Unused Ticket Manager Predicts Travel Patterns
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current travel booking systems fail to effectively manage and utilize unused travel tickets, leading to significant losses due to expired or underutilized tickets, as they lack the ability to track and optimize the use of residual ticket values based on user behavior and travel patterns.
Innovation Solution
The Unused Ticket Manager (UTM) system connects to a database of unused tickets and a service platform, using behavioral data and predictive algorithms to rank and recommend the best unused tickets for future bookings, considering residual value, expiration date, and user travel habits, allowing users to make informed selections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional travel booking systems are used to manage tickets, then ticket booking functionality is provided, but tracking and managing unused tickets becomes difficult leading to financial losses
Solution Approach 1:
The patent combines unused ticket tracking with the existing travel booking system by integrating a database that stores ticket information alongside traveler profiles. The system merges ticket issuance, tracking, and management functions into a unified platform, allowing automatic identification and monitoring of unused tickets without requiring a separate complex system.
Solution Approach 2:
The travel booking system is designed to perform multiple functions: issuing tickets, tracking their usage status, identifying unused tickets, predicting future travel needs, and recommending optimal ticket usage. This multi-functional approach eliminates the need for separate specialized systems while comprehensively addressing ticket management challenges.
2Loss of energy
If no predictive analysis is performed, then system simplicity is maintained, but travelers cannot optimize ticket usage leading to expired tickets and financial loss
Solution Approach 1:
The system performs preliminary analysis by examining historical travel data and predicting future travel needs before tickets expire. By proactively identifying patterns in traveler behavior and anticipating future trips, the system recommends optimal ticket usage in advance, preventing financial losses from expired tickets before they occur.
Solution Approach 2:
The system continuously analyzes traveler behavior patterns and uses this feedback to refine predictions about future travel needs. By monitoring actual travel against predicted patterns, the system adapts and improves its recommendations, enabling more accurate optimization of ticket usage over time while managing computational resources efficiently.
3Productivity
If manual tracking of unused tickets is performed, then system complexity is reduced, but productivity and ability to manage large volumes of tickets decreases
Solution Approach 1:
The system automatically identifies unused tickets by comparing issued tickets against actual travel records without requiring manual intervention. It self-updates traveler profiles, automatically detects patterns in travel behavior, and generates recommendations without human input, dramatically improving productivity while the automated processes manage system complexity.
Solution Approach 2:
The patent replaces manual mechanical tracking processes with automated electronic database queries and algorithmic analysis. Instead of manual review of ticket records, the system uses automated data retrieval, pattern recognition algorithms, and computer-generated recommendations, vastly increasing management efficiency for large volumes of tickets.
Data Source
AI summary
A method and system for unused ticket management, that identifying travel data related to one of future or past travel data for one or more travelers; identifying one or more unused travel purchase; generating a value for the unused travel purchase, the value corresponding to the one or more travelers, the respective values based at least in part on the travel data of the one or more travelers; and presenting to at least one of the one or more travelers, one or more options of unused travel purchases and the respective generated values.