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Background: During the COVID-19 pandemic, the popularity of teleworking has risen. Telework seems poised to remain popular even after the pandemic fades away. As a result, it is important to understand the humanistic effects of telework such as distress, coping responses, and related effects. Literature review: Uncertainties related to telework can lead to distress. When this occurs, teleworkers may employ a variety of coping responses, which vary across several important dimensions. These coping responses vary in the extent to which they affect telework outcomes. Research questions: 1. What strategies do teleworkers use for dealing with telework distress? 2. How are various coping strategies related to humanistic telework outcomes? Methodology: Data from a survey of 504 American teleworkers were used to test a theoretical model. Results: Results suggest that teleworkers cope with telework distress through assistance seeking, technology experimentation, venting, and negative and positive emotions. Coping responses had differential effects on telework exhaustion and satisfaction, with negative and positive emotions and venting affecting exhaustion, and assistance seeking, task experimentation, emotions, and venting affecting satisfaction. Distress had a direct effect on exhaustion, but not on satisfaction. Conclusion: The effects of emotion-focused coping on telework satisfaction and exhaustion are notably stronger than those of problem-focused coping responses. Emotion-focused coping responses that are adaptive have beneficial effects, while those that are maladaptive have detrimental effects. Adaptive problem-focused responses have similar effects. The extent of communication focus does not seem to affect the impact of coping responses on outcomes.

This study investigates antecedents to and outcomes of two stress reactions, telework distress (detrimental stress), and telework eustress (beneficial stress) using a model derived from an integration of the transactional model of stress with the job-demands and resources model. The model includes a person antecedent (resilience), and three environment antecedents (work-family conflict, work overload, and autonomy). These factors should influence experienced distress and eustress, which, in turn, affect telework outcomes (telework satisfaction, exhaustion, perceived performance, and perceived productivity. The model is evaluated using a sample of 329 Chinese teleworkers. This study findings indicate that resilience, work-family conflict, and work overload affect experienced distress, while resilience and autonomy affect experienced eustress. Experienced distress influenced satisfaction, exhaustion, and perceived performance; eustress had effects on all four outcomes. Interestingly, resilience had the largest total effect sizes on telework outcomes.

The COVID-19 pandemic brought about a surge in telework, with many organizations using telework to continue operations. Teleworkers are subject to stress due to the demands of working from home. Despite the common view of stress as being detrimental, stress can also be beneficial. In this paper, we investigate two forms of stress, eustress (beneficial stress), and distress (detrimental stress) using a theoretically-derived model that includes antecedents and outcomes of eustress and distress. We test our model using data from a survey of 525 American teleworkers. Results indicate that job resources (autonomy, managerial support, and technical support), and personal resources (resilience and self-efficacy) affect eustress, while job demands (work overload, social isolation, and resource inadequacies) affect distress. Eustress is positively associated with job and telework satisfaction and negatively associated with telework exhaustion. Distress has the opposite effects. Our findings hold implications for researchers and practitioners.

Organizations face both opportunities and risks with big data analytics vendors, and the risks are now profound, as data has been likened to the oil of the digital era. The growing body of research at the nexus of big data analytics and cloud computing is examined from the economic perspective, based on agency theory (AT). A conceptual framework is developed for analyzing these opportunities and challenges regarding the use of big data analytics and cloud computing in e-business environments. This framework allows organizations to engage in contracts that target competitive parity with their service-oriented decision support system (SODSS) to achieve a competitive advantage related to their core business model. A unique contribution of this paper is its perspective on how to engage a vendor contractually to achieve this competitive advantage. The framework provides insights for a manager in selecting a vendor for cloud-based big data services.