Online Customer Reviews Research Articles

Pengaruh Perceived Risk Dan Online Customer Review Terhadap Keputusan Pembelian Melalui Kepercayaan Pada Pengguna Marketplace Di Kota Bekasi

Currently, many marketplaces are starting to develop in Indonesia. Marketplace is an online intermediary that is used to build buying and selling activities and transactions between sellers and buyers. This involves a trilateral relationship between sellers, buyers and marketplace providers. The purpose of this study was to determine the effect of perceived risk and online customer review on purchasing decisions through trust in marketplace users in Bekasi City. The number of samples specified is a minimum of 135 samples consisting of 27 question items. Collecting data in this study using a questionnaire using Google Forms. Data analysis in this study used a multivariate analysis method using SPSS software version 22 and SEM (Structural Equation Model) with SmartPLS. The research results show that perceived risk has no effect on the trust variable. Meanwhile, online customer reviews have an effect on trust. The perceived risk variable on purchasing decisions shows insignificant results, online customer reviews show that the results influence purchasing decisions. While the trust variable on purchasing decisions, the results show no significant effect. Perceived risk has no effect on purchasing decisions through trust, and finally, online customer reviews have an effect on purchasing decisions through trust. This means that the better the consumer reviews and the trust that consumers experience, the higher the purchase decision of the Shopee marketplace consumers.

Aspect-based sentiment analysis on online customer reviews: a case study of technology-supported hotels

研究目的本研究通过使用意见挖掘技术旨在确定入住酒店的客人的满意度。这些客人接受酒店提供的产品相关的技术支持和服务。研究设计/方法/方法在这项研究中, 使用基于特定方面的情感分析技术评估了 booking.com 上与属于连锁酒店的 10 家酒店相关的 12,396 条客户评论, 这些酒店均使用科技支持的产品。研究发现作为这项研究的结果, 已经确定在酒店业务中使用科技会对客户满意度产生积极的影响。已经确定, 标准酒店商务产品（例如床、房间照明等）的丰富科技以不会非常昂贵的方式影响客人。此外, 客户感兴趣的是在本研究的服务过程中包括机器人和技术特征, 例如客房服务机器人, 作为“高科技”层面。研究实际意义酒店管理层分析了客人的在线评论, 并有机会评估他们的服务并从客人的眼中看到自己的形象。酒店企业必须了解客户对高投资成本技术的期望。本研究分析了直接体验过的消费者的意见。因此, 研究结果将使决定投资服务技术的酒店企业受益。研究原创性/价值在这项研究中, 我们对一家在许多国家经营的酒店集团的客户评论进行了调查。该酒店属于一家酒店集团, 该集团以技术丰富其标准产品, 并以“智能酒店”的概念提供服务。该研究有助于了解客户在酒店业务中使用技术产品的体验。该研究扩展了客户对酒店科技产品和服务的满意度的文献, 以及对酒店投资技术的决策做出贡献。

Pengaruh Online Customer Review Dan Online Customer Rating Terhadap Keputusan Pembelian Pada Marketplace Lazada

This study aims to analyze the influence of online customer reviews and online customer ratings on purchasing decisions on the Lazada marketplace. In this study using a descriptive verification approach with quantitative methods. The sample used in this study was 400 respondents. Sampling using the Nonprobability Sampling method. The test stages used were validity test, reliability test, classic assumption test, multiple linear regression analysis technique and hypothesis testing using t test, f test and coefficient of determination using SPSS 26 tools. The results of this study were obtained by Online Customer Reviews and Online Customers Ratings have a positive and significant partial effect on purchasing decisions on the Lazada marketplace with variable values of 20.8% and 91.0% respectively. While Online Customer Reviews and Online Customer Ratings simultaneously influence purchasing decisions on the Lazada marketplace, they contribute 39.2% to purchasing decisions, while the remaining 60.8% is contributed by other factors not examined that influence purchasing decisions (Y ).

It is about inclusion! Mining online reviews to understand the needs of adaptive clothing customers

AbstractThe adaptive clothing market, which focuses on the inclusive design of clothing and footwear for people with varying degrees of disability, has grown substantially in recent years. However, few scholars have sought to understand the perspectives of online adaptive clothing consumers. This study employed topic modelling, sentiment analysis and collocation analysis to discover common themes and insights emerging from online customer reviews, scraped from a third‐party review platform and three retailing web sites. We utilized customer value and functional, expressive and aesthetic theories to group the results from topic modelling into key themes. Clothing function is the most frequently discussed theme in online customer reviews, followed by customer service and clothing aesthetics. Collocation analysis revealed the cause underlying each theme vis‐à‐vis customer satisfaction (e.g., fit and material quality) and dissatisfaction (e.g., sewing defects and lost shipment). The findings contribute to understanding the clothing needs and wants of people living with disabilities. It also provides practical guidelines on product offerings and online service optimization for adaptive clothing retailers.

THE INFLUENCE OF PRICE PERCEPTION, PROMOTION, AND ONLINE CUSTOMER REVIEW ON CONSUMER BUYING INTEREST IN LAZADA E COMMERCE IN PADANG UTARA DISTRICT

ABSTRACTThis study has a problem formulation, namely whether price perception affects consumer buying interest in Lazada e-commerce and whether promotion affects consumer buying interest in Lazada e-commerce and whether online customer reviews affect consumer buying interest in Lazada e-commerce. And this study aims to determine whether price perceptions, promotions, and online customer reviews have an effect on consumer buying interest in Lazada e-commerce. The research method used is the Explanatory Research method. The sample obtained is 80 respondents. Data analysis used multiple linear regression analysis, classical assumption test, and hypothesis testing. The results showed that the price perception variable partially had a positive and significant effect on consumer buying interest in Lazada e-commerce. While the promotion variable partially has a positive and significant effect on consumer buying interest in Lazada e-commerce. And the online customer review variable partially has a positive and significant effect on consumer buying interest in Lazada e-commerce.Keywords: Buying Interest, Price Perception, Promotion, Online Customer Review

The Influence of Product Packaging Design and Online Customer Review on Brand Awareness and Their Impact on Online Purchase Intention

Extensive research on skin care products, particularly in Indonesia, is intriguing. It is as a result of alterations in behavior that consumers always desire to appear attractive. Due to technological advancements, shopping habits have also changed, impacting the sales of skincare products. This study aimed to investigate the direct and indirect impacts of product packaging design and online customer review on online purchase intention mediated through brand awareness. Data were collected from 200 people in Indonesia who were familiar with Scarlett Whitening products. They were selected using a purposive sampling technique. Afterward, the collected data were analyzed using the SEM AMOS 26. The primary findings in this study were that Product Packaging Design and Online Customer Review had a positive and significant impact on the Online Purchase Intention of Scarlett Whitening products mediated through Brand Awareness in Indonesia.

Pengaruh Labelisasi Halal, Personal Selling dan Online Customer Review Terhadap Keputusan Pembelian (Studi Pada Follower Instagram Scarlett Whitening)

This study aims to determine the effect of halal labeling, personal selling and online customer reviews on purchasing decisions for Instagram followers of Scarlett Whitening products. This study uses a quantitative analysis approach using multiple linear regression analysis techniques. Primary data was obtained through a questionnaire distributed to respondents, namely Scarlett Whitening's Instagram followers. The sample of this study amounted to 348 people. The results of this study indicate that there is no influence of halal labeling on purchasing decisions, while personal selling and online customer reviews have an influence on purchasing decisions for Scarlett Whitening products.

Developing Nonlinear Customer Preferences Models for Product Design Using Opining Mining and Multiobjective PSO-Based ANFIS Approach.

Online customer reviews can clearly show the customer experience, and the improvement suggestions based on the experience, which are helpful to product optimization and design. However, the research on establishing a customer preference model based on online customer reviews is not ideal, and the following research problems are found in previous studies. Firstly, the product attribute is not involved in the modelling if the corresponding setting cannot be found in the product description. Secondly, the fuzziness of customers' emotions in online reviews and nonlinearity in the models were not appropriately considered. Thirdly, the adaptive neuro-fuzzy inference system (ANFIS) is an effective way to model customer preferences. However, if the number of inputs is large, the modelling process will be failed due to the complex structure and long computational time. To solve the above-given problems, this paper proposed multiobjective particle swarm optimization (PSO) based ANFIS and opinion mining, to build customer preference model by analyzing the content of online customer reviews. In the process of online review analysis, the opinion mining technology is used to conduct comprehensive analysis on customer preference and product information. According to the analysis of information, a new method for establishing customer preference model is proposed, that is, a multiobjective PSO based ANFIS. The results show that the introducing of multiobjective PSO method into ANFIS can effectively solve the defects of ANFIS itself. Taking hair dryer as a case study, it is found that the proposed approach performs better than fuzzy regression, fuzzy least-squares regression, and genetic programming based fuzzy regression in modelling customer preference.

Hybrid Approach with VADER and Multinomial Logistic Regression for Multiclass Sentiment Analysis in Online Customer Review

Hybrid Approach with VADER and Multinomial Logistic Regression for Multiclass Sentiment Analysis in Online Customer Review

LSTM-DGWO-Based Sentiment Analysis Framework for Analyzing Online Customer Reviews.

Sentiment analysis furnishes consumer concerns regarding products, enabling product enhancement development. Existing sentiment analysis using machine learning techniques is computationally intensive and less reliable. Deep learning in sentiment analysis approaches such as long short term memory has adequately evolved, and the selection of optimal hyperparameters is a significant issue. This study combines the LSTM with differential grey wolf optimization (LSTM-DGWO) deep learning model. The app review dataset is processed using the bidirectional encoder representations from transformers (BERT) framework for efficient word embeddings. Then, review features are extracted by the genetic algorithm (GA), and the optimal review feature set is extracted using the firefly algorithm (FA). Finally, the LSTM-DGWO model categorizes app reviews, and the DGWO algorithm optimizes the hyperparameters of the LSTM model. The proposed model outperformed conventional methods with a greater accuracy of 98.89%. The findings demonstrate that sentiment analysis can be practically applied to understand the customer's perception of enhancing products from a business perspective.

From Hospitality Basics to Customer Value and Memorable Experiences: Evidence from Online Customer Reviews of the Major Cruise Line Corporations

From Hospitality Basics to Customer Value and Memorable Experiences: Evidence from Online Customer Reviews of the Major Cruise Line Corporations

Pengaruh Online Customer Review dan Online Customer Rating terhadap Keputusan Pembelian Produk Fashion di Shopee

The research was conducted with the aim of analyzing the level of influence of online customer review and online customer rating variables on purchasing decisions for fashion products at Shopee using a population of all students of the Faculty of Economics, Tidar University by taking a sample of 96 respondents with certain criteria. This research is a quantitative research that uses regression analysis with the help of SPSS to solve problems. The data used is primary data with data collection techniques distributing questionnaires to respondents. This study uses the analysis technique of the F test, t test, and determination test which then results in the online customer review and online customer rating variables having a positive and significant influence on purchasing decisions. The percentage level of influence of online customer reviews and online customer ratings on purchasing decisions is 35.2%, while the other 64.8% is influenced by other factors.

TRUST MEMEDIASI ONLINE CUSTOMER REVIEW DAN RATING TERHADAP MINAT BELI MELALUI MARTKETPLACE SHOPEE

This study used quantitative data and the data collection method used in this study was a questionnaire using a Likert scale. The population used in this study were STIE Sampit students who used Shopee as a place to shop online. While the sample in this study amounted to 75 respondents and used a sampling technique based on accidental sampling, namely based on the coincidence of anyone who met and made a purchase at the shopee marketplace. The results of this study indicate that (1) online customer reviews have a significant effect on purchase intention with a t statistic value of 2.664 (2) online customer reviews have a significant effect on trust with a t statistical value of 4.709 (3) online customer ratings have no effect on purchase intentions with a t value statistic 1.028 (4) online customer rating has a significant effect on trust with a t statistic value of 4.555 (5) trust has a significant effect on purchase intention with a t statistic value of 2.346 (6) trust mediates online customer review of purchase intention with a t statistic value of 2.029 (7) trust mediates online customer rating of purchase intention with a statistical t value of 2.019. The R Square result of buying interest is 0.393 indicating that the research model is classified as moderate and means that online customer reviews, online customer ratings, and trust together contribute to buying interest of 39.9% and the rest is influenced by other variables outside of this study.

The Impact of Online Reviews and Ratings toward Shopee’s Customer Purchase Intention in Gianyar Regency

Purchase intention is one of the aspects that ensures the success of the company's revenue goals. Customers' online purchase intention is confirmed by various aspects, including online customer reviews and online customer ratings. Likewise, for Shopee customers in Gianyar Regency, online customer reviews and online customer ratings are two variables that can influence purchase intention. This study also aims to identify the positive and significant influence between online customer reviews and online customer ratings simultaneously and partially on the purchase intention of Shopee customers in Gianyar Regency. Information collection methods used in this study were observation, interviews and questionnaires. The number of respondents used in this study are 96 people with the method of determining the sample using purposive random sampling. Furthermore, the information was analyzed using quantitative analysis consisting of Research Instrument Test, Classical Assumption Test, Multiple Linear Regression Analysis, Determination Analysis, F-Test and t-Test, using the IBM SPSS Statistic 25 software. The results of the analysis prove that there is a positive and significant influence simultaneously and partially between online customer reviews and online customer ratings on Shopee customer purchase intention in Gianyar Regency. The critical review in this paper can contribute to researchers in the field of marketing, making use of online commerce to explore opportunities for future research gaps, explore various other signals that have not been revealed and develop more diverse future studies.

Prediction of Customer Review's Helpfulness Based on Feature Engineering Driven Deep Learning Model

Online consumer reviews play a pivotal role in boosting online shopping. After Covid-19, the e-commerce industry has been grown exponentially. The e-commerce industry is greatly impacted by the online customer reviews, and a lot of work has been done in this regard to identify the usefulness of reviews for purchasing online products. In this proposed work, predicting helpfulness is taken as binary classification problem to identify the helpfulness of a review in context to structural, sentimental, and voting feature sets. In this study, the authors implemented various leading ML algorithms such as KNN, LR, GNB, LDA and CNN. In comparison to these algorithms and other existing state of art methods, CNN yielded better classification results, achieving highest accuracy of 95.27%. Besides, the performance of these models was also assessed in terms of precision, recall, F1 score, etc. The results shown in this paper demonstrate that proposed model will help the producers or service providers to improve and grow their business.

Effect of Digital Marketing, Influencer Marketing and Online Customer Review on Purchase Decision: A Case Study of Cake Shop "Lu’miere"

Lu'Miere is a brand of cake shop owned by Anang Hermansyah and Ashanty. Located in Pondok Indah Jakarta, this cake shop has succeeded in attracting many cake lovers. Moreover, this store offers an interesting variety of menus and provides a unique atmosphere. This study aims to examine the effect of Digital Marketing, Influencer Marketing, and Online Customer Reviews on purchase decisions from customers of Lu'Miere. The objects used in this study are the Lu'Miere's Customers. Analysis of the data used in this study begins with direct observation and exploration to develop a conceptual framework for the study, then distributing questionnaires to 101 respondents from the customer of Lu'Miere. The results showed that Digital Marketing, Influencer Marketing, and Online Customer Review significantly affect purchasing decisions. The R2 value of 0.585 means that the percentage of the influence of digital marketing, influencer marketing, and online customer review on purchasing decisions is 58.5%. At the same time, the rest is influenced by other variables that are not included in this model.

The effect of Online Costumer Reviews and Influencer Marketing on Shopee Purchasing Decisions

The purpose of this research id to determine the partial and simultaneous effect of the variables studied. In this research using quantitative research approach with a sample number of 99 students with multiple regression analysis methodes spss aplikasi assistance 25. This research was conducted at (Case Study of Undergraduate Students) STIE Amkop Makassar. The purpose of this research shows that from the results of data management using the SPSS 25 application, it is known that that there is a positive and significant effect of online customer review on purcashing decision, and so is partial teasting of influencer marketing on meaningful perfomance of positive and significant effect, while simultaneous testing shows that online customer review and influencer marketing have a positive and significant effect on perfomance

Influence of Influencer Marketing Strategy and Online Customer Reviews on Purchase Intention of Sociolla Customer (Case Study on AB Students at Polines 2018 – 2019)

<em>This study aims to determine and analyze the influence of influencer marketing strategies and online customer reviews on purchase intention of Sociolla users. The population in this study were students of the Semarang State Polytechnic Department of Business Administration in the 2018 - 2019 batch, which amounted to 376 students. The number of samples as many as 80 respondents with sampling using purposive sampling technique. The type of this research is quantitative research and data collection in this research is literature study and questionnaires. The scale used in this research questionnaire is the Likert scale. The analytical method used is descriptive analysis, instrument test, classical assumption test, homepage linear regression analysis method, and hypothesis testing. Calculations were carried out using SPSS software. Based on the calculation of the regression equation, namely Y = 0.940 + 0.2740X1 + 0.342X2. So it can be said that influencer marketing (X1) and online customer reviews (X2) have a significant effect on purchase intention (Y).</em>

A research article on Importance of Online Customer Reviews on Customer Purchase

Online product reviews have grown into a valuable source of information influencing purchases with the rise of digital and social media. Customer reviews are a type of feedback for online stores and electronic commerce. Nowadays, consumers have constant access to online product reviews because to resources like smart phones, 24x7 internet access, and other resources to access websites. This product review has developed into a well-liked and successful marketing and sales tool that influences consumer product purchase behaviour. There are many platforms, such as online retailer websites, E-Commerce websites, brand websites, brand community blogs, and third-party reviews, where consumers can participate and engage in discussions about their purchase and consumption experience. Consumer opinions may influence the overall product sales and assist a customer in making a purchase. The goal of this study was to determine whether there is a link between consumer reviews and consumer buying habits. The purpose of this study is to clarify how various internet reviews affect consumers' purchasing decisions and intents. Online customer reviews (OCRs) are now a key resource for product details and have a significant impact on consumers' purchasing decisions. The decision-making process for consumer purchases has been significantly impacted as a result. OCRs' implications on customer behaviour have recently drawn a lot of scholarly interest. Therefore, it is necessary to review these impacts. The most recent research on the connections and linkages between OCRs and client buying is thus examined in this study.

A new theoretical model for online customer review intention

PurposeThis study aims to investigate the insights on how international customer behavior is impacted toward online customer review (OCR) by the mediating effects of social and personal norms in the varied cultural context. The study also investigates how support of peer influence could moderate the effect of OCR.Design/methodology/approachThis study has used socialization theory, congruity theory and theory of planned behavior along with studies of different literature to develop a conceptual model. The conceptual model has been validated using PLS-SEM analysis with survey considering 306 usable respondents. The mediating effects and moderating impacts have been analyzed by mediating analysis process (process tool) and multi group analysis, respectively.FindingsThe results of the model, with 62% explanative power, highlight that social norm acts as a strong mediating variable to impact OCR intention while peer influence acts as a vital moderator to impact OCR intention.Research limitations/implicationsThe theoretical model provides a solid foundation to future researchers for further study in this field. This study also provides the practitioners a unique opportunity towards understanding customer motivation for OCR intention. Accordingly, practitioners could bring some transformational changes in their organizations for getting better reviews from the customers.Originality/valueThis study develops a unique theoretical model with high explanative power. Very few studies have ventured in this field. This study has added value to the body of literature on consumer behavior as well as individualism. Furthermore, this study has developed some of the novel relationships between different factors such as individualism, peer influence, international consumers, social norm and so on in the context of OCR which is one of the unique contributions of this study.