مقاله انگلیسی شکست های شدید خدمات و تبلیغات شفاهی انتقام جویانه آنلاین
Abstract
Keywords
Introduction
What we know (and don’t) about different wom types
Conceptual framework and hypotheses
Hypotheses testing
Discussion
Declaration of Competing Interest
Appendix A. Quota sampling by the market research company
Appendix B. Social network–specific regression results
Appendix C:. Results of separate fractional regression analyses
Appendix D:. Results of ordinary least squares regression analyses
Appendix E. Multinomial logistic regressions for WOM types ranks
References
ABSTRACT
In the digital era, consumers choose among various types of word of mouth (WOM) when searching for product information. This research investigates how consumers allocate their search efforts across three key WOM types: face-to-face (e.g., offline communication among consumers), Internet opinion sites (e.g., product reviews), and social media platforms (e.g., recommendations on Facebook). The authors develop a conceptual framework of WOM types and derive hypotheses about the determinants of WOM search behaviors, which they test against representative data from more than 2,000 consumers. Several product and consumer characteristics have systematic effects on search effort allocation, as do WOM type–specific resources. A process-related analysis also suggests different roles of WOM types during customers’ search journeys, such that face-to-face conversations and Internet opinion sites tend to be consulted early, whereas social media mostly serve as final information sources. Overall, the results caution against assuming that the different WOM types are arbitrary or random substitutes.
Introduction
Word of mouth (WOM) is one of the most influential information sources for consumers (Brown & Reingen, 1987; Katz & Lazarsfeld, 1955). In addition to receiving information through face-to-face interactions with others, consumers in the digital age can learn from product reviews on Internet opinion sites (e.g., Amazon, Yelp, Trustpilot) or social media (e.g., Facebook, Twitter). Because these platforms and the forms of WOM they produce differ vastly, in terms of personal connections, synchronicity, and feedback options, a deeper understanding of the functions of various types of WOM for consumers is demanded, beyond imposing a simple online–offline dichotomy (Berger & Iyengar, 2013; Hennig-Thurau et al., 2015; Lovett et al., 2013). While research has shed light on each WOM type individually (e.g., face-to-face, de Matos & Rossi, 2008; Internet opinion sites, You et al., 2015; social media, Hennig-Thurau et al., 2015), limited insights exists into how the differences manifested by various WOM types influence consumers’ WOM usage, particularly over the course of their search process (cf. Berger & Iyengar, 2013; Rosario et al., 2020)