A0904
Title: Factors shaping innovative behavior: A meta-analysis of technology adoption studies in agriculture
Authors: Michail Tsagris - University of Crete (Greece) [presenting]
Abstract: Despite extensive empirical research on the drivers of technology adoption in agriculture, there is only little agreement among researchers over how improved agricultural technologies can be effectively promoted among individual farmers. A meta-regression analysis approach is employed to synthesize empirical evidence on the average partial effects of eleven adoption determinants that regularly appear in empirical studies examining farmers' adoption behavior worldwide. The analysis considers a total of 122 studies from the adoption literature using discrete choice models that have been published in 24 peer-reviewed journals since 1985, covering farmers' adoption behavior around the world and for a wide variety of agricultural technologies. Using this unique and broad meta-dataset, it is investigated whether each of the eleven determinant factors has a true average partial effect on technology adoption rates. Moreover, the sources of heterogeneity are identified across reported estimates on average partial effects, and whether publication bias is one of the drivers of observed asymmetries in estimates is examined. The meta-regression model is estimated using a weighted least squares (WLS) estimator that allows capturing observed heterogeneity arising from differences in population characteristics across studies or study attributes.
