2 research outputs found
Datasets of skills-rating questionnaires for advanced service design through expert knowledge elicitation
No full textThis 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
Human-centered design for advanced services: A multidimensional design methodology
No full textAdvanced services have caught the attention of industries and academics as a way to exploit new customer value propositions. However, the existing design methodologies for advanced services are limited to partially addressing one or some key design elements, hence causing confusion in practice. Moreover, human factors are not often addressed, even though the design for advanced services requires human-centered thinking. Aiming to advance the body of research, the current study aims to conceptually propose a multidimensional design methodology called DIMAND that captures the key design elements and their relations in a single-view structure in accordance with a human-centric approach. Specifically, DIMAND encapsulates the (i) life-cycle service design interrelated with other key design elements—(ii) stakeholder networks, (iii) new service development methods, and (iv) design skills—that must be considered to develop effective advanced service design. Based on a hybrid research design, DIMAND was conceptually developed through systematic reviews and structured analysis of existing design methodologies, as well as an elicitation of expert knowledge in the domain through the analytical hierarchy process (AHP). For validation, the average usability score of DIMAND as evaluated by 26 practitioners was 72.2, which falls into “excellence” on the simplified system usability scale (SUS), hence confirming its potential utility. As a result, DIMAND offers a novel and holistic guideline for design practitioners and engineers to obtain coherence in all the life-cycle design processes by simultaneously taking these key design elements and their relations into account, making the design of advanced services more practical
