Purpose
Unlike the effect of management styles on employee attitudes, little is known about the effect of managerial assumptions on workers within the gig economy. The purpose of this paper is to utilize McGregor’s Theory X and Theory Y as a framework to discuss two gig economy platforms and how their differing management assumptions affect worker perceptions of themselves as entrepreneurs.
Design/methodology/approach
The author utilized qualitative interviews and demographic surveys with 41 contract workers from TaskRabbit, a personal assistant platform, and Kitchensurfing, a “rent-a-chef” service, to examine the impact of differing management assumptions on independent contractor perceptions of themselves as entrepreneurs.
Findings
The Theory X management assumptions and correlated behaviors directly contradict the entrepreneurial ethos marketed by the platforms, resulting in a psychological contract violation for workers and negative responses to the platform. In comparison, Theory Y managerial assumptions and correlated behaviors can be utilized to encourage worker innovation, creativity and sense of self as an entrepreneur.
Practical implications
As the gig economy continues to grow, algorithms are likely to take on increased importance as a management tool. Although some have suggested that such algorithms may reduce the impact of a capricious manager, the fact remains that algorithms are created by management. If the gig economy intends to encourage entrepreneurship, additional attention must be paid to how differing management assumptions, and their resulting behaviors and algorithms, affect worker attitudes and experience.
Originality/value
This study represents one of the initial academic investigations into how the Theory X and Theory Y management assumptions and correlated perspectives may be applied to independent contractors within the gig economy. Additionally, this study is among the first to examine how gig worker attitudes toward platform firms, and views of themselves as entrepreneurs, are affected by algorithm-implemented management policies.
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