Evaluating Collaboration in a Translational Research Ecosystem
A core challenge of a multidisciplinary and multi-organizational translational research program is to set up and promote collaboration between researchers, labs, and organizations. Although the literature has studied and provided guidelines for collaboration, little has been written on how to evalua...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/11/10/503 |
| _version_ | 1797572227605987328 |
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| author | Néstor Armando Nova Rafael Andrés González |
| author_facet | Néstor Armando Nova Rafael Andrés González |
| author_sort | Néstor Armando Nova |
| collection | DOAJ |
| description | A core challenge of a multidisciplinary and multi-organizational translational research program is to set up and promote collaboration between researchers, labs, and organizations. Although the literature has studied and provided guidelines for collaboration, little has been written on how to evaluate it in large research projects and in a practical way. This study aims to identify dimensions and barriers to evaluating and leveraging collaboration in a large translational research ecosystem related to developing phytotherapy-based cancer treatments. By applying the Collaboration Evaluation and Improvement Framework (CEIF), our paper adds value by developing a methodological design for evaluation, incorporating mixed data in a real research ecosystem. Empirical findings provide support for applying the assessment approach and show that a research project’s sustainability depends on several collaboration factors and barriers at the socio-technical, management, operational, and institutional levels. Research results provide valuable insights for managing and improving collaborative efforts in large research groups, by anticipating collaboration issues with actionable and opportune strategies that can enhance the planning process, ecosystem performance, sustainability, research outcomes, and the program’s overall success. As a result, monitoring governance, management, leadership, and social relationships throughout the different phases of a translational research program is crucial in assessing and promoting collaboration. |
| first_indexed | 2024-03-10T20:51:23Z |
| format | Article |
| id | doaj.art-fbfb955ebae6481caac0eca995735b25 |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-03-10T20:51:23Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-fbfb955ebae6481caac0eca995735b252023-11-19T18:19:42ZengMDPI AGSystems2079-89542023-10-01111050310.3390/systems11100503Evaluating Collaboration in a Translational Research EcosystemNéstor Armando Nova0Rafael Andrés González1Department of Information Science, Pontificia Universidad Javeriana, Bogotá 110231, ColombiaDepartment of Systems Engineering, Pontificia Universidad Javeriana, Bogotá 110231, ColombiaA core challenge of a multidisciplinary and multi-organizational translational research program is to set up and promote collaboration between researchers, labs, and organizations. Although the literature has studied and provided guidelines for collaboration, little has been written on how to evaluate it in large research projects and in a practical way. This study aims to identify dimensions and barriers to evaluating and leveraging collaboration in a large translational research ecosystem related to developing phytotherapy-based cancer treatments. By applying the Collaboration Evaluation and Improvement Framework (CEIF), our paper adds value by developing a methodological design for evaluation, incorporating mixed data in a real research ecosystem. Empirical findings provide support for applying the assessment approach and show that a research project’s sustainability depends on several collaboration factors and barriers at the socio-technical, management, operational, and institutional levels. Research results provide valuable insights for managing and improving collaborative efforts in large research groups, by anticipating collaboration issues with actionable and opportune strategies that can enhance the planning process, ecosystem performance, sustainability, research outcomes, and the program’s overall success. As a result, monitoring governance, management, leadership, and social relationships throughout the different phases of a translational research program is crucial in assessing and promoting collaboration.https://www.mdpi.com/2079-8954/11/10/503research ecosystemresearch sustainabilitycollaborationtranslational researchnetwork analysis |
| spellingShingle | Néstor Armando Nova Rafael Andrés González Evaluating Collaboration in a Translational Research Ecosystem Systems research ecosystem research sustainability collaboration translational research network analysis |
| title | Evaluating Collaboration in a Translational Research Ecosystem |
| title_full | Evaluating Collaboration in a Translational Research Ecosystem |
| title_fullStr | Evaluating Collaboration in a Translational Research Ecosystem |
| title_full_unstemmed | Evaluating Collaboration in a Translational Research Ecosystem |
| title_short | Evaluating Collaboration in a Translational Research Ecosystem |
| title_sort | evaluating collaboration in a translational research ecosystem |
| topic | research ecosystem research sustainability collaboration translational research network analysis |
| url | https://www.mdpi.com/2079-8954/11/10/503 |
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