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The purpose of this study is to operationalise and measure the effects of negative customer engagement (CE) in conjunction with positive CE. Both valences are explored through affective, cognitive and behaviour dimensions, and, in relation to the antecedent of involvement and outcome of word-of-mouth (WOM). It also explores the moderating influence of service context by examining engagement within a social service versus a social networking site (SNS). Engagement with the dual focal objects of a service brand and a service community are also examined.

Structural equation modelling is used to analyse 625 survey responses.

Involvement is a strong driver of positive CE, and positive CE has a strong effect on WOM. These findings are consistent across the “brand” and “community” object, suggesting positive CE is mutually reinforced by different objects in a relationship. Positive CE is also found to operate consistently across the service types. Involvement is a moderately negative driver of negative CE, and negative CE is a positive driver of WOM. These relationships operate differently across the objects and service types. Involvement has a stronger inverse effect on negative CE for the social service, diverging from assumptions that negative CE is reflective of highly involved customers. Interestingly, negative CE has a stronger effect on WOM in the social service, highlighting the active and vocal nature of customers within this service context.

To the best of the authors’ knowledge, this is the first paper to quantitatively measure positive and negative valences of engagement concurrently, and examine the moderating effect of dual objects across contrasting service types.

The study considers time-varying risk premium in investigating the capability of technical analysis (TA) to predict and outperform a buy–hold strategy in Bitcoin exchange rate returns.

The study tests the technical trading rule of fixed moving average (FMA) on daily actual and equilibrium returns of Bitcoin exchange rates. The equilibrium returns are computed using dynamic CAPM in conjunction with a VAR-MGARCH (1, 1) system. The empirical evaluation of the study uses a case study of four Bitcoin exchange rates (BTC/AUD, BTC/EUR, BTC/JPY and BTC/ZAR) for the period 19 June 2010 to 30 October 2020.

The findings are consistent with related studies in conventional foreign exchange markets that find TA to be profitable, especially in emerging markets. Nevertheless, the consideration of risk premium has the effect of reducing the abnormal returns. Also, further robust tests reveal that Bitcoin returns possess a momentum effect which prompts further study in efficient market hypothesis research.

The empirical findings of this study should benefit portfolio managers and active investors on the strength of TA to predict returns in a speculative market like the Bitcoin exchange rate market.

The study takes cognisance that cryptocurrency trading is speculative in nature which renders it a good candidate for TA methods. While there are studies that have explored the value of TA in Bitcoin exchange rates, these studies fail to incorporate the effects of time-varying risk premiums, the strength and focus of the current paper.