Computational Clustering Applied to Mental Models for Understanding the Valley of Death in Innovation Processes
The Valley of Death is the gap between the completion of research and development (R&D) projects and their transition to innovation. A key aspect to explain it are mindsets, which are one of the most complex to explain due to the number of factors they contain. What remains unclear is how people...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-08-01
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| Series: | Journal of Open Innovation: Technology, Market and Complexity |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2199-8531/8/3/154 |
| _version_ | 1797669027611410432 |
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| author | Jim Giraldo-Builes René Yepes Iván Rojas Juan Carlos Briñez-De León |
| author_facet | Jim Giraldo-Builes René Yepes Iván Rojas Juan Carlos Briñez-De León |
| author_sort | Jim Giraldo-Builes |
| collection | DOAJ |
| description | The Valley of Death is the gap between the completion of research and development (R&D) projects and their transition to innovation. A key aspect to explain it are mindsets, which are one of the most complex to explain due to the number of factors they contain. What remains unclear is how people might have patterns of understanding the processes and activities that define mental models. This paper aims to explore how persons involved in R&D activities have a pattern to understand the processes. Data for this study were collected using a survey applied to directives, coordinators, technology managers, intellectual property managers, researchers, and entrepreneurs in a group of 11 universities in Medellín (Colombia) through a computational clustering analysis. The main contribution of this article is the generation of five patterns or mental models, in which the different roles linked to R&D converge, to this extent we could speak of shared mental models. One of the more significant findings that emerge from this study is that a simpler mental model with specific and relevant activities prioritised may work better than a complex one. |
| first_indexed | 2024-03-11T20:38:12Z |
| format | Article |
| id | doaj.art-437c1dbf190a4e8db1d408193933134d |
| institution | Directory Open Access Journal |
| issn | 2199-8531 |
| language | English |
| last_indexed | 2024-03-11T20:38:12Z |
| publishDate | 2022-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Open Innovation: Technology, Market and Complexity |
| spelling | doaj.art-437c1dbf190a4e8db1d408193933134d2023-10-02T04:53:13ZengElsevierJournal of Open Innovation: Technology, Market and Complexity2199-85312022-08-01815415410.3390/joitmc8030154Computational Clustering Applied to Mental Models for Understanding the Valley of Death in Innovation ProcessesJim Giraldo-Builes0René Yepes1Iván Rojas2Juan Carlos Briñez-De León3Grupo Qualipro, Facultad de Producción y Diseño, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellín 050034, ColombiaGrupo GTI.UPB, Universidad Pontificia Bolivariana, Medellín 050031, ColombiaGrupo Qualipro, Facultad de Producción y Diseño, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellín 050034, ColombiaGrupo GIIAM, Facultad de ingeniería, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellín 050034, ColombiaThe Valley of Death is the gap between the completion of research and development (R&D) projects and their transition to innovation. A key aspect to explain it are mindsets, which are one of the most complex to explain due to the number of factors they contain. What remains unclear is how people might have patterns of understanding the processes and activities that define mental models. This paper aims to explore how persons involved in R&D activities have a pattern to understand the processes. Data for this study were collected using a survey applied to directives, coordinators, technology managers, intellectual property managers, researchers, and entrepreneurs in a group of 11 universities in Medellín (Colombia) through a computational clustering analysis. The main contribution of this article is the generation of five patterns or mental models, in which the different roles linked to R&D converge, to this extent we could speak of shared mental models. One of the more significant findings that emerge from this study is that a simpler mental model with specific and relevant activities prioritised may work better than a complex one.https://www.mdpi.com/2199-8531/8/3/154innovation processmental modelsValley of Deathcomputational clusteringdata science |
| spellingShingle | Jim Giraldo-Builes René Yepes Iván Rojas Juan Carlos Briñez-De León Computational Clustering Applied to Mental Models for Understanding the Valley of Death in Innovation Processes Journal of Open Innovation: Technology, Market and Complexity innovation process mental models Valley of Death computational clustering data science |
| title | Computational Clustering Applied to Mental Models for Understanding the Valley of Death in Innovation Processes |
| title_full | Computational Clustering Applied to Mental Models for Understanding the Valley of Death in Innovation Processes |
| title_fullStr | Computational Clustering Applied to Mental Models for Understanding the Valley of Death in Innovation Processes |
| title_full_unstemmed | Computational Clustering Applied to Mental Models for Understanding the Valley of Death in Innovation Processes |
| title_short | Computational Clustering Applied to Mental Models for Understanding the Valley of Death in Innovation Processes |
| title_sort | computational clustering applied to mental models for understanding the valley of death in innovation processes |
| topic | innovation process mental models Valley of Death computational clustering data science |
| url | https://www.mdpi.com/2199-8531/8/3/154 |
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