Adoption of Emerging Technologies Under Output Uncertainty

Abstract

A model of divisible technology adoption under incomplete information dissemination and output uncertainty is developed. We identify economic and subjective factors affecting technology adoption and its intensity. Empirical estimation employs a mixed dichotomous‐continuous framework with nonrandom sample selection. Producers' adoption intensity is conditional on their knowing about and deciding to adopt the new technology. Using survey data on bST (bovine somatotropin) adoption among Texas dairy producers, we find that larger and more educated operators are likely to adopt more intensively. Traditional dichotomous adoption models without sample selection significantly overestimate the adoption rate.

Agricultural policy for quality and producers’ evaluations of quality marketing indicators: a Greek case study

“…In this work, we consider three components of human capital: formal education, work experience and knowledge of the institutional environment acquired through experience with past policies and/or programmes. Theories of managerial efficiency and learning-by-doing imply that years of formal education have a positive impact on firm growth in general (Variyam and Kraybill, 1994;Barkham, 1994), while past experience with schemes has been found to influence the producerÕs willingness to adopt new methods of production, new inputs, or adopt new marketing strategies (Saha et al, 1994;Dimara and Skuras, 2003a;Dimara et al, 2003). A growing body of literature in economic sociology stresses that markets are socially structured institutions, infused with cultural norms and meaning (Lie, 1997).…”

Joint estimation of information acquisition and adoption of new technologies under uncertainty

“…Few studies have actually considered these decisions jointly. Saha et al (1994) focused on the role of incomplete information in the adoption of bovine somatropin by a sample of farmers in Texas. Due to differences in natural resources, political and socioeconomic conditions, the importance of factors affecting the joint decisions to acquire information and adopt new innovations differ across countries and regions.…”

The impact of water price uncertainty on the adoption of precision irrigation systems

“…The magnitude of the effect is higher with the matched sample, providing additional evidence that samples may differ before pre-processing. Previous research has shown that large operations tend to be less risk averse than small operations (Saha, Love, and Schwart, 1994;Saha, Shumway, and Talpaz, 1994;Koundouri et al, 2009). This result indicates that both efficient irrigation and perennial crops are used as risk reducing investments by small operations.…”

“…However, previous literature has found that farm size is a significant predictor of risk attitudes, with farm size negatively correlated with risk aversion (Saha, Love, and Schwart, 1994;Koundouri et al, 2009). When separating relative and absolute risk aversion, Saha, Shumway, and Talpaz (1994) found that small farms have higher absolute risk aversion and lower relative risk aversion than large farms.…”