The Role of Job Satisfaction in Turnover and Turn-away Intention of IT Staff in South Africa

Abstract:
Aim/Purpose: This study forms part of the World IT Project, which aims to gain a deeper understanding of individual, personal and organisational factors influencing IT staff in a modern, work environment. The project also aims to provide a global view that complements the traditional American/Western view. The purpose of this study is to investigate and report on some of these factors, in particular, the role that job satisfaction has in turnover intention (i.e., changing jobs within the IT industry) and turn-away intention (i.e., moving to another industry other than IT) in South Africa. Background: Several studies have reported on the importance of an employee’s job satisfaction to organisation success, and the various factors that influence it. Most studies on job satisfaction adopted a Westernised and not a global view. Very few empirical studies have been conducted on job satisfaction of IT workers in South Africa. This paper reports on the individual, personal and organisational factors that influence the job satisfaction of IT staff in South Africa. Methodology: The study uses statistical analysis of survey data acquired through the World IT Project. Both online and paper based questionnaires were used. A sample size of 301 respondents was obtained from the survey, which was conducted over a period of 6 months during 2017. The factors that influence IT job satisfaction were analysed using correlation analysis, multiple regression analysis and discriminant analysis. The factors investigated were employee and organisational demographics, aspects of occupational culture, and various job-related individual issues. Contribution: This paper presents the only study focused specifically on turnover and turn-away intention amongst IT staff in South Africa. The final proposed model, grounded in the empirical dataset, clearly shows job satisfaction as a strong mediating construct explaining most of the variance in the IT professional’s intention to leave the organisation (i.e. their turnover intention) and the industry (i.e. their turn-away intention). Findings: The findings revealed that there was a significant correlation between job satisfaction and turnover intention as well as between job satisfaction and turn-away intention of IT staff. Perceived professional self-efficacy, strain and experience were also highly correlated with turnover intention. Professional self-efficacy was also significantly correlated with turn-away intention. Based on the analyses that were conducted, a research model is presented that shows the relationships between the various antecedents of turnover and turn-away intention. Recommendations for Practitioners: Managers in organisations dealing with the shortage of IT skills can use the model to plan interventions to reduce IT staff turnover rates by focussing on addressing the identified individual issues such as strain, job (in)security and work load as well as the personal value and IT occupational culture issues. Recommendation for Researchers: Researchers in the field of IT staff recruitment and management can find value for their research in the proposed refined model of IT job satisfaction and turnover intention. Future research could possibly replicate the study in other countries or could focus on different factors. Impact on Society: IT skills play a crucial role in society today and are therefore in high demand. However, this demand is not being satisfied by the current rate of supply. Research into what factors influence IT staff to leave the organisation or the industry can assist managers with improving their employee relations and job conditions so as to reduce this turnover and increase organisations’ and society’s competitiveness and economic growth. Future Research: It would be interesting to determine if the findings are similar for a sample of smaller organisations and/or younger IT employees since this study focussed on larger organisations and more experienced staff. Future research could also compare the findings of South African organisations with those in other countries.
Author Listing: Brenda Scholtz;Kennedy Njenga;Alexander Serenko;Prashant Palvia
Volume: 14
Pages: 077-097
DOI: 10.28945/4267
Language: English
Journal: Interdisciplinary Journal of Information, Knowledge, and Management

Interdisciplinary Journal of Information, Knowledge, and Management

影响因子:0.0 是否综述期刊:否 是否OA:否 是否预警:不在预警名单内 发行时间:- ISSN:1555-1229 发刊频率:- 收录数据库:Scopus收录 出版国家/地区:- 出版社:Informing Science Institute

期刊介绍

年发文量 -
国人发稿量 -
国人发文占比 -
自引率 0.0%
平均录取率 -
平均审稿周期 -
版面费 -
偏重研究方向 Computer Science-Computer Science (all)
期刊官网 -
投稿链接 -

质量指标占比

研究类文章占比 OA被引用占比 撤稿占比 出版后修正文章占比
0.00% 0.00% - -

相关指数

{{ relationActiveLabel }}
{{ item.label }}

期刊预警不是论文评价,更不是否定预警期刊发表的每项成果。《国际期刊预警名单(试行)》旨在提醒科研人员审慎选择成果发表平台、提示出版机构强化期刊质量管理。

预警期刊的识别采用定性与定量相结合的方法。通过专家咨询确立分析维度及评价指标,而后基于指标客观数据产生具体名单。

具体而言,就是通过综合评判期刊载文量、作者国际化程度、拒稿率、论文处理费(APC)、期刊超越指数、自引率、撤稿信息等,找出那些具备风险特征、具有潜在质量问题的学术期刊。最后,依据各刊数据差异,将预警级别分为高、中、低三档,风险指数依次减弱。

《国际期刊预警名单(试行)》确定原则是客观、审慎、开放。期刊分区表团队期待与科研界、学术出版机构一起,夯实科学精神,打造气正风清的学术诚信环境!真诚欢迎各界就预警名单的分析维度、使用方案、值得关切的期刊等提出建议!

预警情况 查看说明

时间 预警情况
2024年02月发布的2024版 不在预警名单中
2023年01月发布的2023版 不在预警名单中
2021年12月发布的2021版 不在预警名单中
2020年12月发布的2020版 不在预警名单中

JCR分区 WOS分区等级:Q0区

版本 按学科 分区
WOS期刊SCI分区
WOS期刊SCI分区是指SCI官方(Web of Science)为每个学科内的期刊按照IF数值排 序,将期刊按照四等分的方法划分的Q1-Q4等级,Q1代表质量最高,即常说的1区期刊。
(2021-2022年最新版)

关于2019年中科院分区升级版(试行)

分区表升级版(试行)旨在解决期刊学科体系划分与学科发展以及融合趋势的不相容问题。由于学科交叉在当代科研活动的趋势愈发显著,学科体系构建容易引发争议。为了打破学科体系给期刊评价带来的桎梏,“升级版方案”首先构建了论文层级的主题体系,然后分别计算每篇论文在所属主题的影响力,最后汇总各期刊每篇论文分值,得到“期刊超越指数”,作为分区依据。

分区表升级版(试行)的优势:一是论文层级的主题体系既能体现学科交叉特点,又可以精准揭示期刊载文的多学科性;二是采用“期刊超越指数”替代影响因子指标,解决了影响因子数学性质缺陷对评价结果的干扰。整体而言,分区表升级版(试行)突破了期刊评价中学科体系构建、评价指标选择等瓶颈问题,能够更为全面地揭示学术期刊的影响力,为科研评价“去四唯”提供解决思路。相关研究成果经过国际同行的认可,已经发表在科学计量学领域国际重要期刊。

《2019年中国科学院文献情报中心期刊分区表升级版(试行)》首次将社会科学引文数据库(SSCI)期刊纳入到分区评估中。升级版分区表(试行)设置了包括自然科学和社会科学在内的18个大类学科。基础版和升级版(试行)将过渡共存三年时间,推测在此期间各大高校和科研院所仍可能会以基础版为考核参考标准。 提示:中科院分区官方微信公众号“fenqubiao”仅提供基础版数据查询,暂无升级版数据,请注意区分。

中科院分区 查看说明

版本 大类学科 小类学科 Top期刊 综述期刊
暂无数据