What you give is what you get: Willingness to pay for green energy. (August 2021)

• Record Type: Journal Article
• Authors: Hojnik, Jana; Ruzzier, Mitja; Fabri, Stephanie; Klopčič, Alenka Lena
• Is Part Of: Renewable energy. Volume 174(2021)
• Page Start: 733
• Page End: 746
• Publication Date: 2021-08
• Subjects: Green energy -- Willingness to pay -- Consumers' knowledge -- Perceived risk -- Consumers' commitment -- Consumers' environmental responsibility; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2021.04.037
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: Renewable energy has become an important objective especially for fighting climate change and improving energy security. This study has employed two methods for data analysis (i.e., regression analysis and fuzzy-set Qualitative Comparative Analysis) in order to seize the complexity of the phenomenon and explore antecedents of willingness to pay for green energy. The results derived from fuzzy-set Qualitative Comparative Analysis indicate that knowledge and/or social norms and moral obligations are present in all configurations when we have high willingness to pay for green energy. Furthermore, we conducted linear regression analysis, which revealed that acceptance of green energy, social norms and moral obligations and knowledge about green energy exert a significant positive impact on willingness to pay for green energy and, thus, work as drivers of willingness to pay for green energy. We have also examined the differences among socio-demographic characteristics of consumers (e.g., gender, education, income, and age) related to their environmental concern, consumers' commitment, acceptance of green energy, perceived risk, social norms and moral obligations, knowledge about green energy, and consumers' willingness to pay for green energy. Use of different methods allowed us to better understand the issue pertaining to antecedents of willingness to pay for green energy. Highlights: This study employed two methods for data analysis (regression analysis and fsQCA). Knowledge is always linked to high willingness to pay for green energy (GE). Social norms, moral obligations are always linked to high willingness to pay for GE. Regression analysis identified drivers of willingness to pay for green energy. Differences among socio-demographic characteristics of consumers were explored.