Abstract

This study addresses the challenges of uncertainty, vagueness, and imprecision in real-world decision-making, particularly for small-scale farmers selecting short-term crops. The central problem is the lack of a systematic framework to evaluate conflicting criteria such as investment, yield, market demand, and soil requirements. To solve this, a Multi-Criteria Decision-Making (MCDM) framework is introduced, which integrates Cubic Spherical Neutrosophic Sets (CSNS) and Neutrosophic Hyper Soft Sets (NHSS). The research also proposes a novel cubic spherical neutrosophic Bonferroni mean operator for aggregating neutrosophic sets. The effectiveness of this approach is demonstrated through a case study in Tamil Nadu, focusing on selecting the most suitable crop for different climatic zones. A sensitivity analysis confirms the model's robustness and reliability. The tool aims to improve resource utilization, reduce risks, and promote agricultural sustainability.