multicollerarity between variables. This is observed especially among socioeconomic

data. Unfortunately, due to small sample size, I was unable to run other types of analysis

to determine association between variables.

 When considering the importance of the economic model as a predictor of behavior

it is important to reconsider the historical context of the study group. The historical

context shows that there is distinction between two farming groups. The wealthier

farmers rapidly adopted and adapted many facets of Western farming and ranching. The

poorer group does not do so as quickly or fully. The results from this research rediscover

this distinction between groups some components of group differences persist.

 Research illustrates various effects of the influence of socioeconomic

characteristics in predicting behavior. Adoption of new technologies are often considered

a function of economics (Marra, Pannell, Gaudim, 2003).Research does indicate that

many economic models are enhanced in predicting decision-making behavior when

considering other factors, such as attitudes (Luzar & Diagne, 1999; Lynne, Shonkwiler,

& Rola, 1988) and access to resources (Floyd, et al, 2003). My research indicates that

components of the TPB may strengthen the predictive power of the economic model.

 The majority of research examining rational decision-making focuses on adoption

behavior as opposed to persistence behavior, especially those which may not have direct

observable benefits. I discuss my results in light of this research by interpreting low TAP

users as the adopters of new technologies. However, as previously discussed, I have

some reservations about this interpretation due to interview responses. Many participants

who do use conventional agricultural technologies indicated that they have always used

them. So, these individuals may also be persisters as opposed to adopters. Overall