Factors and Interpretable Models in Data-Driven Management Information Systems to Enhance Job Satisfaction of Road Transport Employees

Abstract

Adopting interpretable models is crucial in shaping employee job satisfaction within the road transport industry. This research examines the Management Information Systems (MIS) factors influencing the adoption of these models and their subsequent impact on enhancing job satisfaction among employees responsible for ground services. Employing a mixed-methods approach with 200 respondents, the study combines quantitative surveys and qualitative interviews. Key factors explored include training, communication, employee involvement, workload, organizational support, job autonomy, perceived job security impact, and cultural alignment. Data robustness is ensured through validity and reliability tests, complemented by statistical analyses such as independent sample T-tests, ANOVA, regression analysis, and qualitative thematic analysis. The findings provide strategic insights for industry leaders, highlighting the importance of training and communication in fostering a supportive work environment.