A theme that emerges from the empirical literature into the impact of road traffic congestion on supply chains is the compounding effect of consignee behaviour on distribution costs: even as congestion levels rise, customers of manufacturers/distributors replenish product on a just-in-time (JIT) basis, which further drives up distribution costs. The reluctance of customers to receive shipments outside business hours exacerbates the distribution task. Since the isolation of the impact of congestion on logistics costs is not always easy, organisations may be tempted to unjustifiably impute rising logistics costs to congestion. Through continuous approximation models, the present research aims to clarify the relative impact of relevant dimensions of consignee behaviour, particularly, JIT replenishment and the length of the workday, and traffic congestion on distribution costs. A critical element of such modelling is the estimation of the required number of vehicles, which in turn depends on the average daily number of commercial trip chains per vehicle. We identify two polar cases. In one case, the estimation of this number is trivial and therefore enables further analysis, including the quantification of the relative impact of congestion on distribution costs and the deduction of empirically testable hypotheses. The other case is considerably less tractable; we consider a specific instance of this case that was broadly relevant to one of the companies that participated in the research. A simulation experiment using real-world data from a NZ manufacturer-distributor serves to validate our analysis. © 2007 Elsevier Ltd. All rights reserved.
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