This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link Managing Brands in the Social Media Environment AbstractThe dynamic, ubiquitous, and often real-time interaction enabled by social media significantly changes the landscape for brand management. A deep understanding of this change is critical since it may affect a brand's performance substantially. Literature about social media's impact on brands is evolving, but lacks a systematic identification of key challenges related to managing brands in this new environment. This paper reviews existing research and introduces a framework of social media's impact on brand management. It argues that consumers are becoming pivotal authors of brand stories due to new dynamic networks of consumers and brands formed through social media and the easy sharing of brand experiences in such networks.Firms need to pay attention to such consumer-generated brand stories to ensure a brand's success in the marketplace. The authors identify key research questions related to the phenomenon and the challenges in coordinating consumer-and firm-generated brand stories.

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Not all repeat purchases are created equal. They can be driven by both positive reaction toward a brand (i.e., attitudinal loyalty) and automaticity triggered by non-brand-related contextual cues (i.e., habit). Combining the loyalty literature with recent habit research, the authors suggest ways to distinguish the two drivers of repeat purchase and examine how they affect consumer response to cross-selling promotions. In Study 1, the authors propose a method to derive individual-level habit strength from consumer transaction records and demonstrate the influence of both attitudinal loyalty and habit on repeat purchase. Studies 2a and 2b then show that attitudinal loyalty facilitates cross-selling, whereas habit has the opposite effect. Finally, in Study 3, the authors suggest a specific promotional design that works better for habitual consumers than for those with attitudinal loyalty and demonstrate that ignoring these two underlying drivers can lead to unintended negative consequences on consumer behavior. This research adds to a richer understanding of repatronage and yields important managerial insights into more effective cross-selling to repeat customers.

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With the explosive growth of online user-generated content and the desire by marketers to better utilize this space, it is beneficial to understand the viral diffusion of such content and to identify messages that are most likely to achieve popularity. In this paper, we combine network analysis and the diffusion literature to study the spreading of user-generated videos online. We identify three groups of factors that affect diffusion outcomes: network structure, content characteristics, and author characteristics. Using a proportional rates model, we analyze the diffusion of a sample of videos on YouTube. Our results show that it is preferable to have many subscribers who each has a few friends than to have a few subscribers with many connections. Furthermore, a curvilinear relationship exists between subscriber network connectivity and diffusion rate such that diffusion is at its highest under moderate connectivity. Examining content characteristics, we show that entertainment and educational values affect diffusion but production quality does not matter. Moreover, we find that quality as manifested by user ratings influences diffusion more than innate content quality. Not surprisingly, an author's past success carries over to the current content, and content from younger authors is more popular.

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Artificial intelligence (AI) continues to transform firm-customer interactions. However, current AI marketing agents are often perceived as cold and uncaring and can be poor substitutes for human-based interactions. Addressing this issue, this article argues that artificial empathy needs to become an important design consideration in the next generation of AI marketing applications. Drawing from research in diverse disciplines, we develop a systematic framework for integrating artificial empathy into AI-enabled marketing interactions. We elaborate on the key components of artificial empathy and how each component can be implemented in AI marketing agents. We further explicate and test how artificial empathy generates value for both customers and firms by bridging the AI-human gap in affective and social customer experience. Recognizing that artificial empathy may not always be desirable or relevant, we identify the requirements for artificial empathy to create value and deduce situations where it is unnecessary and, in some cases, harmful.

As direct-to-consumer marketing of medical genetic tests grows in popularity, there is an increasing need to better understand the ethical and public policy implications of such products. The complexity of genetic tests raises serious concerns about whether consumers possess the knowledge to make sound decisions about their use. This research examines the effects of educational intervention and feedback on consumers' genetic literacy and calibration-the gap between consumers' actual knowledge and how much they think they know. The authors find that consumers' genetic knowledge was generally low and that people tended to underestimate their knowledge level. Furthermore, consumers' perceived rather than actual knowledge levels drove attitude and purchase intention. Regarding the effect of educational intervention, exposure to an online educational module improved both genetic knowledge and calibration. Offering instant feedback resulted in greater knowledge gain than delayed feedback. The worst learning outcome occurred when feedback was both delayed and brief. On the basis of these findings, the authors offer recommendations for formulating ethically sound public policies in this area.