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Datasets of skills-rating questionnaires for advanced service design through expert knowledge elicitation

This article presents a dataset of service design skills which service design experts value as important requirements for design team members. Purposive sampling and a chain referral approach were used to recruit appropriate experts to conduct questionnaire-based research. Using the analytical hiera...

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Detalles Bibliográficos
Autores principales: Nguyen, Hien Ngoc, Lasa, Ganix, Iriarte, Ion, Atxa, Ariane, Unamuno, Gorka, Galfarsoro, Gurutz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9203804/
http://dx.doi.org/10.1038/s41597-022-01421-3
Descripción
Sumario:This article presents a dataset of service design skills which service design experts value as important requirements for design team members. Purposive sampling and a chain referral approach were used to recruit appropriate experts to conduct questionnaire-based research. Using the analytical hierarchy process (AHP), pairwise skills-rating questionnaires were designed to elicit the experts’ responses. The resulting dataset was processed using AHP algorithms programmed in R programming language. The transparent data and available codes of the research may be reused by design practitioners and researchers for replication and further analysis. This paper offers a reproduceable research process and associated dataset for conducting multiple-criteria decision analysis with expert purposive sampling.