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

Assessment, Implication, and Analysis of Online Consumer Reviews: A Literature Review

The onset of e-marketplace, virtual communities and social networking has appreciated the influential capability of online consumer reviews (OCR) and therefore necessitate conglomeration of the body of knowledge. This article attempts to conceptually cluster academic literature in both management and technical domain. The study follows a framework which broadly clusters management research under two heads: OCR Assessment and OCR Implication (business implication). Parallel technical literature has been reviewed to reconcile methodologies adopted in the analysis of text content on the web, majorly reviews. Text mining through automated tools, algorithmic contribution (dominant majorly in technical stream literature) and manual assessment (derived from the stream of content analysis) has been studied in this review article. Literature survey of both the domains is analyzed to propose possible area for further research. Usage of text analysis methods along with statistical and data mining techniques to analyze review text and utilize the knowledge creation for solving managerial issues can possibly constitute further work. Available at: https://aisel.aisnet.org/pajais/vol9/iss2/4

An Experimental Investigation of Regulatory Orientation and Post-Choice Regret in Online Product Selection

Delivering product information effectively is fundamental to customer satisfaction and e-retailer success. In this study we examine the way in which the presentation of online customer reviews in peer endorsement systems (PES) impact perceptions of post-choice regret. The theory of Regulatory Orientation is used to account for individual differences in the way that online review content is processed. Results of a laboratory experiment comparing two peer endorsement system formats show that PES content presentation significantly impacts perceptions of post-choice regret. These perceptions are found to be strong influencers of user intention to use the PES. The study’s findings provide theoretical insights into how individual orientation and PES technology influence online decision-making with regards to product selection. As a result, the study has important implications for managers looking to get the most from investment in PES systems deployment and online web retail space design

How buyers perceive the credibility of advisors in online marketplace: review balance, review amount and misattribution

In an online marketplace, buyers rely heavily on reviews posted by previous buyers (referred to as advisors). The advisor’s credibility determines the persuasiveness of reviews. Much work has addressed the evaluation of advisors’ credibility based on their static profile information, but little attention has been paid to the effect of the information about the history of advisors’ reviews. We conducted three sub-studies to evaluate how the advisors’ review balance (proportion of positive reviews) affects the buyer’s judgement of advisor’s credibility (e.g., trustworthiness, expertise). The result of study 1 shows that advisors with mixed positive and negative reviews are perceived to be more trustworthy, and those with extremely positive or negative review balance are perceived to be less trustworthy. Moreover, the perceived expertise of the advisor increases as the review balance turns from positive to negative; yet buyers perceive advisors with extremely negative review balance as low in expertise. Study 2 finds that buyers might be more inclined to misattribute low trustworthiness to low expertise when they are processing high number of reviews. Finally, study 3 explains the misattribution phenomenon and suggests that perceived expertise has close relationship with affective trust. Both theoretical and practical implications are discussed

A text-mining based model to detect unethical biases in online reviews: a case-study of Amazon.com

The rapid growth of social media in the last decades led e-commerce into a new era of value co-creation between the seller and the consumer. Since there is no contact with the product, people have to rely on the description of the seller, knowing that sometimes it may be biased and not entirely truth. Therefore, reviewing systems emerged in order to provide more trustworthy sources of information, since customer opinions may be less biased. The problem was, once sellers realized the importance of reviews and their direct impact on sales, the need to control this key factor arose. One of the methods developed was to offer customers a certain product in exchange for an honest review. However, in the light of the results of some studies, these "honest" reviews were proved to be biased and skew the overall rating of the product. The purpose of this work is to find patterns in these incentivized reviews and create a model that may predict whether a new review is biased or not. To study this subject, besides the sentiment analysis performed on the data, some other characteristics were taken into account, such as the overall rating, helpfulness rate, review length and the timestamp when the review was written. Results show that some of the most significant characteristics when predicting an incentivized review are the length of a review, its helpfulness rate and the overall polarity score, calculated through VADER algorithm, as the most important sentiment-related factor.O rápido crescimento das redes sociais nas últimas décadas levaram o comércio electrónico a uma nova era de co-criação de valor entre o vendedor e o consumidor. Uma vez que não há contacto com o produto, os clientes têm de se basear na descrição do vendedor, mesmo sabendo que por vezes tal descrição pode ser tendenciosa e não totalmente verdadeira. Deste modo, surgiu um sistema de reviews com o propósito de disponibilizar um meio de informação de maior confiança, uma vez que se trata de partilha de informação entre clientes e por isso mais imparcial. No entanto, quando os vendedores se aperceberam da importância das "reviews" e o seu impacto direto nas vendas, surgiu a necessidade de controlar este fator chave. Uma das formas de o fazer foi através da oferta de determinados produtos em troca de "reviews" honestas. Contudo, à luz dos resultados de alguns estudos, foi demonstrado que estas "reviews" "honestas" são tendenciosas e enviesam a classificação geral do produto. O objetivo deste estudo foi o de encontrar padrões na forma como estas "reviews" incentivadas são escritas e criar um modelo para prever se uma determinada review seria enviesada. Para esta análise, além da análise de sentimentos realizada sobre os dados, outras características foram tidas em conta, tal como a classificação geral, a taxa de "helpfulness", o tamanho da "review" e a hora a que foi escrita. Os modelos gerados mostraram que as características mais importantes na previsão de parcialidade numa "review" são o tamanho e a taxa de utilidade e como característica sentimental mais relevante a pontuação geral da "review", calculada através do algoritmo VADER

Dreading and Ranting: The Distinct Effects of Anxiety and Anger in Online Seller Reviews

This paper explores effects of the emotions embedded in a seller review on its perceived helpfulness. Drawing on frameworks from the emotion and cognitive processing literatures, the authors propose that although emotional review content is subject to a well-known negativity bias, the effects of discrete emotions will vary, and that one source of this variance is perceptions of reviewers’ cognitive effort. We focused on the roles of two distinct, negative emotions common to seller reviews: anxiety and anger. In Study 1, actual seller reviews from Yahoo Shopping websites were collected to determine the effects of anxiety and anger on review helpfulness. In Study 2, an experiment was utilized to identify and explain the differential impact of anxiety and anger in terms of perceived reviewer effort. Our findings demonstrate the importance of examining discrete emotions in online word-of-mouth, and they also carry important practical implications for consumers and online retailers

Exploring determinants of attraction and helpfulness of online product review:a consumer behaviour perspective

To assist filtering and sorting massive review messages, this paper attempts to examine the determinants of review attraction and helpfulness. Our analysis divides consumers’ reading process into “notice stage” and “comprehend stage” and considers the impact of “explicit information” and “implicit information” of review attraction and review helpfulness. 633 online product reviews were collected from Amazon China. A mixed-method approach is employed to test the conceptual model proposed for examining the influencing factors of review attraction and helpfulness. The empirical results show that reviews with negative extremity, more words, and higher reviewer rank easily gain more attraction and reviews with negative extremity, higher reviewer rank, mixed subjective property, and mixed sentiment seem to be more helpful. The research findings provide some important insights, which will help online businesses to encourage consumers to write good quality reviews and take more active actions to maximise the value of online reviews

From Reviews to Revenues Website Design’s Role in Converting Opinions into Purchase Intentions

This research is to examine and investigate the relationship between online reviews, web design, and buying interest in the context of online commerce. The purpose of this study is to investigate and investigate the relationship between online reviews and web design. According to the findings of this research, which employs both qualitative and quantitative methods, user reviews posted on the internet are an important tool for reducing informational inequality. This, in turn, influences consumer trust, which in turn influences the decisions that consumers make when they are making purchases. Concerns, however, including a lack of trustworthiness and the potential of incorrect evaluations, argue for a stronger level of intervention. These concerns call for an intervention level that is stronger. In this context, web design appears as a powerful moderating factor, having the ability to improve purchase confidence and interest by giving an appealing appearance and clear navigation. This can be accomplished through the use of a website that is well-designed. The findings of this study have management implications that can assist the e-commerce business in the creation of customer-focused platforms, ethical content efforts, as well as technological and design breakthroughs that break new ground. These findings also provide a framework for additional research, such as an investigation into the consequences of phony reviews, studies that cross cultural divides, and the development of tools to manage reviews. In general, the findings of the study offer substantial new insights into the ways in which online evaluations and website design interact to form the experience of shopping online. In addition to this, the study offers direction for the development of best practices in this highly competitive and ever-changing sector of the economy