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Formative Evaluation of Data-Driven Business Models – The Data Insight Generator

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Title:Formative Evaluation of Data-Driven Business Models – The Data Insight Generator
Authors:Kühne, Babett
Böhmann, Tilo
Keywords:Developing Visual Collaborative Tools
business model design
data-driven business models
design science research
evaluation
show 1 morethinking aloud
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Date Issued:07 Jan 2020
Abstract:New technological developments such as Big Data or, the Internet of Things lead to exponentially increasing amounts of data created and stored by organizations. As a consequence, new data-driven business models (DDBMs) appear. These business models have special characteristics which need to be included in the business model development process. Thus, different methods and tools have emerged to support the development of DDBMs. One of these is the Data Insight Generator (DIG) which seeks to combine the key resource and value proposition of a DDBM. This paper comprises the application of the thinking-aloud method for a formative evaluation of the DIG. The contribution of this paper is twofold. First, the usability of the DIG is tested and implications for further development are derived. Second, the paper provides empirically-based insights into development of DDBM that facilitate the future development of such business models.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/63792
ISBN:978-0-9981331-3-3
DOI:10.24251/HICSS.2020.053
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Developing Visual Collaborative Tools


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