Gig workers’ self-protective behaviour against legal risks: an application of protection motivation theory

Purpose: Given the illegal nature of the gig economy in some cities, this study aims to draw on protection motivation theory to examine the formation of Uber drivers’ self-protective behaviour against legal risks. Design/methodology/approach: In-depth interviews with 10 Uber drivers in Hong Kong were conducted to yield eight maladaptive perceptions, which were then validated using online surveys completed by 232 Uber drivers. These results were then used to examine a mechanism through which threat appraisal, coping appraisal and maladaptive perceptions influence drivers’ unwillingness to work and weekly working hours. Findings: Eight maladaptive perceptions were found to empirically fit a bidimensional conceptualization of cognitive and affective components that significantly reduce workers’ unwillingness to work illegally in the gig economy. The effects on Uber drivers’ unwillingness to work and weekly working hours varied across threat appraisal, coping appraisal and maladaptive perceptions. Practical implications: Platform companies should find the results insightful because they demonstrate ways of negotiating with governments about its legality of the gig economy. The findings can also assist governments with policy development to make sense of illegal gig work or to legalize the gig economy. Originality/value: This study complements the overoptimistic discussion of the gig economy to investigate why people engage in illegal work in this context. Protection motivation theory is applied to a new domain to explore gig workers’ maladaptive perceptions of illegal working.