Title
Data science for service design: An introductory overview of methods and opportunities
Author
Kunneman, Y.
Alves da Motta-Filho, M.
de Waa, J
Publication year
2022
Abstract
To support effective and successful projects, Service Design practitioners rely on insights that mainly build on qualitative research methodology. The literature on data science promises to help transform how design research is done, adding sophisticated quantitative analyses, complementing existing methods with the power of machines. Due to this potential, data science receives widespread attention from both design practitioners and academics. However, the literature is fragmented and specialized, making it hard for designers to engage with data science. This paper addresses the opportunities and challenges for data science to support Service Design projects, evaluating existing technologies from designers’ perspective and providing an entry-level guide for service designers. These methods can help increase the quality of design research, making hidden information accessible and assisting creative processes. Together, these results are expected to inspire organizations to advance their data science resources for Service Design projects.
Subject
Service design
Data science
Data mining
Service design methods
Practised-based design research
To reference this document use:
http://resolver.tudelft.nl/uuid:abffeacf-7bd2-4288-a33c-6d1da1481ee7
DOI
https://doi.org/10.1080/14606925.2022.2042108
TNO identifier
966571
Source
the Design Journal, 25 (25), 186-204
Document type
article