Table 4.: Respondents unintended consequences on arable crop technology

The relationship between unintended consequences and independent variables was established using Pearson Product Moment of Correlation. Some independent variable were selected and tested against unintended consequences. At a significance level of 0.05, age and farm size shows no significant relationship with unintended consequences. This suggests that the age of the respondent and the size of the farm do not reflect perceived negative consequences of technology adopted.

Social participation and contact with extension agent shows positive significant relationship between them and the unintended consequences. This is because this activity shows the respondent’s contact or relationship with the linkage system through which the technology are being disseminated. Social participation and contact with extension agent influence adoption of agricultural technology disseminated. Therefore, social participation and contact with extension agent are important activities in determine the unintended consequences of technology.

Table .5 also shows that there is a significant inverse relationship between the benefits of an adopted technology and the unintended consequences produced. This indicates that the technology with benefits (economic, social, cultural, etc.) will likely produce negative consequences which may lead to rejection of such technology and the resulting benefits of a technology is cogent to any technological innovation that any innovation without benefits may be rejected or discontinued.

The table also indicates that there is a relationship between adoption and unintended consequences. This reflects that some agricultural technology adopted produces some unintended consequences, which makes some farm families worse-off than if they had been left alone. The adoption of various agricultural technologies, which demonstrate some negative consequences, negates what researchers have said about the fulfillment of the characteristics or elements of innovation.

The null hypothesis that there is no significant relationship between respondent age and farm size and their perception of unintended consequences is accepted because age and farm size cannot determine their perception of unintended consequences. The null hypothesis that social participation and contact with extension agent and their perception unintended consequences is rejected because the social participation and contact with extension agent determine the perception of unintended of the respondent.

This relationship was established using Pearson Product Moment of Correlation. Six independent variables were selected and tested against perceived benefits.

The table indicates that there is a significant relationship between perceived benefits and adoption. This suggests that most agricultural technology adopted benefits the various adopter categories

The table also indicates that the income is significantly related to the perceived benefits that is, the amount/income earnings generated from agricultural technology is as a result of the benefits involved in the technology. If agricultural technology has no benefit it will not be accepted, if accepted it will be discontinued when realized. Therefore, this suggests that to ensure adoption for agricultural technology it has to be profitable.

From the table age, contact with extension agent, social participation and farm size are not significantly related to the perceived benefits.

The relationship shows that the age of a farmer does not influence the benefit of an agricultural technology. Likewise, the farm size may not show the benefits perceived by the farmer. This thing applies to the social participation and the contact with extension agent. This might only facilitate adoption process but will not reflect or demonstrate the perceived benefit.

The null hypothesis states that there is no significant relationship between the age and farm sizes of respondent and their perception of positive consequences of technology is accepted. This is because the age and farm size of farmers do not determine their perception of positive consequences of technology. The null statement that income is not significant to perception of positive consequences of technology is rejected because, farmer’s income determine the perceived benefits of technology.

Also, the null statement that the contact with extension agent and social participation and their perception of positive consequences of technology is accepted. This is because the social participation of farmers and their contact with extension agent do not determine the perception of positive consequences of technology.

Also, the null hypothesis that there is no significant relationship between farmer’s membership of an association and membership of religious organization and their perception of unintended consequences of technology is accepted. This is because their level of significance is lower than 0.05 while the statement is rejected for membership of cooperative and past executive because their significant level is greater than 0.05. The membership of cooperative and past executive of respondent determines the perception of unintended consequences of technology while membership of farmers association and religious organization do not.

P < 0.05 is significant

P > 0.05 is not significant
The result of the regression analysis in Table 4.8 shows that R = 0.76, which means that there is a strong correlation between unintended consequences and all the independent variable in the equation. R² = 0.58, which shows that 58% of the variation in the dependent variable was accounted by the independent variables.

The standardized partial regression weight that is, Beta values shows that adoption of arable crop technology is the most important predictor of the unintended consequences. This is followed by frequencies of meetings with extension agent (Beta = 0.59) and contact with extension agent (Beta = -0.317). The negative sign shows an inverse relationship.

ANOVA

Model	Sum of squares	df	Mean Square	F	Significant
1 Regression	142.926	24	5.995	5.561	000
Residual	101.741	25	1.071
Total	244.667	119

Coefficient

The result shows that there is no significant difference among different educational level of respondents for adoption of technology and benefits derived from the technology (F = 1.54, p = 1.60; F = 1.12, p = 0.35 respectively). However, there is a significant difference in the unintended consequences among respondents of different educational level. F = 3.05, p = 0.006. The Duncan ratings shows that the respondent having M.Sc and above have the highest mean of unintended consequences and it is the only group that is significantly different from the other educational levels.

Table .9: Differences in the adoption, benefits and unintended consequences of