scholarly journals Differential Effects of the Valence and Volume of Online Reviews on Customer Share of Visits: The Case of US Casual Dining Restaurant Brands

2020 ◽  
Vol 12 (13) ◽  
pp. 5408 ◽  
Author(s):  
Jooa Baek ◽  
Yeongbae Choe
Keyword(s):  
Online Reviews ◽  
Purchase Decisions ◽  
Check Size ◽  
Differential Effects ◽  
Customer Reviews ◽  
Casual Dining ◽  
Online Customer Reviews ◽  
Casual Dining Restaurant ◽  
Source Of Information ◽  
The Ideal

Online customer reviews increasingly influence customer purchase decisions. Indeed, many customers have highlighted the significance of online reviews as an influential source of information. This study reports an investigation of the differential effects of online reviews, such as valence and volume, on the customer share of visits. Our findings suggest that valence (i.e., star rating) had more effect, giving a higher average check size to restaurants on the share of visits, while number reviews (volume) did not drive the share of visits to restaurants regardless of the average check size. Therefore, the ideal for casual dining restaurant brands would be to manage highly positive ratings to retain their customers.

Sentimental Analysis of Online Reviews Using Fuzzy Sets and Rough Sets

2017 ◽  
pp. 376-394
Author(s):  
Anuradha Jagadeesan ◽  
Amit Patil
Keyword(s):  
Fuzzy Sets ◽  
Sentiment Analysis ◽  
Rough Sets ◽  
Opinion Mining ◽  
Online Reviews ◽  
Purchase Decisions ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Excellent Source ◽  
The Web

With the increased interest of online users in E-commerce, the web has become an excellent source for buying and selling of products online. Customer reviews on the web help potential customers to make purchase decisions, and for manufacturers to incorporate improvements in their product or develop new marketing strategies. The increase in customer reviews of a product influence the popularity and the sale rate of the product. This lead to a very important question about the analysis of the sentiments (opinions) expressed in the reviews. As such internet does not have any quality control over customer reviews and it could vary in terms of its quality. Also the trustworthiness of the online reviews is debatable. Sentiment Analysis (SA) or Opinion Mining is the computational analysis of opinions, sentiments, emotions and subjectivity of text. In this chapter, we take a look at the various research challenges and a new dimension involved in sentiment analysis using fuzzy sets and rough sets.

A Systematic Methodology Based on Word Embedding for Identifying the Relation Between Online Customer Reviews and Sales Rank

2018 ◽  
Vol 140 (12) ◽  
Author(s):  
Dedy Suryadi ◽  
Harrison Kim
Keyword(s):  
Online Reviews ◽  
Word Embedding ◽  
Data Sets ◽  
Alternative Evaluation ◽  
Customer Reviews ◽  
Product Features ◽  
Online Customer Reviews ◽  
Dependency Tree ◽  
Systematic Methodology ◽  
Source Of Information

In the buying decision process, online reviews become an important source of information. They become the basis of evaluating alternatives before making purchase decision. This paper proposes a methodology to reveal one of the hidden alternative evaluation processes by identifying the relation between the observable online customer reviews and sales rank. This methodology applies a combined approach of word embedding (word2vec) and X-means clustering, which produces product-feature words. It is followed by identifying sentiment words and their intensity, determining connection of words from dependency tree, and finally relating variables from the reviews to the sales rank of a product by a regression model. The methodology is applied to two data sets of wearable technology and laptop products. As implied by the high predicted R-squared values, the models are generalizable into new data sets. Among the interesting findings are the statements of problems or issues of a product are related to better sales rank, and many product features that are mentioned in the review title are significantly related to sales rank. For product designers, the significant variables in the regression models suggest the possible product features to be improved.

Automated Keyword Filtering in LDA for Identifying Product Attributes from Online Reviews

2020 ◽  
pp. 1-10
Author(s):  
Junegak Joung ◽  
Harrison M. Kim
Keyword(s):  
Product Design ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Previous Method ◽  
Product Attributes ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Dirichlet Allocation

Abstract Identifying product attributes from the perspective of a customer is essential to measure the satisfaction, importance, and Kano category of each product attribute for product design. This paper proposes automated keyword filtering to identify product attributes from online customer reviews based on latent Dirichlet allocation. The preprocessing for latent Dirichlet allocation is important because it affects the results of topic modeling; however, previous research performed latent Dirichlet allocation either without removing noise keywords or by manually eliminating them. The proposed method improves the preprocessing for latent Dirichlet allocation by conducting automated filtering to remove the noise keywords that are not related to the product. A case study of Android smartphones is performed to validate the proposed method. The performance of the latent Dirichlet allocation by the proposed method is compared to that of a previous method, and according to the latent Dirichlet allocation results, the former exhibits a higher performance than the latter.

The Relationship between Online Reviews, Brand Trust, and Willingness to Buy

2015 ◽  
pp. 139-161 ◽  
Author(s):  
V. Cheng ◽  
J. Rhodes ◽  
P. Lok
Keyword(s):  
Decision Making ◽  
Online Reviews ◽  
Mediating Effect ◽  
Consumer Decision Making ◽  
Brand Trust ◽  
Purchasing Decisions ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Willingness To Buy ◽  
The Relationship

This chapter investigates how online customer reviews affect consumer decision-making (willingness to buy) during their first purchase of services or products using brand trust as a mediating variable. A brief literature review, rationale and significance, and methodology are discussed, and a conceptual framework based on the relationships between the stated variables is adopted in this empirical study to demonstrate linkages and insights. The findings demonstrate that the “reliability dimension” of brand trust had a mediating effect on online customer reviews' valence to willingness to buy, while the “intentionality dimension” of brand trust had little effect. Furthermore, the findings demonstrate that online customer reviews generated by in-group and out-group reviewers have little effect on purchasing decisions (willingness to buy). These results suggest that marketers should focus more on managing negative online customer reviews that have a damaging effect on brand trust.

Measuring social influence from online traveler reviews

2019 ◽  
Vol 3 (1) ◽  
pp. 54-72 ◽  
Author(s):  
Laura A. Book ◽  
Sarah Tanford
Keyword(s):  
Social Influence ◽  
Design Methodology ◽  
Online Reviews ◽  
Purchase Decisions ◽  
Content Type ◽  
Customer Reviews ◽  
Informational Influence ◽  
Travel Decisions ◽  
Different Characteristics ◽  
Item Scale

Purpose The purpose of this paper is to develop a scale to measure normative and informational influence in online traveler reviews. Design/methodology/approach Through proper scale development techniques and a two-sample validation process, the resulting 2-factor, 11-item scale yields a valid and reliable measure of social influence. Findings The resultant scale provides a tool for researchers to investigate the process whereby different characteristics of online reviews influence travel decisions. Originality/value Customer reviews are prevalent and powerful sources of influence on travel decisions. However, it is unclear how social influence manifests in today’s online purchasing environment. For several decades, the domain of social influence has played an important role in the advancements of consumer behavior and hospitality/tourism research. In particular, normative and informational influences are applicable, since online reviews contain numerous informational and normative cues. These principles were formulated under much different conditions than today’s purchasing environment. This research provides a way to measure normative and informational influence in the online review environment, thus enhancing the understanding of how reviews influence purchase decisions.

scholarly journals Reading Between the Lines: Understanding Customer Experience With Disruptive Technology Through Online Reviews

2021 ◽  
pp. 183933492199948
Author(s):  
Jeandri Robertson ◽  
Caitlin Ferreira ◽  
Jeannette Paschen
Keyword(s):  
Text Analysis ◽  
Online Reviews ◽  
Customer Experience ◽  
Disruptive Technology ◽  
Word Choice ◽  
Emotional Tone ◽  
Customer Reviews ◽  
Brand Engagement ◽  
Online Customer Reviews ◽  
Computerized Text Analysis

A customer’s experience with a brand, as evidenced in online customer reviews, has attracted multidisciplinary scholarly attention. Customer experience plays an important role as an antecedent to brand engagement, brand adoption, and eventual brand loyalty. Thus, it is important for businesses to understand their customers’ experiences so that they can make changes as necessary. The COVID-19 pandemic has brought unprecedented changes to the business landscape, forcing businesses to move online, with many utilizing enterprise video conferencing (EVC) to maintain daily operations. To ensure efficient digitization, many turned to the online reviews of others’ experiences with EVC before engaging with it themselves. This research examined how the customer experience is portrayed through emotional tone and word choice in online reviews for the EVC platform Zoom. Using computerized text analysis, key differences were found in the emotional tone and word choice for low- and high-rated reviews. The complexity and emotionality expressed in reviews have implications on the usability of the review for others. The results from this study suggest that online customer reviews with a high rating express a higher level of expertise and confidence than low-rated reviews. Given the potential dissemination and impact, digital marketers may be well advised to first and foremost respond to online reviews that are high in emotional tone.

scholarly journals Online Customer Comments and their Impact on Consumer Buying Behavior: using Social Cognitive Theory to Understand Consumer Expectations and Media Influences

2019 ◽  
Vol 8 (2S10) ◽  
pp. 887-892
Keyword(s):  
Social Cognitive Theory ◽  
Social Cognitive ◽  
Word Of Mouth ◽  
Cognitive Theory ◽  
Online Reviews ◽  
Buying Behavior ◽  
Customer Reviews ◽  
Consumer Expectations ◽  
Online Customer Reviews ◽  
Consumer Buying Behavior

Many opportunities, with the help of web-based technologies, are provided to word-of-mouth communication. The method of communication of customers and sharing the product details with others is transformed by the immense utilisation of electronic commerce shopping communities. Until recently, the area of e-commerce shopping communities where buyers participate has been underexplored in the field of academic research. The online reviews provided by the customers exert a high impact on customers’ buying decisions while shopping on e-commerce websites and thus provides significance to the concept of word of mouth. The growing amount of literature covering various domains that emphasizes customers’ reviews online can be considered as a justification of this concept. The factors that affect continual intention of buying online and the extent, reciprocity and reputation of vendor creativity affect consumer expectations. This study provides a brief insight into online customer reviews and their impact on consumer buying behavior by using social cognitive theory. A conceptual framework showcasing the various factors affecting the perceptions and attitudes of consumers in the context of online reviews will be provided in the paper. This study is the first to apply social cognitive theory on online customer reviews and to study their impact on consumer expectations.

Does the length of a review matter in perceived helpfulness? The moderating role of product experience

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Han Jia ◽  
Sumin Shin ◽  
Jinfeng Jiao
Keyword(s):  
Online Reviews ◽  
Product Type ◽  
Online Review ◽  
Content Type ◽  
Level Of Involvement ◽  
Customer Reviews ◽  
Product Experience ◽  
Online Customer Reviews ◽  
Review Helpfulness ◽  
Product Ratings

PurposeThis paper aims to offer a framework explaining how product experience (i.e. think vs feel) and product involvement (high vs low) influence the helpfulness of online reviews. It also reexamined how online consumer review dimensions help to build online review helpfulness under different contexts.Design/methodology/approachData were collected using content analysis on 1,200 online customer reviews on 12 products from four categories to measure the relationships between online review dimensions and the helpfulness of reviews. The regression analysis and analysis of variance (ANOVA) were used to test the hypotheses.FindingsThe findings indicate that the effectiveness of length of a review is moderated by product type; for think products, longer reviews yield higher helpfulness. Furthermore, the level of consistency between individual review ratings and overall product ratings is associated with review helpfulness. The length of product descriptions and product ratings is moderated by the level of involvement. For products with high involvement, longer descriptions yield higher helpfulness.Originality/valueA conceptual connection to customer interaction is proposed by online customer reviews that vary by product type. The findings provide implications for online retailers to better manage online customer reviews and increase the value of product ratings.

Did You Read the Customer Reviews Before Shopping?

2020 ◽  
pp. 178-208
Author(s):  
Ayşegül Sağkaya Güngör ◽  
Çiğdem Tütüncü Özgen
Keyword(s):  
Emotional Attachment ◽  
Repurchase Intention ◽  
Online Retail ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Attachment Strength ◽  
Source Of Information

Online customer reviews are the most trustworthy source of information of consumers while determining the value of online retail platforms. They act to convince customers and serve the purpose of formation of trust and emotional attachment with the platform. This study reports the results of an experiment investigating the effects of online customer reviews on emotional attachment, trust, and repurchase intention while taking the previous emotional attachment strength into consideration. Results revealed that, depending on the previous attachment strength, both positive and negative reviews strongly affect emotional attachment. However, trust is only influenced by positive reviews. Besides, trust is a more durable construct compared to emotional attachment and is not subject to change easily. When the repurchase intention is investigated, only strongly attached consumers are affected by customer reviews.

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