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# Multi-stakeholder Insights on Integrating Public Transport for Urban Freight Deliveries

Cécile Dupouy, François Clautiaux, Walid Klibi, Olivier Labarthe

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Cécile Dupouy, François Clautiaux, Walid Klibi, Olivier Labarthe. Multi-stakeholder Insights on Integrating Public Transport for Urban Freight Deliveries. IPIC 2025 - 11th International Physical Internet Conference, The Hong Kong Polytechnic University, Jun 2025, Hong Kong, China. 10.35090/gatech/13234. hal-05244277

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# Multi-stakeholder insights on integrating public transport for urban freight deliveries.

Cécile Dupouy¹,², François Clautiaux², Walid Klibi¹ and Olivier Labarthe¹

1. The Center of Excellence in Supply Chain Innovation & Transportation (CESIT), Kedge Business School, Bordeaux, France.

2. Université de Bordeaux, Institut de Mathématiques de Bordeaux, UMR CNRS 5251, Centre Inria de l'Université de Bordeaux, France

Corresponding author: cecile.dupouy@kedgebs.com

**Abstract:** This paper explores the integration of public transport networks for urban freight deliveries within the framework of Hyperconnected City Logistics (HCL), focusing on multi-stakeholder perspectives. By synergizing freight and passenger networks, the study optimizes parcel consolidation and containerization in the urban middle-mile, efficiently moving parcels between access hubs during off-peak hours to reduce reliance on dedicated freight vehicles. The model is validated through computational experiments based on public transport system, evaluating various collaboration strategies among multiple logistics service providers. Specifically, it examines three consolidation policies: independent, where each provider reserves its own vehicle; partially shared, where different providers share the same vehicle, but containers remain separate; and fully integrated, where parcels from different providers are consolidated in the same container. To compare policies, a realistic case study based on the city of Bordeaux, provides insights into the operational and collaborative potential of integrating public transport into urban logistics.

**Keywords:** Physical Internet, Hyperconnected City Logistics, Freight transportation, Urban mobility, Public Transportation.

**Physical Internet (PI) Roadmap Fitness:** Select the most relevant area(s) for your paper according to the PI roadmaps adopted in Europe and Japan: ☐ PI Nodes (Customer Interfaces, Logistic Hubs, Deployment Centers, Factories), ☐ Transportation Equipment, ☐ PI Networks, ☒ System of Logistics Networks, ☐ Vertical Supply Consolidation, ☐ Horizontal Supply Chain Alignment, ☐ Logistics/Commercial Data Platform, ☐ Access and Adoption, ☐ Governance.

**Targeted Delivery Mode-s:** ☒ Paper, ☐ Poster, ☐ Flash Video, ☐ In-Person presentation

# 1 Introduction

## 1.1 Motivation

Traditional freight urban delivery systems rely on dedicated vehicles, infrastructures, and flows. However, with the rapid growth of e-commerce sales and the increasing demand for same-day deliveries, urban deliveries with vehicles have surged (Faugère et al., 2022). At the same time, growing urban population density has led to significant passenger flows, supported by dedicated networks of private cars, public buses, tramways, and infrastructures such as roads and rails. Urban areas benefit from diverse public transport services that provide access to pedestrian zones in city centers. While public transport networks operate at full capacity during rush hours, they often have underutilized spare capacity during off-peak periods. Leveraging this existing
infrastructure for freight transport could significantly reduce the reliance on dedicated delivery vehicles (Fatnassi et al, 2015).

Even though the freight and people mobility networks operate similarly in the same environment, the traditional practical scheme imposes a separation between them regarding flows, infrastructures, and resources. The Physical Internet (PI) concept introduced in Montreuil (2011) proposes connecting people, objects, stakeholders, and networks in a unified, open, interconnected system. When applied to urban environments, the concept of Hyperconnected City Logistics (HCL, Crainic et al., 2023) emerges. The HCL concept of integration and interconnection of passenger and freight movements in urban transit systems establishes synergies to move people and freight simultaneously.

<figure><img src="image_3.png" /><figcaption>(a) Amazon tramway, Frankfurt, Germany (2024)</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>(b) La Poste, tramway, Strasbourg, France (sept-oct 2024)</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>(c) GLS, metro, Madrid, Spain (sept 2024)</figcaption></figure>

<caption>Figure 1: Projects integrating public transportation into urban freight delivery</caption>

Recently, several projects have tested the integration of public transportation networks into urban freight deliveries, highlighting the potential of this approach. In Frankfurt, Germany, Amazon operates the Gütertram to transport parcels (Figure 1a). In Strasbourg, France, La Poste, the French postal service, conducted a two-month pilot project (September-October 2024) to evaluate the feasibility of parcel deliveries inside tramways alongside passengers (Figure 1b). In Madrid, Spain, GLS and the metro of Madrid launched the M4G project, using one metro line for freight transportation since September 2024 (Figure 1c). All these projects rely on the principle of containerization, where parcels traveling in the same direction are grouped into containers before being loaded onto public transport. This approach streamlines handling, loading, and unloading operations at hubs, improving efficiency and facilitating seamless integration into an existing network (Kaboudvand et al. 2021, Montreuil et al. 2018). Furthermore, parcel consolidation provides notable environmental benefits by enabling the pooling of supply networks from different stakeholders reducing CO2 emissions (Ballot et al. 2010).

## 1.2 Business context

We consider a parcels' urban delivery system where the public transportation network is appended to a traditional delivery schema to move parcels by dedicated trucks, as characterized in Labarthe et al. (2024). We structure urban logistics around three tiers as represented in Figure 2: the urban first-mile where Logistics Service Providers (LSP) connect local hubs; the urban middle-mile corresponding to the movement of parcels within the city and access hub, and the urban last-mile connecting pick-up or delivery points. Connections and synchronization among LSPs occur between each tier (Delle Donne et al., 2025).
<figure><img src="image_6.png" /><figcaption>Figure 2: Three-tier urban delivery network.</figcaption></figure>

The scope of the synergized network studied in this work is delimited at the urban middle-mile section corresponding to the movement of parcels between access hubs within the city. It starts at an origin access hub where parcels of various logistics service providers arrive by trucks (from a local hub) and ends at a destination access hub where the parcels need to be collected by urban operators for urban last-mile delivery by cargo bikes to their final destination. Similarly, the urban middle-mile also facilitates the upstream movement of parcels collected from customers at pickup points. In this case, last-mile operators bring the parcels to an access hub, from where they are transported through the network to another access hub, before reaching a local hub for further processing. To perform the urban middle-mile, our system offers the possibility of using public transportation services, including different modes and lines. If a demand cannot be served through the public transportation network, an alternative using private freight vehicles is allowed to ensure demand satisfaction. Workforces are deployed in unit zones to authorize the transfer of parcels between public transportation lines and to manage their entry or exit from the network. This flexible approach enables multiple transfers within the public transportation network to use all available lines and modes. Demands from multiple stakeholders are shaped by the number of parcels that need to be delivered within a city divided into predefined unit zones with designated access hubs and stops. These demands originate and terminate in specific unit zones, similarly to Faugère et al. (2022).

The proposed approach uses containerization, where parcels travelling in the same direction are grouped into urban containers to facilitate operations at transfer hubs. This strategy is particularly relevant in scenarios using multiple stakeholders as it allows the implementation of different degrees of collaboration. LSPs can operate independently, each reserving dedicated vehicles and containers or adopt consolidation and containerization strategies to share resources. As we consider multiple LSPs operating within this urban logistics network, an external orchestrator is required to ensure efficient coordination and resource allocation. This orchestrator is responsible for managing the shared infrastructure, synchronizing freight flows, and optimizing the use of transport capacity across different actors. It can be a dedicated entity, a specific LSP, an actor mandated by the city, or a public transport operator (Kwon et al., 2023, Zhang et al., 2025).
As outlined by Mohri (2024), the use of standardized containers in multi-mode delivery systems offers several operational benefits, particularly in terms of reducing fixed and operational costs at transfer access hubs. Modular vehicle concepts, when coupled with consolidation strategies, have also shown strong potential to improve the efficiency of urban logistics by reducing empty kilometers and operating costs (Hatzenbühler et al., 2023). Labarthe et al. (2024) introduced the concept of urban synchromodality, emphasizing the synergies between freight and passenger mobility, highlighting its potential to reduce the time and space consumed by containers in the network. Synchromodal systems utilizing standardized containers also contribute to a reduction in the environmental footprint (Lemmens et al., 2019). However, most of the research is focused on a single actor. In contrast, the concept of multi-stakeholders, multi-modal logistics, as discussed by Montreuil (2018), enables collaboration between multiple logistics stakeholders. Modular containerization, as proposed in this context, facilitates shared resources and maximizes space utilization across various stakeholders. At the operational level, collaboration between stakeholders is essential to optimize resource allocation and reduce empty runs and avoid duplication of services (Zhang et al. 2025).

Integration of public transport and freight logistics requires attention to operational attributes such as space allocation, reliability, and coordination between actors. Yet, few studies address how such integration can support multi-stakeholder, consolidated containerization at the short-term planning level. Focusing on the operational problem of short-term planning, this study evaluates how different consolidation strategies impact LSPs' operational performance, providing key managerial insights into the benefits of containerization in a multi-mode, multi-line integrated public transportation system.

The paper is organized as follows. In section 2, our proposed approach is presented, including levels of consolidation and modelling approach. In section 3, we present the case study and the results. Finally, section 4 concludes this paper.

# 2 Proposed approach

## 2.1 Levels of consolidation

To respond to the business context presented and assess the feasibility and efficiency of integrating freight transport within the public transit system, we explore different consolidation strategies between logistics stakeholders. Specifically, we analyze the level of collaboration among logistics service providers. In many urban settings, multiple logistics stakeholders operate independently, each reserving its own dedicated transport capacity, leading to some resource underutilization (Zhang et al. 2025). We evaluate three levels of collaboration among stakeholders in using public transport for freight movements. In the *independent policy*, each LSP reserves its own dedicated public transport vehicle to carry its dedicated containers. In the *partially shared policy*, the same public transport vehicle is shared by different LSP, but each container remains assigned to a single LSP, meaning that consolidation can only occur at the vehicle level, not at the parcel level. Finally, in the *fully consolidated policy*, parcels from different LSPs are consolidated within the same container, maximizing space utilization. Figure 3 illustrates these three levels of consolidation using an example with two stakeholders, the approach can be extended to multiple actors.
<figure><img src="image_7.png" /><figcaption>Figure 3: Levels of consolidation.</figcaption></figure>

In the partially shared policy, the reserved public transport vehicle does not belong to either stakeholder 1 or stakeholder 2 but is instead managed by an external orchestrator. Similarly, in the fully consolidated policy, not only the vehicle but also the containers are managed by this orchestrator.

## 2.2 Modeling

To compare the level of consolidation, we developed the operational problem of short-term planning for studying the flow of parcels and their consolidation into containers within a multi-mode, multi-line, multi-stakeholder integrated public transportation system. The objective function is different for each consolidation levels, reflecting the different operational cost implications for stakeholders. The model aims to minimize the total cost including reservation costs for public vehicles ($w^R$), and transportation costs ($w_a$) based on parcel ($y$) and container ($x$) operational decisions.

In the *independent policy*, each stakeholder ($s \in S$) operates separately, reserving its own number of dedicated public transport vehicles ($z_s$), and using its individual containers $q \in Q^s$. The objective function (1a) minimizes the total reservation costs and the operational costs of parcels $c \in C^s$ and containers $q \in Q^s$ for each stakeholder $s$.

$$ \text{Min} \sum_{s \in S} w^R z_s + \sum_{s \in S} \left( \sum_{q \in Q^s} \sum_{a \in A^q} w_a x_a^q + \sum_{c \in C^s} \sum_{a \in A^c} w_a y_a^c \right) \quad (1a) $$

In the *partially shared policy*, stakeholders can share the same public transportation vehicle while still using separate containers $q \in Q^s$ for their respective parcels $c \in C^s$. The decision variable $z$ correspond to the total number of public vehicles reserved. The objective function (1b) accounts for the shared vehicle reservation cost ($w^R z$) while maintaining parcels and containers costs for each stakeholder $s$.

$$ \text{Min} \ w^R z + \sum_{s \in S} \left( \sum_{q \in Q^s} \sum_{a \in A^q} w_a x_a^q + \sum_{c \in C^s} \sum_{a \in A^c} w_a y_a^c \right) \quad (1b) $$

Finally, in the *fully consolidated policy*, stakeholders consolidate their parcels into shared containers allowing vehicle and container consolidation. The objective function (1c) minimizes the reservation cost for the shared vehicle, the operational cost for shared containers $q \in Q$ and the individual parcel $c \in C^s$ operational cost for each stakeholder $s$.

$$ \text{Min} \ w^R z + \sum_{q \in Q} \sum_{a \in A^q} w_a x_a^q + \sum_{s \in S} \sum_{c \in C^s} \sum_{a \in A^c} w_a y_a^c \quad (1c) $$
The three policies are subject to the same set of constraints. Capacity constraints regulate the number of containers transported within public transport vehicles, the volume of parcels that can be loaded into each container, and the number of handling operations that can be performed by operators within a given zone. The operational model is formulated as an arc-flow optimization problem, ensuring flow conservation for both containers and parcels. Additionally, linking constraints enforce that parcels are transported exclusively within their assigned containers when applicable.

# 3 Case study

## 3.1 Bordeaux Case study presentation

The proposed operational model is validated through computational experiments on scenarios inspired by Bordeaux's, France, public transport network, chosen for its extensive infrastructure and availability of open data (L'atelier Opendata). This study considers two different network configurations. The first configuration represented in *Figure 4a* considers two tramway lines while in the second configuration as shown in *Figure 4b*, the network is expanded to four lines including three tramway and one bus lines. The addition of new lines enables the system to serve a larger geographical area and reach new demand zones.

<figure><img src="image_8.png" /><figcaption>Figure 4 Public transport networks</figcaption></figure>

In addition to the variation of the public transport network, the number of logistics stakeholders involved in the system is also varied. The experiments are conducted with two and three stakeholders to analyze the impact of the consolidation levels on network performance and resource utilization.

## 3.2 Results and discussion

By leveraging the mathematical formulation of our short-term planning model, we evaluate how different levels of consolidation impact network utilization, delivery efficiency, and cost-effectiveness for all stakeholders. Consolidation levels are assessed using key performance indicators. The first indicator is the impact of consolidation levels on public transportation use. The second indicator is the total operational cost, including both the reservation of public transport vehicles and the handling operations. Finally, we compare the container usage with their routes and their average time spent within the system. All the results presented in the following subsections are based on scenarios with 150 parcel requests distributed over a two-hour operational window.
**3.2.1 Impact of consolidation levels on public transportation use**

In this section, three logistics service providers operate within the system under the three previously defined levels of consolidation using 2 tramway lines.

<figure><img src="image_9.png" /><figcaption>Figure 5: Demand delivered with public transport - 2 lines</figcaption></figure>

*Figure 5* illustrates the proportion of parcel demand delivered via public transport for each of the three stakeholders (S0, S1, S2), under the three consolidation policies. The results reveal a consistent increase in public transport utilization as the level of consolidation increases. While the independent strategy results in lower shares (64% for Stakeholder 0), the fully consolidated case reaches up to 90% of demand delivered with public transportation. This evolution highlights that greater collaboration leads to more deliveries being absorbed by the public transport network rather than relying on dedicated freight vans. This transition has the potential to reduce the number of freight vehicles circulating in dense urban areas. Notably, even partial collaboration already leads to improvements in transport efficiency and network utilization.

**3.2.2 Impact of consolidation levels on operational cost.**

We provide a detailed analysis of operational costs across different consolidation levels. These costs include the direct delivery cost (identical for all stakeholders), incurred when parcels cannot be delivered with public transport; the operational cost, which covers handling and movement of parcels and containers; and the reservation cost, for the reserved capacity on public transport vehicles. It is important to note that only short-term planning costs are considered in this study.

<figure><img src="image_10.png" /><figcaption>(a) Two stakeholders</figcaption></figure>

<caption>(b) Three stakeholders</caption>

<caption>Figure 6: Comparison of cost repartition per stakeholder</caption>
Figures 6 confirms that consolidation significantly reduces the total system cost. Moving from the independent policy to the fully consolidated one, the total cost decreases by 23.3% in the case of two stakeholders (Figure 6a) and by 34.0% in the case of three stakeholders (Figure 6b). This highlights that the benefits of consolidation increase with the number of involved actors. Figure 6 also illustrates how the cost decreases at the stakeholder level. In the fully consolidated policy, the introduction of an orchestrator allows for a more balanced allocation of costs and significantly reduces the individual expenses incurred by each logistics service provider. For each stakeholder, direct delivery costs correspond to the dominating cost. Direct delivery costs are reduced through consolidation, reflecting the increase of resource sharing. In both the independent and partially shared policies, direct delivery represents the largest cost component, accounting for more than half of the total costs. For instance, in the case with three stakeholders, direct delivery costs decrease by 58% from the independent policy to the full consolidation. This substantial reduction illustrates the effectiveness of containerized consolidation in enabling more parcels to be delivered via public transport.

### 3.2.3 Impact of consolidation levels on container routes

To illustrate the operational differences induced by varying consolidation policies, we compare the container routes observed under the *independent* and *partially shared* consolidation policies. In the case with three logistics stakeholders involved and four public transport lines.

<figure><img src="image_11.png" /><figcaption>Figure 7: Container routes per stakeholder</figcaption></figure>
Figure 7 illustrates the paths used by containers for each stakeholder using an *independent* or *partially shared* consolidation policy. Under the *independent* policy, each stakeholder reserves its own public transportation vehicle and container. In contrast, the *partially shared* policy allows containers from different stakeholders to share capacity on the same public transport trips, resulting in a more extensive use of the network. This is visible in the lower row of the Figure 7, where several routes not activated under the *independent* policy are now utilized. This shift in policy translates into an improvement in modal share: the proportion of parcel demand served by public transport increases from an average of 39% under the *independent* policy to 54% under the *partially shared* policy.

<table><caption>Table 1: Container fill rate per consolidation level and owner.</caption><thead><tr><th rowspan="2">Container owner</th><th colspan="3">Independent</th><th colspan="3">Partially shared</th><th rowspan="2">Fully consolidated<br>Orchestrator</th></tr><tr><th>S0</th><th>S1</th><th>S2</th><th>S0</th><th>S1</th><th>S2</th></tr></thead><tbody><tr><td>Container used</td><td>100%</td><td>100%</td><td>100%</td><td>100%</td><td>100%</td><td>100%</td><td>100%</td></tr><tr><td>Average container fill rate</td><td>67.6%</td><td>67.2%</td><td>70.6%</td><td>67.1%</td><td>68.7%</td><td>78.9%</td><td>82%</td></tr><tr><td>Average time for containers (s)</td><td>3621</td><td>3669</td><td>3173</td><td>4093</td><td>4250</td><td>3870</td><td>4000</td></tr></tbody></table>

Table 1 illustrates the average container fill rate per stakeholder under the different consolidation policies. In the *independent* and *partially shared* policies, each stakeholder retains ownership of their 5 containers, resulting in variable fill rates. While stakeholders S0 and S1 display relatively stable averages across the two policies, stakeholder 2 achieves a notable increase from 70.6% to 78.9% when transitioning to the *partially shared* setting. This highlights that the opportunity to share public transport vehicles can significantly benefit stakeholders with more spatially dispersed demand. Under the *fully consolidated* policy, container ownership is centralized under an *orchestrator* who manages both routing and consolidation across all demand requests. This centralization improves the average fill rate to 82%. As a result, containers are more frequently present in the network due to higher fill rates, spending an average of more than 1h in the network across the two-hour interval of the study. In addition, the maximum time spent by a container in the network reaches up to 1 hour and 36 minutes, reflecting the extended duration that containers remain in the system when consolidation is at a higher level.

# 4 Conclusion

This study presents an exploration of integrating public transport networks into urban freight logistics, contributing to the concept of Hyperconnected City Logistics. We propose a short-term planning that coordinates parcel consolidation, containerization, and multimodal routing within the urban middle-mile. By focusing on multi-stakeholder perspectives, the proposed model evaluates three consolidation strategies: *independent*, *partially shared* and *fully consolidated*. Our computational experiments, based on Bordeaux's public transport system, confirm that consolidation within multi-stakeholder networks can significantly improve resource utilization and reduce operational costs. In particular, the *fully consolidated* policy, where parcels from multiple logistics service providers share containers, proves to be the most cost-effective and resource-efficient, allowing for optimal use of available transport capacity. Future research could extend this model along complementary directions. First, by incorporating environmental considerations to assess the ecological benefits of consolidation strategies. Second, by introducing tactical decisions on the number and allocation of operational resources. Third, by exploring strategic aspects such as the selection of transport lines and stops
to include in the network. Finally, a game-theory approach could be adopted to study prioritization mechanisms balancing the interests of multiple stakeholders under limited capacity.

## References

* Ballot, E., & Fontane, F. (2010). *Reducing transportation CO2 emissions through pooling of supply networks: perspectives from a case study in French retail chains*. Production Planning & Control, 21(6), 640-650.

* Crainic, T. G., Klibi, W., & Montreuil, B. (2023). *Hyperconnected city logistics: a conceptual framework*. In Handbook on city logistics and urban freight (pp. 398-421). Edward Elgar Publishing.

* Delle Donne, D., Santini, A., & Archetti, C. (2025). *Integrating public transport in sustainable last-mile delivery: Column generation approaches*. European Journal of Operational Research.

* Fatnassi, E., Chaouachi, J., & Klibi, W. (2015). *Planning and operating a shared goods and passengers on-demand rapid transit system for sustainable city-logistics*. Transportation Research Part B: Methodological, 81, 440-460.

* Faugère, L., Klibi, W., White III, C., & Montreuil, B. (2022). *Dynamic pooled capacity deployment for urban parcel logistics*. European Journal of Operational Research, 303(2), 650-667.

* Hatzenbühler, J., Jenelius, E., Gidófalvi, G., & Cats, O. (2023). *Modular vehicle routing for combined passenger and freight transport*. Transportation Research Part A: Policy and Practice, 173, 103688.

* Kaboudvand, S., Montreuil, B., & Savelsbergh, M. (2021). *Hyperconnected Megacity Parcel Logistic: Joint Parcel Routing and Containerized Consolidation*. arXiv preprint arXiv:2103.02080.

* Kwon, S., Montreuil, B., Dahan, M., and Klibi, W. (2023). *Hyperconnected logistic service networks: Bidding-based design framework*. In IPIC 2023-9th International Physical Internet Conference

* Labarthe, O., Ahmadi, G., Klibi, W., Deschamps, J. C., & Montreuil, B. (2024). *A sustainable on-demand urban delivery service enabled by synchromodality and synergy in passenger and freight mobility*. Transportation Research Part C: Emerging Technologies, 161, 104544.

* Lemmens, N., Gijsbrechts, J., & Boute, R. (2019). *Synchromodality in the Physical Internet–dual sourcing and real-time switching between transport modes*. European Transport Research Review, 11, 1-10.

* L'atelier opendata Bordeaux: https://opendata.bordeaux-metropole.fr/explore/dataset/offres-de-services-bus-tramway-gtfs/export/

* Mohri, S. S., Mohammadi, M., & Van Woensel, T. (2024). *Designing zero-emissions containerized last-mile delivery systems: A case study for Melbourne*. Transportation Research Part C: Emerging Technologies, 159, 104492.

* Montreuil, B. (2011). *Toward a physical internet: Meeting the global logistics sustainability grand challenge*. Logistics Research, 3, 71–87.

* Montreuil, B., Buckley, S.M., Faugere, L., Khir, R., Derhami, S. (2018). *Urban parcel logistics hub and network design: the impact of modularity and hyperconnectivity*. 15th IMHRC Proceedings (Savannah, Georgia. USA – 2018)

* Zhang, Y., Tan, X., Gan, M., Liu, X., & Atasoy, B. (2025). *Operational synchromodal transport planning methodologies: Review and roadmap*. Transportation Research Part E: Logistics and Transportation Review, 194, 103915.