• Fashion & Textile Research Journal
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• v.25 no.4
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• pp.419-428
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• 2023

This study examines customer reviews from online stores of Korean vegan fashion brands to determine the qualities that customers value in vegan fashion items. For this purpose, we conducted a case study of online reviews-2,285 reviews were collected and analyzed. The results are as follows: The clothing evaluation criteria for vegan fashion products can be divided into four categories: aesthetics, material characteristics, affordability, and characteristics. This suggests that evaluation standards for vegan fashion items operate at multiple levels. The animal welfare aspect of the product was the most important factor, followed closely by how well the clothes fit. High-quality vegan materials and the use of recycled materials that are environmentally friendly were emphasized. The findings of this study suggest that even for vegan products, stylistic features remain an essential component of fashion items. To understand the main aspects of clothing evaluation criteria in the current vegan fashion market, this study differs from other studies in that it examined online reviews of vegan fashion brands. This comprehensive analysis contributes to a deeper understanding of customer preferences and highlights the importance of ethical considerations alongside style in the evaluation of vegan fashion items, providing valuable insights for the industry. Moving forward, this study is significant in suggesting that vegan fashion brands should develop their products as well as their brands, capitalizing on the demand for ethically conscious and stylish options.

• Journal of Information Technology Applications and Management
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• v.13 no.3
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• pp.181-200
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• 2006

The purpose of this study is to examine factors influencing online product transformation focusing on benefits of online shopping and word of mouth. Generally, it has been known that buying search goods is more proper than experience goods in the online. However benefits of online shopping and word of mouth make product transformation from experience goods to search goods and the product transformation promote the purchase of experience goods online. We developed a conceptual model of online product transformation including benefits of online shopping(e.g. good price and convenience), online word of mouth (e.g. bulletin board and consumer reviews), and consumer characteristics (e.g. innovativeness and Internet usage). Also, we suggest several research propositions on online product transformation. The implications for marketing strategies of experience goods and furher research direction are suggested.

• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.55-60
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• 2020

As personalized customer services create a society that emphasizes the personality of an individual, the number of product reviews and quantity of user data generated by users on the internet in mobile shopping apps and sites are increasing. Such product review data are classified as unstructured data. Unstructured data have the potential to be transformed into information that companies and users can employ, using appropriate processing and analyses. However, existing systems do not reflect the detailed information they collect, such as user characteristics, purchase preference, or purchase priority while analyzing review data. Thus, it is challenging to provide customized recommendations for various users. Therefore, in this study, we have developed a product recommendation system that takes into account the user's priority, which they select, when searching for and purchasing a product. The recommendation system then displays the results to the user by processing and analyzing their preferences. Since the user's preference is considered, the user can obtain results that are more relevant.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.1-15
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• 2022

In this study, text analysis was performed on the mealkit product review data to identify factors affecting the evaluation of the mealkit product. The data used for the analysis were collected by scraping 334,498 reviews of mealkit products in Naver shopping site. After preprocessing the text data, wordclouds and sentiment analyses based on word frequency and normalized TF-IDF were performed. Logistic regression model was applied to predict the polarity of reviews on mealkit products. From the logistic regression models derived for each product category, the main factors that caused positive and negative emotions were identified. As a result, it was verified that text analysis can be a useful tool that provides a basis for maximizing positive factors for a specific category, menu, and material and removing negative risk factors when developing a mealkit product.

• Journal of Fashion Business
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• v.14 no.5
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• pp.49-65
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• 2010

The purpose of this paper is to derive the categories of negative e-WOM (electronic word of mouth) via consumer review. Disclosing the details of negative e-WOM based consumer reviews has never been done before. For this reason, a content analysis was adopted to provide knowledge and understanding of the phenomenon. This paper analyzes the content of 630 consumer reviews posted on the open market internet site, www.auction.co.kr. The analysis was conducted from October 20th, 2008 to March 10th, 2009. The results indicated that the negative e-WOM based consumer reviews can be divided into two categories: the cognitive evaluation and the expression of consumer's emotion. The category of cognitive evaluation is consisted of negative e-WOM of product, negative e-WOM of service, and warning about the risk of purchasing products. The category of expressing consumers' emotion are composed of venting customers' dissatisfaction and passive response of dissatisfaction. Investigating the details of negative e-WOM has a number of implications. Most importantly, the results revealed multidimensional structure of negative e-WOM. This understanding of negative e-WOM communication allows marketers to improve products and services that better meet customers' current and future needs.

• Knowledge Management Research
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• v.22 no.3
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• pp.273-293
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• 2021

Due to the COVID-19 pandemic, the size of the e-commerce has been increased rapidly. This pandemic, which made contact-less communication culture in everyday life made the e-commerce market to be opened even to the consumers who would hesitate to purchase and pay by electronic device without any personal contacts and seeing or touching the real products. Consumers who have experienced the easy access and convenience of the online purchase would continue to take those advantages even after the pandemic. During this time of transformation, however, the size of information source for the consumers has become even shrunk into a flat screen and limited to visual only. To provide differentiated and competitive information on products, companies are adopting AR/VR and steaming technologies but the reviews from the honest users need to be recognized as important in that it is regarded as strong as the well refined product information provided by marketing professionals of the company and companies may obtain useful insight for product development, marketing and sales strategies. Then from the consumer's point of view, if the ratings of reviews are widely diverged how consumers would process the review information before purchase? Are non-converged ratings always unreliable and worthless? In this study, we analyzed how consumer's regulatory focus moderate the attitude to process the diverged information. This experiment was designed as a 2x2 factorial study to see how the variance of product review ratings (high vs. low) for cosmetics affects product attitudes by the consumers' regulatory focus (prevention focus vs. improvement focus). As a result of the study, it was found that prevention-focused consumers showed high product attitude when the review variance was low, whereas promotion-focused consumers showed high product attitude when the review variance was high. With such a study, this thesis can explain that even if a product with exactly the same average rating, the converged or diverged review can be interpreted differently by customer's regulatory focus. This paper has a theoretical contribution to elucidate the mechanism of consumer's information process when the information is not converged. In practice, as reviews and sales records of each product are accumulated, as an one of applied knowledge management types with big data, companies may develop and provide even reinforced customer experience by providing personalized and optimized products and review information.

• Korean Journal of Human Ecology
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• v.19 no.2
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• pp.311-323
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• 2010

This study includes definitions and major issues relating to product safety, and reviews about product safety laws of Korea and of other countries. In addition, this study suggests several ideas for a future governmental policy concerning product safety and the government policies to guide in securing consumers' safety of products. First, we need to set up consumer safety policies and laws dealing with complex consumer safety issues and to integrate existing laws for the safety of products. Second, opening a consumer safety agency and training workers who have relation to the safety policy, as a profession, are necessary. Third, it is required to redefine the product safety guidelines, strengthen the safety policy and to minimize safety regulations by the government directly. Fourth, each product of the safety management policies must be regularly evaluated and given feedback for improving its effectiveness. Fifth, information gathering, disclosing, and having a feedback system related to product safety should be rebuilt for the effective management of unsafe products. In addition, laws and the aims of product safety management being changed to focus on the consumers, control on imported products, collaboration with network and mutual-assistance systems of product safety-related agencies including international organizations and major countries and taking leading roles in the world are essential.

• Asia pacific journal of information systems
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• v.30 no.4
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• pp.741-757
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• 2020

The outbreak of COVID-19 has changed our lifestyle. People spend much more time on YouTube, SNS and online shopping than before. Accordingly, the number of product review videos are steeply increasing in YouTube platform. When people watched the review videos, they might search additional information if they liked the videos. This study aims to investigate how the informativeness and the degree of attention gathering of product review videos influence on the product information sourcing intention and persuasion knowledge. We also try to find whether prior YouTube experience affects the relationship between the degree of attention gathering and persuasion knowledge. We conducted an online survey on 499 participants and analyzed using partial least square methods. Results show that 1) informativeness and the degree of attention gathering towards product review videos influence on the product information sourcing intention and user's persuasion knowledge. 2) Viewers' YouTube experiences moderate the increase of the viewers' persuasion knowledge caused by increasing the degree of viewers' attention gathering. This study implies that YouTube product review videos could be created in strategic manners. Also, it could be inferred that consumers' prior YouTube experiences may reduce negative potentials of the degree of attention gathering onto persuasion knowledge.

• Proceedings of the Safety Management and Science Conference
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• 2003.11a
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• pp.167-172
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• 2003

This study reviews the revisions and updates to the Release 3.5 version of the TL 9000 Measurements Handbook. This paper introduces the new organization of QuEST Forum Work Groups(WGs) and how to apply TL 9000 standards in software product lifecycle.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.151-161
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• 2016

In the era of the Web 2.0, characterized by the openness, sharing and participation, it is easy for internet users to produce and share the data. The amount of the unstructured data which occupies most of the digital world's data has increased exponentially. One of the kinds of the unstructured data called personal online product reviews is necessary for both the company that produces those products and the potential customers who are interested in those products. In order to extract useful information from lots of scattered review data, the process of collecting data, storing, preprocessing, analyzing, and drawing a conclusion is needed. Therefore we introduce the text-mining methodology for applying the natural language process technology to the text format data like product review in order to carry out extracting structured data by using R programming. Also, we introduce the data-mining to derive the purpose-specific customized information from the structured review information drawn by the text-mining.