Adoption and Diffusion Patterns in Network Structures as Drivers of Individual Consumer Behavior

网络结构中的采用和扩散模式作为个人消费者行为的驱动因素

• 批准号: 258668800
• 负责人: Professor Dr. Michel Clement
• 金额: --
• 依托单位: Schwerpunkt Marketing
• 依托单位国家: 德国
• 项目类别: Research Units
• 财政年份: 2014
• 资助国家: 德国
• 起止时间: 2013-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/258668800?language=en
• 关键词: Adoption; Diffusion; Patterns; Network; Structures

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.

消费者越来越多地面临在线和数字社交媒体(DSM)上的趋势信息(例如，一段时间内YouTube上视频的流媒体数量)的显示。在第一个资助期，我们专注于分析代表其他人通过在线平台聚合采用或使用的趋势信息对个人对产品需求的影响。我们通过研究日益明显的趋势对个人和市场水平的影响，为文献做出了贡献。项目B2在概念上和经验上集中在三个方面：第一，我们概念化了可见趋势曲线(趋势曲线维度的定义)中包含的哪种信息，并提出了测量规则。其次，我们系统化了解释趋势演变的理论，并提供了一个概念框架，建议了所提出的趋势效应的调节因素。最后，我们对趋势信息在微观实验和宏观实验中的作用进行了实证测量和分析。此外，我们还重点分析了趋势的出现和建模。目前，我们专注于现场实验，以测试时事通讯中显示的可视化需求趋势对实际行为的影响。这项实证研究计划与Deezer(音乐流媒体服务)和Skoobe(电子书平台)合作进行。基于不断增长的数据化水平以及当前和已发表的研究结果(表明趋势对个人需求和后续市场结果的影响)，我们希望在下一个研究阶段重点关注三个关键问题：1.消费者如何解释各种趋势曲线维度，以及它们如何相互作用于消费者的行为？2.感知的趋势曲线维度及其交互如何影响消费者的采用和使用行为，以及哪些调节因素影响这些影响？3.消费者不仅面临趋势曲线，还面临HMP的其他社会信息(例如，产品评论)。因此，我们研究了趋势曲线维度和消费者行为之间的关系如何受到这些额外的社会线索的调节。