A Novel Interval-Valued-q-Rung Orthopair Fuzzy-Additive Ratio Assessment Model for Evaluating Logistics Service Quality

Abstract

Logistics service quality is crucial for companies to satisfy customers, gain an advantage over competitors, minimize costs, make effective business processes, and maintain corporate reputation. Companies work with 3PL service providers to ensure the quality of their logistics services. Now, companies adopt technology adoption models closely related to 3PL service and logistics service quality. In this context, this research aims to determine the ideal technology adoption model for ensuring logistics service quality in companies that employ 3PL services. It also seeks to determine the criteria and their significance levels that must be considered to attain the specified aim. A decision-making methodology, including IV-q-ROF-ARAS, has been used to attain these goals. The research revealed that the essential criteria for the quality of logistics services are “reliability, regularity, flexibility, and service usability,” “delivery time and request,” and “availability of ordering information.” According to the study, logistics companies must be reliable and flexible. The “technology acceptance model” has been identified as the ideal adoption model for Turkish companies receiving 3PL services. The study, which focuses on logistics service quality, 3PL service providers, and technology adoption structures, presents significant implications for the literature and companies.

Keywords

• ARAS
• businesses receiving 3PL service
• IV-q-ROF-ARAS
• IV-q-ROF-MCDA
• logistics service quality