Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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This article examines the career narratives of healthcare executives to develop a model of executive leadership competencies. Interviews with thirty executives drawn from a health leadership podcast are examined for themes of leadership failures and surprises. Grounded theory is used to identify a pattern of weaknesses from the lived experiences the executives, then a positive model of leadership is developed from these lessons learned the hard way. The final model consists of three nested categories: organizational awareness, constructing the team, and selfregulation.
Mark J. Bonica. 2020. \u201cLearned the Hard Way: A Model of Executive Leadership Competencies\u201d. Global Journal of Management and Business Research - A: Administration & Management GJMBR-A Volume 20 (GJMBR Volume 20 Issue A12): .
Crossref Journal DOI 10.17406/GJMBR
Print ISSN 0975-5853
e-ISSN 2249-4588
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Total Score: 133
Country: United States
Subject: Global Journal of Management and Business Research - A: Administration & Management
Authors: Mark J. Bonica, Christopher Mayhugh, Mark D. Mellott (PhD/Dr. count: 0)
View Count (all-time): 164
Total Views (Real + Logic): 2308
Total Downloads (simulated): 962
Publish Date: 2020 08, Tue
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Neural Networks and Rules-based Systems used to Find Rational and
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This article examines the career narratives of healthcare executives to develop a model of executive leadership competencies. Interviews with thirty executives drawn from a health leadership podcast are examined for themes of leadership failures and surprises. Grounded theory is used to identify a pattern of weaknesses from the lived experiences the executives, then a positive model of leadership is developed from these lessons learned the hard way. The final model consists of three nested categories: organizational awareness, constructing the team, and selfregulation.
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