Applying innovation attributes to predict purchase intention for the eco-labeled products

Purpose: This paper aims to make use of the innovation diffusion theory to predict the purchase intention for eco-labeled products. Design/methodology/approach: Data are collected from 180 individuals in the Mid Valley shopping mall area in Malaysia. It is then analyzed using SPSS and Smart PLS. The measurement model is analyzed using composite reliability, convergent and discriminate validity, while the structural model is used to predict the relationships between variables. Findings: Results indicate that the relative advantage, trialability and observability are positively related to eco-labeled products purchase intention, while the complexity is negatively related to eco-labeled products purchase intention. However, compatibility is not positively related to eco-labeled products purchase intention. Practical implications: Marketers should enhance the observability of eco-labeled as it is the most influential attribute affecting eco-labeled products purchase intention. Relative advantages of eco-labeled products are also important to stimulate purchase intention. Marketers could best relate the innovation to context-specific use situations enabling consumers to evaluate the use consequences of the innovation, and therefore, may assess its particular benefits. Originality/value: It explores the potential of a theoretical framework based on innovation diffusion theory to explain eco-labeled products purchase intention.