Impact of Health Care Employees Job Satisfaction on Organizational Performance Support Vector Machine Approach

Cemil Kuzey ()
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Cemil Kuzey: Murray State University

Journal of Economics and Financial Analysis, 2018, vol. 2, issue 1, 45-68

Abstract: This study is undertaken to search for key factors that contribute to job satisfaction among health care workers, and also to determine the impact of these underlying dimensions of employee satisfaction on organizational performance. Exploratory Factor Analysis (EFA) is applied to initially uncover the key factors, and then, in the next stage of analysis, a popular data mining technique, Support Vector Machine (SVM) is employed on a sample of 249 to determine the impact of job satisfaction factors on organizational performance. According to the proposed model, the main factors are revealed to be management's attitude, pay/reward, job security and colleagues.

Keywords: Job Satisfaction; Health Care Workers; Support Vector Machine (SVM). (search for similar items in EconPapers)
JEL-codes: J28 J54 J59 J81 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:trp:01jefa:jefa0012

DOI: 10.1991/jefa.v2i1.a12

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