Approaches to Develop Service Quality of Road Freight Transport Service Providers in Industrial 4.0
Kamolpun Noijaroen, Nopporn Bua-In, Thitirat Thawornsujaritkul · Pakistan Journal of Life and Social Sciences (PJLSS) · 2024
High-quality service provision in road freight transport results in a management system that meets established standards.This research aims to enhance the service quality of road freight transport service providers and develop this enhancement into a structural equation model.The study employs both qualitative and quantitative methodologies, involving nine experts and eleven qualified professionals.It also includes a quantitative survey of 500 executives in the industry who have achieved the Q Mark standard for transport services.The research utilizes descriptive statistics, inferential statistics, and multivariate statistics.The study identified four key components of service quality development for road freight transport service providers in Industrial 4.0, ranked by importance: 1) Business Strategy (Mean = 4.30): The most critical elements include clear and easily understood operational planning and processes.2) Smart Operations (Mean = 4.15): The highest priority is the daily readiness of vehicles, monitored through GPS tracking to ensure consistent availability.3) Customer Relationships (Mean = 4.11): The most crucial aspect is the management of digital customer history data (via Dropbox), which helps solve problems related to the appropriate storage of customer information.4) Personnel Capabilities (Mean = 3.95): Key factors include defining employee qualifications, recruitment, capability assessment, and aligning attitudes with business needs.The hypothesis testing revealed that small and medium-sized enterprises differ significantly at the 0.05 level in their emphasis on the development of service quality approaches for road freight transport in the Industrial 4.0 era.Analysis of the developed structural equation model indicated that it meets the assessment criteria and is consistent with empirical data.The model showed a Chi-square probability level of 0.187, a relative Chi-square value of 1.092, a goodness-of-fit index of 0.964, and a root mean square error of approximation (RMSEA) of 0.014, all indicating statistical significance.