The increasing globalisation and interdependence of economies have notably transformed population mobility, with cross-border movements becoming more common. In regions like Lake Constance, where multiple national borders converge, efficient cross-border public transport is vital for fostering regional integration, supporting the job market, and promoting economic cooperation. However, cross-border public transport faces significant challenges due to the need for coordination among various national, regional, and international actors, including administrative, legal, technical, and financial barriers. The adoption of smart services, which leverage advanced technologies like IoT, AI, and Big Data, presents a potential solution by enabling better coordination, communication, and data sharing among stakeholders. Using a mixed-methods approach, the research begins with a literature review to outline the theoretical background and highlight existing gaps, while a detailed analysis of the Lake Constance region uncovers opportunities for implementing smart services. Semi-structured interviews with policymakers and industry leaders provide a comprehensive view of the challenges in cross-border transport. A key contribution of this work is the development of an adapted Double Diamond model for smart mobility, designed to address the specific complexities of cross-border transportation systems and, through the Discover and Define phases, identify core challenges like schedule coordination and environmental impact reduction, facilitating a more integrated, sustainable, and user-friendly public transportation network in the region.