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From WOM to aWOM – the evolution of unpaid influence: a perspective article

Nigel L. Williams (Faculty of Business and Law, Portsmouth Business School, University of Portsmouth, Portsmouth, UK)
Nicole Ferdinand (Oxford School of Hospitality Management, Oxford Brookes Business School, Oxford Brookes University, Oxford, UK)
John Bustard (John Bustard is based at Ulster University Business School, University of Ulster, Belfast, UK)

Tourism Review

ISSN: 1660-5373

Article publication date: 2 October 2019

Issue publication date: 20 February 2020




Advances in artificial intelligence (AI) natural language processing may see the emergence of algorithmic word of mouth (aWOM), content created and shared by automated tools. As AI tools improve, aWOM will increase in volume and sophistication, displacing eWOM as an influence on customer decision-making. The purpose of this paper is to provide an overview of the socio technological trends that have encouraged the evolution of informal infulence strategies from WOM to aWOM.


This paper examines the origins and path of development of influential customer communications from word of mouth (WOM) to electronic word of mouth (eWOM) and the emerging trend of aWOM. The growth of aWOM is theorized as a result of new developments in AI natural language processing tools along with autonomous distribution systems in the form of software robots and virtual assistants.


aWOM may become a dominant source of information for tourists, as it can support multimodal delivery of useful contextual information. Individuals, organizations and social media platforms will have to ensure that aWOM is developed and deployed responsibly and ethically.

Practical implications

aWOM may emerge as the dominant source of information for tourist decision-making, displacing WOM or eWOM. aWOM may also impact online opinion leaders, as they may be challenged by algorithmically generated content. aWOM tools may also generate content using sensors on personal devices, creating privacy and information security concerns if users did not give permission for such activities.


This paper is the first to theorize the emergence of aWOM as autonomous AI communication within the framework of unpaid influence or WOM. As customer engagement will increasingly occur in algorithmic environments that comprise person–machine interactions, aWOM will influence future tourism research and practice.



Williams, N.L., Ferdinand, N. and Bustard, J. (2020), "From WOM to aWOM – the evolution of unpaid influence: a perspective article", Tourism Review, Vol. 75 No. 1, pp. 314-318.



Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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