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Nina Michaelidou
Researcher at Loughborough University
Publications - 72
Citations - 4484
Nina Michaelidou is an academic researcher from Loughborough University. The author has contributed to research in topics: Social media & Consumer behaviour. The author has an hindex of 23, co-authored 68 publications receiving 3821 citations. Previous affiliations of Nina Michaelidou include University of Winchester & University of Birmingham.
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Usage, barriers and measurement of social media marketing: An exploratory investigation of small and medium B2B brands
TL;DR: In this article, the authors focus on B2B SMEs and their social networking practices, particularly, usage, perceived barriers, and the measurement of effectiveness of SNS as a marketing tool.
Usage, barriers and measurement of social media marketing
TL;DR: In this paper, the authors focus on B2B SMEs and their social networking practices, particularly, usage, perceived barriers, and the measurement of effectiveness of SNS as a marketing tool.
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The role of health consciousness, food safety concern and ethical identity on attitudes and intentions towards organic food
TL;DR: In this article, the authors examined the roles of health consciousness, food safety concern and ethical self-identity in predicting attitude and purchase intention within the context of organic produce and found that food safety was the most important predictor of attitude while health consciousness appears to be the least important motive in contrast to findings from some previous research.
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Determinants of social media adoption by B2B organizations
TL;DR: In this paper, a conceptual model, which draws on the technology acceptance model and resource-based theory, is developed and tested using quantitative data from B2B organizations in the UK.
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Emotions, store-environmental cues, store-choice criteria, and marketing outcomes.
TL;DR: In this article, the authors integrate extant research relating to store-related cognitions, customer emotions (arousal and pleasure), satisfaction, and loyalty into one framework, and test the hypotheses and model with structural equation modelling.