A Priority-Based Multiobjective Optimization Framework for Fair Profit Allocation in Cooperative Systems of Cross-Border E-Commerce Logistics Supply Chains

Cross-border e-commerce logistics supply chain alliances face the practical challenge of allocating profits in a way that is both fair and operationally controllable when member contributions and cooperation priorities jointly matter. This study proposes an integrated framework that first evaluates member contributions via a group decision-making (GDM) procedure to derive contribution weights, and then aggregates them to coalition-level importance scores to rank feasible cooperation structures. Building on these inputs, we formulate a Priority-Based Multiobjective Linear Programming (P-MOLP) model that performs tiered (priority) optimization under individual rationality and budget-balance constraints, thereby ensuring implementable allocations. Using alliance data, P-MOLP provides clearer structural differentiation than an ordinary goal-programming model: high-contribution, strategically central members receive larger shares, and low-contribution members receive less (“more-work-more-reward”). Unlike weighted-Shapley, which can violate individual rationality under extreme weights, P-MOLP is individually rational and budget-balanced, aligns better with observed practice, remains applicable when some coalition values are infeasible or missing, and attains ε-core near-stability. Priority weights serve as managerial levers to tune outcomes.