INFORMATION AND THE SPEED OF INNOVATION ADOPTION

Within a Bayesian framework, a random-effects model is developed and a pplied to adoption of new wheat varieties in South Australia. In this model, not all pieces of information add equally to knowledge about th e innovation. The model shows the acquisition of information to be muc h slower than has been suggested by previous Bayesian models and can a lso explain laggards and partial adoption. The results have important practical implications for farmers and support agencies. The paper's t heoretical contributions are to highlight the structure of information , and to demonstrate how qualitative results can be obtained where the posterior Bayesian distribution is intractable.