Where Do the Joneses Go on Vacation? Social Distance and the Influence of Online Reviews on Product Sales

2011 ◽  
Author(s):  
Leif Brandes ◽  
Ingmar Nolte ◽  
Sandra Nolte (Lechner)
Keyword(s):  
Social Distance ◽  
Online Reviews ◽  
Product Sales

scholarly journals Online Reviews and Product Sales: The Role of Review Visibility

2021 ◽  
Vol 16 (4) ◽  
pp. 638-669
Author(s):  
Miriam Alzate ◽  
Marta Arce-Urriza ◽  
Javier Cebollada
Keyword(s):  
Decision Making ◽  
Dynamic Models ◽  
Generalized Method Of Moments ◽  
Online Reviews ◽  
Consumer Decision Making ◽  
Product Sales ◽  
The Impact ◽  
The Relationship ◽  
The Empirical Analysis

When studying the impact of online reviews on product sales, previous scholars have usually assumed that every review for a product has the same probability of being viewed by consumers. However, decision-making and information processing theories underline that the accessibility of information plays a role in consumer decision-making. We incorporate the notion of review visibility to study the relationship between online reviews and product sales, which is proxied by sales rank information, studying three different cases: (1) when every online review is assumed to have the same probability of being viewed; (2) when we assume that consumers sort online reviews by the most helpful mechanism; and (3) when we assume that consumers sort online reviews by the most recent mechanism. Review non-textual and textual variables are analyzed. The empirical analysis is conducted using a panel of 119 cosmetic products over a period of nine weeks. Using the system generalized method of moments (system GMM) method for dynamic models of panel data, our findings reveal that review variables influence product sales, but the magnitude, and even the direction of the effect, vary amongst visibility cases. Overall, the characteristics of the most helpful reviews have a higher impact on sales.

Culturally Contingent Electronic Word-of-Mouth Signaling and Screening: A Comparative Study of Product Reviews in the United States and Japan

2018 ◽  
Vol 26 (2) ◽  
pp. 80-102 ◽  
Author(s):  
Hsin-Chen Lin ◽  
Manohar U. Kalwani
Keyword(s):  
Cultural Differences ◽  
Word Of Mouth ◽  
Online Reviews ◽  
Cross Cultural ◽  
Electronic Word Of Mouth ◽  
National Differences ◽  
Relative Product ◽  
Product Sales ◽  
The Relationship ◽  
Over Time

Electronic word of mouth (eWOM) is an important source of influence on consumer decision making, yet little is known about cross-cultural differences in both the occurrence of eWOM and the relationship between eWOM and sales. The authors draw on signaling theory to develop a conceptual model and assess the relationships between country and the occurrence of eWOM, as well as between online ratings and relative product sales according to country. Online reviews and sales rank data for books, CDs, and DVDs were collected from Amazon U.S. and Amazon Japan in 2009 and 2017. Results suggest cross-national differences in both the occurrence of eWOM (eWOM signaling) and the relationship between eWOM and relative product sales (eWOM screening). These national differences appear to change over time: some remain stable, some disappear, and others emerge. The proposed culturally contingent signaling and screening model may be adopted as a framework for future research on cross-cultural eWOM. The results also inform the literature on cultural change by suggesting that cultural differences in eWOM change in nuanced patterns over time.

EXPRESS: The Upside of Negative: Social Distance in Online Reviews of Identity-Relevant Brands

2022 ◽  
pp. 002224292210747
Author(s):  
Nailya Ordabayeva ◽  
Lisa A. Cavanaugh ◽  
Darren W. Dahl
Keyword(s):  
Social Distance ◽  
Field Data ◽  
Online Reviews ◽  
Conventional Wisdom ◽  
Theory And Practice ◽  
Positive Outcomes ◽  
Marketing Theory ◽  
Brand Preference ◽  
Underlying Process

Conventional wisdom in marketing emphasizes the detrimental effects of negative online reviews for brands. An important question is whether some firms could more effectively manage negative reviews to improve brand preference and outcomes. To address this question, our research examines how customers respond to online reviews of identity-relevant brands in particular, which have been overlooked in the online reviews literature. Eight studies (field data and experiments featuring consequential and hypothetical behaviors) show that negative online reviews may not be so detrimental for identity-relevant brands, especially when those reviews originate from socially distant (but not socially close) reviewers. This occurs because a negative review of an identity-relevant brand can pose a threat to a customer’s identity, prompting the customer to strengthen their relationship with the identity-relevant brand. To document the underlying process, we show that this effect does not emerge when the review is positive or the brand is identity-irrelevant. Importantly, we identify circumstances when negative reviews can actually produce positive outcomes (higher preference) for identity-relevant brands over no reviews or even positive reviews. By demonstrating the upside of negative reviews for identity-relevant brands, our findings have important implications for marketing theory and practice.

scholarly journals What Factors Influence Online Product Sales? Online Reviews, Review System Curation, Online Promotional Marketing and Seller Guarantees Analysis

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 3920-3931 ◽  
Author(s):  
Zhijie Zhao ◽  
Jiaying Wang ◽  
Huadong Sun ◽  
Yang Liu ◽  
Zhipeng Fan ◽  
...  
Keyword(s):  
Online Reviews ◽  
Review System ◽  
Product Sales ◽  
Promotional Marketing

Finding eWOM customers from customer reviews

2019 ◽  
Vol 119 (1) ◽  
pp. 129-147 ◽  
Author(s):  
Pengfei Zhao ◽  
Ji Wu ◽  
Zhongsheng Hua ◽  
Shijian Fang
Keyword(s):  
Evaluation Method ◽  
Online Reviews ◽  
Customer Segmentation ◽  
Product Reviews ◽  
Data Set ◽  
Content Type ◽  
Customer Reviews ◽  
Product Sales ◽  
The Relationship ◽  
New Framework

PurposeThe purpose of this paper is to identify electronic word-of-mouth (eWOM) customers from customer reviews. Thus, firms can precisely leverage eWOM customers to increase their product sales.Design/methodology/approachThis research proposed a framework to analyze the content of consumer-generated product reviews. Specific algorithms were used to identify potential eWOM reviewers, and then an evaluation method was used to validate the relationship between product sales and the eWOM reviewers identified by the authors’ proposed method.FindingsThe results corroborate that online product reviews that are made by the eWOM customers identified by the authors’ proposed method are more related to product sales than customer reviews that are made by non-eWOM customers and that the predictive power of the reviews generated by eWOM customers are significantly higher than the reviews generated by non-eWOM customers.Research limitations/implicationsThe proposed method is useful in the data set, which is based on one type of products. However, for other products, the validity must be tested. Previous eWOM customers may have no significant influence on product sales in the future. Therefore, the proposed method should be tested in the new market environment.Practical implicationsBy combining the method with the previous customer segmentation method, a new framework of customer segmentation is proposed to help firms understand customers’ value specifically.Originality/valueThis study is the first to identify eWOM customers from online reviews and to evaluate the relationship between reviewers and product sales.

scholarly journals Improving Product Sales on E-Commerce Websites Based on Reviewers Opinions

2020 ◽  
pp. 361-366
Author(s):  
S. Kayalvili ◽  
Muthu Priyadharshini. A
Keyword(s):  
Early Stage ◽  
Online Reviews ◽  
Page Rank ◽  
Product Lifetime ◽  
Three Stages ◽  
Product Sales ◽  
Behavior Characteristics ◽  
Source Of Information

Online reviews are the important source of information for users before selecting a product for making a decision. Reviews of product particularly early reviews have impact on the product sales. Study the behavior characteristics of early reviewers through their posted early reviews. At first divide the product lifetime into three stages- Early, majority and laggards. A person who posts reviews in early stage is considered as early reviewers. The Early reviewers are the first one who responds to the product at the beginning stage. Rating behaviors of early reviewers are predicted based on k-means with Page Rank.

scholarly journals Characterizing and Predicting Early Reviewers for Effective Product Marketing on E-commerce Websites

2020 ◽  
pp. 22-27
Author(s):  
S S S D Saichand Chebolu ◽  
P. L. Kiranmay
Keyword(s):  
Product Design ◽  
Real World ◽  
New Products ◽  
Online Reviews ◽  
Marketing Strategies ◽  
Purchase Decision ◽  
Behavioral Characteristics ◽  
Effective Product ◽  
Product Sales ◽  
Source Of Information

Before making an informed purchase decision, online reviews have become an important source of information for users. Early reviews of products often have a significant impact on subsequent product sales. For companies, it is important to find early reviewers, because their feedback can help the company adjust marketing strategies and improve product design, which ultimately leads to the success of new products. In this article, we take the initiative to study the behavioral characteristics of early commenter’s through their comments published on two large e-commerce platforms in the real world.

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