Project Details
Projekt
Adoption and Diffusion Patterns in Network Structures as Drivers of Individual Consumer Behavior
Applicant
Professor Dr. Michel Clement
Subject Area
Accounting and Finance
Term
from 2014 to 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 163849297
Consumers are increasingly confronted with the display of trend information (e.g., the number of streams for a video over time on YouTube) online and in digital social media (DSM). In the first funding period, we focused on the analysis of the effects of trend information representing others’ aggregated adoptions or usage via online platforms on an individual’s demand for a product. We contributed to the literature by studying the effects of increasingly visible trends on the individual and on the market level. The project B2 conceptually and empirically focused on three areas: First, we conceptualized what kind of information is contained in visible trend curves (definition of trend curve dimensions) and proposed measurement rules. Second, we systematized the theories explaining trend evolution, and offered a conceptual framework suggesting moderators of the proposed trend effects. Finally, we empirically measured and analyzed the effects of trend information in micro- and macro-experiments. In addition, we focused on the analysis of the emergence and modelling of trends. Currently, we focus on a field experiment to test the impact of visualized demand trends displayed in newsletters on actual behavior. The empirical study is planned to be conducted in cooperation with Deezer (music streaming service) and Skoobe (e-book platform). Based on the increasing level of datafication and the results of the current and published work, that shows an impact of trends on individual demand and subsequent market outcomes, we want to focus on three key issues in the next research period: 1. How are the various trend curve dimensions interpreted by consumers and how do they interact with each other with respect to the consumer’s behavior?2. How do the perceived trend curve dimensions and their interactions influence adoption and usage behavior of a consumer and which moderators impact these effects? 3. Consumers are not only confronted with trend curves, but also with other social information of HMP (e.g., product reviews). Therefore, we research how the relationship between trend curve dimensions and consumer behavior is moderated by these additional social cues.
DFG Programme
Research Units
Co-Investigators
Professor Dr. Sönke Albers; Professor Dr. Mark Heitmann
