According to behavioral economists, a “nudge” is an attempt to steer individuals toward making desirable choices without affecting their range of choices. We draw on this concept, and design and examine nudges that exploit social influence’s effects to control individuals’ choices. Although recommendation agent research provides numerous insights into extending information systems and assisting end consumers, it lacks insights into extending enterprise information systems to assist organizations’ internal employees. We address this gap by demonstrating how enterprise recommendation agents (ERAs) and social nudges can be used to tackle a common challenge that enterprise information systems face. That is, we use an ERA to facilitate information (i.e., reports) retrieval in a business intelligence system. In addition, we use social nudges to steer users toward reusing specific recommended reports rather than choosing between recommended reports randomly. To test the effects of the ERA and the four social nudges, we conduct a within-subject lab experiment using 187 participants. We also conduct gaze analysis (“eye tracking”) to examine the impact of participants’ elaboration. The results of our logistic mixed-effects model show that the ERA and the proposed social nudges steer individuals toward certain choices. Specifically, the ERA steers users toward reusing certain reports. These theoretical findings also have high practical relevance and applicability: In an enterprise setting, the ERA allows employees to reuse existing resources (such as existing reports) more effectively across their organizations because employees can more easily find the reports they actually need. This, in turn, prevents the development of duplicate reports.
Kretzer, Martin and Maedche, Alexander
"Designing Social Nudges for Enterprise Recommendation Agents: An Investigation in the Business Intelligence Systems Context,"
Journal of the Association for Information Systems, 19(12), .
Available at: https://aisel.aisnet.org/jais/vol19/iss12/4
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