Efficiency improvement and balance in fixed cost allocation: A trade-off approach based on DEA

Abstract

Fixed cost allocation (FCA) is a problem that decision-makers usually encounter in practice. The existing FCA studies based on data envelopment analysis (DEA) have not recognized the trade-off between improving efficiency and balancing FCA result and failed to provide an approach to generate an equilibrium solution between the two goals. In this study, under DEA common-weight evaluation mechanism, we propose an approach for centralized FCA using several principles featuring fairness in the situation where the fixed cost is regarded as a complement of one of the current inputs. It first considers the principle of making equal-proportional efficiency improvements for all the decision-making units (DMUs) in FCA. Then, we define a measure, called “balanced indicator”, to measure the balance of a FCA result. Finally, a bi-objective model is built that considers both the objectives of maximizing the proportional efficiency improvement of the DMUs and improving the balance of the FCA result. A bargaining-game-like model and a trade-off algorithm are provided to generate the final FCA result. Our research contributes by elucidating the trade-off between enhancing efficiency and achieving balance in FCA result. It also makes a distinct contribution by proposing a bargaining-game-like model and a trade-off algorithm to generate a FCA result that is an equilibrium solution between the two goals and ensures no DMU is allocated zero cost. Finally, we demonstrate the superiority of our approach by comparing it with a previous representative approach and applying it to a case study of China National Heavy Duty Truck Group.