Analysis of Factors Influencing Knowledge-Based Gig Work Behavior Based on Text Mining and the TISM Model

In the context of the overlapping scenarios of the sharing economy, the new economy, and emerging industries, exploring the factors influencing knowledge-based gig work behavior is of great significance for improving the efficiency of knowledge-based gig work, as well as for helping platforms and enterprises optimize their incentive strategies and governance measures. This article employs text mining methods to identify 14 key factors that influence knowledge-based gig work behavior. Based on these findings, a TISM (Total Interpretive Structural Modeling) model analysis is conducted to perform an in-depth analysis of these influencing factors from a systematic and holistic perspective, establishing the interaction mechanisms among the factors. The study finds that feedback from task providers and the diversified design of task types are fundamental factors influencing knowledge-based gig work behavior. Finally, the article offers targeted recommendations for improving knowledge-based gig work behavior at both the platform and enterprise levels.