Conceptualising electronic word of mouth activity: An input‐process‐output perspective

In light of the growth of internet usage and its important role in the field of e‐commerce, electronic word‐of‐mouth (eWOM) has been changing people's behavior and decisions. People count on other users' opinions and information; they sometimes even make offline decisions based on information acquired online. The purpose of this paper is to conceptualise eWOM activity from an input‐process‐output (IPO) perspective; propose a classification framework based on the identified academic literature; analyze eWOM literature in terms of quantitative development and qualitative issues that are useful to both academics and researchers; and provide directions and guidelines for future research studies in eWOM.

The authors performed a systematic literature review of peer‐reviewed published journal articles and examined the current state of knowledge on eWOM literature based on a comprehensive search of several leading databases. In total, 94 articles were identified that comprised contributions from different strands of eWOM research. The scope of this investigation was limited to the timeframe of 2000‐2009.

The present study finds that research in eWOM is relatively new and has evolved only during the last ten years. This ten‐year study is deemed to be representative of the available eWOM literature. It is also shown that many scholars have incorporated established theories to explain eWOM communication phenomena. The current study not only fills the current gap in eWOM research but also provides a roadmap in analyzing eWOM communications.

This study serves as a consolidated database that may be used to guide future research. It provides a structured approach to analyzing the literature and identifying trends and gaps in order to map out an appropriate agenda for eWOM research. The proposed integrated classification framework can serve as a roadmap for academic research.

This paper systematically reviews the current state of eWOM research. To contribute to the development of a more comprehensive database for eWOM research, a classification framework of the eWOM literature is presented, building on the IPO model, by summarizing and organizing prior research into three areas covering antecedents, processes, and consequences of eWOM. The authors further summarize the theories and models that previous scholars have applied to their studies.