Beyond replacement: human-machine collaboration in the age of AI
Kunz, Werner H. ; Sajtos, Laszlo ; Flavián, Carlos (Universidad de Zaragoza)
Resumen: Purpose
The purpose is to advance the understanding of human-machine (H-M) collaboration in service industries, conceptualizing a framework that structures the research space and proposing a research agenda to guide future studies on optimizing collaboration dynamics, outcomes and ethical governance.
Design/methodology/approach
The authors use an artificial intelligence (AI)-based systematic literature based on the SERVSIG Literature Alert database to identify articles related to H-M collaboration. Insights from these papers were analyzed to (1) trace the evolution of H-M collaboration research, (2) formulate an integrative framework spanning foundational resources through outcomes and (3) develop a future research agenda.
Findings
The paper develops an integrative framework describing the foundation, process, and outcomes of H-M teamwork in service settings. It also introduces a set of new articles from the special issue.
Social implications
The paper underscores the ethical considerations (e.g. data biases, privacy and transparency) and broader societal concerns (e.g. job displacement and social inequality) and uniquely positions ethics as a cross-cutting theme (product, consumer and societal levels), moving beyond siloed ethical discussions in earlier work.
Originality/value
Unlike earlier work focusing on either human replacement or narrow task automation, this paper proposes a teamwork perspective, showing how AI and humans are working together and combining capabilities to achieve outcomes together. It maps diverse empirical studies to a comprehensive framework, demonstrating its applicability and enriching theoretical rigor with real-world evidence.
Keywords:Human-mach
Idioma: Inglés
DOI: 10.1108/JOSM-04-2025-0194
Año: 2025
Publicado en: Journal of Service Management (2025), 1-19
ISSN: 1757-5818
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Comerci.Investig.Mercados (Dpto. Direc.Mark.Inves.Mercad.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes.
Exportado de SIDERAL (2025-10-09-13:25:56)
Visitas y descargas
The purpose is to advance the understanding of human-machine (H-M) collaboration in service industries, conceptualizing a framework that structures the research space and proposing a research agenda to guide future studies on optimizing collaboration dynamics, outcomes and ethical governance.
Design/methodology/approach
The authors use an artificial intelligence (AI)-based systematic literature based on the SERVSIG Literature Alert database to identify articles related to H-M collaboration. Insights from these papers were analyzed to (1) trace the evolution of H-M collaboration research, (2) formulate an integrative framework spanning foundational resources through outcomes and (3) develop a future research agenda.
Findings
The paper develops an integrative framework describing the foundation, process, and outcomes of H-M teamwork in service settings. It also introduces a set of new articles from the special issue.
Social implications
The paper underscores the ethical considerations (e.g. data biases, privacy and transparency) and broader societal concerns (e.g. job displacement and social inequality) and uniquely positions ethics as a cross-cutting theme (product, consumer and societal levels), moving beyond siloed ethical discussions in earlier work.
Originality/value
Unlike earlier work focusing on either human replacement or narrow task automation, this paper proposes a teamwork perspective, showing how AI and humans are working together and combining capabilities to achieve outcomes together. It maps diverse empirical studies to a comprehensive framework, demonstrating its applicability and enriching theoretical rigor with real-world evidence.
Keywords:Human-mach
Idioma: Inglés
DOI: 10.1108/JOSM-04-2025-0194
Año: 2025
Publicado en: Journal of Service Management (2025), 1-19
ISSN: 1757-5818
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Comerci.Investig.Mercados (Dpto. Direc.Mark.Inves.Mercad.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes. Exportado de SIDERAL (2025-10-09-13:25:56)
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Record created 2025-09-26, last modified 2025-10-09