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The Effect of Social Reputation on Retention: Designing a Social Real-Time Delphi Platform

Kloker, Simon 1; Straub, Tim; Morana, Stefan 1; Weinhardt, Christof ORCID iD icon 1
1 Karlsruher Institut für Technologie (KIT)


Forecasting with high uncertainty and long-time horizons still challenges researchers and practitioners. A widely adopted method in knowledge sharing and forecasting based on experts is the Delphi method and its offspring, the Real-Time Delphi. While the traditional Delphi method already is intensely investigated, the Real-Time Delphi is still evolving, and no dominant design has been found yet. A problem arising in both variants of the Delphi method, are high drop-out rates between rounds. This paper applies a design science research approach to motivate the need for social design elements from literature and derives design principles for Real-Time Delphi platform. Based on the design, we implement and evaluate a prototype in an online experiment as well as an IT artifact in a field study. We find significant supporting evidence, that (the promise of) positive social reputation increases commitment, and therefore subsequent platform engagement of our Real-Time Delphi survey. Our findings, therefore, contribute valuable design knowledge for Real-Time Delphi platforms. Moreover, we provide advice on how to raise retention in knowledge sharing systems.

Zitationen: 3
Zugehörige Institution(en) am KIT Fakultät für Wirtschaftswissenschaften – Institut für Informationswirtschaft und Marketing (IISM)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2018
Sprache Englisch
Identifikator ISBN: 978-1-86137-667-1
KITopen-ID: 1000084161
Erschienen in Proceedings of the 26th European Conference on Information Systems (ECIS2018), Portsmouth, UK, June 23-28, 2018
Verlag Association for Information Systems (AIS)
Seiten Paper 1322
Externe Relationen Abstract/Volltext
Schlagwörter Real-Time Delphi, Delphi Method, Knowledge Sharing, Retention, Crowd-based Forecasting, Decision Support Systems, Knowledge Management, Online Social Interaction, Social Reputation, Drop-Out Rates, Design.
Nachgewiesen in Scopus
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