Exploring the Effects of Learning Organization on Innovative Work Behaviors of White-Collar Workers: Sample from Turkey
Biçer Mehmet ()
Additional contact information
Biçer Mehmet: Kilis 7 Aralık University
A chapter in Organizational Mindset of Entrepreneurship, 2020, pp 79-100 from Springer
Abstract:
Abstract The main purpose of this research is to determine the effects of seven different learning organization types—such as continuous learning, inquiry and dialog, team learning, embedded systems, empowerment, system connection, sharing systems, strategic leadership on innovative work behaviors of white-collar employees who work in different companies. In order to test these effects, an inquiry was conducted on the employees who were the labor of Turkey’s top 500 industrial companies determined by Istanbul Chamber of Industry. Data obtained from 526 participants were used in the analysis of the research. As a result of the correlation analysis, significant and positive relations were determined between all components of learning organization and IWB. Regression analysis was performed to reveal the effects of learning organizations on IWB. According to the results, it has been identified that only continuous learning (0.479, p
Keywords: Learning organization; Innovation work behavior; Organizational learning (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:seschp:978-3-030-36951-4_5
Ordering information: This item can be ordered from
http://www.springer.com/9783030369514
DOI: 10.1007/978-3-030-36951-4_5
Access Statistics for this chapter
More chapters in Studies on Entrepreneurship, Structural Change and Industrial Dynamics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().