As the pet care market continues to expand, pet shampoo products have become an important pet care product category for regular skin and hygiene management, with growing consumer attention to product quality and safety. This study conducted an integrated analysis using Latent Dirichlet Allocation (LDA) topic modeling, sentiment analysis, and Importance-Performance Analysis (IPA) to derive customer requirement attributes for pet shampoo products and identify product improvement priorities based on online review data. A total of 14,072 pet shampoo reviews were collected from Naver Shopping. After preprocessing, 7,103 reviews were used for sentiment analysis and 5,405 reviews were used for LDA topic modeling. Topic proportions derived from LDA were used as a proxy for importance (review salience), and normalized sentiment scores by topic were applied as the performance measure, which were then integrated into an IPA matrix. The analysis identified five customer requirement attributes: user experience and usability, daily preventive skin care, ingredient safety and reliability, skin condition care, and fragrance and coat condition. Daily preventive skin care and skin condition care were positioned in the high-salience, low-performance quadrant, suggesting potential priority areas for product improvement. This study applies a data-driven integrated analytical approach to customer requirement analysis based on online reviews and provides practical implications for supporting consumer-centered new product development and research and development (R&D) decision-making.

This study examines gender differences in language use in online shopping reviews through an analysis of five-star reviews posted on the fashion platform Musinsa. Focusing on reviews of a single unisex sneaker product, a corpus of 977 reviews by male users and 998 reviews by female users were compiled and analyzed. This study used morphological analysis and frequency-based methods to compare high-frequency vocabulary, part-of-speech distributions, abbreviated forms, loanwords, original-language expressions, sentence-ending forms (haeyo-che and hasipsio-che), and symbolic language such as emoticons. The findings show that male users tend to use verbs and nouns directly related to functions and outcomes, whereas female users more frequently employ adjectives and adverbs expressing aesthetics, emotions, and overall impressions. Although the use of hybrid abbreviations and emoticons differed significantly by gender, sentence-ending forms also showed a statistically significant association with gender. These results suggest that gender does not rigidly determine the overall stylistic structure of review discourse but influences language use by shaping evaluative focus, emotional marking, and rhetorical emphasis in positive reviews.

This study examines the impact of others' reviews (reviews, product ratings) on consumer responses (helpfulness & buying intention) in an online shopping platform. We propose that review features, such as review message construal and review inconsistency between review message valence and rating, determine review credibility as product-related information, which in turn influences helpfulness of review and buying intention toward the product. Specifically, low- level construal review messages will be perceived as more credible than high-level construal review messages, which affect helpfulness and buying intention. In addition, the effect of review message construal will be moderated by review inconsistency. The effect of the review message construal will be enhanced in the condition of review consistency (positive content-high rating & negative content-low rating), but it will be disappeared or attenuated in the condition of inconsistency (positive content-low rating, negative content-high rating).

One of the main challenges brands face nowadays is the ability to provide a real-life experience through online platforms. The aim of this study is to analyze an AR try-on app versus a website, considering consumers self-concept and testimonials. To this end, an online survey was conducted, in which respondents were exposed to two of four scenarios: AR APP or website experience, and positive versus negative reviews presence. Our findings indicate that ideal self-congruence impacts both, purchase intention and confidence. The present study positively contributes to the AR and self-concept literature, while opening new avenues of research for both academics and practitioners.

This study investigates how travellers adopt information from travel review websites, i.e., Tripadvisor and how online travel reviews influence their intention to visit a tourist attraction. Based on the Information Adoption Model (IAM), a conceptual model was developed and tested using the data obtained from 227 valid respondents.

Online communities are identified as people gathering online and communicating through the internet to share ideas, objectives, goals, without any geographical boundary. The growth of user-generated content created in online communities has transformed the way consumers search for and share information, particularly in the hospitality industry. Particularly, in the restaurant and food sectors due to the intangible nature of hospitality services, online reviews play an important role on consumer decisions. Furthermore, online reviews on restaurants are not only informational but also, they impact consumers’ choices regarding restaurants. Consequently, the nature of such user-generated content that is produced at a high speed and is diverse and rich should be treated and understood. This study proposes the first tailored BERTopic model together with sentiment analysis based on pre-trained BERT model that takes advantage of its novel sentence embedding for creating interpretable topics into the analysis of restaurant online reviews to determine how the customers elaborate their criteria in the context of certain experiences. An exploratory analysis is presented involving a large-scale review data set of 261,531 restaurant online reviews from 4 different countries retrieved from the eWOM community thefork.com. A broad list of the topics discussed by customers post-dining in restaurants is built. Insights into the behavior, experience, and satisfaction of the customers across the different restaurants are discovered. This approach and findings are encouraging hospitality managers in understanding customers’ perception, through which applicable marketing can be developed to attract and retain potential customers.

This study aims to address two important questions: will advertising on mobile short-form video apps jeopardize the value perception of luxury brands (RQ1), and if so, how will self-deprecating online reviews eliminate these negative effects (RQ2). An experimental design approach was employed to investigate the proposed research questions. Three experiments were conducted to test the hypotheses. SPSS was used for data analysis. The study 1 finds that compared with traditional media, advertising on mobile short-form video apps shortened the psychological distance between consumers and luxury, therefore has a more negative impact on consumers’ perception of luxury brands. The study 2 reveals that self-deprecating online reviews can eliminate the negative effects of advertising of luxury brands. On the basis of previous research, this paper proves the negative influence of social media on luxury brands in the scene of new social media-mobile short format video application. In addition, it also studies the moderating effect of online comments, especially self-deprecating comments, on consumers' perception of luxury brands. This study outlines theoretical contributions and practical implications for the luxury marketing management and made suggestions for future research in the field of luxury marketing in Social Media.

As online reviews become a major factor in the consumer decision making process, firms have started seeking ways to help consumers make informed decisions. To avoid potential information overload, most online retailers provide review helpfulness features by allowing consumers to cast a vote on the (un)helpfulness of a review. Previous research has extensively focused on identifying the drivers of review helpfulness while little attention has been paid to review unhelpfulness. Using an empirical analysis of a large review dataset from a major online retailer, this research investigates the drivers of both review helpfulness and unhelpfulness. By revealing the asymmetry between the consumers’ review helpfulness and unhelpfulness voting behaviors, this study provides practical implications for review platforms.

본 연구는 소비자가 경험재인 웹소설을 선택하는 상황에서 사실적 메시지와 평가적 메시지를 담은 온라인 리뷰를 보았을 때 더 유용하다고 판단하는 리뷰가 무엇인지 탐색하고, 이러한 유용성 평가의 차이에 대한 개인의 분석적 의사결정 성향 수준의 조절효과를 검증하기 위하여 실시되었다. 경험재를 구매하기 전 객관적 정보를 수집하는 소비 자의 성향에 근거하여 웹소설의 소비자는 사실적인 온라인 리뷰의 유용성을 더 높이 평가할 것으로 예상하였다. 또 한 인지적 성향에 따라 구분되는 의사결정 유형 중 분석적 의사결정자는 정확한 정보를 수집하여 논리적인 판단을 내린다. 따라서 분석적 의사결정 성향 수준이 높아짐에 따라 사실적인 온라인 리뷰의 유용성 평가가 높아질 것으로 예상하였다. 실험 1의 결과 사실적인 리뷰를 제시받은 집단이 평가적인 리뷰를 제시받은 집단보다 리뷰의 유용성을 높이 평가하였으며, 실제 웹소설 선택 상황과 유사하게 두 유형의 리뷰를 동시에 제시한 실험 2에서도 리뷰의 유용 성 평가에 대한 리뷰 메시지 유형의 주효과가 확인되었다. 또한 실험 2에서는 분석적 의사결정 성향 수준이 높아짐 에 따라 사실적인 리뷰의 유용성을 높이 평가하는 경향이 드러나 분석적 의사결정 성향 수준의 조절적 역할이 확인 되었다. 본 연구는 경험재인 웹소설을 선택하는 상황에서 리뷰 메시지 유형 및 소비자의 분석적 의사결정 성향 수준 이 소비자의 리뷰 유용성 평가에 영향을 끼친다는 사실을 확인함으로써 웹소설 소비자의 행동 양식을 밝혔다는 이론 적, 실무적 의의를 갖는다.

Online consumer activities have increased considerably since the COVID-19 outbreak. For the products and services which have an impact on everyday life, online reviews and recommendations can play a significant role in consumer decision-making processes. Thus, to better serve their customers, online firms are required to build online-centric marketing strategies. Especially, it is essential to define core value of customers based on the online customer reviews and to propose these values to their customers. This study discovers specific perceived values of customers in regard to a certain product and service, using online customer reviews and proposes a customer value proposition methodology which enables online firms to develop more effective marketing strategies. In order to discover customers value, the methodology employs a text-mining technology, which combines a sentiment analysis and topic modeling. By the methodology, customer emotions and value factors can be more clearly defined. It is expected that online firms can better identify value elements of their respective customers, provide appropriate value propositions, and thus gain sustainable competitive advantage.

This study analyzes the user-generated reviews of Paris-based Michelin three-star restaurants in terms of how they are discursively constructed. Using the reviews posted in Tripadvisor in 2019 as data, it examines how positive reviews (PR) and negative reviews (NR) are framed with distinct discursive practices. While PR and NR a re both characteriz ed by the discursive practice of highlighting professed culinary expertise of the reviewer, this feature is more foregrounded in NR, where the reviewer is generally more oriented to showing themselves as being entitled to write a review. In terms of communicative styles, PR is also characterized by a heavy use of symbolic and metaphoric language, while more ordinary style of language is used in NR, embedded in the context of critiquing specific items of dish or service. While PR and NR both tend to make references to Michelin star status as a basis of their evaluation, they were shown to differ in terms of the tones or keys used in describing chefs, and also in the way the target of evaluation is formulated. The findings shed light on how and why the members of foodie community construct the language the way they do, and have implications for genre analysis.

This paper presents a way of classifying qualitative online consumer reviews (OCRs) in terms of functional and emotional dimensions and measures the direct and indirect impact of both volume and valence of OCRs on product sales. Utilizing four million online postings across 342 mobile games for thirty months, the authors use text analysis and word classification and identify 74 representative words to describe the various levels of functional OCRs consisting of product quality, product innovativeness, price acceptability, and product simplicity, and emotional OCRs including anger, fear, shame, love, contentment, and happiness. They combine the resulting OCR volumes with weekly sales, resulting in 1,835 observations for analysis with hierarchical Bayesian methods. Results suggest that the volume and valence of aggregated functional OCRs and the valence of aggregated emotional OCRs have the positive effects on sales. The volume and valence of functional OCR subcategories have mixed effects on sales and the link is moderated by the share of emotional OCR subcategories. Further, a sales forecasting model which includes 13 variables of OCR subcategories shows the best predictive validity.

This study aims to analyse the overall sentiments of online reviews on restaurants in Malaysia using predictive text analytics. As we know in opinion mining, sentiment analysis is a prominent technique in predictive text mining. It is a technique that categorises opinions in unstructured text format into binary classification (ie. good or bad). The authors attempt to go beyond the binary classification by viewing texts as empirical entities derived using the Term Frequency - Inverse Document Frequency (TF-IDF) weighting algorithm. These empirical entities, based on online reviews of restaurants in Malaysia, are then manifested into hypothetically defined constructs closely reflecting their thematic and semantic nature. The were 4914 customer reviews from restaurants across 20 towns and cities in Malaysia scraped off TripAdvisor.com using web crawler tools. Then a series of analytical tests were carried out. First the online reviews were parsed, filtered and clustered using SAS Text Miner. Then the online reviews underwent the TF-IDF process to identify significant terms and weightages were assigned according to their importance. The TF-IDF process resulted in a series of important nouns and adjectives from the text corpus. Using these weightages of nouns and adjectives, the authors went on to thematise these terms based on their semantic nature to manifest hypothetical constructs. These constructs were based on the Mehrabian–Russell Stimulus Response Model. Subsequently the authors tested the associations among the constructs using variance-based and covariance-based Structural Equation Modelling (SEM). The authors were encouraged by this exploratory methodological approach in formulating predictive text analytics using SEM. Results indicated that sentiments were generally positive towards restaurants and the important terms derived were price, hospitality, location, waiting time, availability of parking and size of food portion.

Considering that the effectiveness of ads varies according to the credibility of consumers, it is necessary to establish data regarding consumer credibility in relation to online reviews. To conduct a successful study on the marketing strategies of online reviews, it is also necessary to analyze the relationship between credibility and the various factors that influence the purchase intentions of consumers. Therefore, this study attempted to examine the relationship between consumer trust of on-line reviews, brand preference, ads credibility, and purchase intentions in relation to cosmetics. The study was conducted through a normative descriptive survey method using stimuli and a self-administered questionnaire. Analysis of the structural equation model was conducted for the data analysis. The results revealed that consumer reliance on online reviews of cosmetics influences brand preference, credibility of brand ads and purchase intentions. The results also revealed that consumers’ on-line reviews, brand preference, and trust of brand ads are important factors for increasing the purchase intentions. The mediation effect of brand preference and brands’ ads credibility were found in the process where on-line reviews exercise an influence on the purchase intentions. It was also found that brand preference has a stronger influence on purchase intention than credibility of brand ads. It was discovered that the credibility of on-line reviews directly influences purchase intentions more than indirectly influences. Considering the results of this study, programs that encourage customers to post on-line reviews, and strategies to promote brand preference by targeting groups that exhibit high trust in online reviews would be recommended.