Abstract
Identifying the factors that influence sustainable purchasing behavior is an important step in understanding the phenomenon and informing industry efforts to promote sustainable consumption. This study aims to develop a situation- and context-specific model that explains sustainable purchasing behavior by drawing on three distinct theoretical frameworks: the theory of planned behavior, alphabet theory, and salience theory. A dataset comprising 396 customers from a Northern European country was analyzed using predictive linear regression and artificial intelligence methods, such as classification and clustering. The results show the interplay between attitudes, intention, and behavior, as well as the indirect effects of knowledge and information-seeking on sustainable purchasing behavior, mediated by attitudes and intentions. Moreover, clustering methods reveal that product pricing is a strong predictor of behavior, but greenness sensitivity is not. By distinguishing between knowledge and information-seeking in a new model of sustainable purchasing, we deepen our understanding of consumer behavior. The findings also offer practical guidance on how price and greenness sensitivities influence decisions, which is helpful for businesses and policymakers to promote sustainable consumption.
| Original language | English |
|---|---|
| Journal | Sustainable Development |
| DOIs | |
| Publication status | E-pub ahead of print - 30 Oct 2025 |
| MoE publication type | A1 Journal article-refereed |
Funding
This work was supported by Åbo Akademi University and Liikesivistysrahasto 230356.
Keywords
- Pricing Strategies
- Sustainability
- Theory of Planned Behavior
- Artificial intelligence, Machine Learning, Hybrid Modelling, Diagnostics, Energy Efficiency, Curriculum change, Data centers
- Sensitivity
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