Open AccessResearch on the Mechanism of the Influence of E-WOM Dispersion on Consumers Return Intention
Author(s) -
Genia Long,
Mengmeng Song,
Yucong Duan,
Zhiyuan Cao,
Wei-Li Wu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1944/1/012023
Subject(s) - attribution , dispersion (optics) , word of mouth , situational ethics , advertising , conceptual model , psychology , product (mathematics) , selection (genetic algorithm) , business , marketing , social psychology , computer science , artificial intelligence , mathematics , physics , database , optics , geometry
Based on the attribution theory, this paper constructs a conceptual framework for the influence of the dispersion of electronic word of mouth on consumers’ return intentions, focusing on the impact of the interaction between robot review and e-WOM dispersion on consumers’ attribution selection, the study uses situational experiments to collect data and verify hypotheses. The study found that: (1) Consumers are more willing to return goods when faced with high-dispersion electronic word of mouth; (2) When facing high-dispersion electronic word of mouth, consumers tend to attribute it to existing reviewers; (3) The influence of word-of-mouth dispersion on attribution selection is regulated by robot reviews. For the word-of-mouth dispersion of robot reviews, the tendency of word-of-mouth dispersion to be attributed to product reasons becomes greater. The research has laid a theoretical foundation for further exploring the influence of e-WOM dispersion on consumers’ return intentions, and also provides theoretical guidance and reference for enterprises to rationally use Internet robots and reduce return rates.