The Moderating Role of User Experience on Expectancy Disconfirmation in Airport-Rail Disruption

Abstract

Managing unexpected service disruptions on the Airport-Rail Link (ARL) is especially challenging for the operator when dealing with the expectations of new (potential) users. These individuals may develop unrealistic expectations regarding response actions, influenced by social amplification and a lack of contextual understanding. To manage reputational risk, ARL operators must consistently monitor and address the recovery disconfirmation ( the gap between user expectations and their perceptions of the operator's response to disruptions ). A key challenge is understanding how this disconfirmation differs between potential and existing users. Existing research on service recovery often treats users homogenously or focuses primarily on existing users, leaving a gap in understanding how prior experience influences the disconfirmation process.  Therefore, this study investigates user experience as a moderating factor (a variable influencing the strength of a relationship) between expectation and perceived performance within the Expectancy Disconfirmation Model, viewed through the lens of justice theory (which assesses the fairness of outcomes, processes and interactions). To overcome the limitations of text-based scenarios for potential users, a comic-based questionnaire was employed to visually represent hypothetical response actions. Data collected from 557 train passengers, including 267 potential users, were analysed using PLS-SEM with SmartPLS software that performs a two-stage approach for moderation analysis. The findings indicate that user experience significantly moderates the relationship between expectations and perceived performance. Potential users’ expectations exert a stronger influence on their judgments of response actions, while existing users are more pragmatic. These results suggest that ARL operators should tailor response actions to better align expectations and performance perceptions for both user groups.