Gender Effects in Directed versus Incidental Learning in a 3D Virtual World Simulation

Kahal, Surinder; Jestice, Rebecca; Huang, Rui

doi:10.17705/1thci.00083

Cited by 7 publications

(8 citation statements)

References 24 publications

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“…Computers, computing technologies, and robots offer flexible and multiple capabilities where a human can interact with another human. Therefore, when human-machine interaction is considered from a broader perspective, human-robot interaction focuses on broad topics beyond objective system usability such as interface design, user-centered design, social computing, augmented reality, mobile and desktop platforms (Johnson et al. , 2016).…”

Section: Methodsmentioning

confidence: 99%

“…They have determined that the performance records of the employees can be made correctly thanks to the information systems. Johnson et al. (2016) carried out a case study in the same field.…”

Section: Methodsmentioning

confidence: 99%

“…Smart human resources management usability such as interface design, user-centered design, social computing, augmented reality, mobile and desktop platforms (Johnson et al, 2016).…”

Section: Article Selection Processmentioning

confidence: 99%

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From traditional to smart human resources management

Kambur

Yıldırım

2022

IJM

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PurposeThe 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.Design/methodology/approachA 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.FindingsThe 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.Originality/valueThis 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.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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From traditional to smart human resources management

Kambur

Yıldırım

2022

IJM

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“…In other words, technology, specifically a HRIS, is central to how organizations deploy and deliver HR functionality and how they manage people. As we noted in our first introduction, much of the research on HRIS/eHRM has appeared in the management, human resources, and industrial/organizational psychology literature (Johnson, Lukaszewski, & Stone, 2016b) and often not focused on how technology design and HCI issues may affect HR outcomes. Therefore, this special issue, we bring together scholars interested in HCI and eHRM and who conduct research that spans the domains of HCI, information systems, and HRIS.…”

Section: Integrating Hci Principles With Ehrmmentioning

confidence: 99%

The Importance of the Interface between Humans and Computers on the Effectiveness of eHRM

Johnson¹,

Lukaszewski²,

Stone³

2017

THCI

Self Cite

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Abstract:Technology has had a dramatic impact on the practice of human resources, and its impact is rapidly increasing. Even so, little research has examined how to apply information systems and human-computer interaction principles to designing human resource information systems. In this paper, we focus more closely on the role that the interface between the computer and human play in the success of electronic human resource management. Specifically, we a) briefly review the individual requirements of several eHRM functions (e.g., e-recruiting, e-selection, e-learning, ecompensation/benefits), b) consider how an understanding of human computer interaction can facilitate the success of these systems, c) reviews research on technical issues associated with eHRM, and d) highlight how applying HCI principles can increase their effectiveness. In addition, we introduce the remaining seven papers in the special issue.

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“…The increasing importance of IT for the HRM market segment is also attested to by recent takeover movements of major software industry players such as SAP, Oracle and IBM, whose respective acquisitions totaled over 1 billion US$ (CB Insight, 2013; Reuters, 2014). Within the scientific community, the increasing importance of e-HRM is attested to by numerous calls for research and the publication of special issues in HR or IS journals including the International Journal of Human Resource Management (Bondarouk and Ruel, 2009), the German Journal of Research in Human Resource Management (Strohmeier et al , 2012), the Journal of Strategic Information Systems (Grant and Newell, 2013; Parry and Strohmeier, 2014), the journal Employee Relations (Parry and Strohmeier, 2014) and recently the journal AIS Transaction on Human–Computer Interaction (Johnson et al , 2016b).…”

Section: Introductionmentioning

confidence: 99%

Taxonomy of business value underlying motivations for e-HRM adoption

Poba‐Nzaou

Uwizeyemunugu

Gaha

et al. 2020

BPMJ

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PurposeThe purpose of this paper was to develop a taxonomy of organizations based on business value (BV) underlying electronic human resource management (e-HRM) adoption motivations.Design/methodology/approachA taxonomy was developed using cluster analysis of the online case stories of 146 firms. Results were validated using discriminant analysis. Differences in organization and environmental characteristics across clusters were examined.FindingsSeven meaningful and distinct clusters were uncovered showing asymmetry in the consideration of strategic BV underlying the motivations of e-HRM adoption. Statistical tests revealed that the seven clusters have high internal validity. Statistically significant differences in organizational conditions were found among clusters.Research limitations/implicationsThis research offers an empirically and conceptually grounded taxonomy of organizations that reveals strategic and nonstrategic BV that organizations actually put forward and the way they combine together to form different profiles. This research is based on secondary data, that is, data initially gathered for a distinct goal different from this research.Practical implicationsThe developed taxonomy provides human resource (HR) managers, executives, researchers and consultants a useful way to describe and understand motivations underlying e-HRM adoption. The taxonomy may also facilitate valid and systematic assessment of e-HRM effectiveness.Originality/valueThis research moves the debate beyond normative arguments to a more analytic assessment of the actual practice of organizations regarding e-HRM adoption and expected BV.

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Gender Effects in Directed versus Incidental Learning in a 3D Virtual World Simulation

Cited by 7 publications

References 24 publications

From traditional to smart human resources management

From traditional to smart human resources management

The Importance of the Interface between Humans and Computers on the Effectiveness of eHRM

Taxonomy of business value underlying motivations for e-HRM adoption

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