Purpose – The purpose of this paper is to present and test a conceptual model for understanding consumer responses to cause related voucher schemes (CRVS), considering the initiatives of two UK-based grocery retailers (Tesco and Morrisons). Design/methodology/approach – The conceptual model incorporates six theoretically derived exogenous constructs, i.e. status of the cause, company-cause fit, personal involvement with the cause, attitudes to the company, perceived sincerity of the company and perceived ubiquity. These are hypothesized to influence consumer responses to three primary endogenous variables: interest in the company, favourability of attitudes to the company and use (impact on purchasing intentions). The model is tested using survey data (n=401) collected in two UK cities. Findings – All but two of the hypothesized path relationships were confirmed and the percentage of explained variance for the primary endogenous variables compares well against previous models. Attitudes to the company, perceived ubiquity and favourability were identified as significant predictors of behavioural intentions (use). Practical implications – In selecting a cause, managers need to think carefully about the status of the cause, its degree of fit with the company and how to build personal involvement. CRVS initiatives should be focused, with consistency in communication. If a company suffers from negative consumer attitudes, a CRVS alone is unlikely to turn around their business performance. Originality/value – The paper represents the first academic assessment of consumer responses to CRVS, introducing and validating a conceptual model.

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Scholars of critical algorithmic studies, including those from geography, anthropology, science talent search, and communication studies, have begun to consider how algorithmic devices and platforms facilitate democratic practices. In this article, I draw on a comparative ethnography of two alternative open-source algorithmic platforms – Decide Madrid and vTaiwan – to consider how they are dynamically constituted by differing algorithmic–human relationships. I compare how different algorithmic–human relationships empower citizens to influence political decision-making through proposing, commenting, and voting on the urban issues that should receive political resources in Taipei and Madrid. I argue that algorithmic empowerment is an emerging process in which algorithmic–human relationships orient away from limitations and towards conditions of plurality, actionality, and power decentralisation. This argument frames algorithmic empowerment as bringing about empowering conditions that allow (underrepresented) individuals to shape policy-making and consider plural perspectives for political change and action, not as an outcome-driven, binary assessment (i.e. yes/no). This article contributes a novel, situated, and comparative conceptualisation of algorithmic empowerment that moves beyond technological determinism and universalism.