research-article

Design Science in Digital Innovation: A Literature Review

Authors:

Flávio Horita E.A.,

Fabio Gomes Rocha,

Layse Santos Souza,

Gustavo R. GonzalesAuthors Info & Claims

SBSI '20: Proceedings of the XVI Brazilian Symposium on Information Systems

Article No.: 28, Pages 1 - 7

https://doi.org/10.1145/3411564.3411638

Published: 03 November 2020 Publication History

Abstract

Digital innovation focuses on using digital technologies to orchestrate new products, services, platforms, or even new business models in a given context. Design science research has the potential to contribute to digital innovation as it focuses on the development of innovative IT artifacts. However, existing literature still lacks an understanding of how these two disciplines would converge. This article conducts a literature review that examines this issue intending to obtain an overview of the current state of the art, which leads to a research agenda. We employ a systematic approach to mapping in first-line journals, and well-known IS conferences. The results of the study revealed that most studies are focused on providing two types of contributions (Model and Method). They also showed, as well as the need to employ design science for developing innovative artifacts in new emerging application domains such as disaster management or urban mobility.

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Cited By

Arsiwala AElghaish FZoher M(2023)Digital twin with Machine learning for predictive monitoring of CO2 equivalent from existing buildingsEnergy and Buildings10.1016/j.enbuild.2023.112851284(112851)Online publication date: Apr-2023
https://doi.org/10.1016/j.enbuild.2023.112851
Silva PSouza VVolpato MSilva V(2022)Regador : APP for coffee water potential estimationProceedings of the XVIII Brazilian Symposium on Information Systems10.1145/3535511.3535545(1-9)Online publication date: 16-May-2022
https://dl.acm.org/doi/10.1145/3535511.3535545

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cover image ACM Other conferences

SBSI '20: Proceedings of the XVI Brazilian Symposium on Information Systems

November 2020

371 pages

ISBN:9781450388733

DOI:10.1145/3411564

Copyright © 2020 ACM.

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Published: 03 November 2020

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National Council for Scientific and Technological Development (CNPq)

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SBSI'20

SBSI'20: XVI Brazilian Symposium on Information Systems

November 3 - 6, 2020

São Bernardo do Campo, Brazil

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Cited By

Arsiwala AElghaish FZoher M(2023)Digital twin with Machine learning for predictive monitoring of CO2 equivalent from existing buildingsEnergy and Buildings10.1016/j.enbuild.2023.112851284(112851)Online publication date: Apr-2023
https://doi.org/10.1016/j.enbuild.2023.112851
Silva PSouza VVolpato MSilva V(2022)Regador : APP for coffee water potential estimationProceedings of the XVIII Brazilian Symposium on Information Systems10.1145/3535511.3535545(1-9)Online publication date: 16-May-2022
https://dl.acm.org/doi/10.1145/3535511.3535545

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