Background: Blockchain has emerged as a promising enabler for improving transparency, trust, and operational efficiency in logistics systems. In PI-oriented logistics environments, where openness, interoperability, and streamlined information exchange are emphasized, blockchain offers a decentralized alternative to conventional coordination methods. However, its economic feasibility remains uncertain due to substantial system development and operational costs. Existing literature largely isolates qualitative benefits from quantitative cost structures. Methods: This study proposes a quantitative–qualitative evaluation framework to assess blockchain adoption in PI-oriented logistics systems. Two Mixed-Integer Linear Programming (MILP) cost-minimization models were constructed to represent alternative coordination approaches: PI–BC (blockchain-enabled coordination) and PI–Human (traditional human-centered coordination). The results of the optimization analysis were integrated into an Analytic Hierarchy Process (AHP) evaluation alongside qualitative criteria such as interoperability, reliability, and transparency. Results: Numerical findings show that although PI–BC incurs higher operational costs, it performs considerably better in qualitative dimensions related to information visibility and robustness. Conclusions: These results suggest that blockchain provides particular value in PI-oriented contexts at the adoption stage. However, the framework does not provide a universal recommendation, as the relative advantage of PI–BC is highly contingent on decision-makers’ subjective criterion weight assignments, as revealed by the sensitivity analysis.

Background: The Physical Internet (PI) promotes resource sharing among independent firms. This can improve logistics efficiency, but shared route capacity and limited compensation may also create unequal outcomes among firms. Methods: This study develops a framework for coordinated logistics planning under shared route capacity constraints. The framework includes two coordination rules. Model 3.3 is an efficiency-oriented participation-guaranteeing rule with individual rationality constraints. Model 3.4 is a fairness-oriented rule that minimizes the maximum firm-level disadvantage under a limited compensation budget. Numerical experiments are conducted using a stylized Japanese domestic consumer goods distribution network. Results: Coordinated planning reduces total logistics cost compared with decentralized sequential allocation. Model 3.3 achieves the lowest system cost but gives benefits unevenly. Model 3.4 gives more balanced firm-level outcomes and improves the worst-off firm in the tested scenarios. The results also show that substantial fairness improvements can be obtained through small route-allocation changes. Conclusions: The study shows how two coordination rules can be used in PI-oriented logistics coordination. Model 3.3 is useful when firms need a no-loss guarantee, especially in an early stage. Model 3.4 is useful in a mature or repeated coordination stage, where the platform needs to avoid excessive disadvantage.

Integrated three separate technical streams into one unified Artificial Intelligence‑based spatiotemporal sustainability decision‑support framework: machine‑learning forecasting (Random Forest, XGBoost, Long short-term memory), Geographic information system spatial hotspot analysis and System dynamics causal simulation.