flows are consolidated, can solve this problem by requiring fewer delivery transactions. In these systems, suppliers deliver to the consolidation center [5], and from there, we can deliver the goods to the stores through cross-docks in a consolidated way. However, a shortcoming of the previous studies is that they do not pay enough attention to where significant improvements can be made and which urban areas are the best for implementing new city logistics systems. In my dissertation [6], I focused on urban areas with a large number of delivery locations in a small area with significant delivery needs (such areas were examined previously only in some papers [7] [8]); I defined these areas as concentrated sets of delivery locations. The related benefits 1. Introduction Nowadays, green considerations have led to a strong focus on efficient and environmentally friendly urban transportation, within which urban freight transport is responsible for significant emissions and traffic congestion, while mainly the last sections of these supply chains are the most expensive delivery steps, and the urban freight transport demands are still increasing [1]. The European Union has also set ambitious targets for emissions in recent years [2] [3]. To meet these targets, the development of urban freight transportation is significant within transportation. Previous results suggest that consolidation-based schemes [4], where urban freight have already been demonstrated in several cities, with significant reductions in emissions and the number of deliveries [9] [10] [11] [12] [13] [14] [15]. 2. Urban concentrated sets of delivery locations As the first step, I examined the different types of urban delivery locations (i.e., stores and accommodations). First, I focused on the case of Budapest, Hungary, where I worked with data from 35 shopping malls, 15 markets, the Váci utca shopping area, and 12 hypermarkets. To analyze their characteristics, I introduced the degree of concentration, which defines how many delivery locations can be found per unit of urban area. Based on this, for the Consolidation-based city logistics developments in the system of the concentrated sets of delivery locations Urban transportation, emissions, traffic congestion, freight transportation, city logistics Selected: Friedrich-List-Preis Dávid Lajos Sárdi DOI: 10.24053/ IV-2024-0072 International Transportation (76) Collection ǀ 2024 6 whole city with around 25000 stores [16], there are 47.8 stores/ km 2 . For comparison, I calculated the degree of concentration of shopping malls (4762 stores/ km 2 ), markets (12365 stores/ km 2 ), the Váci utca shopping area (804,1 stores/ km 2 ), and hypermarkets (688,2 stores/ km 2 ). All the values are significantly higher than the Budapest average, indicating that it is essential to handle these areas separately from a city logistics aspect. Additionally, 20.6% of Budapest‘s total stores are located within these areas; still, they cover only 0.3% of the total urban area (74-fold difference). Further data from Hungary [17] [18] [19] and from Austria [20] [21] have confirmed this trend. Considering these results and the findings of previous city logistics projects, I introduced a new clustering for the urban delivery locations (see Figure 1). The urban delivery locations have been divided into two groups: single delivery locations and concentrated sets of delivery locations, where several stores are concentrated in a relatively small area. In the case of an open infrastructure set, the road infrastructure defines the area, e.g., in a shopping area. A closed infrastructure set can be defined as any building with delivery locations, e.g., a shopping mall. To carry out the further steps of the research, a complex data collection methodology [22] was developed to analyze these sets. The methodology consists of expert interviews, observations, and a questionnaire covering all logistics topics, with an additional topological model for open infrastructure. Between 2015 and 2020, 1239 stores were visited for data collection, of which 627 (50.6%) answered, of which 344 (54.9%) stores‘ data could be used later for simulation. This helped overcome the problem that it is impossible to model these systems without data. Additionally, the survey results confirmed that the supply of goods to the stores of the concentrated sets is currently not coordinated; the stores mainly organize their deliveries themselves, and they deliver goods in small, non-standard units with high frequency. 3. Consolidation-based concepts for the concentrated sets of delivery locations After collecting data, the current structure of the city logistics system of the concentrated sets was formulated, and it became possible to develop consolidationbased concepts based on the current operation and the published experiences. In the reorganized concepts, a consolidation center is placed between the sets and the suppliers. In this structure, larger volumes of goods are delivered from the consolidation center in larger vehicles (using larger capacity road vehicles or cargo trams in the two examined concepts) to the crossdocks of the sets. From the cross-docks, the goods are moved to the stores after deconsolidation. After describing the two reorganized system concepts to be investigated, I modeled the examined systems with mesoscopic level simulation [23]. The first step of the modeling was to develop a mathematical model describing the logistic processes and the cost structure. Finally, a mesoscopic-level discrete event simulation was built for the examined concepts. In all cases, 30day periods were considered. I built the simulation model in MS Excel. After verification, validation, and experiment design, I compared the current system with the reorganized concepts based on the simulation results. In the current system, 6860 delivery transactions/ month are required to serve the 344 modeled stores in 6 examined concentrated sets of delivery locations, which is reduced to 3249 transactions in the reorganized concept using trucks (-52.6%) and 2703 transactions by using trams (-60.6%). As a result, the mileage, fuel consumption, and emissions will also be reduced. In the case of CO 2 , in the current system, 199.3 tons/ month are the emissions, compared to 91.9 tons in the truck-only solution (-53.9%) and 84.4 tons with cargo trams (-57.7%). It was also essential to examine the evolution of logistics costs. The current system‘s total logistics costs in one month are approx. 498000 EUR. In the reorga- Figure 1: Clustering of urban delivery locations Urban transportation  LOGISTICS DOI: 10.24053/ IV-2024-0072 International Transportation (76) Collection ǀ 2024 7 4. Correlation between the city logistics development and the level of concentration As the next step, I investigated the relationship between the concentration of urban areas, their city logistics development level, and the city logistics development potential. For this, a ranking model was created based on the Analytic Hierarchy Process method [33]. The ranking model developed aims to assess the current city logistic development of urban zones and their potential for city logistic development. The ranking criteria were built around these objectives. Since two different ranking values (thus two different sets of criteria) had to be defined, applying two AHP-based rankings was necessary [34]. To assess the importance of the criteria, I used an expert evaluation process involving 18 experts. It was also required to define a fictive zone for the tests since AHP can only measure the zones compared to each other, so a theoretical zone with relatively good characteristics was added. Using the AHP-based ranking model, I examined Budapest‘s previously modeled concentrated sets. Based on the ranking results, all of them are currently in medium development and have medium development potential, which aligns with our previous observations. These results allowed us to examine the correlation between the concentration and the rankings. Next to the simple degree of concentration, the area-proportional degree of concentration was introduced, which defined how much store floor area could be found per unit of urban area. Based on correlation analysis between the rankings and the degrees of concentration, I concluded that the higher the simple degree of concentration, the more developed the examined zone is (medium correlation). It was also found that the higher the area-proportional degree of nized system, this value will decrease to approx. 405000 EUR when using trucks (-18.7%) and approx. 373000 EUR when using cargo trams (-25.2%), primarily because of the reduced delivery costs. The most critical parameters are compared in Figure 2, where the current system is 100%. Based on these results, the reorganized solutions will be more efficient and require fewer delivery transactions, with less consumption, lower emissions, and lower logistics costs. In the modeling phase, I also examined the application of cargo bikes based on the system‘s geometrical structure. Nowadays, they are increasingly used in city logistics, using a wide range of technologies [24] [25] [26] [27], usually combined with other transport modes [28] [29]. The related research results [30] [31] show that their integration can reduce emissions and congestion. In my research, I investigated how these devices could be integrated into the system of the concentrated sets. For this, I developed a new concept based on the radial urban structure, dividing the sets into two groups: sets on the internal city ring and sets on the rays starting from the ring. In the concept, there is a consolidation center, larger trucks can make deliveries to the cross-docks of the sets, and cargo bikes are used for the deliveries on the rays. For this, I defined a graph-theory-based model [32]. Based on this, I built a macroscopic simulation model to investigate the new concept with different cargo bike technologies, which can serve 14.9%-46.9% of the stores in the system. In the case of all the shopping malls in Budapest, 19-20 trucks and 19-38 cargo bikes will be needed based on the simulation. This shows that integrating a relatively small number of cargo bikes in the new concept could efficiently move large volumes of goods, relieving congestion. concentration, the less developed the zone is (medium/ high). Regarding development potentials, the higher the simple degree of concentration, the less developable the zone is (weak/ medium), and the higher the areaproportional degree of concentration, the more developable the zone is (high). 5. Summary In the research related to the concentrated sets, there are several possible future directions. One of these is the further development of the simulation models. For this, the MS Excel-based models are replaced by Python-based DES models [35]. Another significant research direction is to explore the potential use of drones in the examined system [36]. Next to this, as investment issues are also important, the sizing of system components should be examined; here, the cross-docks and the loading areas are the most important. In addition, I will pay special attention to the new concepts with cargo trams and urban waterway solutions. In summary, I can say that my research has produced a new city logistics toolkit to help research projects and developments. In my research, a new clustering and data collection methodology was developed to provide data for projects. If we already know the characteristics of the sets, we can model their systems; for this, mesoand macroscopic-level models are available. Finally, once the sets have been modeled, it will be possible to rank them, for which the ranking methodology has already been developed. These tools are planned to be used in several projects, and we have already incorporated them into several research proposals (e.g., HORIZON2020). Additionally, we are also developing cooperation with the Centre for Budapest Transport, the Municipality of Budapest, and other relevant stakeholders, within the framework of which we expect to participate in several projects aimed at developing the city logistics system of Budapest with this toolkit. ■ REFERENCES [1] GKI Digital (2021). 2020-ban három évet ugrott előre az e-kereskedelem. URL: https: / / gkidigital. hu/ 2021/ 03/ 25/ 2020-online-kiskereskedelem/ (Accessed on 24/ 09/ 2024) [2] European Comission (2022). 2030 Climate Target Plan. URL: https: / / ec.europa.eu/ clima/ eu-action/ eur opean gre en deal/ 2030 climate -tar getplan_en (Accessed on 24/ 09/ 2024) [3] European Commission (2020). 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Application of microscopic discrete event-based simulation in the modeling of the city logistics systems of concentrated sets of delivery locations. Journal of Simulation, online. DOI: https: / / www.doi.org/ 10.1080/ 17477778.202 3.2272967 [36] Dávid Lajos Sárdi, Krisztián Bóna, PhD (2021). Application possibilities of delivery drones in the case of concentrated sets of delivery locations in Budapest. : Editor: Tomislav Letnik. pp. 127-142. URL: https: / / www.fgpa.um.si/ wp-content/ uploads/ 2023/ 10/ Conference-Proceedings_ compressed.pdf (Accessed on 24/ 09/ 2024) Photo credits: © Dávid Lajos Sárdi Dávid Lajos Sárdi, Ph.D., Senior lecturer, Budapest University of Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Department of Material Handling and Logistics Systems david.sardi@logisztika.bme.hu ORCID: 0000-0002-1585-3503 Urban transportation  LOGISTICS DOI: 10.24053/ IV-2024-0072 International Transportation (76) Collection ǀ 2024 9