• Journal of Information Technology Applications and Management
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• v.16 no.4
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• pp.41-58
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• 2009

This research investigated how people are influenced to adopt online review. We applied the Elaboration Likelihood Model (ELM) and the Technology Acceptance Model (TAM) to this study. Our research model highlights the assessment of online review usefulness as a mediator from online review quality to online review adoption. This research predicted online review consensus has a role to bulid up online reviw usefulness. This study also includes vividness and perceived similarity as determinants of online review quality. Survey data reflect user's perceptions of actual online review they read. Results support most of research hypotheses except hypothesis related to moderating effect of user involvement. This research offers a model for understanding online review user's acceptance. Additional theoretical and practical implications are also discussed in the paper.

• Journal of Distribution Science
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• v.18 no.10
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• pp.65-75
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• 2020

Purpose: This study aims to examine how to review contents of experiential and utilitarian products (e.g., skincare products) and how to affect review helpfulness by applying natural language processing techniques. Research design, data, and methodology: This study uses 69,633 online reviews generated for the products registered at Amazon.com by 13 Korean cosmetic firms. The authors identify key topics that emerge about consumers' use of skincare products such as skin type and skin trouble, by applying bigram analysis. The review content variables are included in the review helpfulness model, including other important determinants. Results: The estimation results support the positive effect of review extremity and content on the helpfulness. In particular, the reviewer's skin type information was recognized as highly useful when presented together as a basis for high-rated reviews. Moreover, the content related to skin issues positively affects review helpfulness. Conclusions: The positive relationship between extreme reviews and helpfulness of reviews challenges the findings from prior literature. This result implies that an in-depth study of the effect of product types on review helpfulness is needed. Furthermore, a positive effect of review content on helpfulness suggests that applying big data analytics can provide meaningful customer insights in the online retail industry.

• Journal of Korean Library and Information Science Society
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• v.54 no.3
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• pp.321-346
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• 2023

A data paper describing research data helps credit researchers producing the data while helping other researchers verify previous research and start new research by reusing the data. Publishing a data paper and depositing data to a public data repository are increasing with these benefits. A domestic academic society that plans to publish data papers faces challenges, including timely acquiring tremendous knowledge concerning data paper structures and templates, peer review policy and process, and trustworthy data repositories, as a data paper has different characteristics, unlike a research paper. However, the need for more research and information concerning the critical elements of data paper and the peer-review process makes it difficult to operate for data paper review and publication. To address these issues, we propose essential concepts of the data paper and the data paper peer-review, including the process model of the peer-review with in-depth analysis of five data journals' data paper templates, articles, and other guides worldwide. Academic societies intending to publish or add data papers as a new type of paper may establish policies and define a peer-review process by adopting the proposed conceptual models, effectively streamlining the preparation of data paper publication.

• The Journal of Korean Physical Therapy
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• v.28 no.2
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• pp.77-87
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• 2016

Purpose: The purpose of the study was to review functioning components of studies for measuring functional information using International Classification of Functioning, disability and health (ICF) in Korea. Methods: A literature review was conducted and eligible studies were identified via search of RISS, KISS, DBpia, KoreaMed, PubMed, and ISI databases published from 2001 to 2015. For inclusion in this review, a study should be published in a peer-review journal, must have participation of Korean researchers and/or developed in Korea, and should provide functioning data related ICF. Descriptive studies containing only ICF concepts and review studies were also excluded. Collected functioning data in each study were analyzed using frequency based on ICF domain. Data assessment was performed by two independent reviewers. Results: Eighty publications were included in the analysis. The majority of studies collected data from clinical patients (n=38) and from the disabled (n=28). Fourteen studies assessed functioning data from the elderly and students under special education. The studies reported functioning data using various tools, including ICF itself, ICF checklist, coresets, and conventional measurement tools. Body function domain was most commonly used and the least used domain was the body structure across areas. Interestingly, increasing data related to environmental factors was observed in all studied populations. Conclusion: Functioning data was collected from four domains of ICF across professional areas. The most common collected data was body function and activity and participation for which conventional measurement tools are already available. To understand clients, components of environmental factors that might influence a person's functioning should be considered.

• YAKHAK HOEJI
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• v.53 no.3
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• pp.138-144
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• 2009

The purpose was to implement drug utilization review (DUR) for whom were diagnosed with chronic kidney disease (CKD) population using health insurance claim data. This study constructed drug utilization database using Health Insurance Review and Assessment Service (HIRA) database and selected contraindicated drugs with kidney based on previously developed drug utilization guide and reviewing other countries' examples. Main outcome measures were the proportion of prescription for 1 or more drugs of concern. The cohort included 115,948 subjects, who were diagnosed with chronic kidney disease. Inappropriate drugs with CKD patients was some used, and the most commonly prescribed classes were aluminum drugs. However it is difficult to find problems with inappropriate drug because claims data doesn't have laboratory data. Based on the result of retrospective drug utilization review study, more studies should be analysed drug utilization patterns and monitoring system should be developed.

• Journal of Distribution Science
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• v.15 no.10
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• pp.41-50
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• 2017

Purpose - Online product review has become a crucial part of the online retailer's market performance for a wide range of products. This research aims to investigate how an individual reviewer's review frequency and timing affect her/his average attitude toward products. Research design, data, and methodology - To conduct reviewer-level analysis, this study uses 42,172 posted online review messages generated by 6,941 identified reviewers for 59 movies released in the South Korea from July 2015 to December 2015. This study adopts Tobit model specification to take into account the censored nature and the selection bias arising from the nature of J-shaped distribution of movie rating. Results - Our estimation results support that the negative impact of review frequency and timing on valence. Furthermore, review timing has an inverted-U relationship with the user's average valence and enhance the negative effect of review frequency. Conclusions - This study contributes to the growing literature on the understanding how eWOM is generated at the individual consumer level. On the basis of the main empirical findings, this study provides insights into building a recommendation system in online retail store based on the consumer's review history data - frequency, timing, and valence.

• 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.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.345-357
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• 2001

This review provides a summary of data assimilation applied to the seas around Korea. Currently the worldwide efforts are devoted to applying advanced assimilation to realistic cases, thanks to improvements in mathematical foundations of assimilation methods and the computing capabilities, and also to the availability of extensive observational data such as from satellites. Over the seas around Korea, however, the latest developments in the advanced assimilation methods have yet to be applied. Thus it would be timely to review the progress in data assimilation over the seas. Firstly, the definition and necessity of data assimilation are described, continued by a brief summary of major assimilation methods. Then a review of past research on the ocean data assimilation in the regional seas around Korea is given and future trends are considered. Special consideration is given to the assimilation of remotely-sensed data.

• Journal of Distribution Science
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• v.22 no.3
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• pp.113-124
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• 2024

Purpose: This study is a quantitative study and analyzes the effect of evaluating the extreme and usefulness of product reviews on sales performance by using text mining techniques based on product review big data. We investigate whether the perceived helpfulness of product reviews serves as a mediating factor in the impact of product review extremity on sales performance. Research design, data and methodology: The analysis emphasizes customer interaction factors associated with both product review helpfulness and sales performance. Out of the 8.26 million Amazon product reviews in the book category collected by He & McAuley (2016), text mining using natural language processing methodology was performed on 300,000 product reviews, and the hypothesis was verified through hierarchical regression analysis. Results: The extremity of product reviews exhibited a negative impact on the evaluation of helpfulness. And the helpfulness played a mediating role between the extremity of product reviews and sales performance. Conclusion: Increased inclusion of extreme content in the product review's text correlates with a diminished evaluation of helpfulness. The evaluation of helpfulness exerts a negative mediating effect on sales performance. This study offers empirical insights for digital market distributors and sellers, contributing to the research field related to product reviews based on review ratings.

• Journal of Preventive Medicine and Public Health
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• v.54 no.1
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• pp.8-16
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• 2021

This article aims to introduce the inception and operation of the COVID-19 International Collaborative Research Project, the world's first coronavirus disease 2019 (COVID-19) open data project for research, along with its dataset and research method, and to discuss relevant considerations for collaborative research using nationwide real-world data (RWD). COVID-19 has spread across the world since early 2020, becoming a serious global health threat to life, safety, and social and economic activities. However, insufficient RWD from patients was available to help clinicians efficiently diagnose and treat patients with COVID-19, or to provide necessary information to the government for policy-making. Countries that saw a rapid surge of infections had to focus on leveraging medical professionals to treat patients, and the circumstances made it even more difficult to promptly use COVID-19 RWD. Against this backdrop, the Health Insurance Review and Assessment Service (HIRA) of Korea decided to open its COVID-19 RWD collected through Korea's universal health insurance program, under the title of the COVID-19 International Collaborative Research Project. The dataset, consisting of 476 508 claim statements from 234 427 patients (7590 confirmed cases) and 18 691 318 claim statements of the same patients for the previous 3 years, was established and hosted on HIRA's in-house server. Researchers who applied to participate in the project uploaded analysis code on the platform prepared by HIRA, and HIRA conducted the analysis and provided outcome values. As of November 2020, analyses have been completed for 129 research projects, which have been published or are in the process of being published in prestigious journals.