Addressing Technostress & Well -Being in Gig Economy: A Path to Economic Sustainability

Abstract

Introduction: The growth of gig work has transformed the contemporary labor market, provided flexibility and independence but also subjected workers to high stressors like job insecurity, economic uncertainty, and irregular workloads. Gig workers work in various sectors, such as ridesharing, food delivery, freelancing, and on-demand services, and usually encounter distinctive occupational hazards. Gig Workers' Well-being (GWW) Model, based on the Job Demands-Resources (JD-R) model and Psychological Capital (PsyCap) theory, presents a systematic approach to understanding job demands and resources and their effect on stress resilience, mental well-being, and job performance among gig workers. This research explores how resilience interventions can reduce stress and improve work engagement and productivity among gig workers.

Objectives: The main aim of this research is to create and test a multi-dimensional stress resilience framework that explains the dynamic interaction of multiple influences on wellbeing among gig workers. More specifically, the research intends to explore how job demands can intensify burnout while job resources promote work engagement, and to investigate the dual nature of gig-related factors that can benefit or detract from job performance. Furthermore, the study aims to investigate the contribution of technostress in exacerbating burnout, evaluate the effectiveness of boundary management in enhancing work engagement, and identify the degree to which resilience is responsible for enhanced job performance. Through this holistic examination, the study aims to offer detailed insights into the stress and coping processes in the gig economy, ultimately guiding strategies to enhance the wellbeing and performance of gig workers.

Methods: A qualitative research design was used to obtain rich insights into the well-being of gig workers. A stratified random sampling strategy provided representative diversity across work categories, demographics, and geographic regions. Data were collected through structured online questionnaires distributed through LinkedIn, social media groups, and gig work platforms. The questionnaire contained validated scales assessing stress levels, financial security, work-life balance, resilience, and well-being. 400 questionnaires were distributed and 338 returned (84.5% response rate). After excluding incomplete or invalid responses, the final sample of 323 gig workers was analyzed. Statistical analysis using IBM SPSS 25.0, including correlation and regression analysis, was conducted to examine the relationships between job demands, burnout, resilience, and work engagement.

Results: Correlation analysis indicated significant relationships between the most important variables. Job demands were positively correlated with job resources (r =.900, p <.01), indicating that as stressors, resource needs also increased. Burnout had significant correlations with job demands (r =.489, p <.01) and technostress (r =.804, p <.01), supporting the negative effect of workload unpredictability. Regression analysis showed that job demands strongly predicted burnout (β = 0.489, R² = 0.239, p <.000), whereas job resources positively affected work engagement (β = 0.415, R² = 0.172, p <.000). Gig-specific factors also significantly contributed to the formation of job performance (β = 0.368, R² = 0.135, p <.000). In addition, technostress strongly raised levels of burnout (β = 0.476, R² = 0.227, p <.000), whereas resilience helped job performance to the extent of β = 0.499, R² = 0.289, p <.000, highlighting its significance when managing stress.

Conclusions: The results highlight the intricate interaction between job demands, resilience, and performance in the gig economy. Digital stressors and high job demands are sources of burnout, which is detrimental to well-being. Nevertheless, job resources such as autonomy, skill development, and social support improve work engagement and reduce stress. The GWW Model highlights the importance of resilience in mediating stress outcomes and proposes that interventions like boundary management, adaptive coping, and financial security programs can enhance mental health and performance. Policy measures should aim to augment gig workers' access to social security, training, and mental health care. By building resilience, gig platforms can establish a more sustainable and supportive work culture, guaranteeing long-term well-being and productivity.