Business Model Generation Support via Activity Data Integration
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Solution Overview
Problem
Conventional technologies fail to promptly determine the feasibility and cost of implementing a new business by combining existing businesses, particularly in cross-industry collaborations, as they do not provide clear options or workload estimates for commercialization.
Innovation Solution
A business model generation support method that involves a computer system to receive and combine existing business models, add activities and data items, search for common activities, and output a new business model that can be implemented by bringing two business models into collaboration, while calculating the data collection cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional technologies calculate degree of conformity and similarity for business patterns, then business pattern matching is improved, but the ability to determine implementation cost and workload for cross-industry collaboration is not provided
Solution Approach 1:
The patent segments the business model into distinct components: business patterns, player candidates, and activity data items. This segmentation allows the system to separately calculate similarity metrics for business patterns while also tracking specific activity implementations and their associated costs, thereby resolving the information loss problem without sacrificing matching accuracy.
Solution Approach 2:
The patent performs preliminary actions by pre-defining activities and data items before business pattern matching. This preliminary setup enables the system to later accurately determine implementation costs and workloads for cross-industry collaborations, as all necessary activity and data information is already structured and ready for integration.
2Adaptability or versatility
If the system combines existing business models to generate new businesses, then business innovation is improved, but the promptness of implementation and cost estimation is not achieved
Solution Approach 1:
The patent creates a universal framework that can handle multiple types of business combinations (intra-industry and cross-industry) using the same activity and data item structure. This multi-functional approach enables the system to promptly generate new business models and estimate implementation costs across different collaboration scenarios without requiring scenario-specific processing.
Solution Approach 2:
The patent changes parameters by transforming business model combinations into structured activity and data item representations. This parameter transformation enables systematic calculation of implementation costs and workloads, allowing prompt estimation across different business combination types while maintaining adaptability and versatility.
3Ease of operation
If the system presents business pattern options, then business generation support is improved, but the ability to evaluate commercialization cost is not provided
Solution Approach 1:
The patent implements feedback mechanisms that provide real-time information about implementation costs and workloads during the business generation process. By continuously tracking activity requirements and data item needs, the system can present business pattern options while simultaneously evaluating commercialization costs, eliminating information loss and enhancing ease of operation.
Data Source
AI summary
Disclosed is a business model generation support method for proposing a new business model. A computer receives a first business model and a second business model, and adds, for the plurality of business models, a first activity and a second activity which are respectively performed by the first and second business models to first information that predefines jobs performed by the business models as activities. Next, the computer adds the relation between a first data item and the first activity and the relation between a second data item and the second activity to second information that predefines the relation between the activities and the data items used for performing the activities. The first and second data items are used for performing the first and second activities, respectively. Then, the computer searches the second information to obtain a third activity including both the first data item and the second data item.