A Meta-Analysis on the Determinants of Online Review Helpfulness

Online consumer reviews can help customers decrease uncertainty and risk faced in online shopping. However, information overload and conflicting comments in online reviews can get consumers confused. Therefore, it is important for both researchers and practitioners to understand the characteristics of helpful reviews. But studies examining the determinants of perceived review helpfulness produce mixed findings. We review extant research about the determinant factors of perceived helpfulness. Conflicting findings exist for six review related factors, namely review extremity, review readability, review total votes, linear review rating, quadratic review rating, and review sentiment. We conduct a meta-analysis to reconcile the contradictory findings on the influence of review related factors over perceived review helpfulness. The meta-analysis results confirm that review extremity, readability, total votes, and positive sentiment have a negative influence on helpfulness, but review rating is positively related to helpfulness. We also examine those studies whose findings are contradictive with the meta-analysis results. Measure discrepancy and reviewed product type are the two main reasons why mixed findings exist in extant research

Traditional and Health-Related Philanthropy: The Role of Resources and Personality

I study the relationships of resources and personality characteristics to charitable giving, postmortem organ donation, and blood donation in a nationwide sample of persons in households in the Netherlands. I find that specific personality characteristics are related to specific types of giving: agreeableness to blood donation, empathic concern to charitable giving, and prosocial value orientation to postmortem organ donation. I find that giving has a consistently stronger relation to human and social capital than to personality. Human capital increases giving; social capital increases giving only when it is approved by others. Effects of prosocial personality characteristics decline at higher levels of these characteristics. Effects of empathic concern, helpfulness, and social value orientations on generosity are mediated by verbal proficiency and church attendance.

Moderating Effects of Time-Related Factors in Predicting the Helpfulness of Online Reviews: a Deep Learning Approach

Given the importance of online reviews, as shown by extensive research, we address the problem of predicting the helpfulness of online product reviews by developing a comprehensive research model guided by the theoretical foundations of signaling and social influence theories. We use review order and time interval to incorporate the moderating effects of the time-related variable on the reviewer’s valuation of products and the related details they provide. Applying deep learning techniques in text processing and model building on a dataset of 239297 reviews, the empirical findings represent strong support of the proposed approach and show its superior performance in predicting review helpfulness compared to current approaches. This research contributes to theory by analyzing online reviews from the points of two well-known information processing theories and contributes to practice by developing a model to sort the newly posted reviews

Do same-level review ratings have the same level of review helpfulness? The role of information diagnosticity in online reviews

This research examines whether the written contents of online reviews can generate systematic differences in the review’s perceived helpfulness even with identical ratings. In addition, this research explores which underlying psychological mechanism creates the systemic differences related to helpfulness. Specifically, the results from our two experiments demonstrate that, when an online hotel review has a positive rating, written contents containing both positive and negative information is perceived as more helpful than reviews with only positive written content. In contrast, when an online hotel review has a negative rating, written contents that contain only negative information is perceived as more helpful than reviews with written content containing both positive and negative information. Importantly, our study shows that the degree of information diagnosticity in online reviews behaves as an underlying psychological mechanism in the process. Our findings not only contribute to the extant literature but also provide useful insights and practical implications for travel websites

What Makes Consumer Perception of Online Review Helpfulness: Synthesizing the Past to Guide Future Research

A growing body of academic research has aimed to investigate the helpfulness of online customer reviews (OCRs) given their prevalence and the need to better understand their appraisal mechanisms. However, past studies have applied varied methods and reported conflicting findings. This study aims to improve the understanding of the contributors to OCR helpfulness by synthesizing past studies on the topic. Based on a systematic literature review, a summary of the precursors to OCR helpfulness is provided. We decipher both the consistent and conflicting results and discuss the possible explanations for these mixed findings. By summarizing past studies, the review also points out possible directions for future research

En studie av karakteristikker som gjør produktomtaler hjelpsomme

Online product reviews are an important source of information that facilitates the consumer in the purchase decision process. This study investigates the correlation between three review characteristics and the perceived helpfulness of online reviews. These variables are founded in the theoretical background of information economics. Drawing on the theoretical foundation of information economics these variables are then tested by the product types provided from this theory, namely search goods and experience goods. An analysis of 120 reviews from three different website across four products indicated that the most significant correlation existed between helpfulness and review length. Review timeliness proved to have an inconsequential effect on helpfulness, while the effect of star rating was dependent on product type. Correlations are then discussed in greater detail, after which a theoretical and practical implications are mentioned. Lastly limitations and future research directions are evaluated and suggested.Online product reviews are an important source of information that facilitates the consumer in the purchase decision process. This study investigates the correlation between three review characteristics and the perceived helpfulness of online reviews. These variables are founded in the theoretical background of information economics. Drawing on the theoretical foundation of information economics these variables are then tested by the product types provided from this theory, namely search goods and experience goods. An analysis of 120 reviews from three different website across four products indicated that the most significant correlation existed between helpfulness and review length. Review timeliness proved to have an inconsequential effect on helpfulness, while the effect of star rating was dependent on product type. Correlations are then discussed in greater detail, after which a theoretical and practical implications are mentioned. Lastly limitations and future research directions are evaluated and suggested

What drives the helpfulness of online reviews? A deep learning study of sentiment analysis, pictorial content and reviewer expertise for mature destinations.

User-generated content (UGC) is a growing driver of destination choice. Drawing on dual-process theories on how individuals process information, this study focuses on the role of central and peripheral information processing routes in the formation of consumers’ perceptions of the helpfulness of online reviews. We carried out a two-step process to address the perceived helpfulness of user-generated content, a sentiment analysis using advanced machine-learning techniques (deep learning), and a regression analysis. We used a database of 2,023 comments posted on TripAdvisor about two iconic Venetian cultural attractions, St. Mark’s Square (an open, free attraction) and the Doge’s Palace (a museum which charges an entry fee). Following the application of deep-learning techniques, we first identified which factors influenced whether a review received a “helpful” vote by means of logistic regression. Second, we selected those reviews which received at least one helpful vote to identify, through linear regression, the significant determinants of TripAdvisor users’ voting behaviour. The results showed that reviewer expertise is an influential factor in both free and paid-for attractions, although the impact of central cues (sentiment polarity, subjectivity and pictorial content) is different in both attractions. Our study suggests that managers should look beyond individual ratings and focus on the sentiment analysis of online reviews, which are shown to be based on the nature of the attraction (free vs. paid-for)

A Novel Approach to Predict the Helpfulness of Online Reviews

Online reviews help consumers reduce uncertainty and risks faced in purchase decision making by providing information about products and services. However, the overwhelming amount of data continually being produced in online review platforms introduce a challenge for customers to read and judge the reviews. This research addresses the problem of misleading and overloaded information by developing a novel approach to predict the helpfulness of online reviews. The proposed approach in this study, first, clusters reviews using reviewer-related, and temporal factors. It then uses review-related factors to predict online review helpfulness in each cluster. Using a sample of Amazon.com reviews, the empirical findings offer strong support to the proposed approach and show its superior predictions of review helpfulness compared to earlier approaches. The outcomes of this study help customers in online shopping and assist online retailers in reducing information overload to improve their customers’ experience

Determinants of online review helpfulness that steer consumer purchase decision and their willingness to give review:an extended study in a cross-cultural context

Abstract. The increased use of social media and other online platforms have enabled consumers to communicate and discuss the products and services of brands with others. Consumers’ look for information in online reviews that assist them in informed purchase decisions. Previous literature has identified factors that influence consumers in adopting those online reviews, but whether consumers are willing to provide an online review after the purchase decision is not yet been studied previously. Another gap in the literate that is addressed is to base this study on output obtained from two countries. Therefore, our study is aimed at identifying factors that contribute to a consumer purchase decision and their willingness to give a review in a cross-cultural context. Our study aimed at restaurant reviews in Finland and Pakistan. Adopting and extending the Information Acceptance Model (IACM) proposed by Erkan and Evans (2016), that is developed by integrating Information Adoption Model (IAM) and related aspects of Theory of Reasoned Action (TRA). This study examines the influence of online review helpfulness factors on consumer purchase decision, consequently influencing them to give a review to others. We also aim to identify if review adoption directly influences consumers in providing online review without purchasing the product or service. The proposed model of our study was validated through Structural Equation Modelling by using Smart Partial Least Squares software. A questionnaire was adopted from earlier studies. The questionnaire was measured on a sample size of 104 from Finland and 141 from Pakistan. This study identified review adoption leading towards consumer purchase decision, whereas, onsumers’ willingness to give is not directly linked with their adoption of information, but it is a post-purchase process. The commonalities between the two countries depict the needs of information behind seeking online review information. If the required information is being provided to the customer through online reviews, it will lead to review adoption. Generally, review positiveness, review perceived informativeness and review quality were identified most important factors in consumers review adoption that leads consumers in choosing a restaurant and try the food there. Whereas, the general attitude of consumers towards online reviews was found to be the most exciting factors identified in Pakistan output. Consumers’ perception of online reviews encourages them to read online reviews, and they think that it is always a risk to try a restaurant without referring to online reviews. Pakistani consumers find online reviews useful, providing relevant information about the restaurants that help them in choosing the best restaurant

A big data exploration of the informational and normative influences on the helpfulness of online restaurant reviews

© 2020 Edith Cowan University With the proliferation of user generated online reviews, uncovering helpful restaurant reviews is increasingly challenging for potential consumers. Heuristics (such as “Likes”) not only facilitate this process but also enhance the social impact of a review on an Online Opinion Platform. Based on Dual Process Theory and Social Impact Theory, this study explores which contextual and descriptive attributes of restaurant reviews influence the reviewee to accept a review as helpful and thus, “Like” the review. Utilising both qualitative and quantitative methodologies, a big data sample of 58,468 restaurant reviews on Zomato were analysed. Results revealed the informational factor of positive recommendation framing and the normative factors of strong argument quality and moderate recommendation ratings, influence the generation of a reviewee “Like”. This study highlights the important filtering function a heuristic can offer prospective customers which can also result in greater social impact for the Online Opinion Platform