The effects of social influence on low-cost and high-cost household energy-efficient product adoption: A case study in wuhan

Purpose – Housing energy consumption is a significant contributor to climate change. Encouraging the adoption of energy-efficient products can be an effective way to reduce energy consumption. The impacts of social influences, such as peer effects and social norms, on energy efficiency adoptions were identified; however, these social influences are not quantified and compared with each other or with other influences. This study aims to investigate the choice of energy-efficient product adoption with different costs and how different social influences affect the choice through different processes and paths. Design/methodology/approach – Two stated choice experiments were employed in Wuhan, China, to examine the impact of social influences on energy-efficient product adoption in low-cost and high-cost scenarios. Appliance packages (including fridges and washing machines) and heating and cooling systems were used for the two cost scenarios, respectively. The social influences are evaluated in three aspects: positive versus negative information, physical versus online social networks and peer effects versus social norms. Findings – The study revealed how various factors, including social influences, impact energy-efficient product choices. Research results show that: (1) social influences have greater and wider impacts in the low-cost scenario than in the high-cost scenario; (2) negative information decreases the adoption of low-cost energy-efficient products, while positive information boosts high-cost energy-efficient product adoption and (3) people value the information provided by those they know personally and are more influenced by physical social networks. Originality/value – This study contributes to a better understanding of social influence in energy-efficient product adoption with different costs. This study provides a comprehensive framework to investigate social influences comparing the impact of different processes, paths and types of information. The findings can also provide practical implications for policymakers to accelerate the energy transition in the built environment.