Wednesday, November 3, 2021 - 4:00pm to 4:30pm
Event Calendar Category
LIDS & Stats Tea
Amir Tohidi Kalorazi
LIDS & IDSS
Building and Room Number
Our goal is to measure the effect of habit formation on consumers’ behavior, in particular, the widespread experience of shopping in a store. In-store shopping is a repetitive behavior happening in the same context, so it has a great potential of becoming habitual. Although in the short run habits are formed to help people achieve their goals, in the long run, they could lead to non-optimal behavior. Therefore, it is important to understand the extent to which habit formation influences consumers’ behavior.
We hypothesize that the measured consumer inertia in the literature is a combination of brand loyalty and shopping habits, and we try to disentangle these two phenomena. To this end, we use store closures as the exogenous shock that disrupts part of the households' shopping behavior. The main idea is that in a new environment, consumers are more engaged in thoughtful/deliberative decision-making processes, driving them to explore some other options that are normally ignored in a familiar store. The use of this exogenous shock is crucial to have a valid causal identification strategy and avoid various endogenous factors that could lead people to explore new stores.
Having a better understanding of the psychological mechanisms behind our decision-making can benefit both individuals and firms. On the consumer side, it can help us design more effective interventions to improve people's healthcare, e.g., by nudging them to choose healthier options. Also, it can have managerial implications such as optimal pricing strategies or allocations of goods inside stores.
Amir Tohidi is a Ph.D. student at MIT Institute for Data, Systems, and Society (IDSS) and LIDS. He is also a member of the Interdisciplinary Doctoral Program in Statistics. Before joining MIT, Amir received his Bachelor’s degree in a double major in Electrical Engineering and Physics at the Sharif University of Technology. Amir’s research interests lie at the intersection of causal inference and behavioral economics, where we can use data and statistical modeling to study people’s economic decision making.