☆ 4.6 Review

Understanding of Customer Decision-Making Behaviors Depending on Online Reviews

APPLIED SCIENCES-BASEL (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Chemistry, Multidisciplinary

Recommendation System for a Delivery Food Application Based on Number of Orders

Claudia N. Sanchez et al.

Summary: With the growth of food-delivery applications, creating new recommendation systems tailored to this platform is crucial. The document proposes a recommendation system based on the number of orders stored by a real food-delivery application, using the nearest-neighbor technique to calculate the client's preferred restaurants and analyze other clients with similar buying patterns. The system has been validated using a real dataset and outperformed other state-of-the-art recommendation techniques.

APPLIED SCIENCES-BASEL (2023)

添加到收藏夹

Article Computer Science, Artificial Intelligence

A survey on sentiment analysis methods, applications, and challenges

Mayur Wankhade et al.

Summary: This article provides an overview of sentiment analysis, discussing its applications, advantages, and challenges. Sentiment analysis involves extracting subjective information from text and evaluating and categorizing people's opinions.

ARTIFICIAL INTELLIGENCE REVIEW (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Immersion Measurement in Watching Videos Using Eye-tracking Data

Youjin Choi et al.

Summary: This study proposes an objective model for measuring immersion in video watching by utilizing viewers' gaze behavior. The results of the laboratory study indicate that certain gaze features are highly indicative of viewers' immersion state, and machine learning models based on these features are able to effectively detect the immersion state of viewers. Additionally, post-hoc interviews confirm the applicability of this method for measuring immersion in the middle of video watching.

IEEE TRANSACTIONS ON AFFECTIVE COMPUTING (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

An adaptive deep learning method for item recommendation system

Aminu Da'u et al.

Summary: This paper proposes a RS model that utilizes neural attention techniques to learn adaptive user/item representations and fine-grained user-item interactions, aiming to enhance the accuracy of item recommendation. Experimental results show that the proposed model outperforms existing methods in terms of rating prediction and ranking performances.

KNOWLEDGE-BASED SYSTEMS (2021)

添加到收藏夹

Review Computer Science, Information Systems

Helpfulness of online consumer reviews: A multi-perspective approach

Satanik Mitra et al.

Summary: This study proposed three qualitative perspectives to assess review helpfulness from the semantic, sequential, and structural angles. Various models were employed to analyze these perspectives and it was found that they all impact consumers' perception of review helpfulness.

INFORMATION PROCESSING & MANAGEMENT (2021)

添加到收藏夹

Review Business

Mapping the electronic word-of-mouth (eWOM) research: A systematic review and bibliometric analysis

Naveen Donthu et al.

Summary: Through bibliometric analysis and systematic review, this study found significant growth in electronic word-of-mouth (eWOM) research in terms of publications, mainly from the United States and Europe. Researchers in this field tend to favor mixed research designs and focus on theory building. Prominent research topics include negative word of mouth, consumer behavior and trust, word of mouth in social networks, among others.

JOURNAL OF BUSINESS RESEARCH (2021)

添加到收藏夹

Article Chemistry, Multidisciplinary

Digital Marketing Platforms and Customer Satisfaction: Identifying eWOM Using Big Data and Text Mining

Fotis Kitsios et al.

Summary: This paper explores how to use user-generated content (UGC) to bridge the gap between guest satisfaction and online reviews, as well as analyzes aspects of satisfaction and dissatisfaction among Greek hotel guests. It helps hotel managers identify specific product attributes or service characteristics that impact guest satisfaction and dissatisfaction.

APPLIED SCIENCES-BASEL (2021)

添加到收藏夹

Article Chemistry, Multidisciplinary

Designing Reenacted Chatbots to Enhance Museum Experience

Yeo-Gyeong Noh et al.

Summary: Researchers examined the role of chatbots in history education in museums and how they impact visitors' experiences. The findings demonstrate that embodiment and reflection significantly enhance the museum experience.

APPLIED SCIENCES-BASEL (2021)

添加到收藏夹

Article Business

A meta-analysis of the factors affecting eWOM providing behaviour

Elvira Ismagilova et al.

Summary: This study synthesized findings on factors influencing eWOM from existing studies using meta-analysis, finding 16 significant relationships out of 20 identified. Limitations include the use of limited databases for study collection, suggesting future research should utilize a wider range of databases and consider both qualitative and quantitative studies.

EUROPEAN JOURNAL OF MARKETING (2021)

添加到收藏夹

Review Hospitality, Leisure, Sport & Tourism

Extremely Negative Ratings and Online Consumer Review Helpfulness: The Moderating Role of Product Quality Signals

Raffaele Filieri et al.

Summary: Contradictory findings exist in the literature regarding the impact of extremely negative ratings (ENRR), indicating that not all ENRR are perceived as helpful by consumers. This study suggests that ENRR are viewed as more helpful when a hotel has received a certificate of excellence and has higher average ratings. Managers of higher category hotels are advised to pay more attention to extremely negative reviews, especially those with excellence certificates and high ratings.

JOURNAL OF TRAVEL RESEARCH (2021)

添加到收藏夹

Review Computer Science, Information Systems

Recommender Systems Based on Collaborative Filtering Using Review Texts-A Survey

Mehdi Srifi et al.

INFORMATION (2020)

添加到收藏夹

Review Hospitality, Leisure, Sport & Tourism

Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews

Yabing Zhao et al.

INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT (2019)

添加到收藏夹

Proceedings Paper Computer Science, Theory & Methods

Multi-Domain Gated CNN for Review Helpfulness Prediction

Cen Chen et al.

WEB CONFERENCE 2019: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW 2019) (2019)

添加到收藏夹

Article Business

How stories generate consumer engagement: An exploratory study

Dessart Laurence et al.

JOURNAL OF BUSINESS RESEARCH (2019)

添加到收藏夹

Proceedings Paper Computer Science, Cybernetics

Understanding Visual Cues in Visualizations Accompanied by Audio Narrations

Ha-Kyung Kong et al.

CHI 2019: PROCEEDINGS OF THE 2019 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (2019)

添加到收藏夹

Article Business

Dynamic effects of customer experience levels on durable product satisfaction: Price and popularity moderation

Jying-Nan Wang et al.

ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS (2018)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Dual-regularized matrix factorization with deep neural networks for recommender systems

Hao Wu et al.

KNOWLEDGE-BASED SYSTEMS (2018)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Exploring New Vista of intelligent collaborative filtering: A restaurant recommendation paradigm

Arup Roy et al.

JOURNAL OF COMPUTATIONAL SCIENCE (2018)

添加到收藏夹

Article Hospitality, Leisure, Sport & Tourism

Effects of user-provided photos on hotel review helpfulness: An analytical approach with deep leaning

Yufeng Ma et al.

INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT (2018)

添加到收藏夹

Article Hospitality, Leisure, Sport & Tourism

Positive and negative eWOM motivations and hotel customers' eWOM behavior: Does personality matter?

Yaou Hu et al.

INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT (2018)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Sentiment analysis leveraging emotions and word embeddings

Maria Giatsoglou et al.

EXPERT SYSTEMS WITH APPLICATIONS (2017)

添加到收藏夹

Article Business

Five-star or thumbs-up? The influence of rating system types on users' perceptions of information quality, cognitive effort, enjoyment and continuance intention

Chi-Wen Chen

INTERNET RESEARCH (2017)

添加到收藏夹

Article Business

Predicting the helpfulness of online consumer reviews

Jyoti Prakash Singh et al.

JOURNAL OF BUSINESS RESEARCH (2017)

添加到收藏夹

Article Information Science & Library Science

Customers' purchase decision-making process in social commerce: A social learning perspective

Aihui Chen et al.

INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT (2017)

添加到收藏夹

Review Computer Science, Artificial Intelligence

Do customer reviews drive purchase decisions? The moderating roles of review exposure and price

Ewa Maslowska et al.

DECISION SUPPORT SYSTEMS (2017)

添加到收藏夹

Review Computer Science, Artificial Intelligence

Online review helpfulness: Impact of reviewer profile image

Sahar Karimi et al.

DECISION SUPPORT SYSTEMS (2017)

添加到收藏夹

Review Computer Science, Artificial Intelligence

Predicting the performance of online consumer reviews: A sentiment mining approach to big data analytics

Mohammad Salehan et al.

DECISION SUPPORT SYSTEMS (2016)

添加到收藏夹

Article Management

Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud

Michael Luca et al.

MANAGEMENT SCIENCE (2016)

添加到收藏夹

Review Hospitality, Leisure, Sport & Tourism

What makes an online consumer review trustworthy?

Raffaele Filieri

ANNALS OF TOURISM RESEARCH (2016)

添加到收藏夹

Review Psychology, Multidisciplinary

Helpfulness of user-generated reviews as a function of review sentiment, product type and information quality

Alton Y. K. Chua et al.

COMPUTERS IN HUMAN BEHAVIOR (2016)

添加到收藏夹

Proceedings Paper Computer Science, Cybernetics

Discovering Users' Perceptions on Rating Visualizations

Warih Maharani et al.

PROCEEDINGS OF CHIUXID 2016: BRIDGING THE GAPS IN THE HCI & UX WORLD (2016)

添加到收藏夹

Article Psychology, Multidisciplinary

A study of factors that contribute to online review helpfulness

Albert H. Huang et al.

COMPUTERS IN HUMAN BEHAVIOR (2015)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Orthogonal rotations in latent semantic analysis: An empirical study

Lucian L. Visinescu et al.

DECISION SUPPORT SYSTEMS (2014)

添加到收藏夹

Article Hospitality, Leisure, Sport & Tourism

Predicting Hotel Demand Using Destination Marketing Organization's Web Traffic Data

Yang Yang et al.

JOURNAL OF TRAVEL RESEARCH (2014)

添加到收藏夹

Article Hospitality, Leisure, Sport & Tourism

Refreshing hotel satisfaction studies by reconfiguring customer review data

Lingqiang Zhou et al.

INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT (2014)

添加到收藏夹

Article Business

Which type of online review is more persuasive? The influence of consumer reviews and critic ratings on moviegoers

Wen-Chin Tsao

ELECTRONIC COMMERCE RESEARCH (2014)

添加到收藏夹

Article Computer Science, Cybernetics

Predicting the Helpfulness of Online ReviewsA Replication

Albert H. Huang et al.

INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION (2013)

添加到收藏夹

Article Management

Beyond traditional word-of-mouth An expanded model of customer-driven influence

Vera Blazevic et al.

JOURNAL OF SERVICE MANAGEMENT (2013)

添加到收藏夹

Review Business

Product type and consumers' perception of online consumer reviews

Soonyong Bae et al.

ELECTRONIC MARKETS (2011)

添加到收藏夹

Article Computer Science, Information Systems

Comparing sentiment expression in movie reviews from four online genres

Jin-Cheon Na et al.

ONLINE INFORMATION REVIEW (2010)

添加到收藏夹

Article Hospitality, Leisure, Sport & Tourism

The impact of online user reviews on hotel room sales

Qiang Ye et al.

INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT (2009)

添加到收藏夹

Article Business

The effect of negative online consumer reviews on product attitude: An information processing view

Jumin Lee et al.

ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS (2008)

添加到收藏夹

Article Business

Exploring the value of online product reviews in forecasting sales: The case of motion pictures

Chrysanthos Dellarocas et al.

JOURNAL OF INTERACTIVE MARKETING (2007)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.