Evaluating the Operational Impact and Operator User-Experience Mechanisms of a Real-Time, Rule-Based Boarding Route Management System (rtBRMS) in International Airport Gate Operations

Passenger-flow variability during boarding and deboarding remains a persistent source of turnaround instability at capacity-constrained airports, despite advances in Airport Collaborative Decision-Making (A-CDM) and predictive analytics. Existing research relies predominantly on simulations and controlled experiments, leaving a gap in field-validated evidence on whether real-time automated systems that actively regulate passenger movement can reduce turnaround variability under authentic conditions. Equally, little is known about how frontline staff experience and respond to such systems in their daily work.
This thesis evaluates the operational impact and human-factor consequences of deploying a real-time, rule-based Boarding Route Management System (rtBRMS) in live airport gate operations. The investigation adopts a multi-method quantitative research design consisting of two complementary, integrated empirical investigations. Study 1 establishes what the system does to objective turnaround performance through a 48-stratum quasi-experimental field experiment across 171 short-haul flights at Mashhad International Airport (MHD), with continuous outcomes analysed via Welch t-tests and Type-III General Linear Models, and binary fast-process thresholds analysed via Firth-penalised logistic regression. Study 2 examines how frontline operators, who actively utilise rtBRMS in their daily gate work, experience those changes and how that user-experience shapes their engagement, performance, and satisfaction, through a cross-sectional survey of 224 operators (gate agents, ramp coordinators, supervisors, security personnel, and ground-handling staff) analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) with 5,000 bootstrap resamples. Together, Study 1 and Study 2 form a single socio-technical evidence arc from technological intervention to human-factor outcomes, integrated in the discussion chapter.
The operational findings (Study 1) show that rtBRMS reduces Gate Occupation Time by approximately 12 to 13 minutes (Cohen's d = 4.37; partial η² = .87), compresses boarding windows by 15.8% and deboarding windows by 8.2%, and increases passenger throughput by approximately 1.6 to 1.7 passengers per minute. Effects are larger at more complex gate configurations and remain consistent across all passenger load levels. The user-experience findings (Study 2) show that perceived flow stability strongly predicts perceived system predictability (β = 0.584), which drives work engagement, individual performance (R² = .573), productivity (R² = .662), and system satisfaction (R² = .486), with the mechanism stable across roles and experience levels.
The thesis contributes novel field-based evidence that real-time passenger-flow automation can measurably improve turnaround performance under authentic conditions, and provides an integrated explanation of how frontline staff convert stabilised flow into engagement and performance. The findings identify shared-access gates under high passenger loads as the highest-priority deployment contexts, and demonstrate that making system behaviour visible and predictable to operators is as important as the technical performance of the system itself, with direct implications for interface design, staff training, and change management in airports deploying digital operational technologies.