Impact of Social Learning on Consumer Subsidies and Supplier Capacity for Green Technology Adoption

Due to the innovative nature of green-technology products (e.g., electric vehicles and solar panels), customers are usually a priori uncertain about their purchasing benefits and typically consult user experiences via online product reviews and word-of-mouth communications. Despite the critical role of this social learning behavior for customers’ adoption decisions, its implications for consumer subsidies aimed at facilitating adoption are not well-understood. In this paper, we investigate how social learning affects the government’s optimal consumer subsidies considering a supplier’s capacity decision and examine the welfare impact overall. We develop a game-theoretic model in which the government first decides consumer subsidies for purchasing a green-technology product, then the supplier sets capacity and sells the product in two periods. The product quality is a priori unknown and can be learned from period-1 consumers’ online reviews. We find that, social learning may lead to lower social welfare by disincentivizing capacity supply and diluting demand with weak-preference customers. Moreover, due to social learning, the government may follow a declining or rising subsidy path, which critically hinges on both market and product characteristics. When the government can adjust subsidies after observing online reviews, social learning leads to greater social welfare at given capacity level, whereas the equilibrium social welfare may still be lower due to capacity oversupply. Finally, we calibrate our model using real-world data and show that accounting for social learning in subsidy design can improve social welfare by as much as 5.7%