This research uses the Fuzzy Tsukamoto Method to construct a decision support system (DSS) to change hotel investment decision-making. The study integrates quantitative and qualitative elements, accommodates uncertainties, and provides stakeholders with full insights for informed decision-making to meet the complexity of hotel investments. Systematic data collecting from financial measures, market trends, customer preferences, and expert opinions is used. The DSS combines various inputs using computer intelligence to analyze investment opportunities. The DSS's capacity to include subjective inputs and enable scenario evaluations shows its complete grasp of investments. Consumer behavior, market trends, risk assessments, and sustainability correlations greatly impact investment strategies. System strengths include adaptability, extensive analysis, and educated decision-making. However, interpretability, data quality, and real-time adaption issues recommend future study improvements. In hotel investment decision assistance, this research is groundbreaking. The DSS's sophisticated, data-driven insights can allow stakeholders to take a more strategic, sustainable, and adaptive approach to the changing hospitality business. Further refinements and innovations will strengthen its effectiveness, enabling robust and informed hotel investment decisions in the changing landscape
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