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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A large proportion of information systems research is concerned with developing and testing models pertaining to complex cognition, behaviors, and outcomes of individuals, teams, organizations, and other social systems that are involved in the development, implementation, and utilization of information technology. Given the complexity of these social and behavioral phenomena, heterogeneity is likely to exist in the samples used in IS studies. While researchers now routinely address observed heterogeneity by introducing moderators, a priori groupings, and contextual factors in their research models, they have not examined how unobserved heterogeneity may affect their findings. We describe why unobserved heterogeneity threatens different types of validity and use simulations to demonstrate that unobserved heterogeneity biases parameter estimates, thereby leading to Type I and Type II errors. We also review different methods that can be used to uncover unobserved heterogeneity in structural equation models. While methods to uncover unobserved heterogeneity in covariance-based structural equation models (CB-SEM) are relatively advanced, the methods for partial least squares (PLS) path models are limited and have relied on an extension of mixture regression-finite mixture partial least squares (FIMIX-PLS) and distance measure-based methods-that have mismatches with some characteristics of PLS path modeling. We propose a new method-prediction-oriented segmentation

The research presented in this article addresses the issue of the significance and relative importance of the determinants of extension success by simultaneously investigating ten success factors. The empirical analysis considers the direct relationships between success factors and extension success, the structural relationships among investigated factors, and moderating effects. The authors find that fit between the parent brand and an extension product is the most important driver of brand extension success, followed by marketing support, parent-brand conviction, retailer acceptance, and parent-brand experience. The authors also find several important structural relationships among the investigated success factors (e.g., marketing support → fit → retailer acceptance → extension success). Finally, the interaction terms of fit with the quality of the parent brand and with parent-brand conviction are statistically significant, albeit of relatively low importance.

This article focuses on the measurement of the overall importance of brands for consumer decision making—that is, brand relevance in category, or BRiC—across multiple categories and countries. Although brand equity measures for specific brands have attracted a large body of literature, the questions of how important brands are within an entire product category and the extent to which BRiC differs across categories and countries have been neglected. The authors introduce the concept of BRiC (a category-level measure, not a brand-level measure). They develop a conceptual framework to measure BRiC and the drivers of BRiC, test the framework empirically with a sample of more than 5700 consumers, and show how the construct varies across 20 product categories and five countries (France, Japan, Spain, the United Kingdom, and the United States). The results suggest a high validity of the proposed BRiC measure and show substantial differences between categories and countries. A replication study two-and-a-half years later confirms the psychometric properties of the suggested scale and shows remarkable stability of the findings. The findings have important implications for the management of brand investments.