UNDERSTANDING THE INFLUENCE OF TECHNOSTRESS ON WORKERS’ JOB SATISFACTION IN GIG-ECONOMY: AN EXPLORATORY INVESTIGATION
2019
- 1,077Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage1,077
- Abstract Views649
- Downloads428
Conference Paper Description
Gig-economy is a recent concept that has been attracting growing attention. Online labour markets (OLMs) are a prominent part of gig-economy and require completion of tasks digitally through platforms such as MTurk and Upwork. The World Bank estimated the total market size of OLMs to be $4.8 billion in 2016 which is expected to increase up to $25 billion in 2020. Despite the rapid growth of OLMs, the implications of workers’ wellbeing in such markets are not well understood and highly debated. A report commissioned by EU-OSHA has identified psycho-social risks associated with the work in OLMs. The highly competitive and fast-paced nature of OLMs necessitates workers to multitask and perform intense technology-enabled work which may lead to technostress. This paper investigates workers’ job satisfaction in OLMs using technostress and job characteristic theories with the aim of providing an in-depth understanding of the experiences and perceptions of workers. Our research model has both theoretical and practical implications which will help to diagnose potential problems and improve the wellbeing of workers by formulating strategies for OLMs and workers. The paper presents the results of a pilot study in a popular OLM using structural equation modelling.
Bibliographic Details
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