One of the most striking trends in individuals’ careers over the last decade has been the dramatic increase in the proportion of the labor force working beyond their employers’ physical boundaries because of the digital revolution in the gig economy. This trend has drawn much attention in the changing nature of work, workplace and careers. However, little empirical research has explored how and why individuals behave in the interface between online platforms and traditional organizations. In my dissertation, I explore these questions by studying medical professionals’ digital careers in the Chinese healthcare crowdsourcing industry, also known as “mobile doctors.”
First, by analyzing approximately 240-hour observations and 43 interviews with Chinese physicians, I identify a key issue in this new career – time conflict between crowdsourcing and traditional work. The findings show that physicians respond to time conflict in a variety of ways, including time theft, an essential yet under-researched construct in the crowdsourcing literature which reflects the tension between traditional work and crowdsourcing. Second, by analyzing archival data of 4,034 doctors’ 3.1 million time records on a Chinese healthcare platform across half a year, I show that time theft for crowdsourcing is related to the traditional work context, including hospitals’ boundary control and offline crowd worker social groups. Finally, I further explore, via interview data, why such seemingly costly and deviant time theft is adopted by mobile doctors. The findings reveal that medical professionals assume the extra burden of working for crowdsourcing with the hope of answering unfulfilled occupational callings in traditional work and adding meaning to their work. Overall, these findings contribute to a better understanding of the shifting nature of work and careers in the digital economy by documenting and explaining mobile doctors’ participation in this new world of work.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/30074 |
| Date | 30 June 2018 |
| Creators | Wang, Lan |
| Contributors | Hall, Douglas T., Anteby, Michel |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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