The maritime sector operates in an environment characterized by multidimensional uncertainty—technical, operational, and financial. Mechanical failures, volatile fuel prices, and fluctuating freight rates simultaneously influence vessel performance and profitability, making effective decision-making increasingly complex. This study develops an integrated reliability–financial modeling framework that combines Multi-State Systems (MSS) Theory, Markov Chains, Markov Switching Models, and the Universal Generating Function (UGF) methodology to capture both physical system reliability and market-driven volatility. Using the Panamax Index as a case study, the model evaluates vessel availability, fuel price dynamics, and freight rate fluctuations to forecast profitability under uncertain operating conditions. The findings indicate that transient probabilities of vessel availability converge faster than financial variables, suggesting higher predictability of technical systems compared with market indices. The proposed framework provides maritime stakeholders with a strategic decision-support tool capable of forecasting profitability and identifying optimal operating routes within a 26-week horizon. According to our Panamax data, 3/5 routes have positive expected profit, availability stabilizes by ~ week 3, and freight regimes by ~ week 15. By integrating reliability engineering with financial modeling, the study enhances operational planning and risk management in the maritime industry.
Markopoulos et al. (2026) studied this question.