Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability

It is important to understand factors affecting the perceived online review helpfulness as it helps solve the problem of information overload in online shopping. Moreover, it is also crucial to explore the factors’ relative importance in predicting review helpfulness in order to effectively detect potential helpful reviews before they exert influences. Applying Elaboration Likelihood Model (ELM), this study first investigates the effects of central cues (review subjectivity and elaborateness) and peripheral cues (reviewer rank) on review helpfulness with readability as a moderator. Second, it also explores their relative predicting power using the machine learning technique. ELM is tested in online context and the results are compared between experience and search goods. Our results provide evidence that for both types of products review subjectivity can play a more significant role when the content readability is high. Furthermore, this study reveals that the dominant predictor is varied for different product types

Essays on the Influence of Review and Reviewer Attributes on Online Review Helpfulness: Attribution Theory Perspective

With the emergence of digital technology and the increasing availability of information on the internet, customers rely heavily on online reviews to inform their purchasing decisions. However, not all online reviews are helpful, and the factors that contribute to their helpfulness are complex and multifaceted. This dissertation addresses this gap in the literature by examining the antecedents that determine online review helpfulness using attribution theory. The dissertation consists of three essays. The first essay examines the impact of authenticity (review attribute) on review helpfulness, showing that the expressive authenticity of a review enhances its helpfulness. The second essay investigates the relationship between the reviewer attributes i.e., motivation, activity, and goals in online reviews. The study employs various machine learning techniques to investigate the influence of these factors on reviewers\u27 goal attainment. The third essay explores how the reviewer attributes are related to the helpfulness of online reviews. The dissertation offers significant theoretical and practical implications. Theoretically, the dissertation provides new insights into novel review and reviewer attributes. The study proposes a taxonomy of online reviews using means-ends fusion theory offering a framework for understanding the relationships between different components of online reviewer attributes and their contribution to the attainment of specific goals, such as emotional satisfaction. The study also highlights the importance of understanding the motivations and activities of online reviewers in predicting emotional satisfaction and the conditional effects of complaining behavior on emotional satisfaction. The findings inform review platform owners, business owners, reviewers, and prospective consumers in decision-making through helpful reviews. To review platform owners, the findings help segregate helpful reviews from the humongous number of reviews by determining the authenticity of the review. To business owners, the findings can help in understanding consumer behavior and taking necessary actions to provide better service to their customers. To reviewers, this dissertation can act as a guideline to write helpful reviews and to determine their helpfulness. Finally, to consumers or review readers, this dissertation provides an understanding of helpful reviews, thus allowing them to take product or service purchase decisions

How to Identify Tomorrow\u27s Most Active Social Commerce Contributors? Inviting Starlets to the Reviewer Hall of Fame

Social commerce contributors share their experiences of products and services, which is appreciated by consumers and online retailers. Since such user generated content is especially valuable for online retailers, they incentivize the most active contributors to provide further product reviews. Our paper aims to explore the question of which user characteristics can be used to identify contributors of valuable contents. This is especially relevant for newly registered users who have not extensively contributed yet. Drawing upon the literature on social information processing, signaling and communication theory, we explore how individual user characteristics published in the personal user profiles are associated with the actual contribution activity. Therefore, we analyze more than 30,000 user profiles from amazon.com. We find that information disclosure, emotiveness and problem-orientation are related to the contribution activity. Consequently, our results advance the understanding of who are the most active contributors and provide new implications for theory and practice

Online Video Reviews Helpfulness: Exploratory Study

Online reviews assist consumers in making an informed purchase decision and they became a trusted source for product information. This study aims to investigate online video reviews on YouTube to understand what are the most commonly reviewed products and what are the factors of YouTube video reviews which contribute to review helpfulness. We use qualitative and quantitative techniques as research methodologies. The results show that major categories reviewed on YouTube are video games, movies, and technology. Exploratory factor analysis revealed four important factors that may determine online video review helpfulness which are review popularity, comments, video information, and review depth. A conceptual model is introduced based on the factor analysis. The study has significant implications to research as it provides new insights regarding the role of online video reviews in purchases decision making process

Do Customers Perceive Reviews as Manipulated? A Warranting Theory Perspective

Online customer reviews proved to have an influence on customer’s purchase. However, most online reviews don’t always prove effective in guiding the purchase process, because of fake reviews. While e-commerce platforms do tend to incorporate ways to counter review manipulation, customer perception on review quality is more important. In this study we aim to understand the impression mechanism of online reviews. Using warranting theory, as theoretical lens we found that textual and review characteristics play a crucial role in forming an impression amongst the customers. Further, research suggest that higher contamination of reviews influence customers to perceive reviews less authentic

”Status Effect” in User-Generated Content: Evidence from Online Service Reviews

This paper provides first empirical evidence on the impact of reviewer status on the objectivity of his contributions in online communities. While previous research indicates that user-generated online reviews guide consumer decision making, little is known about drivers of the actual review generation process. By drawing on Functional Role Theory, we derive four research hypotheses covering the general research question of factors influencing the objectivity of service reviews. Utilizing a data sample covering 413,077 reviews posted over 12 years on www.TripAdvisor.com, we evaluate our research model. Our findings indicate that with increased user status, review objectivity increases. Thus, we contribute to theory by generalizing the so-called Popularity Effect to a multi-dimensional Status Effect , which is more widely applicable (e.g. settings without users-follow-users relationships). Furthermore, our results enable practitioners to find their most valuable content-producers

How and When Review Length and Emotional Intensity Influence Review Helpfulness: Empirical Evidence from Epinions.com

Although longer reviews are generally considered more helpful, no research has investigated whether “the more the better” also applies to the expression of emotions. This paper explores the distinct effects of review length and emotional intensity. We propose that, in contrast to review length, the intensity of emotions has a negative effect on review helpfulness, and that this effect only applies to positive emotions. Additionally, drawing on elaboration likelihood model and the literature on the social functions of emotions, we predict that the respective effects of review length and emotional intensity are moderated by reviewer trustworthiness and the difficulty of reading review content. To test these hypotheses, we collected a rich data set from Epinions.com - a leading provider of consumer reviews. Our findings reveal the importance of taking the intensity of emotions into consideration when evaluating review helpfulness, and the results carry important practical implications

First-Mover Advantage in Online Review Platform

While first-mover advantage has been widely studied at firm-level, our research focuses on individual-level first-mover advantage in online review platform. More specifically, we study whether early reviews receive higher proportion of helpful votes than later reviews. We try to answer three questions. (1) Does first-mover have advantage in online review platform? (2) Does the first-mover advantage differs across different types of reviewers? (3) Are reputation-seeking reviewers more likely to exploit the first-move advantage? We analyze the model using Zero-inflated Beta with the review data from Amazon.com. Our preliminary results show that early reviews are perceived more helpful than later reviews when controlling for total time being posted, review characteristics, and reviewer characteristics. The first-mover advantage is greater for high frequency reviewer than low frequency reviewer

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