Understanding configurations of continuance commitment for platform workers using fuzzy-set QCA
ISSN: 0025-1747
Article publication date: 5 December 2023
Issue publication date: 22 January 2024
Abstract
Purpose
How to improve continuance commitment for platform workers is still unclear to platforms' managers and academic scholars. This study develops a configurational framework based on the push-pull theory and proposes that continuance commitment for platform workers does not depend on a single condition but on interactions between push and pull factors.
Design/methodology/approach
The data from the sample of 431 full-time and 184 part-time platform workers in China were analyzed using fuzzy-set qualitative comparative analysis (FsQCA).
Findings
The results found that combining family motivation with the two kinds of pull factors (worker's reputation and algorithmic transparency) can achieve high continuance commitment for full-time platform workers; combining job alternatives with the two kinds of pull factors (worker's reputation and job autonomy) can promote high continuance commitment for part-time platform workers. Particularly, workers' reputations were found to be a core condition reinforcing continuance commitment for both part-time and full-time platform workers.
Practical implications
The findings suggest that platforms should avoid the “one size fits all” strategy. Emphasizing the importance of family and improving worker's reputation and algorithmic transparency are smart retention strategies for full-time platform workers, whereas for part-time platform workers it is equally important to reinforce continuance commitment by enhancing workers' reputations and doing their best to maintain and enhance their job autonomy.
Originality/value
This study expands the analytical context of commitment research and provides new insights for understanding the complex causality between antecedent conditions and continuance commitment for platform workers.
Keywords
Acknowledgements
This study was supported by the National Natural Science Foundation of China (No: 71832007) and the National Natural Science Foundation of China (No.71572157).
Citation
Deng, T., Tang, C. and Lai, Y. (2024), "Understanding configurations of continuance commitment for platform workers using fuzzy-set QCA", Management Decision, Vol. 62 No. 1, pp. 352-369. https://doi.org/10.1108/MD-06-2022-0830
Publisher
:Emerald Publishing Limited
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