چکیده مقاله
This study investigates the feasibility and implementation of an intelligent automated reservation system in airline ticketing platforms and examines how combining data driven personalization, automated booking processes, and a quality supervision layer can lead to increased online sales and improved customer satisfaction In this research, machine learning models were first developed to analyze users’ purchase history, travel patterns, and individual preferences in order to more accurately recommend the most suitable flight options Then, a multi leg automated booking mechanism was designed that generates the optimal combination of flights by considering criteria such as cost, travel duration, and delay risk To enhance user trust, an intelligent supervisory layer was added to the system as a quality controller for the final decision The methodology followed a mixed methods approach; quantitative data were collected through A/B tests, satisfaction surveys, and the auto purchase regret index, while qualitative data were analyzed through semi structured interviews The results showed that the automated reservation system increased conversion rates, reduced decision making time, and improved user satisfaction Additionally, the auto purchase regret index revealed psychological dimensions of the customer experience more effectively, and the supervisory layer significantly reduced this phenomenon These findings indicate that intelligent automated reservation can serve as an effective solution for improving travel service quality and increasing sales in online platforms
کلیدواژهها
نویسندگان
شیوه ارجاع
Torabi, Mohammad Jalal and Sharifi Tehrani, Omid,1404,Feasibility Study and Implementation of Automated Airline Ticket Reservation and Its Impact on Sales and Customer Satisfaction,1St International conference on new horizons in management,business, economics and humanities
ارائهشده در
مجموعه مقالات اولین کنفرانس بین المللی افق های نوین در مدیریت، تجارت، اقتصاد و علوم انسانی10 آذر 1404