Treffer: Transformational Leadership, Organizational Support, and Dynamic Ambidexterity Capabilities in Troubleshooting: Strategic Efforts to Improve Lecturer Performance: Empirical Evidence from Private Universities in Central Java Province and the Yogyakarta Special Region, Indonesia

Education is the key to achieve success in every sphere of life. That is why education of a nation should be managed in a right way to get high level in performance. The objective of this research is to dig deeper into the role of Transformational Leadership to enhance lecturers performance that is mediated by Organizational Support and Dynamic Ambidexterity Capability. Population of this research are lecturers in private universities in Central Java and the Special Region of Yogyakarta. The samples were taken randomly from 350 lecturers who have had academic position in their institutions. Data were collected by submitting questions to the respondents in the form of questionnaires. To get quality data, the present researchers undertook some tests concerning their validity, reliability, normality, and the properness. Structure Equation Modell was used to run a hypothetical test. The results of this research showed that Transformational Leadership had significant influence to Organizational Support and Dynamic Ambidexterity Capability. In turn, the Dynamic Ambidexterity Capability gave significant influence to Lecturer Performance in a positive way. This research concluded that Dynamic Ambidexterity Capability had a big role as a mediation variable in enhancing Lecturer Performance, whether it was preceded by exogenous variables or endogenous variables, or the combination of exogenous and endogenous variables. [ABSTRACT FROM AUTHOR]

Copyright of Quality - Access to Success is the property of Romanian Society for Quality Assurance (SRAC) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)