Do we follow the crowd on social media? Experimental evidence on consumer attitudes in the contexts of NeWOM and firm crisis response

Boonchoo, Pattana; Suwandee, Senee; Lertwannawit, Aurathai; Racela, Olimpia C.

doi:10.1108/apjml-06-2019-0349

Cited by 9 publications

(10 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence, there is consensus within this community that maintaining a high level of purchases is a desirable behaviouras shown by the frequency of haul publications from the same YouTubers (Jeffries, 2011;Wood, 2020). Community consensus, which indicates the degree of agreement among network members JRIM 15,1 regarding a particular issue (Suwandee et al, 2020), has been found as an important factor influencing the evaluation of positive and negative eWOM (Golmohammadi et al, 2020;Lee and Cranage, 2014), with results indicating that higher levels of consensus make the effects of those eWOM messages in line with the predominant view more powerful, while attenuating eWOM messages that are not in line with the predominant opinion (Suwandee et al, 2020). Hence, in a community where hauls of new products are highly appreciated by users (Choi and Behm-Morawitz, 2017), anti-hauls clash against the dominant discourse, breaking the consensus.…”

Section: Hypotheses Developmentmentioning

confidence: 99%

You absolutely (don’t) need this!examining differences on customer engagement components for (anti)haul youtubers’ videos

García-de-Frutos

Estrella-Ramón

2021

JRIM

View full text Add to dashboard Cite

Purpose This study aims to focus on the content published by social media influencers – i.e. YouTubers – on their YouTube channels. The main purpose of this research is to analyse whether anti-consumption-framed content (anti-hauls) generates more views, more dislikes (and less dislikes) and more comments, as customer engagement components, than pro-consumption-framed content (hauls). Design/methodology/approach Based on 160 videos published on YouTube by 80 influencers on their respective channels, this study mainly analyses whether there are differences between anti-consumption and pro-consumption content in the various elements that constitute customer engagement (i.e. number of views, likes, dislikes and comments). Findings Results indicate that there are differences between anti-consumption and pro-consumption content in terms of total number of views, likes, dislikes and comments. All these customer engagement components are higher for anti-consumption-framed videos, which offers interesting implications for both theory and practice. Originality/value This study extends previous literature by accounting content published by social media influencers on their social media accounts, instead of analysing the most traditionally studied content that is published by brands on their own social media; and classifying this content as anti/pro-consumption rather than using the traditional dichotomy between transactional/emotional content. Brands should pay special attention to the content generated by social media influencers because it is a powerful form of electronic word-of-mouth that currently plays a significant role in customers’ (non)purchase decisions.

show abstract

Section: Hypotheses Developmentmentioning

confidence: 99%

You absolutely (don’t) need this!examining differences on customer engagement components for (anti)haul youtubers’ videos

García-de-Frutos

Estrella-Ramón

2021

JRIM

View full text Add to dashboard Cite

show abstract

“…and spreads faster and more widely. The motives and purposes for sharing NWOM with different emotional intensity are more difficult to discern (De Keyzer et al, 2017;Suwandee et al, 2021). The findings of previous research on the emotional intensity of online reviews may not be directly applicable to the research of WOM in social media.…”

Section: Negative Wordof-mouthmentioning

confidence: 88%

“…The motives and purposes for sharing NWOM with different emotional intensity are more difficult to discern (De Keyzer et al. , 2017; Suwandee et al. , 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of emotional intensity of negative word-of-mouth on perceived helpfulness in social media

Chen

Zhang

2022

IMDS

View full text Add to dashboard Cite

PurposeNegative word-of-mouth has a variety of negative effects on companies. Thus, how consumers process and evaluate negative word-of-mouth is an important issue for companies. This research aims to investigate the effect of emotional intensity of negative word-of-mouth on consumers' perceived helpfulness.Design/methodology/approachThe research model was developed based on attribution theory. A four-study approach involving two field experiments and two online experiments was employed to examine the proposed hypotheses.FindingsThe results show that the emotional intensity of negative word-of-mouth negatively affects altruistic motive attributions, while altruistic motive attributions positively affect perceived helpfulness and plays a mediating role in the relationship between the emotional intensity of negative word-of-mouth and perceived helpfulness. Consumers' self-construal moderates the effects of emotional intensity of negative word-of-mouth on altruistic motive attributions and perceived helpfulness, with the negative effects of emotional intensity of negative word-of-mouth on altruistic motive attributions and perceived helpfulness being weaker for consumers with high interdependent self-construal than for those with high independent self-construal.Originality/valueThe findings not only have a significant theoretical contribution, deepening the understanding of the effects of negative word-of-mouth but also have useful implications for practitioners to improve the management of negative word-of-mouth.

show abstract

“…Response is the last fundamental component in the model regarding customer and firm reactions to negative online review susceptibility. Many studies focus on customer (e.g., Abubakar, Ilkan, Al-Tal, & Eluwole, 2017;Agusto & Torres, 2018;Gruen, Osmonbekov, & Czaplewski, 2006;Matute, Polo-Redondo, & Utrillas, 2016;Tandon, Dhir, Kaur, Kushwah, & Salo, 2020;Williams, Crittenden, & Henley, 2021) and firm responses (e.g., Golmohammadi, Mattila, & Gauri, 2020;Herhausen, Ludwig, Grewal, Wulf, & Schoegel, 2019;Nazifi et al, 2020;Suwandee, Lertwannawit, Racela, & Boonchoo, 2020;Van den Broek, Langley, & Hornig, 2017;Vermeer, Araujo, Bernritter, & van Noort, 2019) to online reviews. However, few investigate firm responses to negative online review susceptibility by considering customer journey and response.…”

Section: Response: Answering the "So What?" Questionmentioning

confidence: 99%

Generation, susceptibility, and response regarding negativity: An in-depth analysis on negative online reviews

Colmekcioglu

Marvi²,

Foroudi³

et al. 2022

Journal of Business Research

View full text Add to dashboard Cite

Do we follow the crowd on social media? Experimental evidence on consumer attitudes in the contexts of NeWOM and firm crisis response

Cited by 9 publications

References 68 publications

You absolutely (don’t) need this!examining differences on customer engagement components for (anti)haul youtubers’ videos

You absolutely (don’t) need this!examining differences on customer engagement components for (anti)haul youtubers’ videos

Impact of emotional intensity of negative word-of-mouth on perceived helpfulness in social media

Generation, susceptibility, and response regarding negativity: An in-depth analysis on negative online reviews

Contact Info

Product

Resources

About