Airport gate assignment performance indicator selection is a complicated decision-making problem with strong subjectivity and difficulty in measuring the importance of each indicator. A better selection of performance indicators (PIs) can greatly increase the airport overall benefit. We adopt a multicriteria decision-making approach to quantify qualitative PIs and conduct subsequent selection using the fuzzy clustering method. First, we identify 21 commonly used PIs through literature review and survey. Subsequently, the fuzzy analytic hierarchy process technique was employed to obtain the selection criteria weights based on the relative importance of significance, availability, and generalisability. Further, we aggregated the selection criteria weights and experts’ score to evaluate each PI for the clustering process. The fuzzy-possibilistic product partition c-means algorithm was applied to divide the PIs into different groups based on the three selection criteria as partitioning features. The cluster with highest weights of the centre was identified as the very high-influence cluster, and 10 PIs were identified as a result. This study revealed that the passenger-oriented objective is the most important performance criterion; however, the relevance of the airport/airline-oriented and robustness-oriented performance objectives was highlighted as well. It also offers a scientific approach to determine the objective functions for future gate assignment research. And, we believe, through slight modifications, this model can be used in other airports, other indicator selection problems, or other scenarios at the same airport to facilitate policy making and real situation practice, hence facilitate the management system for the airport.

中文翻译：

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机场登机口分配问题的多方利益相关者方法：模糊理论在优化性能指标选择中的应用

机场登机口分配绩效指标选择是一个复杂的决策问题，主观性强，每个指标的重要性难以衡量。更好地选择绩效指标 (PI) 可以大大提高机场的整体效益。我们采用多标准决策方法来量化定性 PI，并使用模糊聚类方法进行后续选择。首先，我们通过文献回顾和调查确定了 21 个常用的 PI。随后，基于重要性、可用性和普遍性的相对重要性，采用模糊层次分析法获得选择标准权重。此外，我们汇总了选择标准的权重和专家的分数，以评估聚类过程的每个 PI。C应用-means算法根据三个选择标准作为划分特征将PI划分为不同的组。中心权重最高的集群被确定为非常高影响力的集群，结果确定了 10 个 PI。本研究表明，以乘客为导向的目标是最重要的绩效标准；然而，以机场/航空公司为导向和以稳健性为导向的绩效目标的相关性也得到了强调。它还提供了一种科学方法来确定未来门分配研究的目标函数。并且，我们相信，通过稍加修改，这个模型可以用于其他机场，其他指标选择问题，或同一机场的其他场景，以促进政策制定和实际情况的实践，