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Technostress reduces employees' work performance and increases their turnover intentions, such that technostress harms organizations' success. This paper investigates how the digital mindset of employees, reflecting their cognitive filter while using digital technologies, influences reactions to techno-stressors.

In this quantitative study, the authors conducted a survey among 151 employees who regularly use digital technologies and encounter various techno-stressors in their daily work. To build this research model and evaluate the influence of employees’ digital mindset on technostress, the authors followed arguments from the transactional model of stress. The authors evaluated our research model using the covariance-based structural equation model.

The study findings reveal that employees’ digital mindset influences technostress. Employees with high levels of digital mindset react with less adverse effects on perceived techno-stressors. Further, the authors find that employees with high levels of digital mindset perform well and are satisfied with their job. The authors contribute to technostress research by revealing that digital mindset buffers the adverse effects of techno-stressors. The authors also contribute to research on digital mindset by showing that it influences psychological and behavioral reactions to techno-stressors.

This study develops and empirically tests an integrated model of technostress to explain how digital mindset mitigates technostress. The study findings outline relevant research avenues for studies investigating employees’ characteristics and technostress.

The use of information and communication technologies has become widespread in the field of health as well as in all fields. While the intensive use of these technologies increases the productivity of the employees, on the other hand, it may cause negative effects on the employee such as stress, anxiety, anger, burnout, and addiction. In scientific studies, the use of technology is commonly related with saving time, labor, financial resources, effective, efficient, and quality service; however, there are limited studies focusing on the technostress factors in the health field brought by technological transfer and digital transition. These technostress factors are techno-overload, techno-invasion, techno-confusion, techno-insecurity, and techno-uncertainty. In this study, it is emphasized that technostress causes important mental problems such as productivity and burnout, especially for female health employees. This chapter aims to discuss the role of technostress and its factor, theoretically, in the healthcare field in perspective of digital transition.

Based on the conservation of resource theory, this study aims to develop and test the relationship between workplace technostress and affective organizational commitment. It assumes that the direct relationship between workplace technostress and affective organizational commitment is moderated by perceived organizational support.

For this, this study used a survey method and multiple regression analyses with multisource data from 257 Korean employees.

The results suggest the following. First, workplace technostress was negatively associated with affective organizational commitment fully. Second, there was a stronger negative relationship between workplace technostress and affective organizational commitment for employees with low as opposed to those with high levels of leader–member exchange.

This study provides practical implications that are directly related to the performance management of employees under technostress.

To the best of the authors’ knowledge, this study is the first one to examine the moderating effect of leader–member exchange on the relationship between technostress and affective organizational commitment.

This research study aims to inquire into the technostress phenomenon at an organizational level from machine learning (ML) and artificial intelligence (AI) deployment. The authors investigated the role of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management amongst managers.

The authors applied an exploratory qualitative method and conducted in-depth interviews based on a semi-structured interview questionnaire. Data were collected from 26 subject matter experts. The data transcripts were analyzed using thematic content analysis.

The study results indicated that role ambiguity, job insecurity and the technology environment contributed to technostress because of ML and AI technologies deployment. Complexity, uncertainty, reliability and usefulness were primary technology environment-related stress. The novel integration of ML and AI automation-augmentation interdependence, along with socio-technical systems, could be effectively used for technostress management at the organizational level.

This research study contributed to theoretical discourse regarding the technostress in organizations because of increased ML and AI technologies deployment. This study identified the main techno stressors and contributed critical and novel insights regarding the theorization of coping mechanisms for technostress management in organizations from ML and AI deployment.

The phenomenon of technostress because of ML and AI technologies could have restricting effects on organizational performance. Executives could follow the simultaneous deployment of ML and AI technologies-based automation-augmentation strategy along with socio-technical measures to cope with technostress. Managers could support the technical up-skilling of employees, the realization of ML and AI value, the implementation of technology-driven change management and strategic planning of ML and AI technologies deployment.

This research study was among the first few studies providing critical insights regarding the technostress at the organizational level because of ML and AI deployment. This research study integrated the novel theoretical paradigm of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management.

Online labour markets (OLMs) have recently become a widespread phenomenon of digital work. While the implications of OLMs on worker well-being are hotly debated, little empirical research examines the impact of such work on individuals. The highly competitive and fast-paced nature of OLMs compels workers to multitask and to perform intense technology-enabled work, which can potentially enhance technostress. This paper examines the antecedents and well-being consequences of technostress arising from work in OLMs.

The authors draw from person–environment fit theory and job characteristics theory and test a research model of the antecedents and consequences of worker technostress in OLMs. Data were gathered from 366 workers in a popular OLM through a large-scale online survey. Structural equation modelling was used to evaluate the research model.

The findings extend existing research by validating the relationships between specific OLM characteristics and strain. Contrary to previous literature, the results indicate a link between technology complexity and work overload in OLMs. Furthermore, in OLMs, feedback is positively associated with work overload and job insecurity, while strain directly influences workers' negative affective well-being and discontinuous intention.

This study contributes to technostress literature by developing and testing a research model relevant to a new form of work conducted through OLMs. The authors expand the current research on technostress by integrating job characteristics as new antecedents to technostress and demonstrating its impact on different types of subjective well-being and discontinuous intention. In addition, while examining the impact of technostressors on outcomes, the authors consider their impact at the individual level (disaggregated approach) to capture the subtlety involved in understanding technostressors' unique relationships with outcomes.

The COVID-19 pandemic and technological advancements have enabled employees to telework. Referring to this emerging phenomenon, the authors aim to examine how employees' levels of trust in management mediated by psychological well-being impact their performance as they telework. Deploying the theoretical lens of person-environment misfit, the authors also explore the role of technostress in the trust-wellbeing-performance relationship.

The data was collected from 511 full-time service sector employees across Indian organizations through a structured survey questionnaire. The proposed moderation-mediation model for this study was tested using structural equation modeling and bootstrapping method.

Structural equation modeling results indicate that trust in management significantly impacts employee performance while teleworking. While psychological well-being was observed as a significant mediator, technostress played the moderator role in the trust-performance relationship. The moderated-mediation effect of psychological well-being in the trust-performance relationship was stronger when technostress was low and weaker when technostress was high.

The authors extend the person-environment misfit theory in the context of telework, highlighting the role of technostress that may impact the trust-wellbeing- performance relationship in such work settings.

The study informs leaders and managers on balancing delicate aspects such as employee trust and well-being that significantly impact performance as they telework. The authors also highlight the critical role of managers in respecting employees' personal and professional boundaries to alleviate technostress.

The authors make a novel theoretical contribution to the emerging literature on teleworking by examining the trust-psychological wellbeing-performance link and the role of technostress in this relationship.

The primary objective of this study is to explore consumers' non-adoption intentions towards meta-commerce (or metaverse retailing). Utilizing the Innovation Resistance Theory (IRT) as the theoretical foundation, this study investigates the impact of diverse barriers on non-adoption intentions within the meta-commerce context.

A total of 356 responses were gathered to test the proposed hypotheses. Structural Equation Modelling (SEM) with SmartPLS 4 software was used to examine these hypotheses.

The findings of this study show that perceived cyber risk, perceived regulatory uncertainty, perceived switching cost and perceived technical uncertainty are significantly linked to non-adoption intention towards meta-commerce. Furthermore, the study suggests that the moderating influence of technostress on these connections is more pronounced for consumers with high technostress compared to those with low technostress.

This study makes a significant contribution to the current body of literature by providing valuable insights into the fundamental barriers that consumers encounter when contemplating the adoption of meta-commerce. This contribution is particularly noteworthy as it fills a gap in the existing literature, as no prior study has comprehensively examined the primary obstacles that shape consumer intentions towards meta-commerce adoption. This novel perspective offers scholars, businesses and policymakers a foundation for developing strategies to address these barriers effectively.

While the phenomenon of technostress has received significant attention from researchers in recent years, empirical findings concerning the consequences of specific forms of techno-stressors have remained scattered and contradictory. The authors aim to integrate the conclusions of previous studies to understand the effects of specific techno-stressors on strain and job performance.

This study employs meta-analytic techniques to calibrate the findings of 67 studies investigating more than 63,100 employees.

In general, not all techno-stressors have adverse effects. In particular, techno-uncertainty does not impact job performance. In addition, relative weight analyses reveal the relative importance of techno-complexity and techno-insecurity as predictors of both strain and job performance. Finally, this study finds that the effects of specific techno-stressors on job performance vary depending on research participants' gender, educational attainment and employment status.

First, this study provides a more nuanced view of the effects of specific techno-stressors. Second, this research clarifies the relative importance of specific techno-stressors as predictors of strain and job performance. Finally, this study reveals the moderating effects of demographic variables on the relationships between specific techno-stressors and job performance.

Prior research has extensively examined how bringing technology from work into the non-work life domain creates conflict, yet the reverse pathway has rarely been studied. The purpose of this study is to bridge this gap and examine how the non-work use of smartphones in the workplace affects work–life conflict.

Drawing from three literature streams: technostress, work–life conflict and role boundary theory, the authors theorise on how limiting employees' ability to integrate the personal life domain into work, by means of technology use policy, contributes to stress and work–life conflict. To test this model, the authors employ a natural experiment in a company that changed its policy from fully restricting to open smartphone access for non-work purposes in the workplace. The insights gained from the experiment were explored further through qualitative interviews.

Work–life conflict declines when a ban on using smartphones for non-work purposes in the workplace is revoked. This study's results show that the relationship between smartphone use in the workplace and work–life conflict is mediated by sensed stress. Additionally, a post-hoc analysis reveals that work performance was unchanged when the smartphone ban was revoked.

First, this study advances the authors' understanding of how smartphone use policies in the workplace spill over to affect non-work life. Second, this work contributes to the technostress literature by revealing how, in specific situations, engagement with ICT can reduce distress and strain.

This study aimed to examine the impact of COVID-19 concerns on employees’ well-being, considering workplace stress, aggression, and emotional outcomes, such as emotional engagement, emotional exhaustion, and negative emotional reactions. This study also considers the moderating role of technostress between workplace stress and aggression, which has been overlooked in previous studies.

Data were collected from frontline hotel employees in Turkey. Online data were collected through Amazon Mechanical Turk services. A total of 250 questionnaires were distributed. Nevertheless, only 204 questionnaires with valid responses were usable for analysis through partial least square-structural equation modeling (PLS-SEM).

The analytical findings showed that COVID-19 concerns (financial, social gaze, and technological) cause workplace stress, resulting in aggression. Aggression subsequently affects the employees’ emotional outcomes, impacting their emotional well-being. Furthermore, the results showed that technostress insignificantly moderates workplace stress and aggression.

This study provides valuable practical implications to the hotels’ top management, practitioners, and policymakers to provide preventive measures to employees, such as wearing masks and maintaining distance. Hotel practitioners should limit employees’ direct contact with customers and reduce factors that result in overall financial losses and create financial stress for employees.

The current study examined the relationships between the study’s variables in Turkey’s hotel industry context by employing the conservation of resources (COR) theory. The study investigated stress and aggression phenomena, their impact on employees’ emotional responses, and ultimately their influence on the employees’ well-being.