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Purpose-This paper aims to examine the impact of customers' offline transaction behaviour in the form of loyalty and cross buying on the adoption of self-service technology innovations by non-business customers in the context of online banking. Design/methodology/approach-This study extends the Diffusion of Innovation Theory, as well as the Technology Acceptance Model adapted to describe and model individual customer observed behaviours in the pre-adoption stage of the adoption process. The Log-logistic parametric survival model is applied using panel data for 1,357 randomly-selected new customers from a bank. Findings-Remarkable differences arise among customers' behaviours related to periodicity of interactions with the bank and quantity of products involved in the interactions, as well as convenience and risk of the interactions. Our results corroborate that those customers who are more likely to adopt the online banking faster show an offline behavioural pattern more related to higher periodicity of interactions and convenience, rather than a high number of products involved in their interactions, the use of high-risk products or the maintenance a higher average monthly liabilities. Originality/value-While previous research explaining the process of adoption of the online channel has mainly focused on the analysis of customer's attitudes (i.e., customers' perceptions) and demographics, in this research an additional explanation is proposed using customers' offline transactional behaviours. In addition, there is considerable amount of research about the adoption of new technologies, but there is a scarcity of studies looking specifically at the financial services and banking industry.

Purpose This study aims to focus on the content published by social media influencers – i.e. YouTubers – on their YouTube channels. The main purpose of this research is to analyse whether anti-consumption-framed content (anti-hauls) generates more views, more dislikes (and less dislikes) and more comments, as customer engagement components, than pro-consumption-framed content (hauls). Design/methodology/approach Based on 160 videos published on YouTube by 80 influencers on their respective channels, this study mainly analyses whether there are differences between anti-consumption and pro-consumption content in the various elements that constitute customer engagement (i.e. number of views, likes, dislikes and comments). Findings Results indicate that there are differences between anti-consumption and pro-consumption content in terms of total number of views, likes, dislikes and comments. All these customer engagement components are higher for anti-consumption-framed videos, which offers interesting implications for both theory and practice. Originality/value This study extends previous literature by accounting content published by social media influencers on their social media accounts, instead of analysing the most traditionally studied content that is published by brands on their own social media; and classifying this content as anti/pro-consumption rather than using the traditional dichotomy between transactional/emotional content. Brands should pay special attention to the content generated by social media influencers because it is a powerful form of electronic word-of-mouth that currently plays a significant role in customers’ (non)purchase decisions.

Throughout this research the customer valuation trend in marketing is going to be reviewed, emphasizing Customer Lifetime Value and Customer Equity measures. The main theoretical contributions in the development and evolution of the Customer Lifetime Value concept are analysed. Customer Lifetime Value is also differentiated from Customer Equity and Customer Profitability analysis to estimate customer value in terms of firm profitability. Customer Lifetime Value and Customer Equity concepts are formally defined. Additionally, a classification of a set of published researches into Customer Lifetime Value and/or Customer Equity is developed. This classification has been posited according to several criteria that serves as a guide to key requirements for developing these types of models. Finally,several conclusions, suggestions and future research streams are highlighted.

Citation: ESTRELLA-RAMON, A. and ELLIS-CHADWICK, F., 2017. Do different kinds of user-generated content in online brand communities really work? Online Information Review, 41(7), pp. 954-968.