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The present study seeks to examine the impact of ethical leadership on employees’ voice behavior and internal whistleblowing in organizations. Specifically, the study investigates the mediating role of moral emotions in the link between ethical leadership and employees’ reporting behaviors such as voice behavior and internal whistleblowing.

This research utilized a sample of 200 employees from various private companies in Pakistan, gathering data via questionnaires to validate the hypotheses. We employed Structural Equation Modeling (SEM) to evaluate the model and conducted a mediation analysis using 5,000 bootstrap samples.

This research found that ethical leadership positively impacts employees' moral emotions, encouraging them to voice concerns and report misdeeds. Additionally, the study affirms a direct and positive connection between ethical leadership and employees' reporting behaviors, including voice behavior and internal whistleblowing.

The findings of the study emphasized the development of ethical leadership in organizations by highlighting the critical role of ethical leadership in enhancing moral emotions, voice behavior, and whistleblowing in organizations. It highlights the necessity of promoting moral behavior to enhance organizational effectiveness and the need for ethical leaders to foster an open environment in organizations that encourages whistle bellowing and reporting of unethical practices in organizations.

The current paper extends knowledge of ethical leadership based on the social cognitive theory of morality by considering that moral emotions serve as a strong motivational cognition between ethical leadership and reporting behaviors. Particularly, by examining the mediating role of moral emotion, this study provides a deeper understanding of the underlying mechanism through which ethical leadership influences reporting behaviors of employees at workplace.

In social media, crisis information susceptible of generating different emotions could be spread at exponential pace via multilevel super-spreaders. This study aims to interpret the multi-level emotion propagation in natural disaster events by analyzing information diffusion capacity and emotional guiding ability of super-spreaders in different levels of hierarchy.

We collected 47,042 original microblogs and 120,697 forwarding data on Weibo about the “7.20 Henan Rainstorm” event for empirical analysis. Emotion analysis and emotion network analysis were used to screen emotional information and identify super-spreaders. The number of followers is considered as the basis for classifying super-spreaders into five levels.

Official media and ordinary users can become the super-spreaders with different advantages, creating a new emotion propagation environment. The number of followers becomes a valid basis for classifying the hierarchy levels of super-spreaders. The higher the level of users, the easier they are to become super-spreaders. And there is a strong correlation between the hierarchy level of super-spreaders and their role in emotion propagation.

This study has important significance for understanding the mode of social emotion propagation and making decisions in maintaining social harmony.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0192.

Emotions are widely acknowledged decision-making drivers, taking the front seat when managers lack objective information. Existing evidence indicates that negative emotions often lead to the decision to retrench. Contrary to these insights, our research aims to show that negative emotions can sometimes push top managers to withdraw from retrenching marketing activities. By drawing on the affect-as-information approach, this study aims to examine the direct and conditional effects of top managers’ negative emotions on small and medium-sized enteprises (SMEs’) intention to retrench marketing activities during the recent economic crisis caused by the COVID-19 pandemic.

This study uses a descriptive research design and surveys a sample of 155 chief executive officers from business-to-business (B2B) SMEs in Croatia. The authors empirically test the conceptual framework with hierarchical regression.

Based on the sample of 155 top managers of SMEs operating in B2B industries, negative emotions positively drive marketing retrenchment. However, additional insights reveal that this relationship is conditioned by crisis severity and SMEs' strategic orientations (exploration and exploitation). The relationship between negative emotions and marketing retrenchment weakens for SMEs severely hampered by the crisis and for SMEs following the exploitative orientation. In contrast, this relationship becomes stronger for SMEs whose business customers have been severely hampered and for SMEs following exploratory orientation.

This research advances the body of knowledge by demonstrating that, depending on the severity of the crisis and the strategic orientation of the SME, top managers may interpret negative emotions quite differently, which eventually has lasting consequences on marketing retrenchment during crises. Therefore, by focusing on emotional microfoundations and unique crisis- and firm-level contingencies, this study goes beyond existing theoretical discussions that contrast marketing retrenchment vs investment and offers a different understanding of why and when SMEs retrench their marketing activities during crises.

Previous studies have proven the significant influence of nostalgia on tourists' perceptions, intentions, and behaviors. While much of the research has focused on nostalgia as a motivator for destination choice in the pre-trip stage, fewer studies have explored the effects of nostalgia experienced during visits on other behavioral intentions beyond revisit intention. This paper aims to fill this gap by examining the impact of nostalgic emotion experienced at tourist destinations on behavioral intentions, specifically pro-sustainable behavioral and word-of-mouth (WOM) intentions through destination image.

This study developed a conceptual model grounded in existing literature and empirical research on nostalgia and consumer behavior. Data were gathered from international tourists via surveys conducted in Hue City, a UNESCO World Heritage Site. The hypotheses were tested using structural equation modeling (SEM) with Amos 23.0.

The research results reveal that nostalgic emotion positively impacts destination image and WOM intention. Destination image correlates positively with both pro-sustainable behavioral intention and WOM intention. Destination image serves as a mediator in the relationship between nostalgic emotion and WOM intention. Theoretical and practical implications are also discussed in the current work.

The findings of this research provide guidance for nostalgic elements to be integrated into tourism experiences and marketing campaigns to enhance tourists' emotional connections, thereby improving the destination’s overall appeal. Additionally, while nostalgia does not directly foster pro-sustainable behavioral intentions, a positive destination image can influence these behaviors, suggesting that sustainable tourism strategies should also focus on strengthening the destination’s image.

This paper contributes to both theoretical advancements and practical applications in the field of tourism psychology and marketing by shifting the focus from nostalgia as a motivator for destination choice in the pre-trip stage to exploring the effects of nostalgic emotions experienced during visits on behavioral intentions beyond revisit intentions.

This study aims to provide supplements to the research on digital human avatar (DHA) and suggestions for brands to use DHA appropriately to build brand fans effect.

On the basis of integrating Avatar theory and Stimulus-organism-response theory, this study obtains data from 733 Chinese respondents aged 18–25 and uses regression analysis and bootstrap analysis to verify the relationships among the variables: DHA characteristics (form realism, behavioral realism and brand alignment) as the independent variables, brand fans effect as the dependent variable, consumer positive emotion as the mediating variable and product type (experience vs search) as the moderating variable.

The results show that DHA characteristics positively influence brand fans effect and consumer positive emotion, consumer positive emotion positively influences brand fans effect and consumer positive emotion plays a mediating role. Meanwhile, for experience products, the impact of DHA’s form realism and behavioral realism on consumer positive emotion is higher than that of brand alignment; for search products, the impact of DHA’s brand alignment on consumer positive emotion is higher than that of form realism and behavioral realism.

This study enriches and expands the empirical research perspectives and conclusions in the DHA field, improves its research framework and provides suggestions for brands to appropriately use DHA to build brand fans effect.

To propound a broadened perspective on emotional labor management by exploring mitigatory approaches that could be pre-emptively deployed prior to actual episodic experiences of emotional dissonance and their associated negative consequences (e.g. burnout). At present, the management of emotional labor appears to skew toward reactive measures, such as deploying employee assistance programs (EAPs) to assist overwhelmed employees in coping better with their emotional demands, reducing job-related emotional demands or a combination of both.

Intricate processes of emotion emergence and established literature on emotion regulation are considered. By conceptualizing emotion emergence as a process entailing situation, attention, appraisal and response, current efforts can be seen as primarily acting upon the late stages of this process. General emotion regulation strategies that act upon more upstream processes are then considered and applied to the specific context of emotional labor.

Pre-emptive steps could be taken from the early stages of job selection as well as personnel selection and assessment through systematic and concerted efforts in identifying job-related emotional demands (e.g. specific display rules, frequency and intensity). Formal job descriptions could then reflect these demands to better facilitate self-selection processes. Additionally, considering these identified parameters as personnel selection and assessment criteria could further enhance person-job fit in terms of emotional congruency. For current hires, pre-emptive steps could also be taken to subliminally modulate their emotional emergence trajectory toward more job-congruent emotions. Collectively, these steps may facilitate the pre-emptive reduction of emotionally dissonant work episodes and bear substantive potential to be deployed synergistically with current, more reactive measures.

This paper offers a broadened perspective on emotional labor management. Through considering intricate processes of emotion emergence and established literature on emotion regulation, a pre-emptive perspective toward managing work emotions and emotional labor is propounded. It is believed that the synergistic incorporation of these pre-emptive management approaches with current strategies (e.g. reducing emotional demands, EAPs, etc.) would holistically allow for greater amelioration of this debilitating issue. Finally, it is hoped that this paper could serve as a primer for future research and discourses to be conducted, such that our arsenal available for combating emotional labor could be substantively expanded to holistically target all stages of the emotion emergence process.

This study aims to provide a nuanced understanding of the relationship between task-technology fit and employee innovative behavior, as well as the role of creative self-expectations.

Hierarchical regression analysis was used to test the proposed multilevel model on a sample of 407 employees working in Chinese companies.

Task-technology fit stimulates employee innovative behavior through the regulation of creative self-expectations and positive emotions. When creative self-expectations is low, the promoting effect of task-technology fit on innovative behavior is enhanced. However, when creative self-expectations is too high, this effect is reversed due to employees’ preference for challenging and complex work.

In the process of enterprise digital transformation, managers should not only focus on the alignment between employees' skills and individual task expectations, but also pay attention to employees' emotions and individual trait differences, to enhance the likelihood of innovative behavior occurrence and achieve successful enterprise digital transformation.

This study enriches the research on task-technology fit and provides recommendations for organizations to achieve digital transformation.

The purpose of this study is twofold: first, to identify the categories of artificial intelligence (AI) chatbot service failures in frontline, and second, to examine the effect of the intensity of AI emotion exhibited on the effectiveness of the chatbots’ autonomous service recovery process.

We adopt a mixed-methods research approach, starting with a qualitative research, the purpose of which is to identify specific categories of AI chatbot service failures. In the second stage, we conduct experiments to investigate the impact of AI chatbot service failures on consumers’ psychological perceptions, with a focus on the moderating influence of chatbot’s emotional expression. This sequential approach enabled us to incorporate both qualitative and quantitative aspects for a comprehensive research perspective.

The results suggest that, from the analysis of interview data, AI chatbot service failures mainly include four categories: failure to understand, failure to personalize, lack of competence, and lack of assurance. The results also reveal that AI chatbot service failures positively affect dehumanization and increase customers’ perceptions of service failure severity. However, AI chatbots can autonomously remedy service failures through moderate AI emotion. An interesting golden zone of AI’s emotional expression in chatbot service failures was discovered, indicating that extremely weak or strong intensity of AI’s emotional expression can be counterproductive.

This study contributes to the burgeoning AI literature by identifying four types of AI service failure, developing dehumanization theory in the context of smart services, and demonstrating the nonlinear effects of AI emotion. The findings also offer valuable insights for organizations that rely on AI chatbots in terms of designing chatbots that effectively address and remediate service failures.

This study examines the impact of physical environmental factors on customer retention in fast-food restaurants/cafeterias. Furthermore, this study examines the mediating effect of customers’ positive emotions on this relationship.

In this study, the stimulus-organism-response model developed by Mehrabian and Russell (1974) is applied within the context of the fast-food restaurant/cafeteria industry. Data were collected from a sample of 250 consumers who have patronized establishments within this industry. The assessment model entailed employing the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, which involved a two-stage procedure: measurement model and structural model evaluation.

The study’s results underscore the key role of customer positive emotions in influencing customer retention. Notably, physical environmental factors, encompassing elements like table setting, layout, and service staff, emerge as significant determinants in shaping these positive emotions. Furthermore, the findings indicate that these physical environmental factors exert a direct influence on customer retention, with customer positive emotions acting as mediator role in the relationship between these factors and retention.

This study is the first to use physical environment, customer emotions and customer retention variables together in the fast food restaurant/cafeteria industry.

This research explored the intersection of cognitive processes, emotions and their impacts on digital game-based vocabulary learning (DGVL) among university students. Recognizing the scant research in this area, especially with integrating innovative technologies, this study aims to understand the influence of these elements using advanced monitoring tools.

This inquiry was carried out as an observational study involving 44 university students segmented into three English language proficiency levels: high, intermediate and low based on their English course scores. The methodological tools included a portable eye tracker to observe visual behaviors and deep learning technology to identify and analyze the participants’ emotional responses and engagement with the DGVL during the learning process.

The results showed that distinct fixation sequences and variations in visual attention during DGVL were correlated with different levels of competency, suggesting a direct correlation between visual engagement and language competence. In addition, emotional transitions, predominantly from engagement (“flow”) to challenge (“frustration”), were common among participants, reflecting the emotional dynamics of learning. Furthermore, all participants consistently focused on the English vocabulary definitions, indicative of their targeted approach to understanding and test preparation. These findings highlighted the intricate dynamics between emotions and cognitive processes in learning environments.

Contribution of this study shows the interplay of cognitive engagement and emotional experiences in the context of DGVL. It underscored the complex nature of these factors and their collective influence on learners’ visual and emotional engagement, offering valuable implications for educational strategies and technological applications in language learning.