The willingness of individuals to provide personal data is of interest to policymakers and practitioners seeking to develop more intelligent transportation systems that create value for passengers using technologies, as well as to leverage the use of data more generally to accelerate digital transformation. This study examines the role of perceived benefits as a driver and necessary condition for the willingness of air passengers to provide personal data for non-mandatory digital services at airports. These are services that are not essential for the operation of the airport or for the safety and security of passengers but can enhance the passenger experience or generate additional revenue for the airport. Examples include receiving notifications to a mobile device about their journey and related products and services, accessing customer services online, joining and receiving electronic information from an airport loyalty programme, and making payments for products and services online or via a mobile application. The analysis is based on two samples of 235 and 218 respondents to an online survey where the second sample is used for the purpose of replication. Responses were analysed using a recently developed complementary approach that combines partial least squares structural equation modeling and necessary condition analysis. The findings confirm that perceived benefits are a significant driver and necessary condition for passengers’ willingness to provide personal data. More so, perceived benefits significantly attenuate the negative effect that privacy concerns have on passengers’ willingness to provide personal data. The findings offer theoretical and methodological contributions, as well as implications for policy and practice.

政策制定者和从业者愿意提供个人数据，他们希望开发更智能的交通系统，利用技术为乘客创造价值，并更广泛地利用数据来加速数字化转型。本研究考察了感知利益作为驱动因素的作用，以及航空乘客愿意为机场的非强制性数字服务提供个人数据的必要条件。这些服务对于机场的运营或乘客的安全保障而言并非必不可少，但可以提升乘客体验或为机场带来额外收入。示例包括向移动设备接收有关他们的旅程和相关产品和服务的通知，在线访问客户服务、加入机场忠诚度计划并从中接收电子信息，以及在线或通过移动应用程序为产品和服务付款。该分析基于在线调查的 235 名和 218 名受访者的两个样本，其中第二个样本用于复制目的。使用最近开发的补充方法分析响应，该方法结合了偏最小二乘结构方程建模和必要条件分析。调查结果证实，感知利益是乘客愿意提供个人数据的重要驱动因素和必要条件。更重要的是，感知到的好处显着减弱了隐私问题对乘客提供个人数据的意愿的负面影响。