Habit Formation and Political Persuasion: A Behavioral and Statistical Approach

Abstract

This thesis explores the complex dynamics of human behavior across diverse contexts, integrating perspectives from behavioral science and statistical analysis. The central focus of this study revolves around the analysis of repetitive behavior in various scenarios including shopping, social media use, and news sharing.

The initial study investigates the influence of habits on the in-store shopping experience. By leveraging store closures as a disruptive event, we examine how these closures prompt individuals to alter their purchasing patterns. We propose that such disruptions encourage people to engage in more deliberate decision-making processes, leading them to explore alternatives that they might have previously overlooked due to established habits. Employing a difference-in-differences framework, we estimate the causal impact of habits on brand loyalty. Our findings reveal a significant role of habits, with households exhibiting stronger habits experiencing a temporary disruption in their shopping routines following store closures. Over time, these households appear to develop new habits in different stores, resulting in lasting changes in preferred brands. This suggests that the formation of shopping habits can lead to suboptimal consumer behavior. These insights have practical implications for businesses, including pricing strategies, advertising approaches, and product placement within stores.

The second study introduces an innovative methodology for quantifying habitual behavior in the context of social media usage. Interactions with social media platforms often yield psychological rewards, fostering the development of habitual behaviors driven by cue-response associations. By leveraging entropy as an implicit measure of behavioral regularity, this study aims to uncover the intricate relationship between habit formation and digital routines. Through empirical analyses, we establish the validity of the entropy metric, demonstrating its effectiveness in capturing distinct behavioral patterns beyond mere frequency. Our results highlight the nuanced connection between entropy and future app engagement, indicating a positive association for lower entropy values and a significant decline for excessively irregular patterns. These findings contribute to theoretical understanding of habitual behavior and offer practical insights for managing digital habits. Ultimately, this work advances our comprehension of how habits manifest in the digital realm and provides a robust tool for predicting long-term user behavior.

The third study delves into the intricate interplay between individuals' beliefs and their ability to anticipate the persuasive impact of climate change news articles. The central aim is to determine whether climate change deniers or believers possess varying capacities to predict the persuasive consequences of articles emphasizing climate change severity. Through a series of surveys, we gather predictions about the impact of such articles on climate change deniers. Surprisingly, findings reveal discordant predictions: deniers anticipate a backfire effect among peers, climate believers foresee negligible effects. We rigorously test these predictions with a randomized survey experiment involving deniers, uncovering an unexpected positive opinion shift towards climate change after article exposure. Notably, this effect does not translate into discernible changes in stated or revealed support for climate change actions. In the context of the pressing climate challenge, our study offers insights to inform targeted communication and interventions that foster consensus and meaningful action.