The influence of emoji meaning multipleness on perceived online review helpfulness: The mediating role of processing fluency

Wu, Ruijuan; Chen, Jiuqi; Wang, Cheng Lu; Zhou, Liying

doi:10.1016/j.jbusres.2021.12.037

Cited by 54 publications

(30 citation statements)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Because tips have become a major revenue source for live streaming music platforms, influencers’ role is seen as increasingly important for platforms. They can directly impact user decisions that were previously based on online reviews and third-party-generated recommendations (Wu et al , 2022).…”

Section: Discussionmentioning

confidence: 99%

Understanding the role of influencers on live streaming platforms: when tipping makes the difference

Zhou

Jin²,

Wu³

et al. 2022

EJM

Self Cite

View full text Add to dashboard Cite

Purpose This study aims to examine if the participation of live-stream influencers (LSIs) affects tipping frequency on live streaming platforms, and further investigate the mediating and moderating mechanisms. Design/methodology/approach Quasi-experiment and difference-in-differences models are used for data analysis. Propensity score matching is used to address potential unobservable endogeneity. Findings Real-time live streaming data reveal that LSIs’ participation significantly improves tipping frequency in live streaming rooms. Also, more users are attracted to the live streaming rooms and more users become active in participation. Additionally, the positive impact of LSIs’ participation is enhanced in the live streaming rooms with a greater number of relationship links between users. Research limitations/implications The findings clarify the new role of influencers and reveal the mechanisms on how LSIs benefit the platforms. Practical implications The findings offer novel insights into implementing influencer marketing to interactive social media platforms, by encouraging influencer participation, user relationship building and influencer network growth. Originality/value This study highlights the value of LSIs for interactive social media platforms in terms of organic growth, revenue generation and cost reduction.

show abstract

Section: Discussionmentioning

confidence: 99%

Understanding the role of influencers on live streaming platforms: when tipping makes the difference

Zhou

Jin²,

Wu³

et al. 2022

EJM

Self Cite

View full text Add to dashboard Cite

show abstract

“…The analysis is limited to text reviews. Consumers not only write reviews but also add photographs and emoji’s to their reviews which have useful information (Wu et al , 2022). Including these in the analysis would help further enhance the understanding of customer satisfaction.…”

Section: Discussionmentioning

confidence: 99%

AI-enables product purchase on Amazon: what are the consumers saying?

Gunasekar

Ray

Dixit

et al. 2022

View full text Add to dashboard Cite

Purpose This study aims to identify the product attributes that influence customer satisfaction related to AI-enabled products with a strong forecast of growth. This study is very timely as the market for AI-based smart home products is still at a nascent stage in emerging economies (Vaishali Dar, 2021). Adding evidence to literature on the experience of customers, identifying the attributes that lead to customer satisfaction and those that lead to dissatisfaction are essential for products that were launched recently during the pandemic. This study makes valuable addition to the existing literature. Design/methodology/approach Online reviews (12,326 reviews) for EchoDot products launched by Amazon India during the pandemic were collected for the study. The attributes were identified based on the most frequently discussed attributes in the text reviews. Further review valence was determined to group the reviews under positive reviews indicating customer satisfaction and negative reviews indicating customer dissatisfaction. Logistic regression was used to identify the attributes that significantly impact customer satisfaction/dissatisfaction. Findings The results of the study indicate that while EchoDot is seen to add value to the smart home environment (home variable), video (video variable) and speaker (speaker variable) quality also contribute to customer satisfaction. Further, consumers found the product truly worth their money (value for money variable). Other attributes like a complaint about Bluetooth features are seen to increase the probability of customer dissatisfaction. Originality/value This study identifies the most important attributes that influence customer satisfaction in AI-enabled product sales on e-commerce platforms in pandemic times for India. Such studies are scarce in the emerging markets where the AI-based home appliance market is still in its nascent stage, and the customers are trying out their experiences with these products. What the customers expect and are these products fulfill these expectations is an important question that needs to be addressed by research. This study addresses this gap and adds to this literature.

show abstract

“…Online customer reviews play an increasingly important role in online commerce which has attracted scholars and practitioners’ attention around the world ( Yang et al, 2021 ; Li et al, 2022 ; Wu et al, 2022 ). Extensive numbers of product reviews provide rich information for consumers which can help them decrease the degree of uncertainty and risk ( Zhu and Zhang, 2010 ; Yang et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

“…Many scholars have examined the factors that affect review helpfulness ( Yang et al, 2019 , 2021 ; Aghakhani et al, 2020 ; Wu et al, 2022 ). Factors such as review rating ( Aghakhani et al, 2020 ), review content ( Qazi et al, 2016 ), review length ( Hong et al, 2017 ), and review image ( Karimi and Wang, 2017 ) were identified as influencers of review helpfulness.…”

Section: Introductionmentioning

confidence: 99%

“…However, a large number of reviews may cause significant information overload and high search costs for the reader (Siering et al, 2018). These problems may confuse customers about product quality and make it difficult for them to form purchase decisions (Wu et al, 2022). 10.3389/fpsyg.2022.958386 To address these problems, many e-commerce websites resort to product review systems that enable customers to vote on whether a review is helpful or not (Hong et al, 2017;Malik and Hussain, 2017;Yang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective

Zhang

Jiang²,

Zhou³

et al. 2022

Front. Psychol.

View full text Add to dashboard Cite

As increasingly retail enterprises have adopted the omnichannel retailing strategy, both online-generated and offline-generated reviews should be considered to better understand the helpfulness of online reviews in the omnichannel retailing context. Drawing on the Elaboration Likelihood Model, the present study attempts to examine the impacts of review label volume, review content length, and review label-content relevance on review helpfulness in the omnichannel retailing context. The empirical data of 2,822 product reviews were collected from Suning.com. The results of Negative Binomial Regression showed that both central cue (review label-content relevance) and peripheral cue (review content length) positively affect review helpfulness. Specifically, the positive effect of review content length on review helpfulness will be stronger when the online review is submitted from an omnichannel retailer’s online store. On the contrary, the positive effect of review label-content relevance on review helpfulness will be weaker when the online review is generated from an omnichannel retailer’s online channel.

show abstract

The influence of emoji meaning multipleness on perceived online review helpfulness: The mediating role of processing fluency

Cited by 54 publications

References 69 publications

Understanding the role of influencers on live streaming platforms: when tipping makes the difference

Understanding the role of influencers on live streaming platforms: when tipping makes the difference

AI-enables product purchase on Amazon: what are the consumers saying?

Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective

Contact Info

Product

Resources

About