Research #

While prior research has primarily focused on the direct value of information technology (IT) and IT adoption by individuals and firms, this study explores the indirect value of IT in the form of public infrastructure technology. By exploiting a spatial discontinuity in water monitoring stations, we discover that firms located immediately upstream of water monitoring stations exhibit significantly lower levels of corruption than firms located immediately downstream. These findings are particularly noteworthy given that water monitoring stations have the potential to generate significant indirect value as they are not explicitly designed to mitigate corruption. Further analyses reveal that public infrastructure technology alone does not hold the key to mitigating corporate corruption. Instead, it is the synergistic interplay between public infrastructure technology and organizational change that drives the outcome. These findings contribute to a deeper understanding of the broader IT value landscape, emphasizing the indirect value of technological advancements in public infrastructure that were not originally intended for such benefit. Additionally, our findings highlight the benefits of leveraging existing infrastructure technology to address emerging societal needs.

The literature often explains female labor force participation through factors such as schooling, wage gaps, and fertility. In this study, we identify how technology-induced time savings from household chores increase female labor force participation in South Korea. Using a leads-and-lags difference-in-differences model, we find that the entry of online food delivery platform significantly increased the female employment rate in the three years following the platform’s entry, and the results still hold after excluding employment in the food and beverage sector. Our further analyses show that such digital platforms offered a pathway for women to break free from traditional household roles, thus granting them more time and the opportunity to decide whether to join the labor market or stay at home. We examine the positive externalities generated by the online food delivery platform and find that this new technology-induced female employment accounted for 0.27% of South Korea’s GDP, or 17 times the platform’s direct revenue.

Firms have been proactively holding data science competitions via online contest platforms to look for innovative solutions from the crowd. When firms are designing such competitions, a key question is: What should be a better contest design to motivate contestants to exert more effort? We model two commonly observed contest structures (one-stage and two-stage) and two widely adopted prize structures (high-spread and low-spread). We employ economic experiments to examine how contest design affects contestants’ effort level. The results reject the base model with rationality assumption. We find that contestants exert significantly more effort in both the first stage and the second stage of the two-stage contest. Moreover, it is better to assign most prizes to the winner in the two-stage contest while it does not matter in one-stage. To explain the empirical regularities, we develop a behavioral economics model that captures contestants’ psychological aversion to falling behind and continuous exertion of effort. Our findings demonstrate that it is important for contest organizers to account for the non-pecuniary factors that can influence contestants’ behavior in designing a competition.