Urban Science (Sep 2024)

Application of the MAMCA Method in the Evaluation of Delivery Flows within City Centers: A Case Study of Rijeka

  • Mladen Jardas,
  • Ana Perić Hadžić,
  • Dario Ogrizović

DOI
https://doi.org/10.3390/urbansci8030149
Journal volume & issue
Vol. 8, no. 3
p. 149

Abstract

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The aim of this paper was to propose a model for the evaluation of the flow of goods delivered to urban centers based on a systematic approach, generating possible scenarios of delivery activities and selecting those criteria for evaluation that contributed to the development of delivery activities and their evaluation by individual stakeholders. The number of users of delivery services is increasing, which leads to an increase in the volume of goods in the city center, creating additional traffic congestion—so-called bottlenecks—which results in an increased noise level and the emission of harmful exhaust gases, increasing dissatisfaction with the quality of life of the city population. It is, therefore, necessary for decision-makers to make a decision that achieves the best consensus among stakeholders. A test was carried out in the city of Rijeka. Based on a review of the literature and the spatial planning of the city of Rijeka, this paper proposed the following possible scenarios for the delivery of goods within the city center: status quo, delivery from one consolidation center, delivery from two consolidation centers, delivery by environmentally friendly vehicles from one consolidation center and livability. The criteria were evaluated by relevant stakeholders to determine the weight of each criterion for the development of goods deliveries in the city center. This paper used a multi-actor multi-criteria analysis (MAMCA) based on the optimization and ranking of scenarios in accordance with the given objective, the research problem, the defined criteria and the interests of the stakeholders. The solution of the MAMCA analysis evaluated the scenario with two consolidation centers best in accordance with the specified optimization objective.

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