连续性
定性比较分析
声誉
自治
前因(行为心理学)
背景(考古学)
透明度(行为)
组织承诺
集合(抽象数据类型)
业务
知识管理
营销
计算机科学
心理学
社会心理学
计算机安全
社会学
社会科学
古生物学
机器学习
政治学
法学
生物
程序设计语言
作者
Deng Ting,Chunyong Tang,Yanzhao Lai
出处
期刊:Management Decision
[Emerald (MCB UP)]
日期:2023-12-05
卷期号:62 (1): 352-369
标识
DOI:10.1108/md-06-2022-0830
摘要
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.
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