Beyond the Lexical Sense of Online Reviews: The Role of Emoticons and Consumer Experience

2021 ◽  
Author(s):  
Emmanouela E Manganari ◽  
Evangelos Mourelatos ◽  
Efthalia Dimara
Keyword(s):  
Econometric Model ◽  
Prior Experience ◽  
Personal Characteristics ◽  
Online Reviews ◽  
Research Model ◽  
Consumer Experience ◽  
Online Consumer Reviews ◽  
Shopping Experience ◽  
Online Consumer

Abstract The present study focuses on the effect of emoticon use in online consumer reviews (OCRs) on consumers’ booking intention and the moderating effect of consumer personal characteristics. Consumers’ prior experience and their reliance on OCRs are embedded in the research model. A 2 × 2 (review valence * emoticon use) experimental study is designed, and an econometric model is used. Results show that the interaction between review valence and emoticons affect booking intention. Consumers with no prior experience are mainly affected by the cognitive aspects of their experience (i.e. review credibility and attitude toward the review) while experienced consumers are affected by the experiential aspects of booking process (i.e. entertainment, satisfaction and social influence). Consumers that rely on OCRs are affected by emoticons while consumers without review reliance are affected by emoticons only in the case of positive reviews. The personalization of websites and the provision of a focused list of emoticons can be adopted by managers to enhance OCRs effectiveness and the online shopping experience as a whole.

scholarly journals Understanding and Encouraging Online Reviewing With a Selection-Based Review System

2019 ◽  
Vol 31 (5) ◽  
pp. 446-464
Author(s):  
Rowanne Fleck ◽  
Benjamin R Cowan ◽  
Eirini Darmanin ◽  
Yixin Wang
Keyword(s):  
Cost Benefit ◽  
Online Reviews ◽  
Review System ◽  
Personal View ◽  
Trade Off ◽  
Consumer Reviews ◽  
Online Consumer Reviews ◽  
Mobile Interface ◽  
Online Consumer ◽  
The Cost

Abstract Online consumer reviews are important for people wishing to make purchases online. However, not everyone contributes online reviews. This paper looks at consumer motivations of reviewing and rating behaviour in order to motivate the design of a mobile interface for online reviewing. An interview study found that people tend to contribute reviews and ratings based on their perception of whether they would be helpful or not to others as well as their own personal view of the usefulness of reviews and ratings when buying products. There also seems to be a cost-benefit trade-off that influences people’s decisions to review and rate: people tend to make a decision based on the perceived value of that review or rating to the community against the effort and costs of contributing. A mobile interface was designed that was intended both to reduce the cost of leaving reviews and to increase the perception of the usefulness of the reviews to others. An initial evaluation of this reviewing interface suggests that it could encourage more people to leave reviews.

The Influence of Authenticity of Online Reviews on Trust Formation among Travelers

2019 ◽  
Vol 59 (5) ◽  
pp. 763-776 ◽  
Author(s):  
Minseong Kim ◽  
Jihye Kim
Keyword(s):  
Behavioral Intention ◽  
Information Source ◽  
Online Reviews ◽  
Research Model ◽  
Affective Trust ◽  
Trust Formation ◽  
Review Management ◽  
Online Comments ◽  
Decision Making Processes

Travelers have increasingly used mega review sites as an information source during the decision-making processes. This study focuses on the significant role of the authenticity of online reviews on mega review sites in formulating travelers’ behavioral intention as well as trust toward both websites and their service (i.e., destinations). Extending trust transfer theory, this study aims to formulate a research model and investigate associations among three aspects of trust (i.e., cognitive and affective trust toward mega review sites and trust toward destinations the websites recommend) to predict travelers’ behavioral intention (e.g., purchase). The empirical results indicate the significant roles of perceived authenticity of online comments and trust in the context of online tourism. This study provides some implications for online review management among website administrators.

Online Shopping Experience

2004 ◽  
pp. 15-44 ◽  
Author(s):  
Yi M. Guo
Keyword(s):  
Influencing Factors ◽  
Web Sites ◽  
Online Shopping ◽  
Individual Characteristics ◽  
Consumer Experience ◽  
Preliminary Results ◽  
Factors Influencing ◽  
Shopping Experience ◽  
Research Questions ◽  
Online Consumer

In this chapter, a model of online shopping experience is proposed to unify previous works of online consumer experience. Online shopping experience (OSE) is the interaction between shoppers and commercial web sites. It consists of physical, cognitive, and affective activities, and in-progress responses. Factors influencing shopping experience include individual characteristics of shoppers, characteristics of stores and commercial web sites, characteristics of products and shopping task, and other contextual factors. The outcomes of shopping experience have been studied in many ways. Based on this model, series of research questions can be asked to examine relationships between components of shopping experience and influencing factors, and between shopping experience and shopping outcomes. Preliminary results of a study are reported to illustrate the usefulness of the concept of online shopping experience.

scholarly journals The influence of e-word-of-mouth on hotel occupancy rate

2016 ◽  
Vol 28 (9) ◽  
pp. 2035-2051 ◽  
Author(s):  
Giampaolo Viglia ◽  
Roberta Minazzi ◽  
Dimitrios Buhalis
Keyword(s):  
Critical Role ◽  
Online Reviews ◽  
Three Dimensions ◽  
Occupancy Rate ◽  
Consumer Reviews ◽  
Content Type ◽  
Online Consumer Reviews ◽  
Online Consumer ◽  
Occupancy Rates ◽  
The Impact

Purpose Online consumer reviews have become increasingly important for consumer decision-making. One of the most prominent examples is the hotel industry where consumer reviews on websites, such as Bookings.com, TripAdvisor and Venere.com, play a critical role in consumers’ choice of a hotel. There have been a number of recent studies analyzing various aspects of online reviews. The purpose of this paper is to investigate their effects in terms of hotel occupancy rates. Design/methodology/approach This paper measures through regression analysis the impact of three dimensions of consumer reviews (i.e. review score, review variance and review volume) on the occupancy rates of 346 hotels located in Rome, isolating a number of other factors that might also affect demand. Findings Review score is the dimension with the highest impact. The results suggest that after controlling for other variables, a one-point increase in the review score is associated to an increase in the occupancy rate by 7.5 percentage points. Regardless the review score, the number of reviews has a positive effect, but with decreasing returns, implying that the higher the number of reviews, the lower the beneficial effect in terms of occupancy rates is. Practical implications The findings quantify the strong association of online reviews to occupancy rates suggesting the use of appropriate reputational management systems to increase hotel occupancy and therefore performance. Originality/value A major contribution of this paper is its comprehensiveness in analyzing the relation between online consumer reviews and occupancy across a heterogeneous sample of hotels.

scholarly journals Distribution characteristics of star ratings in online consumer reviews

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
R. Venkatesakumar ◽  
Sudhakar Vijayakumar ◽  
S. Riasudeen ◽  
S. Madhavan ◽  
B. Rajeswari
Keyword(s):  
Online Reviews ◽  
Online Review ◽  
Online Retailing ◽  
Consumer Reviews ◽  
Content Type ◽  
Product Categories ◽  
Online Consumer Reviews ◽  
Online Retailers ◽  
Online Consumer ◽  
Analyse Data

Purpose The star rating summarises the review content and conveys the message faster than other review components. Star ratings influence helpfulness of the reviews, and extreme reviews are considered as less helpful in the decision process. However, literature has rarely addressed variations in star ratings across product categories and variations between two online retailers. In this paper, the authors have compared the distribution of star ratings across 11 products and among the retailers. Design/methodology/approach Online reviews for 11 product categories have collected, and the authors compared the distribution of star ratings across 11 products and retailers. Correspondence analysis has been applied to show the association between star ratings and product categories for the e-retail firms. Findings The Amazon site contains proportionately more number of 1-star rated reviews than Flipkart. In Amazon reviews, few product categories are closely associated with 1-star and 2-star reviews, whereas no product categories are closely associated with 1-star and 2-star reviews in Flipkart reviews. The results indicate two distinct communication strategies followed by the firms in managing online consumer reviews. Research limitations/implications The authors did not analyse data across demographic details because of access restriction policies of the websites. Practical implications Understanding the distribution of review characteristics will improve the consumer’s decision-making ability and using online review content judiciously. Social implications This study’s results show significant insights on online retailing by providing cues in using shopping sites and online review characteristics of two prominent retailers. Originality/value This paper has brought out a distinct distribution pattern of online review between Amazon and Flipkart. Amazon allows a higher degree of negative contents, whereas Flipkart allows more number of positive reviews.

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