Reservation Timing Estimation via Vacancy Trend Analysis
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Solution Overview
Problem
Users often face difficulties in making facility reservations as they approach the scheduled date of use, as facilities may become unavailable, and desired plans may be fully booked, making it challenging to determine the optimal time for reservation.
Innovation Solution
An information provision system that calculates a rate of decrease in facility vacancies based on past reservation data, setting an estimated date for reservation requests by identifying when the number of vacancies falls below a specified threshold, and providing users with this information to guide their reservation timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a user makes a reservation close to the scheduled date of use, then the user can flexible with their schedule, but the facility may become unavailable or desired plans may be fully booked
Solution Approach 1:
The system performs preliminary analysis by calculating the rate of decrease in vacancies from past reservation data and determining the optimal reservation timing in advance. This allows users to make reservations at the best possible moment before facilities become unavailable, resolving the contradiction between scheduling flexibility and availability reliability.
2Adaptability or versatility
If a user waits until the scheduled date approaches to make a reservation, then the user can adapt to last-minute changes, but the likelihood of finding available plans decreases
Solution Approach 1:
The system uses feedback from historical reservation data to calculate the rate of vacancy decrease and determine the optimal reservation timing. This feedback mechanism helps users understand when to book to ensure available plans, resolving the contradiction between last-minute adaptation capability and the quantity of available plans.
3Ease of operation
If the system provides detailed reservation timing information, then users can make informed decisions about when to book, but the system complexity increases
Solution Approach 1:
The system automatically performs the complex analysis of historical reservation data, calculates vacancy decrease rates, and determines optimal booking timing without requiring manual user intervention. This self-service approach provides detailed timing information to users while keeping the user-side operation simple, resolving the contradiction between ease of operation and system complexity.
Data Source
AI summary
An information provision device according to one embodiment includes a receiving unit, an extraction unit, a setting unit and a presentation unit. The receiving unit receives search criteria. The extraction unit extracts reservation acceptance information of the target facility corresponding to a past determination target period based on the search criteria by referring to a storage unit storing reservation acceptance information of a facility. The setting unit calculates a rate of decrease from an initial number of vacancies in the target facility during the past determination target period based on the extracted reservation acceptance information, and when there is a date of change when the number of vacancies has changed to be less than a specified threshold during the determination target period, sets an estimated date for a reservation request. The presentation unit outputs the value set-as estimate information for reservation request.