Zooming in on the Effect of Sociometric Signals on Different Stages of the Design Process

Steffi Kohl, K. Schröder, Mark Graus, Emir Efendic, Jos Lemmink

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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Abstract

Collaborative creativity is an essential part of modern teamwork and is often supported by formal techniques, such as design thinking. Current support tools are often limited in scope as understanding the time-varying nature and structure of team communication is insufficient. We investigate how collaborative creative activities in new product development teams can be digitally supported while maintaining face-to-face communication. This work analyzes to what extent paralinguistic and proxemic features of team interaction relate to performance in new product development teams and if and how this relationship differs for different stages in the design process. This is investigated by applying multilevel modeling on data collected during a four-week new product development cycle. The cycle was completed by four teams, during which data were collected automatically using sociometric badges that capture social signals of team interactions. In addition, the data are combined with survey-based measurements on the team’s daily design process and periodic performance evaluations. The current paper provides evidence that social signals are related to team performance and that this relationship varies across the stages in the product design process. Certain social signals contribute positively in one stage but less in other stages, showing the importance of using multimodal signals when modeling high-level collaborative patterns. This research contributes to the literature by providing a better understanding of relevant factors when designing supporting tools or methods for collaborative creative problem solving.
Original languageEnglish
Title of host publicationC&C '22: Proceedings of the 14th Creativity and Cognition 2022 
PublisherAssociation for Computing Machinery (ACM)
Pages118-124
Number of pages6
ISBN (Print)978-1-4503-9327-0
DOIs
Publication statusPublished - Jun 2022

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