Combining Humans and Machine Learning: A Novel Approach for Evaluating Crowdsourcing Contributions in Idea Contests

Item Type Conference or Workshop Item (Paper)
Abstract The creative potential from innovative contributions of the crowd constitutes some critical challenges. The quantity of contributions and the resource demands to identify valuable ideas is high and remains challenging for firms that apply open innovation initiatives. To solve these problems, research on algorithmic approaches proved to be a valuable way by identifying metrics to distinguish between high and low-quality ideas. However, such filtering approaches always risk missing promising ideas by classifying good ideas as bad ones. In response, organizations have turned to the crowd to not just for generating ideas but also to evaluate them to filter high quality contributions. However, such crowd-based filtering approaches tend to perform poorly in practice as they make unrealistic demands on the crowd. We, therefore, conduct a design science research project to provide prescriptive knowledge on how to combine machine learning techniques with crowd evaluation to adaptively assign humans to ideas.
Authors Dellermann, Dominik; Lipusch, Nikolaus & Li, Mahei
Research Team IWI6, Crowdsourcing, CCC
Journal or Publication Title Multikonferenz Wirtschaftsinformatik (MKWI)
Language English
Keywords Crowdsourcing, Hybrid Intelligence, Idea Evaluation, Latent Drichilet Allocation, Machine Learning
Subjects business studies
economics
information management
other research area
HSG Classification contribution to practical use / society
Date 2018
Event Title Multikonferenz Wirtschaftsinformatik (MKWI)
Event Location Lüneburg, Germany
Event Dates 06.03.2018-09.03.2018
Depositing User Dr. Mahei Li
Date Deposited 16 Dec 2017 10:56
Last Modified 20 Jul 2022 17:33
URI: https://www.alexandria.unisg.ch/publications/253005

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Dellermann, Dominik; Lipusch, Nikolaus & Li, Mahei: Combining Humans and Machine Learning: A Novel Approach for Evaluating Crowdsourcing Contributions in Idea Contests. 2018. - Multikonferenz Wirtschaftsinformatik (MKWI). - Lüneburg, Germany.

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https://www.alexandria.unisg.ch/id/eprint/253005
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