JazzFlow-Analyzing "Group Flow" Among Jazz Musicians Through "Honest Signals"
Faculty/Professorship: | Professur für Wirtschaftsinformatik, insbesondere Soziale Netzwerke |
Author(s): | Gloor, Peter A.; Oster, Daniel; Fischbach, Kai ![]() |
Title of the Journal: | Künstliche Intelligenz : KI ; Forschung, Entwicklung, Erfahrungen |
ISSN: | 0933-1875 |
Corporate Body: | Fachbereich 1 der Gesellschaft für Informatik e.V. |
Publisher Information: | Berlin [u.a.] : Springer |
Year of publication: | 2013 |
Volume: | 27 |
Issue: | 1 |
Pages: | 37-43 ; Illustrationen, Diagramme |
Language(s): | English |
DOI: | 10.1007/s13218-012-0230-3 |
URL: | http://link.springer.com/article/10.1007/s13218... |
Abstract: | In this project we aim to analyze “honest signals” between Jazz musicians by using sociometric badges with the goal of identifying structural properties of self-organizing creative teams. In particular, we are interested in the pre-requisites for “flow,” the state of work where “time flies,” and workers are at their most-productive best. We extend the concept of individual “flow” as defined by Csikszentmihalyi (Flow: the psychology of optimal experience. Harper Row, New York, 1990) to the group level (Sawyer in Group creativity: music, theater, collaboration. Psychology Press, Oxford, 2003; Group genius: the creative power of collaboration. Basic Books, New York, 2007), trying to identify some of the conditions indicative of the group flow state. We speculate that a band of Jazz musicians is particularly well suited to study group flow, because they are an archetype of a self-organizing creative team, involved in highly creatively work while passing leadership of the tune for the solo part from one band member to the next. |
Type: | Article |
URI: | https://fis.uni-bamberg.de/handle/uniba/1224 |
Year of publication: | 25. March 2013 |

originated at the
University of Bamberg
University of Bamberg