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

Nigel L. Williams, Nicole Ferdinand, John Bustard

Research output: Contribution to journalArticlepeer-review

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Abstract

Purpose: Advances in artificial intelligence (AI) natural language processing may see the emergence ofalgorithmic 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 customerdecision-making. The purpose of this paper is to provide an overview of the socio technological trendsthat have encouraged the evolution of informal infulence strategies from WOM to aWOM.

Design/methodology/approach: This paper examines the origins and path of development ofinfluential customer communications from word of mouth (WOM) to electronic word of mouth (eWOM) andthe emerging trend of aWOM. The growth of aWOM is theorized as a result of new developments in AInatural language processing tools along with autonomous distribution systems in the form of softwarerobots and virtual assistants.

Findings: aWOM may become a dominant source of information for tourists, as it can supportmultimodal delivery of useful contextual information. Individuals, organizations and social mediaplatforms 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 bechallenged by algorithmically generated content. aWOM tools may also generate content using sensorson personal devices, creating privacy and information security concerns if users did not give permissionfor such activities.

Originality/value: This paper is the first to theorize the emergence of aWOM as autonomous AIcommunication within the framework of unpaid influence or WOM. As customer engagement willincreasingly occur in algorithmic environments that comprise person–machine interactions, aWOM willinfluence future tourism research and practice.
Original languageEnglish
Number of pages5
JournalTourism Review
Early online date30 Sep 2019
DOIs
Publication statusEarly online - 30 Sep 2019

Keywords

  • Natural language processing
  • WOM
  • eWOM
  • Artificial intelligence
  • aWOM
  • Chatbot

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