The transport sector is one of the most significant contributors to European GHG emissions and is expected to grow even further in the coming years. The target of the European Union to reduce transport-related GHG emissions by 55% by 2030 seems to be a challenging task, keeping in mind the projected growth rates of the sector. In order to achieve the set-out targets, transparent and standardised GHG emissions quantification methodologies and reporting schemes must exist to monitor the GHG emissions of vehicles and reduce them where possible. Vehicle emissions used to be approximated with standard emission factors per vehicle class. However, the accuracy of these traditional emission factors is limited, especially on a larger scale, such as the European Union, leading to inaccurate vehicle emissions. Thus, primary fuel consumption data could be used to calculate the emissions of vehicles accurately by collecting the primary data via onboard sensors. The combination of data management structures for primary data in road logistics with the possibility of improving the accuracy of emissions calculations and reporting from a socio-technical perspective is currently not sufficiently addressed in scientific literature. The study is also highly relevant from a private interest, as new legislative decisions force private companies to declare their emissions on only validated and correct emissions factors.

The research aimed to investigate the current practices of using vehicles’ primary data to improve GHG emissions’ accuracy by creating a system architecture for the data flow from the vehicle to the final visualisation of the GHG emissions. For that, the design science research methodology (DSRM) approach was chosen to answer the main research question of:

”What onboard sensor systems architecture can enable road logistics operators to gather primary data from their fleet to accurately determine their vehicle emissions?”

Four sub-questions were formulated in line with the used DSRM design cycle to answer the main research question and to contribute to the existing body of knowledge via a socio-technical analysis, system requirements, system architecture, and an evaluation.

The research utilised interviews, scientific literature, and informal conversations with industry players as the main knowledge source. The expert interviews were first used during the design process to understand the environment, derive system requirements for the later design, and to create a stakeholder overview. In the second phase of the research, the experts were utilised to evaluate the created design. Interview partners were selected based on their role in the system and potential expertise to help steer the design and evaluation. The feedback received was directly implemented in the designs.
The first step of the analysis was the socio-technical analysis. It revealed the first requirements and design principles for the later design phase, based on the institutional setting and stakeholder demands derived from interviews and the available literature. It also showcased the active and influencing role of the EU in the system, which underlined the need for a socio-technical analysis. Lastly, the stakeholder overview visualised the transport sector’s highly fragmented and multi-stakeholder domain, which industry experts evaluated and approved.

The complete system requirements were established and finalised in the second phase of the research. They were separated into three clusters: institutional, stakeholder, and technical-related requirements and were further categorised into functional and non-functional system requirements. Design principles were also created to steer the design process. Six functional and ten non-function system requirements were derived and four design principles. The requirements were evaluated and approved by the expert interviews and were used as the main input for the design phase. The main conclusion was the stakeholder-specific characteristic of some of the requirements due to the different needs of logistical actors and related IT companies that calculated GHG emissions.

The third phase was the designing of the system architecture. It was separated into two parts. First, the creation of a list of possible design options to address the derived system requirements with another evaluation round with the expert. Second, the creation of the system architecture by creating system architecture components, which incorporate the most fundamental design options from the design phase. The experts again evaluated these system architecture components before they were incorporated into stakeholder-specific system architecture, which captured the overarching processes and data flows of an IT company that specialised in the quantification of GHG emissions of vehicles in road logistics. The main conclusion was that, due to the diversity of system stakeholders, a general system architecture that adresses all stakeholder needs is less feasible than the creation of stakeholder-specific system architectures.

The fourth phase was the evaluation, which happened throughout all stages of this research, and concluded the general correctness of the derived stakeholder-specific system architecture by the experts. It also pointed out potential limitations of the designs. The specific knowledge needed to validate such designs of the technical domain (data management structures), the policy and institutional knowledge, and the specific details of state-of-the-art GHG quantification methodologies makes evaluating the entire system more challenging. Thus, a broad sample of interview partners was needed. Moreover, selecting a design option, especially in the perception and physical layer of the system architecture, can create path dependencies and narrow down the design space. The evaluation phase was concluded by addressing the general success factors of the proposed design. Here the willingness of the logistical operators to adopt the GHG emissions reporting, the importance of methodology alignments and the need for truly value-adding services were especially highlighted as success factors of the system architecture.

The research concluded by recognising the great potential of primary data to improve the accuracy of emission factors in road logistics. Seven main conclusions and contributions to the field of logistics were made:
1. The inclusion of a multi-domain designer perspective when designing an abstract system architecture in the logistical sector - should be mandatory in the scoping of any project.
2. The identification of relevant stakeholder clusters and an abstract stakeholder analysis to be considered when designing in the socio-technical environment.
3. The categorization of systems requirements into institutional, stakeholder and technical requirements to represent the multi-domain character of the system.
4. The need for financial quantification tools of the CO2 reduction for logistical operators to validate their investment decisions.
5. Compliance with leading European GHG emissions quantification methodologies and data regulations - should also be implemented, e.g. in the EU taxonomy.
6. A stakeholder cluster-specific system architecture, which incorporated the derived requirements and outlined business relationships and data flows in the system, evaluated and approved by industry experts.
7. The issue of the stakeholder-specific requirements for the system leading to multiple co-existing system architecture specifications.


Finally, the research concluded with a short and long-term outlook of how the sector might develop and presented potential future research topics, such as the possibility of using other forms of data sharing, such as data spaces or blockchain applications, for secure and trusted data sharing.