Research

[ssrn]

As operations increasingly rely upon flexible labor models – such as gig, part-time, and remote work – it has become commonplace for individuals to work multiple jobs. Across two descriptive studies, relying on a combination of transaction-level data from 90,232 customers of a nationwide retail bank and primary survey data, we study whether people with multiple jobs live their off-the-clock lives materially differently from equivalently compensated people who rely on a single job. We find that people who rely on multiple jobs spend 18.1 percentage points (p.p.) less of their labor income overall, which is driven by a 16.5 p.p. decrease in the share of income spent on necessities and a 2.0 p.p. decrease in the share of income spent on indulgences. They spend meaningfully more on education and transportation, but notably less in all other key spending areas, including categories traditionally associated with enhanced physical wellbeing, such as healthcare and food, and experiential categories often associated with mental wellbeing, such as travel and entertainment. These patterns converge with responses from the General Social Survey, in which equivalently compensated individuals who rely on multiple jobs report lower financial satisfaction and lower family satisfaction than their single-income counterparts. Together, the findings describe systematic variation in off-the-clock outcomes across different working structures and surface considerations for job design that may promote greater sustainability for employees.

HBS Working Knowledge: The True Costs of Gig Work

[ssrn]

Using a combination of field and experimental data, we examine how absolute and relative schedule quality jointly shape employee turnover and firm performance in the restaurant industry. Leveraging detailed shift-level data from a large restaurant group, we develop a data-driven measure of schedule quality and show that turnover is predicted by both absolute schedule quality and relative comparisons to peers. Employees are significantly more likely to leave when their schedules are worse than those of coworkers, even after accounting for the absolute quality of their own schedules. Among employees with below-average schedules, reducing the gap between their schedules and those of their coworkers explains approximately 50% of the difference in exit probabilities. A controlled lab experiment provides causal evidence for this relationship, demonstrating that relative disadvantage reduces perceived fairness, lowers schedule ratings, and reduces intentions to stay. At the restaurant level, we find that scheduling fairness and average schedule quality operate as distinct levers: fairer scheduling is associated with lower turnover but has no detectable effect on operational performance, while higher average schedule quality is associated with significantly higher sales and modestly-higher tips. This pattern is consistent with strategic schedule allocation in the restaurants we study – better schedules go to employees who generate higher sales per guest, who are in turn less likely to leave. These findings highlight the importance of both absolute and relative schedule quality as distinct dimensions of frontline work design, with different implications for retention and performance.