Relationship between Self-Transcendence Value and Ethical Purchase Intention: The Role of Moral Obligation and Perceived Behavioural Control
Wei Li, Norris Syed Abdullah
International Journal of Research and Innovation in Social Science September 18, 2025 DOI: 10.47772/ijriss.2025.908000505 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Quantitative survey study Longitudinal Peer reviewed |
|---|---|
| Sample size | 649 |
| Population | General adults in China |
| Key findings | Self-transcendence values positively influence ethical purchase intention among Chinese adults, with moral obligation mediating this relationship and perceived behavioural control significantly enhancing it. The authors argue these findings help explain the gap between ethical awareness and ethical purchasing and offer practical guidance for companies. |
Abstract
The expansion of the global economy has improved living standards but has also brought significant ecological and social challenges, highlighting a notable gap between consumer ethical concerns and actual purchasing behaviours. Although awareness of ethical issues has increased, traditional factors such as price and quality still largely dominate consumer decisions, limiting the translation of ethical awareness into ethical purchase intention (EPI). Given this background, this study aims to investigate how self-transcendence values influence EPI among general adults in China, specifically examining moral obligation as a mediator and perceived behavioural control (PBC) as a moderator. A quantitative approach using survey data from 649 Chinese adults confirmed that self-transcendence values positively influence EPI through increased moral obligation, while PBC significantly enhances this relationship. These findings contribute to understanding the mechanisms underlying ethical consumption and provide practical benefits for companies seeking to align products with ethical values and improve accessibility to ethical choices. Future research should further examine causal relationships using longitudinal data and employ more representative samples to enhance generalizability.