• Title/Summary/Keyword: Online Product Reviews

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Analysis of Marketing Channel Competition under Network Externality (네트워크 외부성을 고려한 마케팅 채널 경쟁 분석)

  • Cho, Hyung-Rae;Rhee, Minho;Lim, Sang-Gyu
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.1
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    • pp.105-113
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    • 2017
  • Network externality can be defined as the effect that one user of a good or service has on the value of that product to other people. When a network externality is present, the value of a product or service is dependent on the number of others using it. There exist asymmetries in network externalities between the online and traditional offline marketing channels. Technological capabilities such as interactivity and real-time communications enable the creation of virtual communities. These user communities generate significant direct as well as indirect network externalities by creating added value through user ratings, reviews and feedback, which contributes to eliminate consumers' concern for buying products without the experience of 'touch and feel'. The offline channel offers much less scope for such community building, and consequently, almost no possibility for the creation of network externality. In this study, we analyze the effect of network externality on the competition between online and conventional offline marketing channels using game theory. To do this, we first set up a two-period game model to represent the competition between online and offline marketing channels under network externalities. Numerical analysis of the Nash equilibrium solutions of the game showed that the pricing strategies of online and offline channels heavily depend not only on the strength of network externality but on the relative efficiency of online channel. When the relative efficiency of online channel is high, the online channel can greatly benefit by the network externality. On the other hand, if the relative efficiency of online channel is low, the online channel may not benefit at all by the network externality.

Consumer Awareness and Preferences Regarding Apparel Sizing in Online Shopping (온라인 쇼핑에서 의류 제품 사이즈에 대한 소비자 인식 및 관여도 조사)

  • Eun-Jin Jeon;Ah Lam Lee
    • Fashion & Textile Research Journal
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    • v.26 no.1
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    • pp.25-34
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    • 2024
  • This study investigates consumer awareness and concerns regarding apparel sizing in the realm of online shopping. A survey was conducted with 450 women aged 18-59 who had engaged in online clothing purchases within the past year. It was observed that consumers shop for clothes online an average of 1.6 times per month, with those under 50 shopping more frequently. The importance of size is higher when buying pants than jackets, especially in online shopping compared to offline purchases. Key references guiding online shopping decisions encompassed product sizing codes, customer reviews, and garment dimensions, which were notably favored by consumers with significant concerns. Respondents opted for Korean-style sizing codes for jackets but chose inch-sizing codes for pants. While awareness of height and weight remains high, knowledge of specific body measurements crucial for clothing size design is lacking, suggesting inadequate communication of size information. Respondents prioritized specific areas for jacket and pants fit, yet the lack of comprehensive self-measurements beyond height and weight might present challenges in determining fit based solely on product dimensions. To address this issue, online retailers should display essential garment dimensions and visually suggest clothing sizes according to various body types. These findings provide valuable insights for online retailers to effectively present size information and lay a foundational framework for consumer size education.

The Acceptance of Customer Reviews in Taobao (타오바오 쇼핑몰 이용자의 구매후기 수용에 관한 연구)

  • Hao, Qi-Ying;Lee, Sang-Joon;Lee, Kyeong-Rak
    • Journal of the Korea Convergence Society
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    • v.6 no.4
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    • pp.205-212
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    • 2015
  • This paper aims to investigate key factors affecting customer adoption of the online review from the three perspectives such as customer review characteristics, reviewer characteristics, and customer characteristics. We collected data on customers who have experience in purchasing products in Taobao. The major findings are as follows. First, the customer review amount and vividness are not directly related to customer adoption of the online review. Second, the trust of reviewer and perceived similarity have positive effects on customer adoption of the online review. Third, the prior knowledge and product involvement increase customer adoption of the online review. Finally, customers' purchase intention is greatly determined by customer adoption of the online review. This paper presents the importance of the management of customer reviews and management method for the stakeholders of shopping mall to advancing Chinese market.

A Study on the Enhancing Recommendation Performance Using the Linguistic Factor of Online Review based on Deep Learning Technique (딥러닝 기반 온라인 리뷰의 언어학적 특성을 활용한 추천 시스템 성능 향상에 관한 연구)

  • Dongsoo Jang;Qinglong Li;Jaekyeong Kim
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.41-63
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    • 2023
  • As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.

Digital Nudge in an Online Review Environment: How Uploading Pictures First Affects the Quality of Reviews (온라인 리뷰 환경에서의 디지털 넛지: 사진을 먼저 업로드 하는 행동이 리뷰의 품질에 미치는 영향 )

  • Jaemin Lee;Taeyoung Kim;HoGeun Lee
    • Information Systems Review
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    • v.25 no.1
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    • pp.1-26
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    • 2023
  • Consumers tend to trust information provided by other consumers more than information provided by sellers. Therefore, while inducing consumers to write high-quality reviews is a very important task for companies, it is not easy to produce such high-quality reviews. Based on previous research on review writing and memory recall, we decided to develop a way to use digital nudge to help consumers naturally write high-quality reviews. Specifically, we designed an experiment to verify the effect of uploading a photo during the online review process on the quality of review of the review writer. We then recruited subjects and then divided them into groups that upload photos first and groups that do not. A task was assigned to each subject to write positive and negative reviews. As a result, it was confirmed that the behavior of uploading a photo first increases the review length. In addition, it was confirmed that when online users who upload photos first have extremely negative satisfaction with the product, the extent of two-sidedness of the review content increases.

A Study on the Evaluation Differences of Korean and Chinese Users in Smart Home App Services through Text Mining based on the Two-Factor Theory: Focus on Trustness (이요인 이론 기반 텍스트 마이닝을 통한 한·중 스마트홈 앱 서비스 사용자 평가 차이에 대한 연구: 신뢰성 중심)

  • Yuning Zhao;Gyoo Gun Lim
    • Journal of Information Technology Services
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    • v.22 no.3
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    • pp.141-165
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    • 2023
  • With the advent of the fourth industrial revolution, technologies such as the Internet of Things, artificial intelligence and cloud computing are developing rapidly, and smart homes enabled by these technologies are rapidly gaining popularity. To gain a competitive advantage in the global market, companies must understand the differences in consumer needs in different countries and cultures and develop corresponding business strategies. Therefore, this study conducts a comparative analysis of consumer reviews of smart homes in South Korea and China. This study collected online reviews of SmartThings, ThinQ, Msmarthom, and MiHome, the four most commonly used smart home apps in Korea and China. The collected review data is divided into satisfied reviews and dissatisfied reviews according to the ratings, and topics are extracted for each review dataset using LDA topic modeling. Next, the extracted topics are classified according to five evaluation factors of Perceived Usefulness, Reachability, Interoperability,Trustness, and Product Brand proposed by previous studies. Then, by comparing the importance of each evaluation factor in the two datasets of satisfaction and dissatisfaction, we find out the factors that affect consumer satisfaction and dissatisfaction, and compare the differences between users in Korea and China. We found Trustness and Reachability are very important factors. Finally, through language network analysis, the relationship between dissatisfied factors is analyzed from a more microscopic level, and improvement plans are proposed to the companies according to the analysis results.

A Study on the Effects of Quality Characteristics of Online Environment-Friendly Agricultural Products Shopping Malls affecting Customer Trust and Purchase Intention

  • PARK, Duk-Gun;SHIN, Choung-Seob
    • East Asian Journal of Business Economics (EAJBE)
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    • v.8 no.1
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    • pp.1-19
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    • 2020
  • Purpose - This study is to classify quality characteristics of online environment-friendly agricultural products shopping malls into 6 categories and to empirically test their relationship with customer trust, perceived manageability, perceived utility and purchase intention. Research design, data, and methodology - This study targeted adults who have purchased ecofriendly agricultural production online malls for 4 weeks from September 3 to September 30, 2019. The survey type used was a structuralized self-report survey questionnaire made to meet the research purpose in 2019 as the time range. Out of 800 questionnaires, 500 copies are used after excluding surveys with insincere responses. Results - First, results to hypothesis 1, which was about independent variables and customer trust. Analysis showed that health, familiarity, platform reputation, reviews and product quality were found to have significant effect on customer trust; the hypothesis was adopted. On the other hand, system security did not affect customer trust significantly; it was rejected. Second, customer trust was shown to have significant effect on perceived manageability and perceived utility, so the hypothesis was adopted. Third, the hypothesis that perceived manageability moves onto perceived utility was adopted. Moreover, the hypothesis that perceived manageability moves onto purchase intention and the hypothesis that perceived utility moves onto purchase intention were adopted as well. Conclusions - Furthermore, the results of the study imply that it's imperative for online environment-friendly agricultural products shopping malls to consider their characteristics as the means to increase purchase intention of customers.

Antecedents to Consumer Satisfaction with Laundry Detergents and Fabric Softeners in Thailand: A SEM Analysis

  • CHEEWAPATTANANUKUL, Nawin;SAENGNOREE, Amnuay;DEEBHIJARN, Samart
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.8
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    • pp.157-167
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    • 2022
  • The global laundry detergents market in 2021 was valued at nearly $121 billion, with consumers being reported as heightening their search for hygienic products capable of fighting viruses. Therefore, the researchers undertook a study to determine how product innovation (PI), product quality (PQ), and product attitude (PA) effects Thai consumers' satisfaction (CS) with their purchase of laundry detergent and fabric softener. After the questionnaire's validity and reliability confirmation, the authors used multi-stage random sampling by region and province in January and February 2022 to collect 520 questionnaires. LISREL 9.10 was used in the CFA and SEM analysis of the six hypotheses, which were determined to be supported. The results showed that all three causal variables positively influenced CS, with a total effect (TE) R2 value = 87%. Also, latent variable total effect (TE) values showed that PI was strongest (0.93), then PQ (0.56), and finally, PA (0.54). Therefore, consumer satisfaction is essential in a firm's ongoing development and sustainability in a highly competitive, globalized world. Organizations must develop competitive strategies that adjust to consumer needs. Management must monitor online and social media sources where product reviews are given and adjust their strategies accordingly.

A Study of Customer Review Analysis for Product Development based on Korean Language Processing (한글 정형화 방법에 기반한 상품평 감성분석의 제품 개발 적용 방법 연구)

  • Woo, JeHyuk;Jeong, MinKyu;Lee, JaeHyun;Suh, HyoWon
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.1
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    • pp.49-62
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    • 2022
  • Online customer review data can be easily collected on the Internet and also they describe sentimental evaluation of a product in different aspects. Previous sentiment analysis studies evaluate the degree of sentiment with review data, which may have multiple sentences describing different product aspects. Since different aspects of a product can be described in a sentence, the proposed method suggested analyzing a sentence to build a pair of a product aspect terms and sentimental terms. Bidirectional LSTM and CRF algorithms were used in this paper. A pair of aspect terms and sentimental terms are evaluated by pre-defined evaluation rules. The paper suggested using the result of evaulation as inputs of QFD, so that the quantified customer voices effect on the requirements of a new product. Online reviews for a hair dryer were used as an example showing that the proposed approach can derive reasonable sentiment analysis results.

A Text Mining Analysis of Attributes for Satisfaction and Effect of Consumer Ratings to Korea and China Duty Free Stores - Focusing on Chinese Tourists - (텍스트 마이닝을 통한 한국과 중국 시내면세점 만족 속성과 소비자 평점에 미치는 영향 분석 -중국인 관광객을 중심으로)

  • Yang, DaSom;Kim, Jong Uk
    • Journal of Digital Convergence
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    • v.18 no.8
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    • pp.1-9
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    • 2020
  • This study aims to find new attributes by analyzing Korea and China duty free store online reviews and examine the influence of these attributes on star ratings(satisfaction)of duty free store. For study, we used Dazhong Dianping that largest online review site in China. Using R, we analyzed 5,659 reviews of Korea duty free store and 4,051 reviews of China duty free store. According to the analysis, Sale, Food and Membership attributes had a positive effect on star rating of Korea duty free store. Sale, Product, Airport, Food and Membership had a positive effect on star rating of China duty free store. This study has identified new factors such as food that showed the importance of providing space of restaurants while shopping at duty free store. This study has contributed to the existing literature by finding new attribute such as food. Practically, this finding will help to duty free industry workers better understand the impact of providing space of restaurants on duty free store.