A proactive assessment model for taxi service performance: Evidence from Eastern Europe

Taxi service quality is traditionally assessed using objective metrics like waiting time, cost, and comfort. However, contemporary research confirms that subjective psychological factors significantly influence service perception. This study aims to proactively determine the relationship between passenger-driver interaction and the psycho-emotional factors of trust, empathy, and control using a fuzzy logic approach. The empirical basis for the research was a survey of 118 respondents from Ukraine and 101 respondents from Poland. The survey results were converted into percentage distributions for the factors of trust, empathy, and control, which served as the input parameters for a new fuzzy model developed in MATLAB. For model validation, a case study of 10 pilot trips was conducted, comparing the model's predictions with actual passenger ratings. The new fuzzy model predicted interaction levels in the range of 56.05–94.86%, which in most cases aligned with the actual passenger ratings for each trip. The average deviation between the model's predictions and the actual ratings was less than 6.67% according to the Relative Error metric. Analysis of the error revealed that accounting for individual trip circumstances enhances prediction accuracy. The novelty of this research lies in translating a passenger’s subjective psycho-emotional perceptions into quantitative indicators, which increases the reliability of taxi service quality assessment. The results are significant for taxi services and the logistics of their operations, providing a deeper understanding of the psychological factors that influence ratings. Furthermore, this approach can be used by digital taxi platforms for more effective service management. The work demonstrates the potential of fuzzy logic to improve predictive accuracy, develop personalized strategies, and create a foundation for intelligent decision support systems to enhance taxi services in European cities.