Member Trait Modeling for Organizational Cooperation Prediction
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Solution Overview
Problem
Existing techniques struggle to predict and maximize organizational achievement by evaluating member activities and traits effectively, making it difficult to enhance cooperative actions within organizations.
Innovation Solution
A system that identifies personal traits of organization members, predicts cooperative action degrees based on trait relationships, and visualizes information to encourage actions that maximize organizational achievement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If member-by-member evaluation of traits and activities is performed, then individual member information can be presented, but prediction and maximization of overall organizational achievement cannot be achieved
Solution Approach 1:
The patent combines individual member trait evaluations with organizational context to create a comprehensive assessment system. By merging personal trait data with organizational achievement data, the system predicts both individual performance and overall organizational outcomes simultaneously, resolving the contradiction between detailed individual measurement and macro-level prediction capability
2Measurement precision
If only environmental factors are used to evaluate member activity, then individual activity can be quantified, but cooperative action prediction is insufficient
Solution Approach 1:
The patent transforms the evaluation parameters from solely environmental factors to a multi-dimensional parameter set that includes personal traits, environmental factors, and their interactions. This parameter expansion enables the system to predict cooperative actions by considering how individual traits moderate the relationship between environmental factors and member activities, thereby improving prediction reliability
Data Source
AI summary
A system identifies a personal trait of each of members belonging to an organization, from personal trait data that includes data representing the personal trait of each of the members, and predicts a cooperative action degree in the organization, based on the relationship between the personal traits of the members. The system visualizes information about the predicted cooperative action degree.


