Item Type | Conference or Workshop Item (Other) |
Abstract | For entrepreneurs, one of the most pivotal tasks is to develop their business model. Therefore, entrepreneurs try to collect information that might support them in their decision making. Such information includes feedback from other actors to assess the validity of their assumptions and make decisions. However, entrepreneurs are constraint by bounded rationality, which prevents them from making optimal decisions. To solve this problem, the aim of this research is to develop a decision support system (DSS) for supporting entrepreneurs’ decisions regarding their business model to support accessing, processing, and the interpretation of relevant information. To achieve this, we follow a design science approach to develop a Hybrid Intelligence DSS that combines the strength of both machine and collective intelligence. Our contributions will consist of preliminary prescriptive knowledge, extending the scope of DSS to business model innovation, and a novel approach to support decision making by combining machine and collective intelligence. |
Authors | Dellermann, Dominik; Lipusch, Nikolaus; Ebel, Philipp & Leimeister, Jan Marco |
Research Team | IWI6 |
Language | English |
Keywords | Accelerator, Collective Intelligence, Design Science Research, Machine Learning |
Subjects | business studies information management education other research area |
HSG Classification | contribution to scientific community |
Date | 2017 |
Event Title | Electronic Markets Paper Development Workshop |
Event Location | Karlsruhe, Germany |
Event Dates | 02.06.2017 |
Depositing User | Dr. Mahei Li |
Date Deposited | 27 Jul 2017 15:13 |
Last Modified | 20 Jul 2022 17:31 |
URI: | https://www.alexandria.unisg.ch/publications/251307 |
DownloadFull text not available from this repository.CitationDellermann, Dominik; Lipusch, Nikolaus; Ebel, Philipp & Leimeister, Jan Marco: Design Principles for Hybrid Intelligence Decision Support Systems in Entrepreneurship. [Conference or Workshop Item] Statisticshttps://www.alexandria.unisg.ch/id/eprint/251307
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