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Technology‐related factors and their influence on turnover intentions: A case of government employees in South Africa
Author(s) -
Mahlasela Samkelisiwe,
Chinyamurindi Willie T.
Publication year - 2020
Publication title -
the electronic journal of information systems in developing countries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.41
H-Index - 18
ISSN - 1681-4835
DOI - 10.1002/isd2.12126
Subject(s) - autonomy , government (linguistics) , job enrichment , sample (material) , turnover , work (physics) , information technology , business , service (business) , psychology , marketing , public relations , job attitude , job performance , social psychology , job satisfaction , political science , management , engineering , economics , mechanical engineering , philosophy , linguistics , chemistry , chromatography , law
Abstract The purpose of this article is to investigate the influence of technology‐related factors on the turnover intentions of a sample of government employees in South Africa. Technology‐related factors, as argued in the literature, consist of (a) technology‐based job autonomy, (b) technology‐based job overload and (c) technology‐based job monitoring. The backdrop of this study is twofold. First, technology is argued as a central feature to work especially amongst employees in the digital age. Second, the rate at which employees leave their jobs appears to be on the increase, especially within the South African public service. These two factors provide the impetus to our focus on studying turnover intentions. Using a sample of 186 government employees in the Eastern Cape Province of South Africa, a self‐administered questionnaire was deployed. The findings revealed that when employees experience technology‐based job autonomy this did not necessarily result in them having the intention to leave their work. Further, the findings also indicate and show support to the model being tested in that technology factors like: (a) technology‐based job overload and (b) technology‐based monitoring influence employee intentions to leave their work. Based on the findings of the research, recommendations and implications concerning theory and practice are made.

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