Global supply chains increasingly experience disruptions due to climate events, geopolitical changes, and cyber threats. Artificial intelligence (AI) presents opportunities to enhance supply chain resilience; however, these systems may introduce additional risks if not implemented with adequate safeguards. This study examines strategies for designing and governing AI systems to strengthen supply chain resilience while minimizing unnecessary complexity. A mixed-methods approach is employed, combining interviews with AI and supply chain experts and two focus groups. The research identifies three agent design archetypes that clarify the practical contributions of AI to supply chain resilience: Diagnostic and Monitoring Agents, which provide early warnings for slow-moving risks; Response and Coordination Agents, which accelerate disruption recovery by synthesizing fragmented data and take limited actions; and Interface and Learning Agents, which disseminate tacit knowledge and reinforce feedback loops. Furthermore, a two-dimensional evaluation framework is introduced. The first dimension (R-Dimension) as- sesses whether a proposed AI concept credibly enhances supply chain resilience, while the second dimension (D-Dimension) determines the appropriate level of autonomy and implementation feasibility. The Dimensions Interaction Matrix maps resilience value against governability across six decision zones, guiding practitioners from concept rejection to bounded autonomy. The framework also maps Generative AI (GenAI) and Agentic AI to specific Levels of Automation (LoA), enabling practitioners to justify whether a deterministic approach, GenAI, or Agentic AI is suitable for each supply chain decision point. The findings indicate that effective deployment of Agentic AI requires investment in disruption readiness through synthetic scenario testing and organizational preparedness with defined escalation protocols and human override authority. This research provides practical frameworks for practitioners and identifies areas for future validation with real-world data.

In the last few years, e-commerce has experienced exponential growth, increasing the pressure, especially on last-mile delivery. This thesis, building on the freight-on-transit (FOT) concept, investigates whether mobile parcel lockers, when integrated into public transport vehicles, can alleviate the pressure and negative consequences of last-mile delivery.
In this research, a mixed-methods design was adopted, incorporating both qualitative and quan- titative analysis. Eleven semi-structured interviews with public transport operators, logistics firms, municipalities, and academics have been conducted to understand whether this idea was feasible from operational, economic, and governance points of view. Additionally, to capture the end-user’s acceptance, trust, and design preferences, a questionnaire (n = 122) was deliv- ered. Moreover, built on the initial idea of combining freight and public transport for last-mile delivery, six scenarios were created that explore possible alternatives. Regarding the scenarios developed, they have been described as possible ideas which, if combined, can have the most significant effect on emission and cost reduction.
The findings reveal that the original idea of ”locker-on-board” is technically feasible but econom- ically unproven and operationally fragile when applied in dense urban areas; this is because lockers remove seats that generate revenue or wheelchair bays, complicate the duties of drivers, and clash with regulations. However, this idea has been sustained for rural areas, specifically using busses, since this would save many km for delivery vans which, if they have to reach a remote area for just a few deliveries, emit many emissions. In addition, the structure of the busses to rural areas that have a luggage space which is often empty supports, even more, the transportation of packages without disrupting the comfort of passengers.