Socio-Economic Determinants of Work Motivation among Gig Workers in Mumbai’s Food and Beverage Sector: A Logistic Regression Analysis

The gig economy has become an important part of India’s urban job market, especially in the food and beverage industry, where it offers flexible, task-based work opportunities to a many people. Job security, long-term job benefits, and formal employment structures are factors which motivate the workers. This study looks into the socio-economic factors that motivate 2,000 gig workers in the food and beverage sector across the Mumbai Metropolitan Region. Using binary logistic regression, the research examines how various socio-economic variables like age, education, income of the workers, access to social security benefits, and ownership of household items influence the probability of workers showing high levels of motivation. The findings based on the binary logistic regression analysis reveal that younger workers aged between 18 and 26 years tend to be more motivated, possibly because they have fewer family obligations and are more comfortable with the flexible nature of gig work. Workers earning between ₹20,001 and ₹30,000 per month also show higher motivation levels, suggesting that financial stability keeps people engaged in their jobs. Lower motivation among workers with certificate or vocational training may reflect a gap between their training and the realities of gig work in this sector. Having access to sick leave, though uncommon in informal work, greatly increases motivation. On the other hand, owning physical assets like radios or refrigerators had negligible influence on motivation. This could suggest concerns about economic downturn or uncertainty about the future. The study reveals that motivation extends beyond wages and job availability, linked to overall life circumstances and workplace support systems. This research looks at informal work and suggests giving benefits like sick leave, making sure training matches gig work, and providing financial help to improve working conditions. This study helps us understand important issues and provides a basis for future research and policies to make gig work better and more reliable.