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This study explores the link between additional reviews, credibility, and consumers’ online purchasing behavior.

We 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.

The 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.

Existing 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.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

The purpose of this study is to systematically review the existing literature on the concept of consumer sovereignty.

By leveraging a systematic literature review using a data-driven approach and quantitative methodology, this study provides an overview of the intellectual structure of consumer sovereignty research.

We explored the main topics that researchers tackled in consumer sovereignty research. Furthermore, we identified the theoretical lenses used in these studies. Finally, we proposed a research agenda to advance the scholarly debate on consumer sovereignty.

Some limitations should be acknowledged. First, the study only studied and analyzed consumer sovereignty articles that were published in peer-reviewed academic journals. Second, our review comprised journals identified in Scopus. Third, in this study, we have taken into account only articles written in English.

The authors expect the current review to significantly impact the identification of theories for the main trends in the academic analysis of consumer sovereignty and consumer behavior.

This study is the first to provide an integrated view of the body of consumer sovereignty. This review provides a strong contribution to consumer sovereignty literature by recommending a new research agenda for the concept of consumer sovereignty.

In online purchase for dietary supplements, due to the lack of professional advice from pharmacists, electronic word-of-mouth (eWOM) has become an important source of information for consumers to make purchase decisions. How can firms use eWOM resources to increase sales? The purpose of this paper is to provide practical methods for firms by exploring the effects of eWOM on sales and developing a sales prediction model based on eWOM.

The data came from 120 dietary supplements on Tmall.com. The authors extracted the product sales as dependent variable and 11 eWOM factors as independent variables. The multicollinearity was tested by using variance inflation factor and least absolute shrinkage and selection operator. The multiple linear regression was used to investigate the effects of eWOM on sales. Drawing on white- and black-box approaches, six models were developed. Comparing the root mean square error, the authors selected the optimal one as their target sales prediction model.

Product ratings, total reviews and favorites are positively and strongly associated with sales. Questions and additional reviews have negative effects on sales. The random forest model has the best prediction performance.

The research focuses on eWOM of dietary supplement. First, the authors show that easily accessible eWOM from online platforms can be used to evaluate effects and predict sales. Second, the authors introduce white- and black-box models through machine learning to assess eWOM. Firms could use the described models to foster their marketing initiatives.

The purpose of this study is to investigate the influence of credibility and information quality (IQ) of online food vloggers on consumer attitude and purchase intention towards street food consumption. It also examines the relationship between consumer attitude and purchase intention influenced by online food vlogger reviews in North India.

In order to evaluate the framework, primary data were gathered from 389 street food consumers located in Jammu, Chandigarh and Delhi – cities situated in northern India. The collected data were then subjected to analysis using the partial least squares-structural equation modeling (PLS-SEM) techniques.

The results indicate that the perceived value of street food, influenced by the credibility of food vloggers and the quality of information provided, has a positive impact on consumer attitude and purchase intention towards street food consumption. A positive impact of consumer attitude on the purchase and consumption of street food was also observed.

This research offers a thorough investigation into the elements that influence consumers' opinions regarding vloggers endorsements. The findings reveal that consumer's attitudes towards vloggers recommendations are mainly influenced by the quality of information provided, followed by credibility and the intention to make a purchase. Furthermore, this research is of significance to practitioners and academics interested in comprehending consumer behavior in the realms of tourism and food-related endeavors.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2024-0158

The wine market has witnessed intensified competition across all aspects. However, there is a limited systematic assessment of wine marketing literature. This study employs bibliometric and thematic content evaluation methodologies to present a comprehensive summary and trend of the existing research in wine marketing.

This integrates bibliometric and thematic content analytical techniques to trace the evolutionary arc of wine marketing research, underpinned by a framework-based evaluation - the 4 Ws (what, where, why, and how) to give a thorough overview of wine marketing literature. We draw on the thematic structure of wine marketing research by conducting keyword co-occurrence, thematic, social network, and cluster-based content analyses. A total of 291 publications from peer-reviewed journals, spanning the years 2001–2023, were examined in the present study.

The bibliometric analysis is used to determine the most notable journals, authors, nations, articles, and themes, thereby offering a comprehensive understanding of the publication trends within the sphere of wine marketing. Based on the findings, this study advocates a research agenda to extend further contributions to the field of wine marketing.

The study performs a comprehensive analysis of the publication patterns, influential authors, and emerging trends within the wine marketing research field. It provides a unique insight into the evolution and development of wine marketing as a scholarly discipline, facilitating future research directions and knowledge advancement.

Consumer behavior is evolving rapidly due to the increasing role of technology in daily life. Online food ordering has emerged as a key channel in this changing landscape. This paper investigates the relationships between online promotions, consumer skepticism, information sharing on social media and the intention to purchase food and beverages through online delivery services.

Measures were developed based on a review of existing literature. Data from 402 participants were analyzed using Structural Equation Modeling (SEM).

The study reveals that online promotions significantly impact consumers' sharing of restaurant posts. Additionally, consumer skepticism about online food sales affects both their sharing behavior and their intention to purchase online. Engagement in sharing restaurant posts online is a strong predictor of online food purchasing intentions.

The findings offer valuable insights for restaurant operators, policymakers and technology developers in the competitive online food delivery sector. They emphasize the importance of implementing innovative promotions and crafting appealing food presentations. These strategies can accelerate customer decision-making, attract new customers and contribute to market expansion and customer base sustainability.

This research provides significant insights for restaurant owners and contributes to the limited literature on online promotions, consumer skepticism and information sharing in the restaurant industry. It also lays the groundwork for future studies aimed at deepening understanding in this field.

Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

This study aims to identify which types of information quality influence purchase intentions the most in live streaming commerce and to examine the role of network size in this context.

We propose a model to investigate the correlation among the quality of different information in live streaming commerce, consumer trust, network size and purchase intention. An empirical analysis of 505 questionnaires was conducted by constructing a structural equation model.

The empirical findings indicate that information quality can directly enhance purchase intention and exert an indirect influence through the mediating factors of trust in products and streamers. Perceived network size positively moderates the relationship between information quality and trust in products. Of the five types of information, the quality of bullet-screen comments information is most important to consumers.

This study represents the first systematic analysis of how the quality of multiple types of information in live streaming commerce influences consumer trust and purchase intention, integrated within a unified framework. It uniquely introduces network size as a moderating variable, offering both theoretical insights and practical guidance for balancing information quality with network size in live streaming commerce environments.

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.