• Fashion & Textile Research Journal
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• v.22 no.2
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• pp.181-191
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• 2020

The fashion industry has faced environmental, social, and ethical issues due to increased interest in ethical consumption. Numerous ethical studies have been conducted in the fashion industry. This study looked at the current state of research by year, academic journal, and detail in major related papers published in Scopus, KCI and KCI between 2009 and 2019. Ethical fashion studies began to appear in 2009 and were concentrated in certain academic journals and focused on fashion marketing and fashion design. Topics in ethical fashion were terms such as sustainable, eco-friendly, up-cycling, recycling, eco, zero-waist, and organic. In ethical fashion studies, environmental studies were conducted most often; in addition, the terms used along with ethical fashion tend to be frequently used for each particular major. Looking at key words used in research by period, the study showed that research was most diverse between 2016 and 2019. In particular, environmental and social issues of ethical fashion and convergence with animal protection, new distribution, science and technology sectors were newly added between 2016 and 2019. This study used text mining and network analysis to understand the overall trends of ethical fashion studies in Korea. In conclusion it is important to realize the relationship between the main words along with the current status analysis.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.13-24
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• 2015

Customer complaints handling helps organizations to retain existing customers and attract new customers, as well. As Voice of the Customer (VOC) is one of the main sources of customer complaints, many organizations utilize VOC to enhance customer satisfaction. Effective management of VOC has been proved as one of the best ways to maintain organization's brand image and reputation. In spite of its importance, little has been reported on the utilization of VOC to detect faults in a telecommunication industry. In this paper, association rule mining based on VOC is used to identify root fault causes of a telecommunications network. To do that, VOC of a Communication Service Provider has been collected first. Then, association rule mining has also been conducted with various support and confidence levels. As a result, root fault causes of the telecommunications network can be identified. It is expected that this study can be used as a basis for decisions about customer satisfaction management such as preventive maintenances or reduction of the customer maintenance cost.

• Journal of the Korea Safety Management & Science
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• v.7 no.4
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• pp.61-71
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• 2005

Many researches have been focused on the analysis of industry disasters in order to reduce them. As a similar endeavor, this paper provides a propensity analysis of injured people from various industries using classification and regression tree(CART), a data mining algorithm. The sample for this work was chosen from 25,157data related to various industries during one year ( $2003.2\sim2004.1$ ) at Kangwon-Do in Korea. For the purpose of this paper, eight independent variables (injured date, injured time, injured month, type of Injured person, continuous service period, sex, company size, age)are taken from injured person group. According to the analysis result, it is found that five out of the eight factors that are predicted as significant have salient effects. Factors of season, time/hour, day of the week, or month which disasters happened do not show any significant effect. This paper provides common features of injured people. The provided analysis result will be helpful as a starting point for root cause analysis and reduction of industry disasters and also for development of a guideline of safety management.

• Economic and Environmental Geology
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• v.38 no.4 s.173
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• pp.411-419
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• 2005

The recent rapid economic growth of China has an increasing interest to Korea. China is plentiful of the natural mineral resources and has a huge territory with 1.3 billion people, also has a strong foundation in the mining industry as a mineral process and metallurgical technology. Such strong mining industry of China is attractive to Korea which is getting ready the North East Asia epoch. The growth of big mining groups as Gangseo (Jiangxi) Copper Corporation and Honam Juyawhageo (Hunan Zhuye Torch) Metal Co. Ltd. haul up the rapid economic growth in China.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.403-418
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• 2023

Purpose: The acceleration of technological innovation, specifically Industry 4.0, has triggered the emergence of a quality management paradigm known as Quality 4.0. This study aims to provide a systematic overview of dispersed studies on Quality 4.0 across various disciplines and to stimulate further academic discussions and industrial transformations. Methods: Text mining and machine learning approaches are applied to learn and identify key research topics, and the suggested key references are manually reviewed to develop a state-of-the-art overview of Quality 4.0. Results: 1) A total of 27 key research topics were identified based on the analysis of 1234 research papers related to Quality 4.0. 2) A relationship among the 27 key research topics was identified. 3) A multilevel framework consisting of technological enablers, business methods and strategies, goals, application industries of Quality 4.0 was developed. 4) The trends of key research topics was analyzed. Conclusion: The identification of 27 key research topics and the development of the Quality 4.0 framework contribute to a better understanding of Quality 4.0. This research lays the groundwork for future academic and industrial advancements in the field and encourages further discussions and transformations within the industry.

• Safety and Health at Work
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• v.12 no.2
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• pp.201-208
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• 2021

Background: In the mining industry, various methods of accident analysis have utilized official accident investigations to try and establish broader causation mechanisms. An emerging area of interest is identifying the extent to which cultural influences, such as safety culture, are acting as drivers in the reoccurrence of accidents. Thus, the overall objective of this study was to analyze occupational health and safety (OHS) reports in mining to investigate if/how safety culture has historically been framed in the mining industry, as it relates to accident causation. Methods: Using a computer-assisted qualitative data analysis software, 34 definitions of safety culture were analyzed to highlight key terms. Based on word count and contextual relevance, 26 key terms were captured. Ten OHS reports were then analyzed via an inductive thematic analysis, using the key terms. This analysis provided a concept map representing the 50-year data set and facilitated the use of text framing to highlight safety culture in the selected OHS mining reports. Results: Overall, 954 references and six themes, safety culture, attitude, competence, belief, patterns, and norms, were identified in the data set. Of the 26 key terms originally identified, 24 of them were captured within the text. The results made evident two distinct frames in which to interpret the data: the role of the individual and the role of the organization, in safety culture. Conclusion: Unless efforts are made to understand and alter cultural drivers and share these findings within and across industries, the same accidents are likely to continue to occur.

• Journal of Soil and Groundwater Environment
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• v.18 no.4
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• pp.40-49
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• 2013

In the beginning of $20^{th}$ century, the coal mining industry had an important role in Japan at which two-thirds of the coal product came from the Kitakyushu-Chikuho District (KCD). As a consequence of mining activities, land-use condition in this district showed notable changes. This paper presented a study of land-use changes in coal mining area by characterizing land-use pattern transition over the last 100 years. In order to carry out the rigorous analysis of land-use, a series of land-use maps over the last 100 years was developed using geographic information systems (GIS). The historic topographic map and another available old data were used to investigate the long-term changes of land-use associated with past mining within the GIS platform. The results showed that the utilization of a series of developed land-use maps successfully indicated the difference of land-use pattern in the KCD before and after the peak of mining activities. The general findings from land-use analysis described that forest and farm lands were lost and turned into abandoned sites in the last 100 years.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.615-643
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• 2019

Now is the time for IS scholars to demonstrate the added value of academic theory through its integration with text mining, clearly outline how to implement this for text mining experts outside of the academic field, and move towards establishing this integration as a standard practice. Therefore, in this study we develop a systematic theory-based text-mining framework (TTMF), and illustrate the use and benefits of TTMF by conducting a text-mining project in an actual business case evaluating and improving hotel service quality using a large volume of actual user-generated reviews. A total of 61,304 sentences extracted from actual customer reviews were successfully allocated to SERVQUAL dimensions, and the pragmatic validity of our model was tested by the OLS regression analysis results between the sentiment scores of each SERVQUAL dimension and customer satisfaction (star rates), and showed significant relationships. As a post-hoc analysis, the results of the co-occurrence analysis to define the root causes of positive and negative service quality perceptions and provide action plans to implement improvements were reported.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.215-225
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• 2024

With the rapid development of Internet of Things (IoT) and big data technology, a large amount of data will be generated during the operation of related industries. How to classify the generated data accurately has become the core of research on data mining and processing in IoT industry chain. This study constructs a classification model of IoT industry chain based on improved random forest algorithm and text analysis, aiming to achieve efficient and accurate classification of IoT industry chain big data by improving traditional algorithms. The accuracy, precision, recall, and AUC value size of the traditional Random Forest algorithm and the algorithm used in the paper are compared on different datasets. The experimental results show that the algorithm model used in this paper has better performance on different datasets, and the accuracy and recall performance on four datasets are better than the traditional algorithm, and the accuracy performance on two datasets, P-I Diabetes and Loan Default, is better than the random forest model, and its final data classification results are better. Through the construction of this model, we can accurately classify the massive data generated in the IoT industry chain, thus providing more research value for the data mining and processing technology of the IoT industry chain.

• Korean Management Science Review
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• v.26 no.3
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• pp.101-115
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• 2009

In this paper, we propose a technology mining framework for mobile communication industry. We develop a two phase approach of new technology identification and service enhancement. The new technology identification process consists of R&D issues analysis, technology theme design, and emerging technology sampling. On the other hand, existing service enhancement process has technology landscaping, keyword based search, and technological growth analysis. By implementing these two phase frameworks, we develop a technology portfolio for mobile communication industry.