Multi-Party Negotiation Decision Model for Profit Maximization
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Solution Overview
Problem
Existing techniques for maximizing sales amount do not consider the interest relationships among multiple parties involved in commercial transactions, leading to suboptimal profit for one party due to inadequate negotiation strategies regarding procurement prices and amounts.
Innovation Solution
An information processing apparatus and method that calculates and presents optimal quantity sequences and values considering an objective function representing profit or loss, taking into account the interest relationships between multiple parties in negotiations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a demand model is used to maximize total sales amount, then sales volume is improved, but profit cannot be maximized due to inadequate consideration of procurement price and amount
Solution Approach 1:
The patent segments the negotiation process into multiple rounds where the first user presents different first quantities (procurement prices and amounts) sequentially to the second user. This segmentation allows the system to optimize both sales amount and profit by considering multiple negotiation scenarios rather than a single fixed price point.
Solution Approach 2:
The patent introduces dynamic negotiation where the first user can adjust and present different first quantities in subsequent rounds based on the second user's responses. This dynamic approach enables the system to adapt procurement prices and amounts to maximize profit while maintaining sales volume, resolving the contradiction between sales maximization and profit optimization.
2Productivity
If the first user focuses on maximizing sales amount, then revenue is improved, but the interest relationship with the second user is not adequately considered
Solution Approach 1:
The patent incorporates feedback mechanisms where the second user's responses to presented first quantities are considered in subsequent negotiation rounds. This feedback loop enables the first user to adjust their strategy based on the second user's reactions, improving both sales amount and negotiation adaptability simultaneously.
Solution Approach 2:
The negotiation process is designed as a dynamic interaction where the first user presents different first quantities in sequence and adjusts their strategy based on the second user's responses. This dynamic approach enhances negotiation adaptability while maintaining focus on maximizing sales amount through optimized procurement strategies.
3Device complexity
If a simple demand model is used, then calculation complexity is reduced, but the ability to consider multiple party interests is insufficient
Solution Approach 1:
The patent segments the complex negotiation optimization into multiple discrete rounds, where in each round the first user presents specific first quantities and the system evaluates outcomes. This segmentation makes the complex multi-party interest consideration more manageable and computationally feasible while maintaining comprehensive consideration of all interests.
Solution Approach 2:
The system performs preliminary calculations and evaluations of different first quantity scenarios before actual negotiation occurs. By pre-calculating the implications of different procurement strategies and their effects on all parties involved, the system reduces real-time calculation complexity while maintaining comprehensive multi-party interest consideration.
Data Source
AI summary
An information processing apparatus includes at least one memory storing instructions, and at least one processor configured to execute the instructions to calculate an optimum value sequence of a first quantity sequence including first quantities sequentially presented by a first user to a second user in negotiation, and an optimum value of a second quantity presented by the first user to a third user in a case where the negotiation is successful, using an objective function representing a profit or a loss of the first user in the negotiation, sequentially present optimum values of the first quantities included in the optimum value sequence of the first quantity sequence to the second user in the negotiation, and present the optimum value of the second quantity to the third user in a case where the negotiation is successful.