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Recent years have witnessed the rise of new media channels such as Facebook, YouTube, Google, and Twitter, which enable customers to take a more active role as market players and reach (and be reached by) almost everyone anywhere and anytime. These new media threaten long established business models and corporate strategies, but also provide ample opportunities for growth through new adaptive strategies. This paper introduces a new ''pinball'' framework of new media's impact on relationships with customers and identifies key new media phenomena which companies should take into account when managing their relationships with customers in the new media universe. For each phenomenon, we identify challenges for researchers and managers which relate to (a) the understanding of consumer behavior, (b) the use of new media to successfully manage customer interactions, and (c) the effective measurement of customers' activities and outcomes.

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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In light of the emerging discourse on AI systems' effect on society, whose perception swings widely between utopian and dystopian, we conduct herein a critical analysis of how artificial intelligence (AI) affects the essential nature of customer relationship management (CRM). To do so, we survey the AI capabilities that will transform CRM into AI-CRM and examine how the transformation will influence customer acquisition, development, and retention. We highlight in particular how AI-CRM's improving ability to predict customer lifetime value will generate an inexorable rise in implementing adapted treatment of customers, leading to greater customer prioritization and service discrimination in markets. We further consider the consequences for firms and the challenges to regulators.

While many studies examined the effects of online customer reviews (OCRs) on product sales, a clear understanding of the effects of OCRs on product returns is lacking. This study examines the impact of OCRs characteristics (valence, volume, and variance) on return decisions with a rich multi-year dataset from a major online retailer covering the electronics and furniture category. The main finding is that overly positive review valence (i.e., higher than the long-term product average), induces more purchases, but also more returns. An explanation for these findings is that OCRs help to form product expectations at the moment of purchase. Therefore, the purchase probability increases but the high expectations due to overly positive reviews may not be met, which results in negative expectation disconfirmation and consequently increases return probability as well. The effect of review valence on returns is stronger for novice buyers and for cheaper products. We further find that review volume and variance mainly affect purchase decisions, and have little to no effect on product returns. This study thus demonstrates that products returns should be considered when examining OCR effects, especially because overly positive reviews may hinder a retailer's financial performance, due to large reverse logistics costs associated with product returns.

This study examines the relative effectiveness of traditional advertising, impressions generated through firm-toconsumer (F2C) messages on Facebook, and the volume and valence of consumer-to-consumer (C2C) messages on Twitter and web forums for brand-building and customer acquisition efforts. The authors apply vector autoregressive modeling to a unique data set from a European telecom firm. This modeling approach allows them to consider the interrelations among traditional advertising, F2C impressions, and volume and valence of C2C social messages. The results show that traditional advertising is most effective for both brand building and customer acquisition. Impressions generated through F2C social messages complement traditional advertising efforts. Thus, thoroughly orchestrating traditional advertising and a firm's social media activities may improve a firm's performance with respect to building the brand and encouraging customer acquisition. Moreover, firms can stimulate the volume and valence of C2C messages through traditional advertising that in turn influences brand building and acquisition. These findings can help managers leverage the different types of messages more adequately.