifically, STARA awareness was negatively related to job autonomy only when both self-efficacy and resilience were low. When either self-efficacy or resilience was high, the association between STARA awareness and job autonomy became nonsignificant, suggesting the buffering roles of the two personal resources.

Given that the measurement of variables relied on self-reported data, rater biases might have affected the findings of the study. Moreover, the simultaneous measurement of STARA awareness, self-efficacy, resilience and job autonomy could preclude causal inferences between these variables. The authors encourage future studies to use a more rigorous methodology to reduce rater biases and establish stronger causality between the variables.

Service firms can decrease FSEs’ STARA awareness through training in the knowledge and skills necessary to work with these technologies. To promote FSEs’ proactive service performance in this context, service firms need to involve them in decisions related to STARA adoption and allow them to craft their jobs. Service managers should provide FSEs with social support and exercise empowering and supportive leadership to help them view STARA as a challenge rather than a threat.

Distinct from prior research on STARA awareness and employee outcomes, the study identified proactive service performance as a key outcome in the STARA context. By presenting self-efficacy and resilience as crucial personal resources that buffer FSEs from the deleterious impact of STARA awareness, the study provides practitioners with insights that can help FSEs maintain their job autonomy and proactive service performance in times of digitalization and automation.

The COVID-19 pandemic has generated unprecedented public fear, impeding both individuals’ social life and the travel industry as a whole. China was one of the first major countries to experience the COVID-19 outbreaks and recovery from the pandemic. The demand for outings is increasing in the post-COVID-19 world, leading to the recovery of the ride-sharing industry. Integrating protection motivation theory and the theory of reasoned action, this study aims to investigate ride-sharing customers’ self-protection motivation to provide anti-pandemic measures and promote the resilience of ride-sharing industry.

This study followed a two-phase mixed-methods design. In the first phase, the authors executed a qualitative study with 30 interviews. In the second phase, the authors used the results of the interviews to inform the design of a survey, with which 272 responses were collected. Both studies were conducted in China.

The present results indicate that customers’ perceived vulnerability of COVID-19 and perceived COVID protection efficacy (self-efficacy and response efficacy) are positively correlated with their attitude toward self-protection, thus leading to their self-protection motivation during the rides. Moreover, subjective norms and customers’ distrust appear to also impact their self-protection motivation during the ride-sharing service.

The present research provides one of the first in-depth studies, to the best of the authors’ knowledge, on customers’ protection motivation in ride-sharing services in the new normal. The empirical evidence provides important insights for ride-sharing service providers and managers in the post-pandemic world and promote the resilience of ride-sharing industry.

The global impact of the COVID-19 pandemic has been well documented, but there is still limited insight into the complex interaction of factors that determine its longer-term effects on the most vulnerable sectors of society. The current study therefore develops an integrated conceptual framework to investigate how consumers' fear of mortality and the perceived risk of severe illness associated with COVID-19 act as critical determinants of consumer food choices and perceived well-being.

An online survey was utilized to collect data from a sample of 407 adult, low-income consumers across Trinidad and Tobago. The PROCESS macro was used to empirically test the hypothesized relationships in a moderated mediation model.

The results confirm that an increase in the perceived risk of severe illness has a significant negative effect on the consumption of healthy foods and perceived well-being. Moreover, consumers' choice of healthy foods mediates the negative relationship between consumers' perceived risk of severe COVID-19 illness and subjective well-being. Finally, the negative relationship between perceived risk of illness and healthy food choice weakens as an individual's fear of pandemic-related mortality increases.

This research integrates multiple related theoretical constructs to provide a more nuanced understanding of the lingering impact that risk perceptions and fear have on consumer food choices and associated well-being among a vulnerable Caribbean population. The changes identified have important implications for researchers interested in consumer food preferences as well as policymakers seeking to promote a healthy lifestyle among individuals coping with psychologically stressful circumstances.

The present study integrates inclusive leadership and protection motivation theory to propose a new model predicting employees' intention to work from home during an emergency situation such as the COVID-19 pandemic.

A questionnaire was developed to collect data from 939 Taiwanese and Vietnamese office employees using a non-probability convenience sampling method. A total of 887 valid questionnaires were used for further analysis. The data were analysed following a two-stage structural equation modelling using SPSS 22 and AMOS 20 software. The validity and reliability of the instrument were tested and ensured.

The results revealed that inclusive leadership and factors related to protection motivation theory– including perceived severity and perceived vulnerability – have positive direct and indirect effects on employees' work-from-home intentions through the mediating role of employees' work-from-home-related attitudes. Protection motivation theory factors were found to have a stronger effect on employees' work-from-home intention than inclusive leadership. Differences in the relationship between perceived vulnerability, perceived severity and employees' intentions towards working from home were also discovered among participants from the two studied countries.

The integration of inclusive leadership and protection motivation theory brings into light what will drive employees' intention to work from home during an emergency situation. The present study has several theoretical and practical implications for scholars, governments, managers and policymakers that can help them improve management policies for working from home in the future.

Based on integrating inclusive leadership and protection motivation theory to explore employees' intention to work from home during an emergency situation, the present study demonstrated that inclusive leadership and protection motivation theory should be considered for studies on working from home in a pandemic setting.

Travel decreased dramatically during the initial wave of the COVID-19 pandemic, only to return rapidly to prepandemic levels once the degree of fear toward the virus began to diminish among potential travelers. This USA-based 16-month repeated-measure cross-sectional survey study aims to explore the degree to which fear of COVID affected people’s decisions to stay home rather than to travel during the pandemic.

The research used survey data. An extensive data set, composed of over 9,500 respondents, collected through Mechanical Turk over a 16-month time period, was used to compare respondent fear of the pandemic both with their attitudes toward future travel and with Smith Travel Research data reflecting actual pandemic travel patterns.

The results demonstrate how fear of COVID was closely and negatively linked to both travel intentions and travel behavior.

Data were collected from US respondents only.

The findings significantly extend earlier studies and provide guidance for those studying travel consumer behavior regarding trends that should be monitored in the case of a future pandemic or other fear-inducing crisis. For hospitality and tourism managers and marketers, understanding fear as a leading indicator of future travel behavior can result in more timely promotional efforts and staffing and training decisions.

Measuring and understanding consumer fear levels as this relates to travel decisions can help in the future to adjust the message that is sent to the public, perhaps reducing the amount of travel taken during periods when this is unwise and or unsafe.

This paper extends previous work that had been based upon cross-sectional reviews, providing a broader and more valuable study of an important and timely consumer behavior travel topic.

This paper aims to explore the factors affecting cybersecurity implementation in organizations in various countries and develop a cybersecurity framework to improve cybersecurity practices within organizations for cybersecurity risk management through a systematic literature review (SLR) approach.

This SLR adhered to RepOrting Standards for Systematics Evidence Syntheses (ROSES) publication standards and used various research approaches. The study’s article selection process involved using Scopus, one of the most important scientific databases, to review articles published between 2014 and 2023.

This review identified the four main themes: individual factors, organizational factors, technological factors and governmental role. In addition, nine subthemes that relate to these primary topics were established.

This research sheds light on the multifaceted nature of cybersecurity by exploring factors influencing implementation and developing an improvement framework, offering valuable insights for researchers to advance theoretical developments, assisting industry practitioners in tailoring cybersecurity strategies to their needs and providing policymakers with a basis for creating more effective cybersecurity regulations and standards.

Many environmental problems are due to the unfavorable environmental intentions and cultural–behavioral weaknesses in the relationship between man and nature. This study aims to adopt an environmental psychological perspective to green intention (GI) and green behavior (GB) of agricultural students; to this end, protection motivation theory (PMT) was used as the core of the theoretical base.

This research method was based on descriptive–correlational and causal–relational analyses. The statistical population included agricultural students of Iranian universities with green university standards (N = 5,582). Out of the total population, 384 students were selected as the study sample. The research instrument was a questionnaire whose validity was confirmed using a panel of experts and the average variance extracted. Also, its reliability was verified by Cronbach’s alpha coefficients (0.61 ≤ α ≤ 0.92), principal component analysis and composite reliability index.

The results of structural equation modeling showed that the obtained model is able to explain 36.3% and 5.56% of GB and GI variance changes, respectively. In addition, the results revealed that GI has the greatest effect on GB (β = 0.362).

It is worth to mention that according to the results, most of the independent variables, besides the direct effects they have on students’ GB, also indirectly affect this variable. This effect was performed through the key variable – GI. In other words, it can be concluded that the GI variable successfully mediates the effects of variables such as response efficacy (RE), self-efficacy (SE) and environmental norms (EN). Therefore, it is suggested that in the behavioral changes interventions in GB of agricultural studies, it should be considered that the presence or absence of GI can affect the actual behavior of individuals. In other words, it is recommended that to accelerate actual behavioral changes, behavioral interventionists should first focus on encouraging people’s GI.

It can be said that the conclusion of this research can provide a basis for the successful encouragement of students to GB. First, GI, as a key element, can mediate the impacts of variables such as RE, SE and EN on students’ GB. Second, PS only directly affects students’ GB. Third, RE has no significant impact on GB, but its effect on GI is significant. Fourth, RC affects students’ GI directly, without mediation. Fifth, SE and EN constructs affect students both directly and indirectly GB of students through GI. Knowing the location of the effect of these variables on each other and the role they have in explaining GI and GB of agricultural students presented some suggestions that can prepare the ground for further development of GB. Hence, managers, students, agricultural educators and other users can use these results to accelerate GB changes.

The conclusion of this research might provide a basis for the successful encouragement of students to GB. In interventions to change GB, it would be essential to pay enough attention to the fact that the presence or absence of GI might affect the actual behavior. It is suggested that behavioral interventionists focus on encouraging people’s GI so as to be able to accelerate the actual behavioral changes.

Algorithms are widely used to manage various activities in the gig economy. Online car-hailing platforms, such as Uber and Lyft, are exemplary embodiments of such algorithmic management, where drivers are managed by algorithms for task allocation, work monitoring and performance evaluation. Despite employing substantially, the platforms face the challenge of maintaining and fostering drivers' work engagement. Thus, this study aims to examine how the algorithmic management of online car-hailing platforms affects drivers' work engagement.

Drawing on the transactional theory of stress, the authors examined the effects of algorithmic monitoring and fairness on online car-hailing drivers' work engagement and revealed the mediation effects of challenge-hindrance appraisals. Based on survey data collected from 364 drivers, the authors' hypotheses were examined using partial least squares structural equation modeling (PLS-SEM). The authors also applied path comparison analyses to further compare the effects of algorithmic monitoring and fairness on the two types of appraisals.

This study finds that online car-hailing drivers' challenge-hindrance appraisals mediate the relationship between algorithmic management characteristics and work engagement. Algorithmic monitoring positively affects both challenge and hindrance appraisals in online car-hailing drivers. However, algorithmic fairness promotes challenge appraisal and reduces hindrance appraisal. Consequently, challenge and hindrance appraisals lead to higher and lower work engagement, respectively. Further, the additional path comparison analysis showed that the hindering effect of algorithmic monitoring exceeds its challenging effect, and the challenge-promoting effect of algorithmic fairness is greater than the algorithm's hindrance-reducing effect.

This paper reveals the underlying mechanisms concerning how algorithmic monitoring and fairness affect online car-hailing drivers' work engagement and fills the gap in the research on algorithmic management in the context of online car-hailing platforms. The authors' findings also provide practical guidance for online car-hailing platforms on how to improve the platforms' algorithmic management systems.