Investigation of Road Transport Enterprise Functioning on the Basis of System Dynamics

Tolujevs, Jurijs; Shedenov, Otegali; Askarov, Gani · 2018 · Crossref

DOI: 10.2478/ttj-2018-0001

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Summary

This study investigates the applicability of System Dynamics (SD) for analyzing the operational performance of road transport enterprises, motivated by the high cost and complexity of traditional simulation methods like Discrete Event and Agent-Based modeling. The authors argue that while Discrete Event and Agent-Based paradigms offer high detail, they are often prohibitively expensive and technically demanding for small and medium-sized businesses. In contrast, SD provides a more accessible, macroscopic approach suitable for analyzing enterprise-level processes without requiring specialized external expertise. The research focuses on a specific international road transport company in Kazakhstan, aiming to evaluate how maintenance strategies impact annual profitability under varying demand conditions. The methodology involves two stages: qualitative modeling via a causal loop diagram and quantitative simulation using Vensim software. The causal loop diagram identifies key factors influencing competitiveness, such as infrastructure state, truck pool size, employee qualification, and transportation tariffs. The quantitative model simulates the enterprise’s operations over a 365-day period with a daily time step. The model represents a fleet of 200 trucks handling trips with durations ranging from 4 to 21 days. Input data, derived from real enterprise statistics, includes probability distributions for trip durations, repair times (1–4 days), and average profitability per trip. The simulation accounts for order flow intensity and the "share of trips without idle," which determines the proportion of trucks returned from trips that are immediately available for new orders versus those sent for maintenance. Numerical experiments were conducted by varying two parameters: the share of trips without idle (60%, 70%, 80%) and the order flow intensity factor (0.8, 0.9, 1.0, 1.1). Results indicate that at low demand levels (intensity 0.8), the maintenance strategy has no impact on profit, as all orders are accepted regardless of truck availability. At higher demand levels (intensity 1.0 and 1.1), increasing the share of trips without idle from 60% to 80% increases annual profit by approximately 3%. For instance, at an intensity of 1.1, profit rose from €5,196 thousand to €5,339 thousand. However, the authors note that maximizing truck availability may compromise traffic safety, suggesting that maintaining a 60% idle share is a reasonable balance between profit and safety. The study concludes that System Dynamics is a viable and practical tool for analyzing specific road transport enterprises, offering a simpler alternative to complex simulation paradigms. The use of free software like Vensim PLE allows enterprise employees with mathematical training to develop and interpret models effectively. The findings demonstrate that SD can provide actionable insights into operational strategies, such as balancing fleet availability with maintenance needs, thereby supporting decision-making in transport logistics without the high costs associated with detailed microscopic simulations.

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• Theoretical Contribution: computational model