Marketing Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2790
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Item Online Social Influence(2014) Zhang, Yuchi; Moe, Wendy W; Godes, David; Business and Management: Marketing; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation studies the behaviors of consumers in an online, social context. In the first essay, we jointly model the drivers of social media rebroadcasting behavior. Our goal in this research is to propose a framework and model of social media rebroadcasting behavior that integrates the various factors shown to influence rebroadcasting behavior. These include the role of message content and influence, factors that have been studied separately with very little integration. The results from our proposed model show that not only does rebroadcasting activity vary with the content of the original message but also that individuals are more likely to rebroadcast content that closely fits with their own interests. In the second essay, we ask whether online opinions impact consumers' decision quality and assess whether this impact occurs immediately or requires one to undergo learning first. We focus on a setting where consumers have multiple learning episodes based on their experiences with opinions from both uni- and bi-directional ties (i.e. weak and strong ties). We find that the dynamic effects are dependent on the strength of the tie. Additional strong ties (operationalized as bi-directional links) lead to immediate positive effects on decision quality. In contrast, additional weak ties (uni-directional, follower relationships) as a source of information lead initially to lower decision quality. However, highly-experienced consumers receive, ultimately, higher positive effects on decision quality from weak ties as compared with strong ties. Finally, in the third essay, we propose a new framework and model for identifying dimension specific influentials. We explicitly model individuals' preferences by estimating their locations on a market map to disentangle purchase behavior due to homophily from that due to influence. Our results show that it is important to estimate dimension specific influence, based on a comparison of model fit with a baseline model that measures influence along one dimension. We also show that individuals have varying levels of influence across dimensions, and an influencer for one dimension is not always influential on all dimensions.Item Marketing Applications of Social Tagging Networks(2012) Nam, Hyoryung; Kannan, P.K.; Joshi, Yogesh; Business and Management: Marketing; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation focuses on marketing applications of social tagging networks. Social tagging is a new way to share and categorize content, allowing users to express their perceptions and feelings with respect to concepts such as brands and firms with their own keywords, “tags.” The associative information in social tagging networks provides marketers with a rich source of information reflecting consumers’ mental representations of a brand/firm/product. The first essay presents a methodology to create “social tag maps,” brand associative networks derived from social tags. The proposed approach reflects a significant improvement towards understanding brand associations compared to conventional techniques (e.g., brand concept maps and recent text mining techniques), and helps marketers to track real-time updates in a brand’s associative network and dynamically visualize the relative competitive position of their brand. The second essay investigates how information contained in social tags acts as proxy measures of brand assets that track and predict the financial valuation of firms using the data collected from a social bookmarking website, del.icio.us, for 61 firms across 16 industries. The results suggest that brand asset metrics based on social tags explain stock return. Specifically, an increase in social attention and connectedness to competitors is shown to be positively related to stock return for less prominent brands, while for prominent brands associative uniqueness and evaluation valence is found to be more significantly related to stock return. The findings suggest to marketing practitioners a new way to proactively improve brand assets for impacting a firm’s financial performance. The third essay investigates whether the position of products on social tagging networks can predict sales dynamics. We find that (1) books in long tail can increase sales by being strongly linked to well-known keywords with high degree centrality and (2) top sellers can be better sellers by creating dense content clusters rather than connecting them to well-known keywords with high degree centrality. Our findings suggest that marketing managers better understand a user community’s perception of products and potentially influence product sales by taking into account the positioning of their products within social tagging networks.