Understanding Intention to Adopt Smart Thermostats: The Role of Individual Predictors and Social Beliefs Across Five EU Countries

2025-04-12

Proceedings of the 14th International Conference on Smart Cities and Green ICT Systems

AI Summary

This study investigates the drivers of smart thermostat adoption among residents in five European countries—including Austria—to unlock their energy-saving potential in buildings. Drawing on 2,250 cross-national survey responses, we extend the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating multidimensional social belief constructs—descriptive social norms, collective efficacy, social identity, and trust—and test the model using structural equation modeling (SEM). Our key contribution lies in the first systematic incorporation of these social belief variables into the UTAUT framework, revealing significant cross-national heterogeneity in their effects. Results indicate that performance expectancy, price value, and effort expectancy are the strongest predictors of adoption; social beliefs exert significant yet comparatively weaker influences, supporting a cognition-dominated adoption pathway. The findings provide theoretical grounding and policy-relevant insights for differentiated smart thermostat deployment strategies across diverse sociocultural contexts.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Application Domains: Humanities & Computational Social Science
• Knowledge Representation and Reasoning: Reasoning with Beliefs

Application Category

• Responsible Web: Social and technical mechanisms of refusal for web technologies and applications
• Security and Privacy: Privacy-enhancing technologies
• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems

Abstract

Heating of buildings represents a significant share of the energy consumption in Europe. Smart thermostats that capitalize on the data-driven analysis of heating patterns in order to optimize heat supply are a very promising part of building energy management technology. However, factors driving their acceptance by building inhabitants are poorly understood although being a prerequisite for fully tapping on their potential. In order to understand the driving forces of technology adoption in this use case, a large survey (N = 2250) was conducted in five EU countries (Austria, Belgium, Estonia, Germany, Greece). For the data analysis structural equation modelling based on the Unified Theory of Acceptance and Use of Technology (UTAUT) was employed, which was extended by adding social beliefs, including descriptive social norms, collective efficacy, social identity and trust. As a result, performance expectancy, price value, and effort expectancy proved to be the most important predictors overall, with variations across countries. In sum, the adoption of smart thermostats appears more strongly associated with individual beliefs about their functioning, potentially reducing their adoption. At the end of the paper, implications for policy making and marketing of smart heating technologies are discussed.

Problem

• Identify factors influencing smart thermostat adoption in EU
• Assess role of social beliefs in technology acceptance
• Evaluate country-specific variations in adoption predictors

Innovation

• Used structural equation modeling for data analysis
• Extended UTAUT with social beliefs metrics
• Identified key predictors for smart thermostat adoption