Antecedents and consequences of technostress in online labour markets
Umair, Azka
Umair, Azka
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Publication Date
2024-06-28
Type
doctoral thesis
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Abstract
Technology plays a pivotal role in the digitalisation of work practices, and that led to the emergence of new forms of employment, including digital gig work facilitated by online platforms that match employers and workers through online labour markets. Despite the apparent simplicity of joining these platforms, sustaining and thriving in such work environments presents challenges, often impacting worker well-being. Given that platform work is deeply embedded in technology use workers are more prone to technology-induced stress also known as technostress. This thesis investigates the impact of technostress on the well-being of platform workers, highlighting the complexities inherent in this novel work. Platform work is unique in that algorithms control various aspects of work organisation, feedback and evaluation systems, and the probability of participation. Technostress can be exacerbated by factors such as competition, algorithmic control, work intensification, unpredictable schedules, multitasking, surveillance, low wages, and precarious conditions. This thesis is based on three core articles. The first article discusses the concept of technostress in detail, explores how this phenomenon has evolved with the changing nature of work and identifies the gap in understanding it within the context of platforms. The second article investigates platform-specific technology and job characteristics that can result in technostress creating an impact on worker well being. The third, article examines the technostress concept through the lens of temporal characteristics and its impact on work outcomes. To investigate the research questions, the thesis develops research models and employs a quantitative survey design, conducted specifically on Amazon Mechanical Turk (MTurk), a widely used online labour market. The surveys are designed following the protocols of conducting behavioural research on MTurk and structural equational modelling partial least square (SEM-PLS) is used to empirically analyse the results of the research models. In doing so, the research adopts both aggregated and disaggregated approaches to examine technostress. The findings demonstrate that job and temporal characteristics play significant roles in shaping the technostress experience within online labour markets. The research contributes to technostress research by going beyond the notion of technology characteristics solely as environmental antecedents and identifying technostress related outcomes in the unique context of platforms. The results show that technology complexity, feedback and time pressure shape the technostress process in these platforms. The research also contributes by exploring the concept of technostress from a positive perspective, aligning with the call made by many recent studies. The research findings contribute to our understanding of technostress and establish a foundation for future research in the platform context. Furthermore, the findings help in the development of strategies aimed at promoting well-being and mitigating technostress in this novel type of work.
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University of Galway
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Attribution-NonCommercial-NoDerivatives 4.0 International