• Title, Summary, Keyword: Product Review

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Economic Evaluation of Delayed Product Differentiation: Literature Review (제품 차별화 지연생산의 경제적 타당성: 문헌연구)

  • Lee, Ho-Chang
    • IE interfaces
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    • v.17 no.1
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    • pp.56-70
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    • 2004
  • Expanding product variety and high customer service provision place an enormous burden on demand forecasting and the matching of supply with demand in a supply chain. Postponement of product differentiation has been found to be powerful means to improve supply chain performance in the presence of increasing product variety. Delaying the point of product differentiation implies that the process would not commit the work-in-process into a particular finished product until a later point. This paper reviews the recent analytical models that quantify the value of delayed product differentiation. We conclude the literature review by summarizing and synthesizing the economic evaluation of the postponement and outline directions for future research.

Performance Evaluation of Review Spam Detection for a Domestic Shopping Site Application (국내 쇼핑 사이트 적용을 위한 리뷰 스팸 탐지 방법의 성능 평가)

  • Park, Jihyun;Kim, Chong-kwon
    • Journal of KIISE
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    • v.44 no.4
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    • pp.339-343
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    • 2017
  • As the number of customers who write fake reviews is increasing, online shopping sites have difficulty in providing reliable reviews. Fake reviews are called review spam, and they are written to promote or defame the product. They directly affect sales volume of the product; therefore, it is important to detect review spam. Review spam detection methods suggested in prior researches were only based on an international site even though review spam is a widespread problem in domestic shopping sites. In this paper, we have presented new review features of the domestic shopping site NAVER, and we have applied the formerly introduced method to this site for performing an evaluation.

User Sentiment Analysis on Amazon Fashion Product Review Using Word Embedding (워드 임베딩을 이용한 아마존 패션 상품 리뷰의 사용자 감성 분석)

  • Lee, Dong-yub;Jo, Jae-Choon;Lim, Heui-Seok
    • Journal of the Korea Convergence Society
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    • v.8 no.4
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    • pp.1-8
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    • 2017
  • In the modern society, the size of the fashion market is continuously increasing both overseas and domestic. When purchasing a product through e-commerce, the evaluation data for the product created by other consumers has an effect on the consumer's decision to purchase the product. By analysing the consumer's evaluation data on the product the company can reflect consumer's opinion which can leads to positive affect of performance to company. In this paper, we propose a method to construct a model to analyze user's sentiment using word embedding space formed by learning review data of amazon fashion products. Experiments were conducted by learning three SVM classifiers according to the number of positive and negative review data using the formed word embedding space which is formed by learning 5.7 million Amazon review data.. Experimental results showed the highest accuracy of 88.0% when learning SVM classifier using 50,000 positive review data and 50,000 negative review data.

A Study on Factory Review Using Virtual Reality Model based on P3R Information (P3R 정보 기반의 가상현실 모델을 이용한 공장 품평에 관한 연구)

  • Lee, Ju-Yeon;Choi, Sang-Su;Park, Yang-Ho;Noh, Sang-Do
    • Korean Journal of Computational Design and Engineering
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    • v.15 no.5
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    • pp.343-353
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    • 2010
  • Time to market and cost-efficient production are some of the challenge that manufacturing industries face. Modern methods of engineering can't help such organizations attain competitive advantage. To help these situations, MEMPHIS (Middleware for Exchanging Machinery and Product Data in Highly Immersive Systems) was introduced as an approach that enables VE (Virtual Engineering) and links engineering applications with VR (Virtual Reality) solutions. Thus an environment is provided to implement virtual design reviews and enable the application of virtual prototyping methods. However MEMPHIS could just handle Product data for virtual design review and simulation. In this paper, we newly define and develop the extended MEMPHIS that enables virtual manufacturing with Process, Resource and Plant data as well as Product data.

A Study of the Product Safety Review for the Food Industry: Safety Review Process - Case study - (식품안전을 위한 제품안전 검토 절차(PSR-Logic)에 관한 연구 - 사례 연구)

  • Hyun One-Soon;Lee Yong-Soo;Jung Soo-Il
    • Journal of the Korea Safety Management and Science
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    • v.7 no.5
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    • pp.85-96
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    • 2005
  • The purpose of the research is to discuss the product safety procedures for the food industry The producer and supplier of the products should satisfy the increasing consumer safety needs. To develop and produce safe products, the food industry must rigorously perform potential hazard findings and very thorough risk analysis to detect even the very minute potential danger. The ultimate product liability rests with the consumer safety and the manufacturer's capability which competes in the market places. This is especially important in the food industry. However, small to medium sized food producing companies are facing challenges in this area due to their overall capabilities. Therefore this research presents safety procedures which are relatively simple to implement.

Your Expectation Matters When You Read Online Consumer Reviews: The Review Extremity and the Escalated Confirmation Effect

  • Lee, Jung;Lee, Hong Joo
    • Asia pacific journal of information systems
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    • v.26 no.3
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    • pp.449-476
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    • 2016
  • This study examines how an initially perceived product value affects consumer's purchase intention after reading online reviews with various tones. The study proposes that associations among initially perceived overall product value, degree of confirmation resulting from reading the reviews, and final purchase intention differ across review tones such that 1) when the tone is favorable, the effect of an initially perceived product value is stronger than when the tone is critical, and 2) when the tone is extreme, the effect of confirmation is stronger than when the tone is moderate. The survey was conducted with 276 online shopping mall users in Korea, and most of the hypotheses were supported. This study asserts that the effects of online reviews should be considered together with customer's level of expectation formed prior to reading online reviews, which resulted from extensive search and screening processes that the customer went through before reading online reviews.

Improving Development Process for Product Safety

  • Jung, Won
    • Proceedings of the Korean Reliability Society Conference
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    • pp.262-267
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    • 2004
  • In designing and evaluating a new product, the company needs to give thought to the entire spectrum of produceability, usability, and ultimate reliability, as well as safety of users. For each design review(DR) stage, a formal, systematic, documented review and evaluation of a product design is conducted to assure that the product is safe and reliable, that costs and materials have been optimized, and that the design complies with its specifications and requirements. This paper presents how to improve development process for product's safety and reliability. The process requires gathering the appropriate information, determining the limits of the product, estimating risk associated with the task-hazard combinations, and reducing risk according to a prioritized procedure.

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Impact of Semantic Characteristics on Perceived Helpfulness of Online Reviews (온라인 상품평의 내용적 특성이 소비자의 인지된 유용성에 미치는 영향)

  • Park, Yoon-Joo;Kim, Kyoung-jae
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.29-44
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    • 2017
  • In Internet commerce, consumers are heavily influenced by product reviews written by other users who have already purchased the product. However, as the product reviews accumulate, it takes a lot of time and effort for consumers to individually check the massive number of product reviews. Moreover, product reviews that are written carelessly actually inconvenience consumers. Thus many online vendors provide mechanisms to identify reviews that customers perceive as most helpful (Cao et al. 2011; Mudambi and Schuff 2010). For example, some online retailers, such as Amazon.com and TripAdvisor, allow users to rate the helpfulness of each review, and use this feedback information to rank and re-order them. However, many reviews have only a few feedbacks or no feedback at all, thus making it hard to identify their helpfulness. Also, it takes time to accumulate feedbacks, thus the newly authored reviews do not have enough ones. For example, only 20% of the reviews in Amazon Review Dataset (Mcauley and Leskovec, 2013) have more than 5 reviews (Yan et al, 2014). The purpose of this study is to analyze the factors affecting the usefulness of online product reviews and to derive a forecasting model that selectively provides product reviews that can be helpful to consumers. In order to do this, we extracted the various linguistic, psychological, and perceptual elements included in product reviews by using text-mining techniques and identifying the determinants among these elements that affect the usability of product reviews. In particular, considering that the characteristics of the product reviews and determinants of usability for apparel products (which are experiential products) and electronic products (which are search goods) can differ, the characteristics of the product reviews were compared within each product group and the determinants were established for each. This study used 7,498 apparel product reviews and 106,962 electronic product reviews from Amazon.com. In order to understand a review text, we first extract linguistic and psychological characteristics from review texts such as a word count, the level of emotional tone and analytical thinking embedded in review text using widely adopted text analysis software LIWC (Linguistic Inquiry and Word Count). After then, we explore the descriptive statistics of review text for each category and statistically compare their differences using t-test. Lastly, we regression analysis using the data mining software RapidMiner to find out determinant factors. As a result of comparing and analyzing product review characteristics of electronic products and apparel products, it was found that reviewers used more words as well as longer sentences when writing product reviews for electronic products. As for the content characteristics of the product reviews, it was found that these reviews included many analytic words, carried more clout, and related to the cognitive processes (CogProc) more so than the apparel product reviews, in addition to including many words expressing negative emotions (NegEmo). On the other hand, the apparel product reviews included more personal, authentic, positive emotions (PosEmo) and perceptual processes (Percept) compared to the electronic product reviews. Next, we analyzed the determinants toward the usefulness of the product reviews between the two product groups. As a result, it was found that product reviews with high product ratings from reviewers in both product groups that were perceived as being useful contained a larger number of total words, many expressions involving perceptual processes, and fewer negative emotions. In addition, apparel product reviews with a large number of comparative expressions, a low expertise index, and concise content with fewer words in each sentence were perceived to be useful. In the case of electronic product reviews, those that were analytical with a high expertise index, along with containing many authentic expressions, cognitive processes, and positive emotions (PosEmo) were perceived to be useful. These findings are expected to help consumers effectively identify useful product reviews in the future.

Online Word-of-Mouth: Motivation for Writing Product Reviews on Internet Shopping Sites (온라인 구전 커뮤니케이션: 온라인 쇼핑몰에서의 소비자 사용후기 작성동기)

  • Kim, Sung-Hee
    • Journal of Fashion Business
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    • v.14 no.2
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    • pp.81-94
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    • 2010
  • The online shopping environment has radically changed consumer shopping behavior. Without the actual physical shopping experience in a brick-and-mortar store, consumers make purchasing decisions over the Internet. They make an effort to obtain product information not only from online merchants, but also from previous purchasers in order to make an informed decision. Accordingly, customer comments are expected to have a significant impact on decisions to purchase goods and services online. This paper focuses on one type of electronic word-of-mouth, the online consumer review. It derives several motivations why customers post product reviews on shopping mall sites. Customer motives were identified through an in depth one-on-one interview with twenty female respondents conducted twice from June $17^{th}$ to September $11^{th}$, 2009. The interviews lasted between 40 and 60 minutes. The results showed that consumers write product reviews based on six motivations: to receive a reward or remuneration for writing a product review, to share information with other customers, to improve the quality of goods and services, to reduce customer dissatisfaction, to recommend products and services, and to derive pleasure.

An Empirical Study on the Interaction Effects between the Customer Reviews and the Customer Incentives towards the Product Sales at the Online Retail Store

  • Kim, J.B.;Shin, Soo Il
    • Asia pacific journal of information systems
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    • v.25 no.4
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    • pp.763-783
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    • 2015
  • Online customer reviews (i.e., electronic word-of-mouth) has gained considerable interest over the past years. However, a knowledge gap exists in explaining the mechanisms among the factors that determine the product sales in online retailing environment. To fill the gap, this study adopts a principal-agent perspective to investigate the effect of customer reviews and customer incentives on product sales in online retail stores. Two customer review factors (i.e., average review ratings and the number of reviews) and two customer incentive factors (i.e., price discounts and special shipping offers) are used to predict product sales in regression analysis. The sales ranking data collected from the video game titles at Amazon.com are used to analyze the direct effects of the four factors and the interaction effects between customer review and customer incentive factors to product sales. Result reveals that most relationships exist as hypothesized. The findings support both the direct and interaction effects of customer reviews and incentive factors on product sales. Based on the findings, discussions are provided with regard to the academic and practical contributions.