2026-04-23T11:40:14Zhttps://ebiltegia.mondragon.edu/oai/request

oai:ebiltegia.mondragon.edu:20.500.11984/58212024-03-04T13:30:25Zcom_20.500.11984_473col_20.500.11984_478

Datasets of skills-rating questionnaires for advanced service design through expert knowledge elicitation Nguyen Ngoc, Hien Lasa, Ganix Iriarte, Ion Atxa Gamboa, Ariane Unamuno Eguren, Gorka Galfarsoro Urrestilla, Gurutz 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. 2022-11-10T10:15:47Z 2022-11-10T10:15:47Z 2022 http://purl.org/coar/resource_type/c_6501 2052-4463 https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=167940 https://hdl.handle.net/20.500.11984/5821 eng Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ © 2022 The Authors Springer Nature