Social Media Information Search Behavior in Consumption Decisions: Consumer Segmentation and Discriminant Factors
Type of DegreePhD Dissertation
Consumer and Design Sciences
Restriction TypeAuburn University Users
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Upon recognition of the theoretical and empirical literature gap of research integrating the diverse roles of consumer information search on social media (Choi & Park, 2006), this study proposes the modified consumer decision-making (M-CDM) model and segments consumers in terms of their social media information search behavior (SMISB) characteristics for consumption decisions, within the theoretical framework of the M-CDM model. Differences of the SMISB-based segments are explained based on demographic, psychographic, and behavioral characteristics. An online survey was employed to collect data, and the sample was recruited from a U.S. consumer panel through an online research firm. A total of 501 respondents aged between 20 to 64 provided usable data. The SMISB frequency and the variety of social media types used for SMISB in four ISSs were assessed across a variety of product/service consumption categories. A hierarchical cluster analysis using the Ward’s method was employed to group the participants into SMISB segments. Results revealed four clusters demonstrating unique SMISBs, namely Maximizers as the most intensive info-seekers, The Disinterested who hardly engaged in social media information search, Slackers as occasional info-seekers, and Diggers as diligent task-oriented info-seekers. The four segments demonstrated various tendencies according to different descriptor variables. This study contributes to the consumer behavior literature by proposing multifaceted stages of information search consumers may perform, which significantly addressed the limitation of the traditional consumer decision-making models and enhanced the relevancy and applicability to today’s consumer information search patterns in the social media environment. The present study also contributes to identifying distinctive consumer segments by utilizing heterogeneous SMISBs, instead of using traditional segmentation methods based on demographic or psychographic characteristics. Further, this study benefits a product/service marketing literature by providing general knowledge on SMISB applicable to both product and service consumption contexts by implementing diverse product/service contexts. Lastly, as practical insights, identifying SMISB-segments enhances marketers’ understanding of various consumer segments with diverse information search motivations and resultant information search patterns. The knowledge on psychographic, behavioral, and demographic characteristics of SMISB-segments benefits marketers in designing strategic social media marketing plans for their target audiences.