Open Access

Road freight operators (RFOs) optimize their fleet management pro- cesses using fleet telematics systems (FTSs). Therefore, the selection of FTSs by RFOs is driven by transport specifications from the customer side leading to sub- stantial search costs. However, FTSs vary significantly in their design require- ments to assist road freight operations. Hence, we analyze 74 web pages from FTSs of existing telematics vendors to elicit 31 design requirements (DRs) which we aggregated into nine requirement sets (RSs). Subsequently, 42 practitioners from five digital road freight service enterprises experienced in using FTSs vali- date the DRs and evaluate their importance with RSs following the Analytical Hierarchy Process (AHP) method. The results reveal that DRs and RSs promot- ing driver monitoring and IT integration are perceived more important than items promoting fleet and logistics support. Our contribution sheds light on an emerg- ing topic in logistics and establishes a knowledge base that guides the design of future FTSs.

Purpose: In this paper, the authors investigate logistics platform strategies in the road freight market through the analysis of business models of logistics service providers (LSPs) and freight technology providers (FTPs). The purpose of this paper is to gain knowledge of emerging freight technologies and to explore logistics platform strategies between LSPs and FTPs enabling smart services. Methodology: This paper follows an empirical analysis approach to study business models using the concept of Business Model DNA. To this end, the business models of 25 LSPs and 15 FTPs are investigated according to 55 business model patterns (BMPs). Subsequently, the authors conceptualize four logistics platform models to demonstrate how LSPs can manage nascent freight technologies. Findings: The authors argue that freight technology-enabled smart services can promote digital forwarding by logistics platform strategies. LSPs can make use of complementary service capabilities while FTPs can benefit from profound customer access and physical logistics resources. Originality: To the best of the authors' knowledge, no empirical research exists that consistently focuses on logistics platform strategies for freight technology-enabled smart services. The obtained insights in this study lead to the first contribution of digital platform strategies for road freight transportation in the sphere of digital logistics.

Urban transportation is increasingly challenged by growing populations and the rapid growth of e-commerce, thus, driving data-driven innovations for sustainable mobility services. Shared mobility consequently emerges as a promising city transport concept, while combined service opportunities between public transport, crowd mobility, and last mile logistics are scarcely investigated. In this paper, we explore the co-creation of urban mobility services within federated ecosystems focusing on a transshipment hub, and propose a novel approach called “co-bility.” Following a design science research (DSR) approach, we conceptualize a co-bility hub based on literature and expert interviews with practitioners from the mobility sector. The exchange of data and services in urban spaces is based on the technical framework Gaia-X. Our study findings show that a Gaia-X-enabled co-bility hub can be achieved by (a) a federated ecosystem orchestrating mobility services and resources, (b) municipalities ensuring coherent platform governance, and (c) eclectic incentives to make co-bility successful.

Road freight transportation presents a vital element of our economies while heavy-duty truck drivers (HTDs) make use of emerging technologies for operations. However, the work environment of HTDs is yet characterized by time pressure, social isolation, and safety concerns. Surprisingly, scientific knowledge about driver’s well-being and mood enhancement scarcely exists in the context of IS. This paper addresses the research gap by the exploration of a mood-based truck driver assistance system (MTDAS) – the “Truck Buddy”. We establish a design science research (DSR) project to explore the requirements and design objectives of an MTDAS based on data from a comprehensive literature review and expert interviews. Our results indicate that a context-sensitive MTDAS can assist HTDs well-being by five design objectives enabling system integration, communication, mood-detection, automated driver support, and the provision of driver feedback. This first iteration step constitutes a foundation for further evaluations and developments within a continuous DSR process.