Management-Oriented Assessment of Transport Service Quality Using Logistics Monitoring System and Harrington’s Desirability Function in Support of SDG 9

Victor Aulin, Oleh Liashuk, Dmytro Mironov (), Piotr Staliński, Marek Rutkowski and Sergiy Lysenko
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Victor Aulin: Faculty of Construction, Transport and Energy, Central Ukrainian National Technical University, 25006 Kropyvnytskyi, Ukraine
Oleh Liashuk: Faculty of Engineering of Machines, Structures and Technologies, Ternopil Ivan Puluj National Technical University, 46001 Ternopil, Ukraine
Dmytro Mironov: Faculty of Engineering of Machines, Structures and Technologies, Ternopil Ivan Puluj National Technical University, 46001 Ternopil, Ukraine
Piotr Staliński: Faculty of Social Sciences and Computer Sciences, School of Business, National-Louis University w Nowym Sączu, 33-300 Nowy Sącz, Poland
Marek Rutkowski: Faculty of Administration and Social Sciences, University of Economics and Innovation in Lublin, 20-209 Lublin, Poland
Sergiy Lysenko: Faculty of Construction, Transport and Energy, Central Ukrainian National Technical University, 25006 Kropyvnytskyi, Ukraine

Sustainability, 2025, vol. 17, issue 17, 1-27

Abstract: The quality of transport services is not only a measure of operational efficiency but also an important factor of strategic logistics management in the pursuit of sustainable development. This study identifies five key transport service quality indicators (timeliness, routing, economy, safety, efficiency) and uses data from a logistics monitoring system to assess them with Harrington’s desirability function. Each indicator’s performance is converted into a partial desirability score and these scores are combined into a single overall desirability score (D), with weights determined from the data. Notably, a threshold around D = 0.63 emerged as the benchmark for acceptable service quality. This numeric threshold provides managers with a clear KPI target—if the service quality index falls below 0.63, it signals the need for corrective action, whereas consistently achieving values near 0.8 reflects very good performance aligned with strategic sustainability goals. Based on the proposed approach, an algorithm and software tool were developed to automate the assessment process. The obtained results show how improvements in service reliability, safety and efficiency can be aligned with broader sustainability goals in automotive transportation. The proposed approach offers managerial decision makers a robust tool to guide policy and investment, ensuring that enhancements in transport service performance also advance environmental and social sustainability. In doing so, the framework advances SDG 9 by turning logistics telemetry into an actionable management index that strengthens resilient transport infrastructure and fosters practical innovation at the enterprise level.

Keywords: SDG 9; transport service quality; logistics monitoring; Harrington desirability function; multi-criteria decision making; managerial decision support (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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