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Information and the Speed of Innovation Adoption
Author(s) -
Fischer A.J.,
Arnold A.J.,
Gibbs M.
Publication year - 1996
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1243863
Subject(s) - bayesian probability , bayesian inference , distribution (mathematics) , knowledge management , econometrics , posterior probability , computer science , marketing , business , data science , economics , mathematics , artificial intelligence , mathematical analysis
Within a Bayesian framework, a random‐effects model is developed and applied to adoption of new wheat varieties in South Australia. In this model, not all pieces of information add equally to knowledge about the innovation. The model shows the acquisition of information to be much slower than has been suggested by previous Bayesian models and can also explain laggards and partial adoption. The results have important practical implications for farmers and support agencies. The paper's theoretical contributions are to highlight the structure of information, and to demonstrate how qualitative results can be obtained where the posterior Bayesian distribution is intractable.