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The aim of this study is to develop a reliable and valid scale. At the same time, it is to reveal the perceptions of HR employees towards artificial intelligence (AI). In addition, examining the change made by AI in the HR department is another purpose of the study.

A scale was developed in this study. A total of 821 observation out of the samples from the human resource managers and employees of the Turkey's largest organizations in terms of capital were analyzed by applying all scientific steps of scale development process. Using appropriate statistical criteria, scale was showed to be valid and reliable. General condition was demonstrated in the human resource departments of large companies in Turkey as a result of these tests.

Human resource employees and managers could have the perception that this technology will save the work done from monotony, reduce the stress experienced to find the suitable candidate and access more candidates with the desired qualifications. It was found that when AI technology was included in training and development process, human resource managers and employees could have a perception that the time spent for training and the lack of attention in training will decrease compared to the traditional method.

The contribution of this study to the literature is the development of a valid and reliable scale. Data collected with the developed scale were evaluated in Turkey.

This study aims to examine the current state of literature on structural equation modeling (SEM) studies in “cloud computing” domain with respect to study domains of research studies, theories and frameworks they use and SEM models they design.

Systematic literature review (SLR) protocol is followed. In total, 96 cloud computing studies from 2009 to June 2018 that used SEM obtained from four databases are selected, and relevant data are extracted to answer the research questions.

A trend of increasing SEM usage over years in cloud studies is observed, where technology adoption studies are found to be more common than the use studies. Articles appear under four main domains, namely, business, personal use, education and health care. Technology acceptance model (TAM) is found to be the most commonly used theory. Adoption, intention to use and actual usage are the most common selections for dependent variables in SEM models, whereas security and privacy concerns, costs, ease of use, risks and usefulness are the most common selections for causal factors.

Previous cloud computing SLR studies did not focus on statistical analysis method used in primary studies. This review will display the current state of SEM studies in cloud domain for all future academics and practical professionals.