Exploring the Influencing Factors of Carbon Footprint Tracking Application Usage Intention: A Combined UTAUT and NAM Approach

Abstract

The rising concentration of greenhouse gases has created various environmental challenges. Carbon footprint tracking applications are designed to encourage individual-level energy conservation and emission reduction. These applications have significant potential for widespread adoption. This study combines the Unified Theory of Acceptance and Use of Technology with the Norm Activation Model to form a comprehensive research framework. Partial Least Squares Structural Equation Modeling is used to analyze key factors. These factors include performance expectancy, effort expectancy, social influence, awareness of consequences, ascription of responsibility, and personal norms. The aim is to explore their impact on the intention to use carbon footprint tracking applications. The results show that performance expectancy, effort expectancy, social influence, and personal norms significantly affect usage intention. Performance expectancy is the strongest predictor. Social influence and personal norms emphasize the role of external social factors and moral obligations in shaping user behavior. Additionally, ascription of responsibility has a stronger mediating effect on usage intention than awareness of consequences. This study offers insights into how factors from the Unified Theory of Acceptance and Use of Technology and the Norm Activation Model influence user intentions. It also provides practical recommendations for businesses and policymakers to promote the use of carbon footprint tracking applications.

Keywords

• Carbon footprint software
• unified theory of acceptance and use of technology
• norm activation model
• usage intention