Purpose - The purpose of this paper is to present an integrated analysis of determining factors of farmers' genetically modified (GM) technology adoption behavior, with a special emphasis on information acquisition, knowledge accumulation, product attributes and technology traits. Design/methodology/approach - Extending the expected profit maximization framework into a random utility model which accommodates joint decisions of information acquisition and technology adoption, the authors use the full information maximum likelihood method to yield both consistent and efficient estimates. The model is applied to a field survey collecting a sample of 141 randomly selected bananas farmers. Findings - The empirical results indicate information acquired through social network will increase the probability of adoption. Knowledge accumulation as depicted by education and farming experience is found to play a role in farmers' technology adoption, whereas disease-resistant technology trait and flavor-enriching product attribute of GM bananas also appear to be important determinants for GM seeds adoption in Taiwan. Practical implications - Empirical evidence supports significance of technology traits and product attributes in farmer's GM technology adoption, suggesting the close collaboration between industry, government and academia is the key to successful commercialization of GM crops. Social implications - Understanding the determinants of farmers' GM technology adoption can serve as the basis for promoting new biotechnology, and thus can facilitate the establishment of tenable solutions to food security issues. Originality/value - This paper is the first attempt to incorporate information acquisition into the behavioral analysis of GM technology adoption. The present study also extends previous literature by considering influential factors related to both consumers' and producers' preferences in modeling technology adoption.
