Abstract
This research centers on the relationship between information overload as an aspect of information quality on the one side, and, on the other side, user resistance to knowledge management systems as an aspect of an individual’s decision process. While discussing this relationship theoretically we propose a bipartite influence of information overload as on the one hand it fosters acceptance of these system, but on the other hand also causes user resistance. By analyzing information overload in pre- and post-implementation phases of knowledge management systems we argue that information overload has an ambivalent causal effect as it can act both positively and negatively in relation to the point of time overload occurs or is expected. Therefore, based on existing literature we propose a research model and illustrate the relationships through results of a case study.
Recommended Citation
Wild, Udo; Laumer, Sven; and Kroenke, Aenne, "The Bipartite Influence of Information Overload on User Resistance to Knowledge Management Systems" (2012). AMCIS 2012 Proceedings. 11.
https://aisel.aisnet.org/amcis2012/proceedings/DataInfoQuality/11
The Bipartite Influence of Information Overload on User Resistance to Knowledge Management Systems
This research centers on the relationship between information overload as an aspect of information quality on the one side, and, on the other side, user resistance to knowledge management systems as an aspect of an individual’s decision process. While discussing this relationship theoretically we propose a bipartite influence of information overload as on the one hand it fosters acceptance of these system, but on the other hand also causes user resistance. By analyzing information overload in pre- and post-implementation phases of knowledge management systems we argue that information overload has an ambivalent causal effect as it can act both positively and negatively in relation to the point of time overload occurs or is expected. Therefore, based on existing literature we propose a research model and illustrate the relationships through results of a case study.