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The present study investigates human behavioral and emotional experiences based on human-built environment interaction with a specific interest in urban graffiti displaying fear and pleasure-inducing facial expressions. Regarding human behavioral and emotional experience, two questions are asked for the outcome of human responses and two hypotheses are formulated. H1 is based on the behavioral experience and posits that the urban graffiti displaying fear and pleasure-inducing facial expressions elicit specified behavioral fear and pleasure responses. H2 is based on emotional experience and states that the urban graffiti displaying fear and pleasure-inducing facial expressions elicit specified emotional fear and pleasure responses.

The research design is developed as a multi-method approach, applying a lab-based experimental strategy (N:39). The research equipment includes a mobile electroencephalogram (EEG) and a Virtual Reality (VR) headset. The behavioral and emotional human responses concerning the representational features of urban graffiti are assessed objectively by measuring physiological variables, EEG signals and subjectively by behavioral variables, systematic behavioral observation and self-report variables, Self-assessment Manikin (SAM) questionnaire. Additionally, correlational analyses between behavioral and emotional results are performed.

The findings of behavioral and emotional evaluations and correlational results show that specialized fear and pleasure response patterns occur due to the affective characteristics of the urban graffiti's representational features, supporting our hypotheses. As a result, the characteristics of behavioral fear and pleasure response and emotional fear and pleasure response are identified.

The present paper contributes to the literature on human-built environment interactions by using physiological, behavioral and self-report measurements as indicators of human behavioral and emotional experiences. Additionally, the literature on urban graffiti is expanded by studying the representational features of urban graffiti as a parameter of investigating human experience in the built environment.

The purpose of this article is to examine all the studies carried out within the scope of e-HRM and smart HRM, grouped according to the sub-functions of technical and HRM. The use of technology in HRM has started since the mid-1990s. However, this study focused on the articles published after 2014 in order to keep up to date. Any search strategy should allow for the completeness of the search to be evaluated. The terms “electronic-HRM”, “AI and HRM”, “Industry 4.0 and HRM”, “Society 5.0 and HRM”, “Human Resource Information Systems” and “Digital Technologies and HRM” “Human-robot interaction” has been questioned in IEEE Xplore, ALM digital library, Emerald Insight, SpringerLink, and Science Direct. The Web of Science and Scopus were also queried to double-check the findings and find other relevant articles in lesser-known libraries. Google Scholar was also used for forward and backward searches. These online databases have been chosen because they present the most important peer-reviewed full-text journals, conference proceedings, book chapters. Then, the references of each article were reviewed for additional articles on digital technologies and HRM. Each subsequent article is then reviewed for additional reference.

A total of 5,580 articles have been reviewed. Duplicate items have been removed. The titles and abstracts of 3,500 articles have been scanned to identify potential articles. The full-text evaluation of 2,554 was based on compliance with the inclusion criteria. In addition, 2,458 studies have been excluded. In total, 96 studies have been selected for data extraction. Additionally, questionnaires and reviews have been used to provide comprehensive research on e-HRM and smart HRM. The search terms used are expected to cover most, if not all, of the studies involving e-HRM and smart HRM.

The study carried out in this article is qualitative research. In the article, which methods are used and what has changed in e-HRM and smart HRM are examined. In particular, it has been thought about what can happen with the inclusion of human-machine interaction, AI, chatbots, industry 4.0 and information systems in HRM. Unlike previous studies, this review takes HRM from a broader perspective and groups it by topic, both by technical and HR functions. In addition, the reviewed articles provide brief information about the AI technologies used. In particular, criteria were taken into account according to the field, type and subject of the articles.

This study has the distinction of being the first in the literature in terms of examining all the studies carried out within the scope of e-HRM and smart HRM and grouped according to the sub-functions of technical and HRM in line with its purpose. The article focuses specifically on research published after 2014. It is expected to contribute to the literature in terms of collecting all studies in a single article. Other contributions of this article can be summarized in four main articles: 1) it presents a summary of previous research by grouping the studies on e-HRM and smart HRM according to the interests of researchers. 2) It saves time for the reader as it provides a brief explanation of the studies on the subject. 3) Instead of explaining in detail the general details analyzed in other articles, it offers a practical perspective by focusing on the type, subject and field of the article. 4) With the digitalization of HRM, new, up-to-date research and techniques are introduced.