scholarly journals The Effects of Online Information on E-Book Pricing Strategies: A Text Analytics Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Kang Li ◽  
Lunchuan Zhang ◽  
Dianwei Wang ◽  
Dinglu Pan
Keyword(s):  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Online Information ◽  
Pricing Strategies ◽  
Text Analytics ◽  
Online Data ◽  
Managerial Implication ◽  
Multiple Regression Method ◽  
Book Prices ◽  
The Impact

Nowadays, electronic book vendors are increasingly proactive in trying to strategically capitalize on online big data generated by consumers. It will bring great profit for vendors if they can make the most of online reviews to figure out the impact of online data on the selling prices of e-books. In this paper, we complement an emerging body of research to explore how e-book prices could be affected by online information via analyzing the sheer volume of online data from e-book websites, namely, we first employ a domain ontology-based method to select the most discriminative features that may affect e-book prices. Then, the topic modeling method latent Dirichlet allocation and aspect-oriented sentiment analysis methods are applied as a supplement. Using the multiple regression method, we identify the key features that may have effects on the prices of e-books and give the related regression equation. In our results, some factors including paper book prices, paper book pages corresponding to the e-book, and e-book content have significant effects on the price of e-books. The managerial implication is that e-book firms can obtain a reference price for an e-book and may dynamically adjust the price to increase e-book sales according to our data analysis results.

The effect of emotions, eWOM quality and online review sequence on consumer intention to follow advice obtained from digital services

2020 ◽  
Vol 31 (3) ◽  
pp. 465-487 ◽  
Author(s):  
Carla Ruiz-Mafe ◽  
Enrique Bigné-Alcañiz ◽  
Rafael Currás-Pérez
Keyword(s):  
Structural Model ◽  
Online Reviews ◽  
Moderating Effect ◽  
Online Information ◽  
Bias Effect ◽  
Content Type ◽  
Digital Services ◽  
Information Cues ◽  
Cognitive Information ◽  
The Impact

PurposeThis paper analyses the interrelationships between emotions, the cognitive information cues of online reviews and intention to follow the advice obtained from digital platforms, paying special attention to the moderating effect of the sequencing of review valence.Design/methodology/approachThe data were collected from 830 Spanish Tripadvisor users. In a two-step approach, a measurement model was estimated and a structural model analysed to test the proposed hypotheses. SmartPLS 3.0 software was used. The moderating effect of sequencing of reviews is tested.FindingsThe data analysis showed a bias effect of review sequence on the impact of online information cues and emotions on intention to follow advice obtained from Tripadvisor. When the online reviews of a restaurant begin with positive commentaries, their perceived persuasiveness is a stronger driver of the pleasure and arousal elicited by online reviews than when they begin with negative reviews. On the other hand, the perceived helpfulness of online reviews only triggers arousal when the user reads negative, followed by positive, comments. The impact of pleasure on intention to follow the advice provided in an online travel community is higher with positive-negative than with negative-positive sequences.Originality/valueWhile researchers have demonstrated the benefits of customer reviews on company sales, a largely uninvestigated issue is the interplay between emotions and cognitive information cues in the processing of online reviews. This is one of the first studies to examine the moderating effect of conflicting reviews on the impact of emotions and cognitive information cues on consumer intention to follow the advice obtained from digital services.

scholarly journals CREMOR: CREdibility Model on Online Reviews-How people Consider Online Reviews Believable

2017 ◽  
Vol 10 (7) ◽  
pp. 56 ◽  
Author(s):  
Patrizia Grifoni ◽  
Fernando Ferri ◽  
Tiziana Guzzo
Keyword(s):  
Purchase Intention ◽  
Source Credibility ◽  
Online Reviews ◽  
Online Information ◽  
Perceived Credibility ◽  
Product Service ◽  
Fake Reviews ◽  
The Impact ◽  
The Web

The Internet is deeply changing how buyers and sellers interact in the marketplace. The Web enables consumers to be informed on their purchases both online and offline thanks to crowdsourced reviews. However, recent studies have found evidence that online consumers review could be not truthful as some users such as owners, competitors, paid users, sometimes post fake reviews. In this context the question of credibility is becoming more and more relevant in the Web 2.0 environment in which the concepts of social influence and electronic word of mouth are acquiring a great importance. The user’s perception of online reviews can influence source credibility and the perception of the quality of a product/service, as well as the likelihood that someone will purchase the product/service. This study proposes a model that analyses elements that influence online information credibility and the impact of the perceived credibility on purchase intention.

scholarly journals AN AUTOMATED METHOD TO CONDUCT IMPORTANCE-PERFORMANCE ANALYSIS OF PRODUCT ATTRIBUTES FROM ONLINE REVIEWS - AN EXTENSION WITH A CASE STUDY

2021 ◽  
Vol 1 ◽  
pp. 417-426
Author(s):  
Kangcheng Lin ◽  
Harrison Kim
Keyword(s):  
Performance Analysis ◽  
Latent Dirichlet Allocation ◽  
Product Information ◽  
Online Reviews ◽  
Product Attributes ◽  
Attribute Importance ◽  
Online Data ◽  
Automated Method ◽  
Ibm Watson

AbstractWith the growth of online marketplaces and social media, product designers have been seeing an exponential growth of data available, which can serve as an extremely valuable source of information communicated from customers without geographical limitations. The data will reveal customers’ preferences, which can be expensive and slow to obtain via traditional methods such as survey and questionnaires. While existing methods in the literature have been proposed to extract product information and make inference from online data, they have limitations, especially in providing reliable results and in dealing with data sparsity. Therefore, this paper proposes a method to conduct an Important-performance analysis from online reviews. The major steps of this method involve using latent Dirichlet allocation (LDA) to identify product attributes, using IBM Watson Natural Language Understanding tool to perform aspect-based sentiment analysis, and using XGBoost model to infer product attribute importance from the collected dataset. In our case study, we have collected over 150,000 text reviews of more than 3,000 laptops from Amazon.

scholarly journals A Text Analytics-Based Importance Performance Analysis and Its Application to Airline Service

2019 ◽  
Vol 11 (21) ◽  
pp. 6153 ◽  
Author(s):  
Seungju Nam ◽  
Hyun Cheol Lee
Keyword(s):  
Firm Performance ◽  
Performance Analysis ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Text Analytics ◽  
Service Experience ◽  
Customer Perceptions ◽  
Statistical Correlations ◽  
Air Transport Industry ◽  
Service Experiences

We introduce a new importance-performance analysis (IPA) methodology while making use of direct service experience perceptions represented by online reviews with numerical ratings. The proposed IPA, which we call the text analytics-based IPA (TAIPA), allows the real-time calculation of importance using the probability distribution of word frequency via the latent Dirichlet allocation (LDA) application to online reviews, and of performance using numerical rating values. The importance is also adjusted with the help of a sentiment analysis of online reviews to provide more precise measurements for service experience perceptions. To ensure an evaluation of the entire service process, we employ service encounters, in which service experiences occur and thus most customer perceptions are created, as a set of attributes composed of LDA topics that contain direct perceptions of service experiences. We investigate statistical correlations between TAIPA calculations and typical benchmarks of firm performance in the air-transport industry to verify how effective the proposed TAIPA is with respect to the degree that customer satisfaction is represented. As a primary result, TAIPA is more effective than comparison targets in that it shows stronger correlations with firm performance. TAIPA is specialized in determining which service step (i.e., a one-to-one relationship with a service encounter) needs to be improved. Moreover, TAIPA is flexible in considering multiple competitors.

scholarly journals The Sustainability of Cruise Tourism Onshore: The Impact of Crowding on Visitors’ Satisfaction

2019 ◽  
Vol 11 (6) ◽  
pp. 1510 ◽  
Author(s):  
Silvia Sanz-Blas ◽  
Daniela Buzova ◽  
Walesska Schlesinger
Keyword(s):  
Online Reviews ◽  
Text Analytics ◽  
Negative Effects ◽  
High Satisfaction ◽  
Cruise Tourism ◽  
Negative Effect ◽  
Tourism Activity ◽  
The Impact ◽  
Human Crowding

The sustainability of cruise tourism has been questioned in relation to its negative effects on ports of call, among which crowding has recently become more pronounced. However, an understanding of how crowdedness influences cruise tourists’ experience onshore is lacking. The study analyzed online reviews on onshore experiences in the main European ports of call through Leximancer, an automated text analytics software. The results revealed that the perceived destination crowding was not always negatively evaluated by tourists, but was also discussed as a factor adding up to the authenticity of the visit under certain circumstances. Nevertheless, the evidence indicates that only human crowding might be positively assessed, while the spatial crowdedness was always reported as detracting from the enjoyment of the visit. The analysis also showed that the crowding phenomenon was represented differently in the accounts of the low, average and high satisfaction cruise tourists’ groups. The role of the guide, as well as the attractiveness of the sightseeing were identified as factors that can ameliorate the negative effect of crowding on the destination visit. The findings yield relevant implications for all actors involved in the cruise tourism activity, which should manage destination crowdedness in a more sustainably innovative way.

The cultural influences of narrative content on consumers’ perceptions of helpfulness

2021 ◽  
pp. 147078532110230
Author(s):  
Ning Fu
Keyword(s):  
Rapid Development ◽  
Cultural Influences ◽  
Online Reviews ◽  
The United States ◽  
User Generated Content ◽  
Text Analytics ◽  
Word Count ◽  
Cultural Backgrounds ◽  
Linguistic Inquiry ◽  
The Impact

The rapid development of text analytics enables marketers to obtain the information extracted from the narrative content in user-generated content (UGC). Recent studies have also demonstrated that people with different cultural backgrounds may express their opinions about their purchase in diverse manners. This study focuses on the impact of the narrative content of consumers’ perception of helpfulness. It first identifies four contextual dimensions to propose a theoretical model, demonstrating that perceptions of helpfulness may differ in respect to the consumers’ varied cultural backgrounds (e.g., individualism vs. collectivism). By using Linguistic Inquiry and Word Count (LIWC), the study empirically tests the hypotheses by analyzing 111,857 movie reviews collected for 167 American movies released both in the United States and in China from 2013 to 2016. The results reveal that individualist consumers perceive an online review that contains more self-description and future-focus content as helpful, whereas collectivist consumers rely more on online reviews containing social description and past-focus content.

The Impact of a Highly Publicized Celebrity Suicide on Suicide-Related Online Information Seeking

Crisis ◽  
2017 ◽  
Vol 38 (3) ◽  
pp. 207-209 ◽  
Author(s):  
Florian Arendt ◽  
Sebastian Scherr
Keyword(s):  
Suicide Prevention ◽  
Information Seeking ◽  
The Internet ◽  
Online Information ◽  
Search Queries ◽  
Related Information ◽  
Search Terms ◽  
Celebrity Suicide ◽  
Online Information Seeking ◽  
The Impact

Abstract. Background: Research has already acknowledged the importance of the Internet in suicide prevention as search engines such as Google are increasingly used in seeking both helpful and harmful suicide-related information. Aims: We aimed to assess the impact of a highly publicized suicide by a Hollywood actor on suicide-related online information seeking. Method: We tested the impact of the highly publicized suicide of Robin Williams on volumes of suicide-related search queries. Results: Both harmful and helpful search terms increased immediately after the actor's suicide, with a substantial jump of harmful queries. Limitations: The study has limitations (e.g., possible validity threats of the query share measure, use of ambiguous search terms). Conclusion: Online suicide prevention efforts should try to increase online users' awareness of and motivation to seek help, for which Google's own helpline box could play an even more crucial role in the future.

ANALYSING SENTIMENTS OF ONLINE REVIEWS ON RESTAURANTS IN MALAYSIA USING PREDICTIVE TEXT ANALYTICS

2018 ◽  
Vol 2018 ◽  
pp. 200-200
Author(s):  
Kok Wei Khong ◽  
◽  
Fon Sim Ong ◽  
Babajide AbuBakr Muritala ◽  
Ken Kyid Yeoh
Keyword(s):  
Online Reviews ◽  
Text Analytics

scholarly journals The impact of online reviews on e-commerce sales in India: a case study

2021 ◽  
pp. 1-17 ◽  
Author(s):  
Mithun S. Ullal ◽  
Cristi Spulbar ◽  
Iqbal Thonse Hawaldar ◽  
Virgil Popescu ◽  
Ramona Birau
Keyword(s):  
Online Reviews ◽  
The Impact

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.

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