A Smart Decision-Support System: Evaluating Cost-Effectiveness of Agri-Tech Investments
DOI:
https://doi.org/10.54536/ijsa.v4i1.6337Keywords:
Agri-finance, Cost-Effectiveness, Decision-Support System, Economic Evaluation, Investment AppraisalAbstract
This study outlines an intelligent decision support system that would be used to determine the cost effectiveness of agri-tech investments. The problem it addresses is simple but widespread, since farmers, cooperatives, lenders and policymakers often do not have clear, consistent, finance-prepared appraisals to understand whether an investment is worth pursuing or investing in. The system sums up the simple inputs about the benefits, costs, yields, prices and operating assumptions, such as initial investment, the project lifetime and the discount rate and then calculates six most common indicators, including Return on Investment (ROI), Net Present Value (NPV), Internal rate of Return (IRR), Benefit-Cost Ratio (BCR), Payback Period, and Discounted Payback Period (DPP). It also carries out the scenario analysis and one-way sensitivity analysis to help show how the implications change with the major risks that include the market price, yield, input cost, and interest rate. Outputs are provided in the form of clear visualization and two types of reports; a plain-language summary, suitable for farmers and a report to lenders, which is consistent with common appraisal practice. It is multilingual and produces short and explainable narratives to allow users who are not specialists to understand the logic behind each recommendation. The standardization of indicators, explicit risk, and exposure of results to concrete financing conditions make the tool useful to conduct comparative evaluation of options, cash-flow planning, and give transparent and evidence-based decisions. The key contribution is an actively useful, expandable structure, which is a combination of divergent approaches into a unified agri-finance support instrument that is agreeable to adoption, lending, and policy targeting.
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