Design Principles for Industrial Data-Driven Services

被引:5
作者
Azkan, Can [1 ,2 ]
Moeller, Frederik [1 ,2 ]
Iggena, Lennart [1 ]
Otto, Boris [1 ,2 ]
机构
[1] TU Dortmund Univ, D-44227 Dortmund, Germany
[2] Fraunhofer Inst Software & Syst Engn, D-44227 Dortmund, Germany
关键词
Business; Technological innovation; Modeling; Biological system modeling; Companies; Interviews; Taxonomy; Data-driven services; design principles; design science; digital business models; service innovation; BIG DATA ANALYTICS; DOMINANT LOGIC; INNOVATION; SYSTEMS; FUTURE; SERVITIZATION; SCIENCE;
D O I
10.1109/TEM.2022.3167737
中图分类号
F [经济];
学科分类号
02 ;
摘要
The continuously growing availability and volume of data pressure companies to leverage them economically. Subsequently, companies must find strategies to incorporate data sensibly for internal optimization and find new business opportunities in data-driven business models. In this article, we focus on using data and data analytics in product-oriented industrial companies. Although data-driven services are becoming increasingly important, little is known about their systematic design and development in research. Surprisingly, many companies face significant challenges and fail to create these services successfully. Against this background, this article presents findings from a multicase based on qualitative interviews and workshops with experts from different industrial sectors. We propose ten design principles and corresponding design features to successfully design industrial data-driven services in this context. These design principles help practitioners and researchers to understand the peculiarities of creating data-driven services more in-depth on a conceptual, technical, and organizational level.
引用
收藏
页码:2379 / 2402
页数:24
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