Deliverable 1: Collaborative Business Modelling - ERP Future Proof Smart Logistics: Results year 1
report
Logistics Service Providers (LSPs), companies offering transport and logistic services between carrier, shipper and receiver (Karam et al., 2021; Zenezini et al., 2019), often operate vehicles with empty containers, representing an estimated 12% (Europe) to 22% (nationally) of total mileage (Karam et al., 2021). As empty milage is one of the biggest logistical problems, reducing these empty trips has become essential – not only to improve cost efficiency in a market characterized by tight margins, but also to lower CO₂ emissions caused by non-productive transport movements (Matusiewicz & Książkiewicz, 2023). {Citation}
While individual LSPs have optimized their planning processes extensively, the potential for further efficiency gains within a single company is now limited. To achieve additional improvements, the sector is exploring Horizontal Transport Collaboration (HTC) – a “bundling transport of competitors, i.e., companies operating on the same level of the supply chain, who have similar or complementary transportation needs” (Vanovermeire et al., 2014). Research has shown that such collaboration can, in theory, improve economic performance, sustainability, operational efficiency, and strategic resilience (e.g., Durán-Micco et al., 2025; Grote et al., 2023; Zenezini et al., 2019). In practice, however, successful examples remain scarce, largely because collaboration among competitors introduces challenges such as trust deficits and unequal benefit distribution (Ahmadi et al., 2024; Durán-Micco et al., 2025; Karam et al., 2021).
To address these challenges, TNO – the Netherlands Organization for Applied Scientific Research – in the Exploratory Research Program ‘Future Proof Smart Logistics’ is developing a Collaborative Fleet Management System (CFMS) consisting of a decentralized planning algorithm supported by a data space. A data space is a common digital infrastructure and governance framework to help support the sharing and exchange of data for economic and societal impact, whilst simultaneously keeping individuals and companies owning the data in control (Commission, 2020). Data spaces adhere to secure and trustworthy data sharing principles, which guarantee control over the access and use of data shared by the data provider (Möller et al., 2024). The decentralized planning algorithm uses Multi-Party Computation (MPC) to match deliveries to pickups in a blind manner in several steps. In the first step, the parties collaboratively calculate a cost matrix in secret-shared form. Then, a modified, MPC-friendly version of the Hungarian algorithm is applied which assigns deliveries to pickups. Lastly, the delivery pickup pairs are assigned to companies in an efficient way (Leder et al., 2025). This decentralized approach removes the need for a central coordinating party and includes mechanisms for fair yield distribution among participants. These features help to reduce some of the main barriers to HTC.
Nonetheless, technological solutions alone are insufficient. Trust and governance issues continue to hinder collaboration (Vargas et al., 2020; Vargas et al., 2018). One example is Boxreload, an initiative where at its peak more than 40 transport companies coordinated their planning. The initiative eventually collapsed because there were no clear agreements on how to handle undesirable situations. Companies began sharing only their ‘leftover trips’ instead of their full schedules, resulting in increasingly inefficient shared planning and a gradual loss of interest from participants.
Collaborative business models are suggested to be an effective approach to overcome such trust issues, governance barriers and technology and information sharing barriers in HTCs (Vargas et al., 2020; Vargas et al., 2018). Therefore, this research focuses on developing a collaborative business model – a structured framework that defines how collaborating LSPs share value, allocate costs and responsibilities, and agree on governance arrangements – for the creation of the decentralized planning system.
Although collaborative business models have been proposed as a promising approach to strengthen trust and fairness in HTCs, their practical application remains limited (Vargas et al., 2020; Vargas et al., 2018). Therefore, this project aims to develop and test such a model in a use case involving six LSPs – Transportbedrijf G. van der Heijden & Zonen BV, Vepco, Kamps Transport, HebraGTO, H.N. Post & Zonen and Kooy Transport – that will implement TNO’s CFMS. In specific, our part of the project will deliver:
-A scalable collaborative business model that can serve as a reference for other groups of LSPs using the same system.
-A practical modelling process that guides new groups of LSPs in designing their own collaboration model.
In addition, a well-functioning value network around the decentralized planning system must be established. This network comprises the broader set of organizations involved in developing, operating, and commercializing the system, such as transport management system providers, logistics consultancies, and a knowledge center. To support this, we will also design a roadmap collaborative business model for the wider ecosystem as the system evolves from development to exploitation.
These objectives lead to two central research questions:
-How can a collaborative business model be designed for a group of LSPs using adecentralized planning system?
-What is the roadmap for a collaborative business model for the value network that supports this system?
The following chapters outline how we approached these questions. We start with a review of the relevant literature, examining research on business models for collaboration, logistics, and data spaces, as well as literature on coopetition, which offers useful perspectives on governing collaboration among competitors – an important aspect of this case. We then present illustrative examples based on archival source (such as news articles and reports) and a series of interviews with the involved stakeholders. From these materials, we derive key lessons learned, which inform the development of an initial blueprint for the collaborative business modelling process for both the HTC and the value network. Finally, we describe how this blueprint was applied in the use case, summarizing the outcomes of the first workshop conducted with the five participating parties and outlining the next steps for further validation.
While individual LSPs have optimized their planning processes extensively, the potential for further efficiency gains within a single company is now limited. To achieve additional improvements, the sector is exploring Horizontal Transport Collaboration (HTC) – a “bundling transport of competitors, i.e., companies operating on the same level of the supply chain, who have similar or complementary transportation needs” (Vanovermeire et al., 2014). Research has shown that such collaboration can, in theory, improve economic performance, sustainability, operational efficiency, and strategic resilience (e.g., Durán-Micco et al., 2025; Grote et al., 2023; Zenezini et al., 2019). In practice, however, successful examples remain scarce, largely because collaboration among competitors introduces challenges such as trust deficits and unequal benefit distribution (Ahmadi et al., 2024; Durán-Micco et al., 2025; Karam et al., 2021).
To address these challenges, TNO – the Netherlands Organization for Applied Scientific Research – in the Exploratory Research Program ‘Future Proof Smart Logistics’ is developing a Collaborative Fleet Management System (CFMS) consisting of a decentralized planning algorithm supported by a data space. A data space is a common digital infrastructure and governance framework to help support the sharing and exchange of data for economic and societal impact, whilst simultaneously keeping individuals and companies owning the data in control (Commission, 2020). Data spaces adhere to secure and trustworthy data sharing principles, which guarantee control over the access and use of data shared by the data provider (Möller et al., 2024). The decentralized planning algorithm uses Multi-Party Computation (MPC) to match deliveries to pickups in a blind manner in several steps. In the first step, the parties collaboratively calculate a cost matrix in secret-shared form. Then, a modified, MPC-friendly version of the Hungarian algorithm is applied which assigns deliveries to pickups. Lastly, the delivery pickup pairs are assigned to companies in an efficient way (Leder et al., 2025). This decentralized approach removes the need for a central coordinating party and includes mechanisms for fair yield distribution among participants. These features help to reduce some of the main barriers to HTC.
Nonetheless, technological solutions alone are insufficient. Trust and governance issues continue to hinder collaboration (Vargas et al., 2020; Vargas et al., 2018). One example is Boxreload, an initiative where at its peak more than 40 transport companies coordinated their planning. The initiative eventually collapsed because there were no clear agreements on how to handle undesirable situations. Companies began sharing only their ‘leftover trips’ instead of their full schedules, resulting in increasingly inefficient shared planning and a gradual loss of interest from participants.
Collaborative business models are suggested to be an effective approach to overcome such trust issues, governance barriers and technology and information sharing barriers in HTCs (Vargas et al., 2020; Vargas et al., 2018). Therefore, this research focuses on developing a collaborative business model – a structured framework that defines how collaborating LSPs share value, allocate costs and responsibilities, and agree on governance arrangements – for the creation of the decentralized planning system.
Although collaborative business models have been proposed as a promising approach to strengthen trust and fairness in HTCs, their practical application remains limited (Vargas et al., 2020; Vargas et al., 2018). Therefore, this project aims to develop and test such a model in a use case involving six LSPs – Transportbedrijf G. van der Heijden & Zonen BV, Vepco, Kamps Transport, HebraGTO, H.N. Post & Zonen and Kooy Transport – that will implement TNO’s CFMS. In specific, our part of the project will deliver:
-A scalable collaborative business model that can serve as a reference for other groups of LSPs using the same system.
-A practical modelling process that guides new groups of LSPs in designing their own collaboration model.
In addition, a well-functioning value network around the decentralized planning system must be established. This network comprises the broader set of organizations involved in developing, operating, and commercializing the system, such as transport management system providers, logistics consultancies, and a knowledge center. To support this, we will also design a roadmap collaborative business model for the wider ecosystem as the system evolves from development to exploitation.
These objectives lead to two central research questions:
-How can a collaborative business model be designed for a group of LSPs using adecentralized planning system?
-What is the roadmap for a collaborative business model for the value network that supports this system?
The following chapters outline how we approached these questions. We start with a review of the relevant literature, examining research on business models for collaboration, logistics, and data spaces, as well as literature on coopetition, which offers useful perspectives on governing collaboration among competitors – an important aspect of this case. We then present illustrative examples based on archival source (such as news articles and reports) and a series of interviews with the involved stakeholders. From these materials, we derive key lessons learned, which inform the development of an initial blueprint for the collaborative business modelling process for both the HTC and the value network. Finally, we describe how this blueprint was applied in the use case, summarizing the outcomes of the first workshop conducted with the five participating parties and outlining the next steps for further validation.
Topics
TNO Identifier
1028709
Publisher
TNO
Collation
33 p.