Exploring factors influencing entry into the gig economy: A study of Chinese workers

This study explores the factors influencing the choices of Chinese workers to enter the gig economy using data from the China Labor-force Dynamics Survey (CLDS) for the years 2014, 2016, and 2018. Drawing on self-determination theory, Labor Market Segmentation Theory and Precarity Framework, this paper conducts analysis with variables mainly from individual and work perspectives. Three complementary machine learning models are adopted for feature importance. Both SHAP values and logistic regression are employed to examine the direction and magnitude of influence. The findings reveal that wage is the most important factor influencing the decision to engage in the gig economy, increasing the likelihood of participation. Work flexibility also plays a positive and crucial role. Moreover, females show a lower inclination toward gig economy work than males. Though social security has a negative effect, its relative importance is minor. The adoption of a narrower definition of gig workers further confirms the robustness of the findings. This research contributes to literature by comprehensively identifying importance and direction of the factors influencing entry into the gig economy in China and highlighting the intrinsic motivation and external structural pressures in decision-making. The study concludes with evidence-based policy recommendations, and implications for future research.