Estimation of Conflict: A System Approach to Predict Social Entropy in Farm Ecology

The present empirical study has focused on an alternative paradigm for managing human behavior and organizations, social institution and society through measuring entropy and by withdrawing disorders from the system crippled with conflict and non-performance. The ex-post facto research was conducted in the village Chiroura of Naubatpur block in Patna district of Bihar. Astructured pretested interview schedule was used to conduct survey of 75 farmers in the research locale. Regression analysis, Path analysis, Factor analysis were the statistical tools for the analysis of data with the help of statistical software SPSS (Version-16). Inter and Intra relationships among the 32 independent variables and 8 dependent variables revealed that predictor variable viz. Information seeking behavior (x₂₉), Market orientation (x₂₆) and Scientific orientation (x₁₈) were positively and significantly correlated with the predicted variable Conflict, whereas Fuel consumption (x₁₅), Farm size (x₁₀) and Annual income (x₁₃) were found to be significant but negatively correlated with Conflict. Market orientation (x26), Innovation proneness (x₂₀), Farm size (x₁₀), Expenditure Allotment (x₁₁), Fuel consumption (x₁₅) and Cropping intensity (x₉) were retained at the last step of stepwise regression analysis. Path analysis shows that Farm size has recorded the highest direct effect on conflict. Factor analysis has generated new factor Family resources, which has contributed in enhancing entropy in farm ecology with explaining 16.431 per cent of variance. There is possibility to enhance farmers'income by reducing conflict and shifting high entropy agriculture to low entropy agriculture.