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Understanding electronic word of behavior: conceptualization of the observable digital traces of consumers’ behaviors

Abstract

The widespread digitization of consumers’ daily lives entails a plethora of digital traces of consumers’ behaviors. These traces can be turned into meaningful communicative and observable content by the services that possess the trace data. While extant research has empirically showed this to have a significant impact on consumer choices we argue that the phenomenon is undertheorized. In this theoretical paper, we conceptualize this kind of observable behavior-based information as ‘Electronic Word of Behavior’ (eWOB) and define it as “published accounts of behavior, based on the unobservable digital traces of consumers’ behaviors”. We characterize eWOB as an instantiation of Digital Trace Data and situate it within the established concepts of Social Interactions and Electronic Word of Mouth (eWOM). By drawing on extant empirical research and constructs from Digital Trace Data, Social Interactions and eWOM, we propose a framework for eWOB that highlights its unique characteristics and design dimensions.

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Notes

  1. 1.

    To simplify, we refer to these almost identical concepts as ‘Social Interactions’

  2. 2.

    Cheung & Thadani’s original term for this element was ‘Contextual Factor’, however it basically describes the channel/platform on which the eWOM was published, and thus we will refer to it as Channel which also aligns it with the SI framework

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Author information

Correspondence to Katrine Kunst.

Additional information

Responsible Editors: Christian Matt and Christy M.K. Cheung

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Cite this article

Kunst, K., Vatrapu, R. Understanding electronic word of behavior: conceptualization of the observable digital traces of consumers’ behaviors. Electron Markets 29, 323–336 (2019). https://doi.org/10.1007/s12525-018-0301-x

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Keywords

  • Electronic word of mouth (eWOM)
  • Electronic word of behavior (eWOB)
  • Social influence
  • Observational learning
  • Social interactions
  • Digital trace data

JEL classification

  • M15: IT Management
  • M31: Marketing
  • L81 Retail and Wholesale Trade; e-Commerce
  • D11 Consumer Economics: Theory