Navigating the green wave: Understanding behavioral antecedents of sustainable cryptocurrency investment

Abstract

This study fills a void in the literature on the intention to invest in sustainable cryptocurrency. It examines the behavioral antecedents of individuals' decision making in this expanding financial industry. A mixed-methods approach that combines partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) is used to gain an understanding of the factors that lead to acceptance of sustainable cryptocurrencies and the obstacles to investing in them. This study is valuable for investors, policymakers, and managers in the digital currency business, providing practical insights and strategic implications. The study's findings underscore the relevance of regulatory frameworks and government assistance in fostering the adoption of sustainable cryptocurrencies. The study emphasizes the importance of customer trust and sustainability in influencing the adoption of sustainable cryptocurrencies. It advances the theory of sustainable finance, technology adoption, and behavioral economics. The study's limitations and recommendations for future research offer a path to further the understanding of this developing topic. • This study uses PLS-SEM and fsQCA to analyze factors influencing sustainable cryptocurrency investments comprehensively. • PU, PEU, and PT significantly predict attitudes and behavioral intentions toward investing in sustainable cryptocurrencies. • The study shows ECS and SOS shape positive attitudes, while ENVS needs more awareness to become a key driver for investors. • The findings guide policymakers to improve regulations, highlight sustainable crypto benefits, and address concerns for wider adoption.