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

Kloker, Simon; Straub, Tim; Morana, Stefan; Weinhardt, Christof

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.

Zugehörige Institution(en) am KIT 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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