Behavioral Economics of Urban Household Electricity Saving: A Case Study for Mazandaran Province

As technological advancements drive economic development and energy diversification, reliance on electricity has steadily increased. With the residential sector being a major electricity consumer, understanding the behavioral patterns of this group is crucial for managing electricity consumption and mitigating pollution associated with power generation. The main purpose of this study is to evaluate household electricity consumption behavior alongside its determining economic factors based on Theory of Planned Behavior (TPB).In this framework, the relationship between electricity pricing and socio-demographic factors with saving intention is examined to assess the intention of households to conserve electricity and explain their saving behaviors. To test the research hypothesis regarding the significant and dominant effect of behavioral factors on household electricity consumption, structural equations are employed. Research data is gathered through a field study involving 405 subjects (based on Cochran-Orcutt statistics) from residential electricity customers in Mazandaran Province of Iran. According to the results, the path coefficients for attitude, perceived behavioral control, and subjective norm were estimated to be 0.442, 0.323, and 0.128, respectively. Notably, the path coefficient for electricity price was estimated to be 0.121 (lower than subjective norm), indicating a significant but less influential role compared to behavioral factors. Additionally, the path coefficient for electricity saving intention was estimated to be 0.617, again highlighting the substantial importance of behavioral factors in electricity consumption. Based on the findings of this research, it is recommended that policymakers consider behavioral factors alongside pricing measures to control electricity consumption. For instance, in the framework of nudge approach, designing bills based on behavioral patterns and sending monthly and quarterly reports to compare the consumption of residents with their neighbors can have a significant effect on reducing electricity consumption. This approach not only contributes to resource and environmental conservation but also mitigates the adverse income distribution effects stemming from electricity price hikes.