The effect of emotional changes in composite reviews on consumers' information adoption from a dual perspective

Zhang, Depeng; Ma, Jiaxin; He, Zhenxing

doi:10.1108/imds-06-2023-0396

Cited by 3 publications

References 61 publications

(172 reference statements)

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Additional reviews, perceived credibility and consumer online purchasing behavior: a study of university students in China

Wang,

Bai,

Zhao

2024

APJML

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PurposeThis study explores the link between additional reviews, credibility, and consumers’ online purchasing behavior.Design/methodology/approachWe employ a 2 × 2 between-subjects design to measure subjects’ purchasing behavior with versus without additional reviews and with important versus non-important attributes. A total of 529 valid questionnaires are collected from university students across 30 Chinese provinces.FindingsThe addition of negative reviews to a positive initial review enhances consumers’ perceived credibility of the reviewer and the overall review content. This effect is positively moderated by the attribute importance in additional reviews. Moreover, we find that as the time interval increases, consumers’ perceived credibility gradually increases but eventually decreases after reaching a certain threshold. In addition, the attribute importance in additional reviews negatively moderates the impact of perceived credibility on consumer purchasing behavior.Originality/valueExisting studies on first and subsequent reviews mainly focus on the difference in perceived usefulness between the two. They do not examine how additional reviews affect potential customers’ perceived credibility and their purchase decision-making. This study bridges the gap between the word-of-mouth literature and marketing practices.

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Additional reviews, perceived credibility and consumer online purchasing behavior: a study of university students in China

Wang,

Bai,

Zhao

2024

APJML

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Text Mining Based Approach for Customer Sentiment and Product Competitiveness Using Composite Online Review Data

Wen,

Chen,

Liu

et al. 2024

JTAER

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We aimed to provide a realistic portrayal of customer sentiment and product competitiveness, as well as to inspire businesses to optimise their products and enhance their services. This paper uses 119,190 pairs of real composite review data as a corpus to examine customer sentiment analysis and product competitiveness. The research is conducted by combining TF-IDF text mining with a time-phase division through the k-means clustering method. The study identified ‘quality’, ‘taste’, ‘appearance packaging’, ‘logistics’, ‘prices’, ‘service’, ‘evaluations’, and ‘customer loyalty’ as the commodity dimensions that customers are most concerned about. These dimensions should therefore serve as the primary entry point for improving the commodity and understanding customers. A review of customer feedback reveals that the composite reviews can be divided into three time stages. Furthermore, the sentiment expressed by customers can become increasingly negative over time. The product competitiveness based on the composite review can be characterised by four regional quadrants, such as ‘Advantage Area’, ‘Struggle Area’, ‘Opportunity Area’, and ‘Waiting Area’, and merchants can target these areas to improve product competitiveness according to the dimensional distribution. In the future, it will also be possible to take customer demographics into account in order to gain a deeper understanding of the customer base.

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Evaluating the Influence of YouTube Vlogs on Hotel Booking Decisions

Lata,

Rana

2024

Advances in Human and Social Aspects of Technology

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With the popularity of social media, YouTube Vlogs are playing a crucial role for travelers' hotel booking. YouTube Vloggers create videos of their travelling experiences and upload which help the novice travelers to make an informed choice about their decision on hotel booking. The current study examines what determines travelers to adopt information from YouTube Vlogs for online hotel bookings and how it influences their intentions. A research model was prepared and further, analyzed by sampling 256 Indian travelers who used YouTube Vlogs prior to their hotel booking. The hypotheses of this paper were analyzed by applying structural equation modeling (SEM) using partial least squares (PLS). The findings of this study identified that information quality, source credibility, and trust emerged as crucial factors influencing the adoption of YouTube Vlogs for hotel booking among travelers. This study expanded the information adoption model by introducing a new element, specifically the inclusion of the construct of trust.

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The effect of emotional changes in composite reviews on consumers' information adoption from a dual perspective

Cited by 3 publications

References 61 publications

Additional reviews, perceived credibility and consumer online purchasing behavior: a study of university students in China

Additional reviews, perceived credibility and consumer online purchasing behavior: a study of university students in China

Text Mining Based Approach for Customer Sentiment and Product Competitiveness Using Composite Online Review Data

Evaluating the Influence of YouTube Vlogs on Hotel Booking Decisions

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