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Purpose The purpose of this study is to provide a better understanding of customer brand engagement (CBE) by proposing and empirically testing a model of antecedents and consequences of CBE for user-initiated online brand communities (OBCs). Design/methodology/approach The model is tested using a sample of 584 participants in two relevant OBCs created and managed by brand fans. Specifically, data were collected from two communities in the photography products category: Nikonistas and Canonistas. Findings The results indicate that community and brand identification positively and significantly influence CBE. Furthermore, the supporting role of OBCs’ moderators facilitates CBE and moderates the influence of community identification on CBE. Regarding the outcomes of CBE, the results show that higher levels of engagement are positively, directly and significantly associated with favorable intentions towards the brand and the community. These effects are then mediated by brand affective commitment. Research limitations/implications The study has been conducted in two Spanish OBCs of two specific high-involvement products category: it is cross-sectional and focuses on a limited number of antecedents and consequences. Practical implications Evidence from this research supports and emphasizes the potential that these platforms have for brand management such that firms’ resources could be best allocated on those elements that lead to superior CBE. Originality/value The study endorses the role of CBE in fostering brand and community-related favorable outcomes in the context of user-initiated OBCs. It shed lights on the potential that these online platforms have for brands and on the role that brand management should play in digital contexts that are outside the direct control of the company.

The evolution of the internet, including developments such as Web 2.0, has led to new relationship realities between organizations and their stakeholders. One manifestation of these complex new realities has been the emergence of an internet-based democratization of brand management. Research about this phenomenon has so far mainly focused on investigating just one or more individual themes and thereby disregarded the inherent multilayered nature of the internet-based democratization of brand management as a holistic, socio-technological phenomenon. The aim of this paper is to address this limitation through an investigation of the various socio-technological democratization developments of the phenomenon. To achieve this aim, a balanced and stakeholder-oriented perspective on brand management has been adopted to conduct an integrative literature review. The review reveals three key developments, which together form the essential parts of the phenomenon: (I) the democratization of internet technology, (II) the democratization of information, and (III) the democratization of social capital. The insights gained help to clarify the basic structures of the multi-layered phenomenon. The findings contribute also to the substantiation of a call for a new brand management paradigm: one that takes not only company-initiated but also stakeholder-initiated brand management activities into account.

Online ratings provide valuable information to operators. However, the use of this information for revenue maximization purposes remains at a moot point. This article proposes a new method to decompose ratings based on their relevance to hotel performance. From a methodological standpoint, we propose a multi-criteria decision analysis approach. The empirical validation includes two independent data sources, online ratings from Booking.com and RevPAR data from STR. By means of pairwise comparisons in PROMETHEE, the findings reveal the different weights of individual ratings, helping operators to understand the weight of each rating attribute in terms of revenue maximization. In particular, apart from the importance of the location, the role of staff and facilities emerge as central in terms of revenue maximization. The proposed model offers new theoretical insights on the relevant dimensions, helping hoteliers to prioritize when making trade-off decisions.