Dynamic Pricing Verification Interface for On-Demand Services
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing pricing systems for mobile services are inflexible and do not dynamically adjust based on real-time demand and supply conditions, leading to inefficiencies and potential overcharging or undercharging.
Innovation Solution
A system that uses real-time data from mobile devices to determine the number of requesters and available service providers, adjusting prices relative to a default price based on supply and demand conditions, and communicates these adjustments to users and providers through mobile computing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed pricing is used for mobile services, then pricing simplicity is maintained, but the system cannot adapt to varying real-time demand and supply conditions
Solution Approach 1:
The patent implements dynamic pricing by allowing prices to change in real-time based on demand and supply conditions. The system continuously monitors requester volume and service provider availability, then adjusts prices accordingly rather than using fixed pricing. This resolves the contradiction by making the pricing system adaptable to changing conditions while maintaining operational simplicity through automated adjustments.
Solution Approach 2:
The system changes the price parameter dynamically based on monitored conditions. When demand increases or supply decreases, the price parameter is adjusted upward; when demand decreases or supply increases, the price parameter is adjusted downward. This parameter change approach enables adaptability to market conditions without requiring complex manual intervention or system restructuring.
2Measurement precision
If dynamic pricing is implemented, then pricing accuracy reflects market conditions, but system complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors demand (requester volume) and supply (service provider availability) conditions, then uses this feedback to adjust prices dynamically. The feedback loop ensures pricing accuracy by constantly comparing current market conditions against pricing decisions, automatically correcting deviations without requiring complex external intervention.
Solution Approach 2:
The pricing system performs self-adjustment based on monitored conditions without requiring external manual intervention. The system automatically detects when pricing accuracy needs adjustment and implements corrections autonomously, reducing the operational complexity despite the increased sophistication of the pricing mechanism itself.
3Measurement precision
If real-time monitoring of requesters and providers is performed, then pricing decisions are accurate, but data processing requirements increase
Solution Approach 1:
The system implements partial monitoring by focusing on key metrics (requester volume and service provider availability) rather than tracking every individual transaction or detail. This selective approach to data collection provides sufficient accuracy for pricing decisions while significantly reducing the computational energy required compared to comprehensive real-time monitoring of all system activities.
Data Source
AI summary
A method for enabling a user to verify a price change for an on-demand service is provided. One or more processors can determine a real-time price for providing the on-demand service to the user. The one or more processors can determine when the real-time price is equal to or exceeds a threshold price. In response to a request from the user for the on-demand service when the real-time price is equal to or exceeds the threshold price, an intermediate interface can be provided that the user is to correctly respond to before a service request can be transmitted to a service system.