1,721,008 research outputs found
sj-pdf-1-jmx-10.1177_00222429221141066 - Supplemental material for Nudging App Adoption: Choice Architecture Facilitates Consumer Uptake of Mobile Apps
No full textSupplemental material, sj-pdf-1-jmx-10.1177_00222429221141066 for Nudging App Adoption: Choice Architecture Facilitates Consumer Uptake of Mobile Apps by Crystal Reeck, Nathaniel A. Posner, Kellen Mrkva and Eric J. Johnson in Journal of Marketing</p
Foundations of Consumer Neuroscience
No full textConsumer neuroscience is, to some extent, defined by its methodologies. Traditional consumer research relies upon traditional behavioral techniques, such as examining choice, asking people to provide self-report ratings, and measuring response time. Consumer neuroscience utilizes many of these tools, but also employs neuroscientific methodologies, including eye-tracking, psychophysiology, neuroimaging, and circulating hormones. The present chapter examines how these tools have shed light in a range of domains. I focus here on brands, brand personalities, neuroforecasting, and purchase decisions. With respect to brands, I discuss findings from work comparing two brands (e.g., Coke and Pepsi) as well as multiple brands. For brand personalities, I discuss how brands are judged compared to people and novel neural techniques for capturing brand personality judgments. The neuroforecasting section discusses a range of types of predictions made using neural data. In investigating pricing and purchasing, I review a host of evidence from different paradigms. Across these topic areas, I review a range of types of evidence, including data from functional magnetic resonance imaging, circulating hormones, and lesion research, among others. In each case, evidence from neuroscience provides novel insight into a process that guides consumer behavior
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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