Utilization of the Bayesian Decision Model in Agri-Business Value Chain Intervention Projects in the Niger Delta

This research is aimed at Applying Bayesian decision model in Agribusiness value chain intervention project in Niger Delta. The objectives are: to determine Prior (Prototype) and Posterior (Model) Probability, Expected Monetary Value (EMV), Marginal Probability, Expected Value of Perfect Information (EVPI), Expected Profit in Perfect Information (EPPI), The problems the study solve were: inadequate funding of multipurpose scheme, inefficient economic benefits and losses. The methodology applied involves data which were collected from the beneficiaries (Incubators and Incubatess) in selected beneficiaries of LIFE-ND agribusiness cluster across the 98 selected local government across the Nine states , Nine LIFE-ND mandate State Offices of Abia, Bayelsa, Cross River, Akwa Ibom, Edo, Delta, Rivers, Ondo, Imo, and the National Coordinating Office in Port Harcourt and Federal Ministry of Agriculture and Rural Development. The methods used in this research for the Agri-business intervention projects were as follows: estimating the performance of economic efficiency of the multipurpose projects, estimating performance of the net benefits of the interaction between multi-purpose and the multi-objective, assembling the total net benefits of the interaction between multipurpose and the multi-objective, analyzing the data obtained as the total net benefits to ascertain the reliability and validation of the sources of data by using: Contingency coefficient and association, Pearson moment correlation coefficient and T- distribution test. The results of Bayesian model of expected monetary values of the Agribusiness multipurpose project are as follows: Economic efficiency which produces the Maximum Expected Monetary Value (EMV*) ₦8.16 Billion, Expected Profit in perfect information is (EPPI) is ₦20.34 Billion. Expected Value of Perfect Information (EVPI) ₦12.17Billion.