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Data science for service design: An introductory overview of methods and opportunities
The Design Journal ( IF 0.8 ) Pub Date : 2022-03-07 , DOI: 10.1080/14606925.2022.2042108
Youetta Kunneman 1 , Mauricy Alves da Motta-Filho 1 , Jasper van der Waa 2, 3
Affiliation  

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.



中文翻译:

服务设计的数据科学:方法和机会的介绍性概述

摘要

为了支持有效和成功的项目,服务设计从业者依赖主要基于定性研究方法的见解。数据科学文献有望帮助改变设计研究的方式,增加复杂的定量分析,用机器的力量补充现有的方法。由于这种潜力,数据科学受到了设计从业者和学者的广泛关注。然而,文献是零散的和专业化的,这使得设计师很难接触到数据科学。本文探讨了数据科学支持服务设计项目的机遇和挑战,从设计师的角度评估现有技术,并为服务设计师提供入门级指南。这些方法可以帮助提高设计研究的质量,使隐藏的信息可访问并协助创作过程。总之,这些结果有望激发组织为服务设计项目推进其数据科学资源。

更新日期:2022-03-07
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