Online Review Ratings Research Articles

온라인 리뷰가 매출에 미치는 영향력 분석: 텍스트기반 감성지수를 중심으로*

온라인 리뷰가 매출에 미치는 영향력 분석: 텍스트기반 감성지수를 중심으로*

How do online reviewers’ cultural traits and perceived experience influence hotel online ratings?

Purpose The purpose of this study is to examine the role and influence of online reviewers’ cultural traits and perceived experience on online review ratings of Russian hotels by taking a direct measurement approach. Design/methodology/approach The authors adopt an explanatory sequential research design consisting of two stages. In the first stage, based on a sample of almost 75,000 Booking.com online reviews covering hotels located in Moscow (Russia), this study examines quantitatively to what extent the cultural traits of online reviewers and hotel guests’ perceived experience in online reviewing affect online ratings also using censored regressions. In the second stage, it interprets the results in light of semi-structured interviews conducted with a convenience sample of managers. Findings Each of the Hofstede’s cultural dimensions (namely, individualism, masculinity, uncertainty avoidance and power distance) exerts a significantly negative influence on the hotel online ratings. More specifically, the higher the levels of individualism, masculinity, uncertainty avoidance and power distance, the lower the hotel’s online ratings. Reviewers’ perceived experience in online reviewing is negatively related to online ratings. Research limitations/implications The study’s findings bear relevant practical implications for hotel managers and online platform managers in countries that are not typically covered by online consumer behavior studies in hospitality such as Russia. From a theoretical viewpoint, this study contributes to cultural studies in hospitality management and marketing with a further development of the nascent research stream taking a direct measurement approach to the study of cultural influences on consumers’ behaviors. Furthermore, this study offers a better and in-depth understanding of the role of cultural traits on electronic word of mouth, as well as international market segmentation theory in online settings. Originality/value The conjoint exploration of the effects of cultural differences and perceived experience in online reviewing adds to the nascent research stream taking a direct measurement approach to the study of the Hofstede’s cultural dimensions on online consumers’ behaviors. The authors make multiple theoretical and methodological contributions, highlighting that online hospitality customers cannot be considered as one homogeneous mass. Instead, the application of Hofstede’s cultural dimensions allows identifying distinctively different online behaviors across international online customers: different online customer groups can be clustered into segments, as they display different online behaviors and give different online evaluations.

Does national culture explain consumers’ reliance on online reviews? Cross-cultural variations in the effect of online review ratings on consumer choice

Abstract Can national culture affect consumers’ reliance on online reviews? 82% of American adults said that they saw online reviews for new purchases ( Smith and Anderson, 2016 ). This paper takes a cultural approach to study how consumers engage in online reviews when they make purchase decisions. This study examined more than ten million transactions made on an online hotel-booking website by consumers’ nationality and five cultural dimensions. The results suggest that collectivism, femininity, uncertainty avoidance, and indulgence are positively associated with consumers’ reliance on online review ratings, while power distance tended to reduce the effect. Consumers’ reliance on online reviews was influenced by multivariate cultural values, and no single cultural value had a significant univariate effect. Consumers in Spain and Australia were most likely to rely on review ratings, and consumers in Germany and China were least dependent on online reviews.

온라인 리뷰 평점의 방향성과 분포의 모드수와 범위가 구매의도에 미치는 영향

온라인 리뷰 평점의 방향성과 분포의 모드수와 범위가 구매의도에 미치는 영향

Decision contamination in the wild: Sequential dependencies in online review ratings.

Current judgments are systematically biased by prior judgments. Such biases occur in ways that seem to reflect the cognitive system's ability to adapt to statistical regularities within the environment. These cognitive sequential dependencies have primarily been evaluated in carefully controlled laboratory experiments. In this study, we used these well-known laboratory findings to guide our analysis of two datasets, consisting of over 2.2 million business review ratings from Yelp and 4.2 million movie and television review ratings from Amazon. We explored how within-reviewer ratings are influenced by previous ratings. Our findings suggest a contrast effect: Current ratings are systematically biased away from prior ratings, and the magnitude of this bias decays over several reviews. This work is couched within a broader program that aims to use well-established laboratory findings to guide our understanding of patterns in naturally occurring and large-scale behavioral data.

<i>Online Review:</i> Indikator Penilaian Kredibilitas Online dalam <i>Platform E-commerce</i>

Online credibility, either for a company or a merchant, is an important thing that have to be considered in the era of e-commerce development. Online review and online rating are part of indicators that used to represent merchant or seller’s online credibility in e-commerce platform. The existence of online review and online rating in e-commerce platform may affect the prominence and interpretation aspects which is associated with online credibility. This is a conceptual paper which aims to describe the concept of online review and its relation with online credibility.
 
 

Online Ratings of the Patient Experience: Emergency Departments Versus Urgent Care Centers

Individuals increasingly use online rating platforms to rate and review hospitals. We seek to describe and compare publicly available online review content and ratings of emergency departments (EDs) and urgent care centers. We analyzed Yelp reviews of EDs and urgent care centers to identify topics most correlated with 1- and 5-star ratings. Latent DirichletAllocation, a method of identifying groups of co-occurring words in narrative text, was used to identify and label 25 topics across 1- and 5-star reviews of urgent care centers and EDs. Differential Language Analysis was then used to measure the correlation of these topics with 1- and 5-star reviews for urgent care centers and EDs. We analyzed 100,949 Yelp reviews, 16,447 from 1,566 EDs and 84,502 from 5,601 urgent care centers. There were significantly more 5-star urgent care center reviews (n=43,487; 51%) than 5-star ED reviews (n=4,437; 27%). Themes associated with 5-star reviews among EDs and urgent care centers were similar for comfort, professionalism, facilities, pediatric care, and staff interactions. Themes associated with 1-star reviews among EDs and urgent care centers were similar for communication, telephone experience, waiting, billing, pain management, and diagnostic testing. Themes unique to 5-star ED reviews included bedside manner, care for family members, and access. Themes unique to 5-star urgent care center reviews were based on recommendation and prescription refills. Themes unique to 1-star ED reviews were service and speed of care. Themes unique to 1-star urgent care center reviews were lack of confidence and reception experience. Understanding drivers for high and low online ratings and what patients value in their ED and urgent care center experiences offers insights for health systems and providers to improve acute care delivery. Patients' perspectives may become increasingly important as they seek care in the expanding urgent care markets.

Sistem Reputasi Penjual dalam Proses Pengambilan Keputusan Pembelian di Platform C2C E-commerce

This study discusses the process of purchase decision making which made through online transaction in customer to customer (C2C) e-commerce platform. Online review and online rating have been known as a part of electronic word of mouth which has an impact on buyer's purchase decisions. This study use Kotler and Keller's (2009) purchase making decision process to finds out the purchase decision making process which happens through C2C e-commerce. This study also aims to finds out how online reviews and online rating are used in purchase decision making process. This study uses post-positivistik paradigm with qualitative approach and case study strategy. Data were obtained from in-depth interview and literature studies. The results of this study show that the informations in online review and online rating can provide an overview of seller's reputation and form buyer's perception of products and services quality. The results also indicate that in the purchase making decisions process, there is a zero moment of truth phase. In this phase, buyers learn about the product or seller's reputation through the information that they got from online sources. One of the informations used in zero moment of truth is from online review and online rating.

Reviews’ length and sentiment as correlates of online reviews’ ratings

PurposeThe purpose of this paper is twofold: first, to identify and validate reviews’ length and sentiment as correlates of online reviews’ ratings; and second, to understand the emotions embedded in online reviews and how they associate with specific words used in such reviews.Design/methodology/approachA panel data set of customer reviews was collected for auto, life, and home insurance from January 2012 to December 2015 using a web scraping technique. Using a sentiment analysis approach, 1,584 reviews for the auto, home, and life insurance services of 156 insurance companies were analyzed.FindingsThe results indicate that, since 2013, consumers have generally had more negative emotions than positive ones toward insurance services. The results also show that consumer review sentiment correlates positively and review length correlates negatively with consumer online review ratings. Furthermore, a two-way ANOVA analysis shows that, in general, short reviews with positive sentiment are associated with high review ratings.Practical implicationsThe findings of this study provide service companies, in general, and insurance companies, in particular, with important guidelines that should be considered to increase consumers’ positive attitude toward their services.Originality/valueThis paper highlights the importance of sentiment analysis in identifying consumer reviews’ emotions and understanding the associations and interactions of reviews’ length and sentiment on online review rating, which can lead to improved marketing strategies.

Spatial heterogeneity of country-of-origin effects within a country: analysis of online review ratings in the US car market

We investigate spatial heterogeneity of country-of-origin effects (COEs) within a country and its determinants. Drawing on the literature of COEs and information economics, we maintain that COEs are heterogeneous across regions within a country, which bears important implications to better understand subnational heterogeneity of consumer preferences. We employ a geographically weighted regression model, a spatial analysis to estimate varying COEs across regions in the USA, and analyze online review ratings of US and foreign car bands in the US market during the 2008–2014 period. The results show that (1) COEs of car brands from Germany, Japan, Korea, and the UK are heterogeneous across regions in the USA; (2) geographic distance from the country-of-origin exerts negative influences on COEs; and (3) the proportion of population born in the country-of-origin positively influences COEs.

Impact of Average Rating on Social Media Endorsement: The Moderating Role of Rating Dispersion and Discount Threshold

This paper examines how a restaurant’s online review ratings affect consumers to endorse deal vouchers sold by the restaurant via social media before they redeem the vouchers. While the effect of the average of review ratings is straightforward, we focus on examining how the effect is moderated by the dispersion of review ratings and the discount threshold set for the group-buying deals. A comprehensive literature review suggests that a large rating dispersion can deliver two different messages to consumers (uncertainty in product quality and uniqueness of product taste) and thus may either positively or negatively moderate the effect of average rating on social media endorsement. Discount threshold may serve as a quality signal, reinforcing the effect of average rating. The empirical results show that the effect of average rating is greater when review ratings are more dispersed and the discount threshold is relatively large. The findings generate important managerial and research implications. The online appendix is available at https://doi.org/10.1287/isre.2017.0728 .

Price determinants of sharing economy based accommodation rental: A study of listings from 33 cities on Airbnb.com

The advent of the “sharing economy” challenges not only the business of hotel industry but also the theories and models based on the conventional hotel industry. A key dimension of the hospitality industry is pricing. The aim of this study is to identify the price determinants of sharing economy based accommodation offers in the digital marketplace. Specifically, a sample of 180,533 accommodation rental offers in 33 cities listed on Airbnb.com is investigated using ordinary least squares and quantile regression analysis. Twenty-five explanatory variables in five categories (host attributes, site and property attributes, amenities and services, rental rules, and online review ratings) are explored for the intricacies of the relationships between pricing and its determinants.

Determinants of Online Word-of-Mouth: Evidence from Durable Goods Market

Online reviews became one of the most effective tools that influence consumer behavior and level of sales. In this paper we consider determinants of online review rating. The study is based on more than three thousand online reviews from Russian consumers of durable goods (electronics and home appliances). It was found that there is a significant difference in the level of influence between new and old reviews. Moreover, the higher the total numbers of reviews available, the higher the number of reviews taken into account by a particular consumer. Another finding is that both average online rank and price of a product are positively correlated with variance of reviews on that product. Based on the differences in the effectiveness of information transmission about quality of products, products were divided into two categories: experience products and search products. At the last stage, we provide an econometric model that allows to explain not only dynamic but also the direction of consumers’ rank of a product.

Predicting hotel review helpfulness: The impact of review visibility, and interaction between hotel stars and review ratings

The tourism industry has been strongly influenced by electronic word-of-mouth (eWOM) in recent years. Currently, there are only limited studies available that look into hotel review helpfulness. This present study addresses three hidden assumptions prevalent in online review studies: (1) all reviews are visible equally to online users, (2) review rating (RR) and hotel star class (HSC) affect review helpfulness individually with no interaction, and (3) characteristics of reviews and reviewer status stay constant.Four categories of input variables were considered in the present study: review content, sentiment, author, and visibility. Our findings confirmed the interaction effect between HSC and RR. The data set was sub-divided into eight subsets as a result. Three review visibility indicators (including days since a review was posted, days since a review has remained on the home page, and number of reviews with the same rating at the time a review was written) had a varying and strong effect on review helpfulness. The model performance was greatly improved after taking account of review visibility features, the interaction effect of HSC and RR, and a more accurate measurement of variables. Model tree (M5P) outperformed linear regression and support vector regression as it better modeled the interaction effect.

The influence of recent hotel amenities and green practices on guests’ price premium and revisit intention

This study examines the influence of hotels’ green practices, recent amenities, and traditionally salient attributes on customers’ overall online evaluation, revisit intention and hotel performance. The researchers acquired data from more than one hundred US hotels located across different states with the assistance of an international hotel chain. In order to demonstrate the incremental information content of recently-adopted hotel amenities and levels of green initiatives, the study compared two extended models with the basic model, which incorporates only salient attributes such as cleanliness, location, room, service and value. The findings indicate that the availability of recently-added amenities such as free Wi-Fi, pet boarding, free self-parking, multilingual staff, and airport transportation, as well as green practice initiatives, have a strong, incremental predictive power in explaining guests’ overall online review ratings, price premium and revisit intention.

The impact of online user reviews on cameras sales

PurposeThe purpose of this research is to help better understand the impact of online user reviews on sales of search goods.Design/methodology/approachThis research is based on digital camera sales data collected from amazon.com and two studies are included in this research. The first study is based on a static model and sample data from one time stamp. The second study is based on two sample data collected from two different time stamps, and a dynamic model is proposed.FindingsThe results from the first study reveal that the average online customer review, the number of online reviews, the price and the camera's physical properties such as the number of pixels and the optimal zoom number (but not LCD screen size) have significant influence on digital camera sales. The results from the second study show that the sales from the previous period are an important indicator for future sales. In addition, change in price, change in average online review rating and change in the total number of online reviews are all significantly associated with future sales.Research limitations/implicationsThe research reveals that there is a significant relationship between the online user review and sales of search goods, and the influence of online user reviews on search goods sales is different from that on experience goods. It also recognizes that the product specifications influence the sales of search goods. In addition, the research on search goods shows that price at the specific time and price changes are significant factors affecting sales.Practical implicationsThe research indicates that retailers should provide channels for, and encourage, customer online reviews for search goods to improve sales. It is also beneficial for online retailers to provide detailed product attributes to help their customers make the purchase decision. Carefully designed and executed price promotions could also be effective ways to improve sales of searchable goods.Originality/valueThis study is one of the first attempts to investigate the impact of online user reviews on sales of search goods.