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We review the implications of the mobile technology for different stages of the consumer path to purchase including awareness, search, evaluation, store visit, and product choice. Real-time and location-specific access to information and products are identified as distinguishing characteristics of mobile devices. While the literature on digital marketing is well developed, knowledge of the effects on the consumer path to purchase in the presence of dynamic and location-specific information is still scarce. Path to purchase models need to recognize the central and powerful role of user-generated content. Better management of marketing resources would require models that connect investments in mobile marketing to sales, and also model the synergies among different digital and offline media. We conclude with a framework that connects mobile media impressions to product choice, in the presence of other marketing media, and consumer and firm feedback loops.

The study examines the potential moderating effects of repeating purchase cues and product knowledge on the relationship between the varying consistency of the review set and causal attribution. This study also investigates how causal attribution correlates with the perceived misleadingness of the review set.

A scenario-based experiment was conducted with 170 participants to explore the relationship between the consistency of the review set and causal attribution and how repeating purchase cues and product knowledge moderates this relationship.

Findings suggest that inconsistent review sets lead to more product (vs reviewer) attribution than consistent review sets. The repeating purchase cues mitigate the negative relationship between the consistency of the review set and product attribution, whereas product knowledge mitigates the positive relationship between the consistency of the review set and reviewer attribution. Furthermore, the results indicate that high product attribution and low reviewer attribution are associated with low perceived misleadingness.

This study is novel because it examines the moderating effects of repeating purchase cues and product knowledge on the relationship between the consistency of the review set and causal attribution. It adds to the literature by shedding light on the causal attribution process underlying the formation of perceived misleadingness of online reviews. The findings of this study provide valuable insights for managers on how to enhance the positive effects of consistent review sets and mitigate the negative effects of inconsistent review sets.

This research aims to examine the factors that influence customers' product return intentions and proposes that YouTube product reviews can mitigate customers' desire to return a product.

The proposed theoretical research model and hypothesized relationship were investigated using a quantitative process. This study used 302 data from Indonesian young adult respondents to examine the structural model, which was analyzed using the SmartPLS 3.2 software package.

The results show that YouTube product reviews, product fit uncertainty and customer satisfaction are the key determinants of customers' product return intention. Furthermore, the results show that the credibility of YouTube product reviews has a major impact on customers' familiarity with a product, satisfaction and the likelihood of returning goods to sellers.

In the e-commerce industry, increasing the use of YouTube product reviews will help businesses eliminate unnecessary product returns. Sellers are also encouraged to collaborate with YouTube producers to review specific products, which can benefit companies by raising brand awareness and gaining customer feedback. Furthermore, YouTube online product reviews can help consumers avoid having an unpleasant shopping experience that causes emotional reactions and lowers satisfaction.

Most research has not considered antecedents in observing the product return phenomenon; this study observes a prerequisite of consumer product returns (i.e. information asymmetry and product familiarity) and investigates the relationships between YouTube product reviews, customer satisfaction and product return intention.

The objective of this study is to examine the effects of pictures (consumer pictures vs. product pictures vs. no pictures) in online consumer reviews on product evaluation and to determine the mechanism and boundary conditions behind such effects.

The research consisted of three laboratory experiments.

The results showed that consumer pictures led to the most favorable product evaluation. Study 1 showed that persuasive effect was the mechanism behind the main effect. Study 2 showed that for problem-solving products, consumer pictures increased product evaluation significantly; for enhancing products, there was no significant difference of product evaluation among consumer pictures, product pictures and no picture. The results of Study 3 showed that for the unfamiliar brand, consumer pictures significantly enhanced product evaluation; for the highly familiar brand, there was no significant difference among consumer pictures, product pictures and no picture. The present research used persuasive effects to examine the mechanism behind the interaction effects.

The study provides managerial implications for online store owners about how to manage pictures in online reviews.

This study supplements the literature on online consumer reviews and enriches the study of effects of pictures.

The purpose of this study is to present a methodology for enhancing the quality and usefulness of online reviews for prospective customers to investigate how this contemporary form of instrumental support can be facilitated to strengthen customer-to-customer support.

This study develops an analytics framework with applications of machine learning models using customer review data from Amazon.com. Linear regression is commonly used for review helpfulness and sales prediction. In this study, Random Forest model is applied because of its strong performance and reliability. To advance the methodology, a custom script in Python is created to generate Partial Dependence Plots for intensive exploration of the dependency interpretations of review helpfulness and sales. The authors also apply K-Means to cluster reviewers and use the results to generate reviewer qualification scores and collective reviewer scores, which are incorporated into the review facilitation process.

The authors find the average helpfulness ratio of the reviewer as the most important determinant of reviewer qualification. The collective reviewer qualification for a product created based on reviewers’ characteristics is found important to customers’ purchase intentions and can be used as a metric for product comparison.

The findings of this study suggest that service improvement efforts can be performed by developing software applications to monitor reviewer qualifications dynamically, bestowing a badge to top quality reviewers, redesigning review sorting interfaces and displaying the consumer rating distribution on the product page, resulting in improved information reliability and consumer trust.

This study adds to the research on customer-to-customer support in the service literature. As customer reviews perform as a contemporary form of instrumental support, the authors validate the determinants of review helpfulness and perform an intensive exploration of its dependency interpretation. Reviewer qualification and the collective reviewer qualification scores are generated as new predictors and incorporated into the helpfulness-based review facilitation services.

Online customer reviews is an important information resource for product innovation. This study aims to investigate the impact of online customer reviews on iterative innovation of software products and the moderating roles of product complexity in the process of online reviews influencing product iterative innovation.

To empirically test the hypotheses, this paper built a panel data of 500 software products from 2019 to 2021 and applied Poisson regression analysis.

Empirically results reveal that both sentiment and quantity of online customer reviews have positive effects on iteration innovation of software products. In addition, the authors find that product complexity negatively moderates the relationship between online reviews and iterative innovation.

This study suggests that firms can acquire valuable information from customers’ online reviews for product iterative innovation and improvement. However, for high-complexity products, it may be difficult for enterprises to obtain useful information for iterative innovation from online reviews. On the other hand, this study provides a reference for firms to choose more useful online reviews from the perspective of sentiment.

This paper provides a new finding that there is a positive relationship between online customer reviews and iterative innovation of software products. Moreover, the authors also provide a deeper understanding of how online customer reviews affects iterative innovation by examining the moderating roles of product complexity.

The purpose of this study is to examine factors affecting the extent of consumers’ use of electronic word-of-mouth (eWOM), specifically online product reviews (OPRs), during their decision-making process. It also examines their motives for using OPRs.

The study uses an exploratory qualitative research methodology involving observation and free-flowing face-to-face interviews with consumers who have previously made a purchase online and who read OPRs during the decision-making process. An adaptation of the grounded theory method is used for collection, coding and data analysis.

Findings confirm previously uncovered motives for consumers’ use of OPRs. In addition, the findings suggest that two previously unidentified factors influence the extent of consumers’ use of OPRs: “decision-making drive” and “decision-making drag”. Decision-making drive is a mental momentum created when one or more factors that enhance decision-making readiness are present. This momentum tends to accelerate the decision-making process and shorten the information search process, leading to a reduction in the extent of OPR use. In contrast, decision-making drag is a mental resistance created when one or more factors that impede decision-making readiness are present. This resistance tends to decelerate the decision-making process and lengthen the information search process, leading to an increase in the extent of OPR use.

Focused on the pre-consumption phase of eWOM, between the stages of product need recognition and information search, this study is the first to identify decision-making drive and decision-making drag as additional psychological mechanisms affecting the extent of OPR use by consumers. For marketers, understanding these mechanisms has strategic marketing implications that can provide guidance to brands, websites and online review systems.

The conclusions of studies on the factors correlated with the perceived usefulness of online reviews are inconsistent due to differences in research perspectives, research objects, research methods and data types. This study conducted a meta-analysis to verify a proposed model of perceived usefulness to obtain general conclusions.

A meta-analysis was conducted to study the factors correlated with the perceived usefulness of online reviews based on 51 studies.

The results indicate that, with the exception of negative reviews, the order of relevance for the perceived usefulness of online reviews is as follows: the trust tendency of review readers, review replies, review depth, review pictures, reviewer trustworthiness, positive reviews, reviewer expertise, review time and reviewer information disclosure. Perceived usefulness was significantly positively correlated with purchase intention. Review time, positive reviews and negative reviews were also more significantly correlated with perceived usefulness for search products than for experiential products. Review depth, reviewer trustworthiness, reviewer expertise and purchase intention had greater positive correlations with perceived usefulness for experiential products than for search products.

This study proposes an extended information adoption model based on argument quality and source credibility. The model includes personal factors such as the trust tendency of review readers, constructs a theoretical model of the factors correlated with the perceived usefulness of online reviews and considers the moderating effects of product type.

The aim of this research is to theorize and demonstrate that analyzing consumers’ text product reviews using text mining can enhance the explanatory power of a product sales model, particularly for hedonic products, which tend to generate emotional and subjective product evaluations. Previous research in this area has been more focused on utilitarian products.

Our text clustering-based procedure segments text reviews into multiple clusters in association with consumers’ numeric ratings to address consumer heterogeneity in taste preferences and quality valuations and the J-distribution of numeric product ratings. This approach is novel in terms of combining text clustering with numeric product ratings to address consumers’ subjective product evaluations.

Using the movie industry as our empirical application, we find that our approach of making use of product text reviews can improve the explanatory power and predictive validity of the box-office sales model.

Marketing scholars have actively investigated the impact of consumers’ online product reviews on product sales, primarily focusing on consumers’ numeric product ratings. Recently, studies have also examined user-generated content. Similarly, this study looks into users’ textual product reviews to explain product sales. It remains to be seen how generalizable our empirical results are beyond our movie application.

Whereas numeric ratings can indicate how much viewers liked products, consumers’ reviews can convey why viewers liked or disliked them. Therefore, our review analysis can help marketers understand what factors make new products succeed or fail.

Primarily our approach is suitable to products subjectively evaluated, mostly, hedonic products. In doing so, we consider consumer heterogeneity contained in reviews through our review clusters based on their divergent impacts on sales.

This paper aims to investigate the influence of consumer reviews on the evaluation, post-experience, of products with a combination of sustainable, hedonic and utilitarian properties.

In the first instance, consumer reviews for organic and non-organic cosmetics posted on the French Web site beauté-test.com were analyzed. Second, a full-factorial two product types (organic and non-organic) × three reviews (positive, negative and no reviews) experiment was conducted. Sixty French women tested a beauty product and evaluated it on hedonic and utilitarian (ambiguous and non-ambiguous) properties. In a second experiment, 132 English-speaking students evaluated an herbal tea at home, along a full-factorial two product types (fair-trade and non-fair-trade) × three product properties (hedonic, utilitarian ambiguous and utilitarian non-ambiguous) × two reviews (negative review and no review) between-subject design.

First, consumers are significantly less influenced by reviews for hedonic products compared to utilitarian products. In particular, they rely on reviews when evaluating utilitarian ambiguous properties (e.g. anti-aging properties) which they find difficult to judge on their own. Second, consumers are more resistant to the persuasive effect of reviews when the product focus is on sustainable (organic or fair-trade) credentials, in particular when judging ambiguous properties.

This paper explores a topic neglected in the literature so far: the moderating role of product properties and sustainability, in particular, on consumers’ responses to persuasion and consumer reviews in the context of this paper. Its originality lies in the demonstration that consumers learn through product testing for hedonic and utilitarian unambiguous product properties and through consumer reviews for utilitarian ambiguous product properties. Additionally, it highlights the resistance of sustainable products (organic and fair-trade in this research) to negative product reviews.