Assessing the Challenges Faced by Women Gig Workers in the Malappuram District of Kerala, India: Logistic Regression Approach

Abstract

The rapid expansion of the gig economy has opened new income opportunities for women in Kerala; however, it has also introduced a distinct set of challenges that remain insufficiently examined. This study empirically assesses the factors associated with the difficulties experienced by women gig workers in Malappuram district, Kerala, with specific reference to economic, social, and occupational constraints. A logistic regression model was applied to a dataset of 285 observations to estimate the likelihood that women who engaged in gig work experienced significant challenges. The dependent variable represents their earnings, coded as 1 for workers earning ₹10,000 or more and 0 for those earning less than ₹10,000. The empirical findings indicate that irregular earnings, absence of social security, household responsibilities, platform-based discrimination, and limited digital skills significantly increase the probability of experiencing adverse work conditions. The analysis highlights the multidimensional vulnerabilities embedded in platform-mediated employment. The paper underscores the need for targeted policy interventions and gender-responsive measures to improve income stability, enhance digital competencies, ensure safer work environments, and strengthen social protection mechanisms.