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Article
Publication date: 19 July 2024

Martina Mori, Sara Sassetti, Vincenzo Cavaliere and Mariacristina Bonti

Starting from the relevance of ethics to the application of artificial intelligence (AI) in the context of employee recruitment and selection (R&S), in this article, we aim to…

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Abstract

Purpose

Starting from the relevance of ethics to the application of artificial intelligence (AI) in the context of employee recruitment and selection (R&S), in this article, we aim to provide a comprehensive review of the literature in light of the main ethical theories (utilitarian theories, theories of justice, and theories of rights) to identify a future research agenda and practical implications.

Design/methodology/approach

On the basis of the best-quality and most influential journals, we conducted a systematic review of 120 articles from two databases (Web of Science and Scopus) to provide descriptive results and adopt a framework for deductive classification of the main topics.

Findings

Inspired by the three ethical theories, we identified three thematic lines of enquiry for the debate on AI in R&S: (1) the utilitarian view: the efficient optimisation of R&S through AI; (2) the justice view: the perceptions of justice and fairness related to AI techniques; and (3) the rights view: the respect for legal and human rights requirements when AI is applied.

Originality/value

This article provides a detailed assessment of the adoption of AI in the R&S process from the standpoint of traditional ethics theories and offers an integrative theoretical framework for future research on AI in the broader field of HRM.

Details

Personnel Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0048-3486

Keywords

Available. Content available
Article
Publication date: 21 November 2019

Alessandra Marasco, Marcella De Martino, Alfonso Morvillo and Cihan Cobanoglu

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Abstract

Details

International Journal of Contemporary Hospitality Management, vol. 31 no. 11
Type: Research Article
ISSN: 0959-6119

Available. Content available
Book part
Publication date: 23 September 2021

Sara Sassetti

Abstract

Details

Entrepreneurship and Emotions: Insights on Venture Performance
Type: Book
ISBN: 978-1-80117-354-4

Available. Open Access. Open Access
Article
Publication date: 15 September 2020

Armando Papa, Roberto Chierici, Luca Vincenzo Ballestra, Dirk Meissner and Mehmet A. Orhan

This study aims to investigate the effects of open innovation (OI) and big data analytics (BDA) on reflective knowledge exchange (RKE) within the context of complex collaborative…

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Abstract

Purpose

This study aims to investigate the effects of open innovation (OI) and big data analytics (BDA) on reflective knowledge exchange (RKE) within the context of complex collaborative networks. Specifically, it considers the relationships between sourcing knowledge from an external environment, transferring knowledge to an external environment and adopting solutions that are useful to appropriate returns from innovation.

Design/methodology/approach

This study analyzes the connection between the number of patent applications and the amount of OI, as well as the association between the number of patent applications and the use of BDA. Data from firms in the 27 European Union countries were retrieved from the Eurostat database for the period 2014–2019 and were investigated using an ordinary least squares regression analysis.

Findings

Because of its twofold lens based on both knowledge management and OI, this study sheds light on OI collaboration modes and highlights the crucial role they could play in innovation. In particular, the results suggest that OI collaboration modes have a strong effect on innovation performance, stimulating the search for RKE.

Originality/value

This study furthers a deeper understanding of RKE, which is shown to be an important mechanism that incentivizes firms to increase their efforts in the innovation process. Further, RKE supports firms in taking full advantage of the innovative knowledge they generate within their inter-organizational network.

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