Development of Morphology Analysis-Based Technology Roadmap Considering Layer Expansion Paths: Application of TRIZ and Text Mining
Morphology analysis (MA)-based roadmapping has been considered an effective means to support the process of technology innovation in a business environment. However, previous research on MA-based roadmaps has commonly focused on the process of developing existing technology roadmaps (TRMs), while th...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/23/8498 |
| _version_ | 1797546424241487872 |
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| author | Lijie Feng Yuxiang Niu Jinfeng Wang |
| author_facet | Lijie Feng Yuxiang Niu Jinfeng Wang |
| author_sort | Lijie Feng |
| collection | DOAJ |
| description | Morphology analysis (MA)-based roadmapping has been considered an effective means to support the process of technology innovation in a business environment. However, previous research on MA-based roadmaps has commonly focused on the process of developing existing technology roadmaps (TRMs), while the paths of layer expansion for seeking new opportunities is rarely a focus. Thus, the aim of this research is to develop MA-based TRMs by utilizing MA to describe the characteristics of the technology and product layers in the TRMs and apply the improved theory of inventive problem solving (TRIZ) inventive principles to establish innovation paths for new opportunities with the aid of text mining tools. This study suggests using a morphological matrix to construct existing TRMs by calculating the correlations among different technology and product nodes and two sparse generative topographic mapping (SGTM)-based maps to discover new technology and product opportunities by identifying technology and product development trends and innovation elements in sparse areas, which is the objective of simplifying TRIZ application. To illustrate the performance of the proposed approach, a case study is conducted using patents and product manuals for underwater vehicles, which are becoming popular high-tech and secure tools to explore sub-sea resources. This approach contributes by suggesting a semi-autonomous and systematic procedure to extend the existing MA-based TRM and simplifying TRIZ application according to the occurrence frequency of the keywords. |
| first_indexed | 2024-03-10T14:29:34Z |
| format | Article |
| id | doaj.art-db06c23d6e8b4daf836a9a68983b1e7c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T14:29:34Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-db06c23d6e8b4daf836a9a68983b1e7c2023-11-20T22:42:02ZengMDPI AGApplied Sciences2076-34172020-11-011023849810.3390/app10238498Development of Morphology Analysis-Based Technology Roadmap Considering Layer Expansion Paths: Application of TRIZ and Text MiningLijie Feng0Yuxiang Niu1Jinfeng Wang2School of Management Engineering, Zhengzhou University, Zhengzhou 450001, ChinaSchool of Management Engineering, Zhengzhou University, Zhengzhou 450001, ChinaSchool of Economic & Management, Shanghai Maritime University, Shanghai 201306, ChinaMorphology analysis (MA)-based roadmapping has been considered an effective means to support the process of technology innovation in a business environment. However, previous research on MA-based roadmaps has commonly focused on the process of developing existing technology roadmaps (TRMs), while the paths of layer expansion for seeking new opportunities is rarely a focus. Thus, the aim of this research is to develop MA-based TRMs by utilizing MA to describe the characteristics of the technology and product layers in the TRMs and apply the improved theory of inventive problem solving (TRIZ) inventive principles to establish innovation paths for new opportunities with the aid of text mining tools. This study suggests using a morphological matrix to construct existing TRMs by calculating the correlations among different technology and product nodes and two sparse generative topographic mapping (SGTM)-based maps to discover new technology and product opportunities by identifying technology and product development trends and innovation elements in sparse areas, which is the objective of simplifying TRIZ application. To illustrate the performance of the proposed approach, a case study is conducted using patents and product manuals for underwater vehicles, which are becoming popular high-tech and secure tools to explore sub-sea resources. This approach contributes by suggesting a semi-autonomous and systematic procedure to extend the existing MA-based TRM and simplifying TRIZ application according to the occurrence frequency of the keywords.https://www.mdpi.com/2076-3417/10/23/8498morphology analysistechnology roadmapTRIZtext mining |
| spellingShingle | Lijie Feng Yuxiang Niu Jinfeng Wang Development of Morphology Analysis-Based Technology Roadmap Considering Layer Expansion Paths: Application of TRIZ and Text Mining Applied Sciences morphology analysis technology roadmap TRIZ text mining |
| title | Development of Morphology Analysis-Based Technology Roadmap Considering Layer Expansion Paths: Application of TRIZ and Text Mining |
| title_full | Development of Morphology Analysis-Based Technology Roadmap Considering Layer Expansion Paths: Application of TRIZ and Text Mining |
| title_fullStr | Development of Morphology Analysis-Based Technology Roadmap Considering Layer Expansion Paths: Application of TRIZ and Text Mining |
| title_full_unstemmed | Development of Morphology Analysis-Based Technology Roadmap Considering Layer Expansion Paths: Application of TRIZ and Text Mining |
| title_short | Development of Morphology Analysis-Based Technology Roadmap Considering Layer Expansion Paths: Application of TRIZ and Text Mining |
| title_sort | development of morphology analysis based technology roadmap considering layer expansion paths application of triz and text mining |
| topic | morphology analysis technology roadmap TRIZ text mining |
| url | https://www.mdpi.com/2076-3417/10/23/8498 |
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