Examining Biased Assimilation of Brand-related Online Reviews

Mafael, Alexander; Gottschalk, Sabrina A.; Kreis, Henning

doi:10.1016/j.intmar.2016.06.002

Cited by 36 publications

(32 citation statements)

References 72 publications

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“…When eWOM communications are useful they significantly affect an individual's purchase intention (Jeong and Koo 2015). Several studies have investigated the relationship between eWOM usefulness and purchase intention (Cheung 2014;Frasquet et al 2015;Gunawan and Huarng 2015;Huang et al 2013;Lee et al 2011;Mafael et al 2016;Lee 2008, 2009). For example, Huang et al (2013) used data from 549 respondents from China and found that eWOM usefulness positively affects hotel booking intention.…”

Section: Ewom Usefulnessmentioning

confidence: 99%

The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis

et al. 2019

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The aim of this research is to synthesise findings from previous studies by employing weight and meta-analysis to reconcile conflicting evidence and draw a “big picture” of eWOM factors influencing consumers’ intention to buy. By using the findings from 69 studies, this research identified best (e.g. argument quality, valence, eWOM usefulness, trust in message), promising (e.g. eWOM credibility, emotional trust, attitude towards website) and least effective (e.g. volume, existing eWOM, source credibility) predictors of intention to buy in eWOM research. Additionally, the effect size of each predictor was calculated by performing meta-analysis. For academics, understanding what influences consumers’ intention to buy will help set the agenda for future research directions; for practitioners, it will provide benefit in terms of practical guidance based on detailed analysis of specific factors influencing consumers’ intention to buy, which could enhance their marketing activities.

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Section: Ewom Usefulnessmentioning

confidence: 99%

The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis

et al. 2019

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“…Brands in B2C markets not only act as a signal in themselves, but they also impact how consumers respond to unintentional signals, such as social media reviews. Mafael, Gottschalk and Kreis (2016) have found that brand attitude is indeed very important in determining how consumers process eWOM information, so that if they have a positive attitude towards the brand, they find positive arguments in an eWOM review more persuasive and negative arguments less persuasive than if they have a negative attitude towards the brand. Such biased information processing of social media signals would be less likely to occur in B2B markets.…”

Section: Signalling Theory In B2b Marketsmentioning

confidence: 99%

The impact of social media signals on supplier selection: insights from two experiments

Banerjee

Ries

Wiertz

2020

IJOPM

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This is the accepted version of the paper.This version of the publication may differ from the final published version.Permanent repository link: https://openaccess.city.ac.uk/id/eprint/23466/ Link to published version: http://dx. AbstractPurpose: Online B2B markets offer buyers a new source of information provided by social media signals about suppliers. These signals have not yet received much attention in the supplier selection literature. This study advances our understanding of how buyers respond to social media signals in the supplier selection process.Design: We develop a choice-based conjoint experimental design to isolate and manipulate two signals from social media: volume (i.e. the number of ratings) and valence (i.e. average evaluation of the ratings). We test how these signals are interpreted in the context of varying deal sizes and price points.Findings: Both volume and valence are positively correlated with supplier selection. However, (i) the signals exhibit diminishing returns and (ii) the efficacy of valence is interpreted in the context of volume. We also find that (iii) there is no influence of the deal size and that (iv) the relationships between signals and supplier selection are negatively moderated by deviations from the reference price.Implications: Social media signals should be considered in supplier selection decisions as they convey valuable information to the buyer. However, signals go through a process of interpretation which has implications for buyers, suppliers, and owners of online B2B markets.Originality: Our research opens new lines of inquiry in behavioural operations management research regarding the mechanisms by which buyers interpret social media signals and how these ultimately influence their choice.

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“…An informal communication about various brands takes place among the consumers in the form of online product reviews, where they share their experiences of such brands in various brand communities, brand pages and other online social media platforms (Steinmann, Mau, & Schramm-Klein, 2015; Ziegele & Weber, 2015). Such reviews can influence the consumer’s purchasing decision (Mafael, Gottschalk, & Kreis, 2016). Consumers generally give their opinions on various brands through online reviews, which creates an image of the brand in consumer’s mind (Költringer & Dickinger, 2015).…”

Section: Introductionmentioning

confidence: 99%

Effect of Credible Reviews on Brand Image: A Mixed Method Approach

Chakraborty

Bhat

2017

IIM Kozhikode Society & Management Review

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Rapid growth of online social media reduces the marketer’s control over brand management. Consumers share their brand-related experiences (through online reviews) in various online social media platforms. It is a major challenge for the marketers to understand the effects of online reviews on a brand’s image. This study addresses the issue and attempts to understand the effects of online reviews on brand image. The concept of brand image is broken up into two parts, namely, functional and hedonic. The study follows a mixed method approach using both quantitative and qualitative techniques. Quantitative techniques have been used to measure the objective experiences of the consumers, whereas qualitative techniques have been used to examine the subjective experiences of the consumers. For quantitative technique, structural equation modelling (SEM) has been adopted to determine the relationships between the variables. For qualitative technique, netnography has been followed. Quantitative data analysis reveals that online credible reviews have more significant effect on hedonic brand image. Qualitative study also shows evidences of functional and hedonic brand images in online community. Future directions for research are mentioned as well.

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Examining Biased Assimilation of Brand-related Online Reviews

Cited by 36 publications

References 72 publications

The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis

The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis

The impact of social media signals on supplier selection: insights from two experiments

Effect of Credible Reviews on Brand Image: A Mixed Method Approach

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