Industrial Investment Payment Strategies a Comprehensive Analysis Using Market Data and Decision Criteria

Abstract

Industrial Investment are paramount to the enterprise to optimise the distribution of resources, improve profitability, and appropriate payment facilities in the changing market environment. Current approaches, including the conventional AHP, WS models, and classical TOPSIS, usually do not deal with the aspect of uncertainty, indecision, and interrelations between various criteria, and thus result in a non-optimal investment decisions. In order to overcome these shortcomings, the research will introduce a hybrid MCDM model, which will combine Intuitionistic Fuzzy AHP to allocate weight to the payment options and TOPSIS to ensure effective ranking of payment options. The methodology uses the same market indicators of the Market Champions dataset  and it is completely carried on the Python platform with libraries including Pandas, NumPy and FuzzyPy. The proposed model shows better performance, and it has high ranking accuracy of 95.2%, low mean absolute error, small ratio of consistency, and good robustness to both scenario and sensitivity analysis. This framework can be used by industrial managers, financial analysts and decision-makers in enterprises to make reliable and accurate and data-driven choices on investment payments.