- Tytuł:
- Unraveling key drivers for engineer creativity and meaningfulness of work: Bayesian network approach
- Autorzy:
-
Wipulanusat, Warit
Panuwatwanich, Kriengsak
Stewart, Rodney A.
Parnphumeesup, Piya
Sunkpho, Jirapon - Powiązania:
- https://bibliotekanauki.pl/articles/407381.pdf
- Data publikacji:
- 2020
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
creativity
work meaningfulness
path analysis
Bayesian networks
engineers - Opis:
- This study builds on an existing structural model developed to examine the influence of leadership and organizational culture on innovation and satisfaction of engineers in Australian public sectors (APS). The objective of this study is to increase the understanding of innovation process with a focus on causal relationships among critical factors. To achieve this objective, the study develops an assessment approach to help predict creativity and work meaningfulness of engineers in the APS. Three quantitative analysis methods were sequentially conducted in this study including correlation analysis, path analysis, and Bayesian networks. A correlation analysis was conducted to pinpoint the strong association between key factors studied. Subsequently, path analysis was employed to identify critical pathways which were accordingly used as a structure to develop Bayesian networks. The findings of the study revealed practical strategies for promoting (1) transformational leadership and (2) innovative culture in public sector organizations since these two factors were found to be key drivers for individual creativity and work meaningfulness of their engineers. This integrated approach may be used as a decision support tool for managing the innovation process for engineers in the public sectors.
- Źródło:
-
Management and Production Engineering Review; 2020, 11, 2; 26-37
2080-8208
2082-1344 - Pojawia się w:
- Management and Production Engineering Review
- Dostawca treści:
- Biblioteka Nauki
Artykuł