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Modelling Innovation competence profiles: the empowering roles of self-monitoring and resilience

BACKGROUND: Innovation competence has been found to constitute distinct innovative abilities that must be analyzed together to get a more comprehensive picture of their effectiveness in various targeted groups. Drawn from the componential theory of creativity, such personal traits as individual resi...

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Autores principales: Ojo, Kolawole Shola, Volkova, Natalia V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10523637/
https://www.ncbi.nlm.nih.gov/pubmed/37759263
http://dx.doi.org/10.1186/s40359-023-01340-x
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author Ojo, Kolawole Shola
Volkova, Natalia V.
author_facet Ojo, Kolawole Shola
Volkova, Natalia V.
author_sort Ojo, Kolawole Shola
collection PubMed
description BACKGROUND: Innovation competence has been found to constitute distinct innovative abilities that must be analyzed together to get a more comprehensive picture of their effectiveness in various targeted groups. Drawn from the componential theory of creativity, such personal traits as individual resilience and self-monitoring play a critical role in developing innovation competence across students. This research aims to investigate the innovation competence profiles of students from various educational levels and study the role of individual resilience and self-monitoring in predicting the memberships of these profiles. METHODS: A cross-sectional survey was conducted among university and college students, studying in a metropolitan area of the North-West region. The sampling scheme was stratified by the level of education and age. The questionnaire included items on the participants’ demographics, including gender, age, and level of education, measures of innovative abilities, individual resilience, and self-monitoring. This study sought to create innovation competence profiles in the student population using latent profile analysis. Multinomial logistic regression was employed to identify the impact of individual resilience and self-monitoring on innovation competence profile membership. RESULTS: A sample of 638 university and college students was analyzed. The latent profile analysis classified students into three different innovation competence profiles - strong, moderate, and weak - with college and female students being identified as the typical members of the weak profile. Individual resilience increases the odds of membership into the strong profile than to moderate and weak profiles. High self-monitors have higher chances of being profiled into the strong profile than the weak and moderate profiles compared to the low self-monitors. CONCLUSIONS: Training investment aimed at boosting the innovative abilities of employees should consider the innovation competence profile of the beneficiaries to inform decisions about the appropriate level of intervention required. Likewise, educators could enrich their courses devoted to improving the innovative abilities of students with content that aims to improve their level of resilience accompanied by social support. Theoretical and practical implications are also discussed.
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spelling pubmed-105236372023-09-28 Modelling Innovation competence profiles: the empowering roles of self-monitoring and resilience Ojo, Kolawole Shola Volkova, Natalia V. BMC Psychol Research BACKGROUND: Innovation competence has been found to constitute distinct innovative abilities that must be analyzed together to get a more comprehensive picture of their effectiveness in various targeted groups. Drawn from the componential theory of creativity, such personal traits as individual resilience and self-monitoring play a critical role in developing innovation competence across students. This research aims to investigate the innovation competence profiles of students from various educational levels and study the role of individual resilience and self-monitoring in predicting the memberships of these profiles. METHODS: A cross-sectional survey was conducted among university and college students, studying in a metropolitan area of the North-West region. The sampling scheme was stratified by the level of education and age. The questionnaire included items on the participants’ demographics, including gender, age, and level of education, measures of innovative abilities, individual resilience, and self-monitoring. This study sought to create innovation competence profiles in the student population using latent profile analysis. Multinomial logistic regression was employed to identify the impact of individual resilience and self-monitoring on innovation competence profile membership. RESULTS: A sample of 638 university and college students was analyzed. The latent profile analysis classified students into three different innovation competence profiles - strong, moderate, and weak - with college and female students being identified as the typical members of the weak profile. Individual resilience increases the odds of membership into the strong profile than to moderate and weak profiles. High self-monitors have higher chances of being profiled into the strong profile than the weak and moderate profiles compared to the low self-monitors. CONCLUSIONS: Training investment aimed at boosting the innovative abilities of employees should consider the innovation competence profile of the beneficiaries to inform decisions about the appropriate level of intervention required. Likewise, educators could enrich their courses devoted to improving the innovative abilities of students with content that aims to improve their level of resilience accompanied by social support. Theoretical and practical implications are also discussed. BioMed Central 2023-09-27 /pmc/articles/PMC10523637/ /pubmed/37759263 http://dx.doi.org/10.1186/s40359-023-01340-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ojo, Kolawole Shola
Volkova, Natalia V.
Modelling Innovation competence profiles: the empowering roles of self-monitoring and resilience
title Modelling Innovation competence profiles: the empowering roles of self-monitoring and resilience
title_full Modelling Innovation competence profiles: the empowering roles of self-monitoring and resilience
title_fullStr Modelling Innovation competence profiles: the empowering roles of self-monitoring and resilience
title_full_unstemmed Modelling Innovation competence profiles: the empowering roles of self-monitoring and resilience
title_short Modelling Innovation competence profiles: the empowering roles of self-monitoring and resilience
title_sort modelling innovation competence profiles: the empowering roles of self-monitoring and resilience
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10523637/
https://www.ncbi.nlm.nih.gov/pubmed/37759263
http://dx.doi.org/10.1186/s40359-023-01340-x
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