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

Nigel Williams, Nicole Ferdinand

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)
169 Downloads (Pure)


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 influence 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.
Original languageEnglish
Article number1
Pages (from-to)314
Number of pages318
JournalTourism Review
Publication statusPublished (in print/issue) - 30 Sept 2019


  • natural language processing
  • WOM
  • EWOM
  • artificial intelligence
  • AWOM
  • Chatbot


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