• Journal of the Korea Institute of Building Construction
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• v.22 no.5
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• pp.463-471
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• 2022

The construction industry has a structure in which information asymmetry problems are complexly scattered compared to other industries. Since the construction industry classification system serves as a guideline for entering the construction market and can provide as a standard for construction consumers to select a supplier who can provide appropriate services, when judging the operation purpose or purpose of the construction industry registration system, it is very important to set up the system by rationally reviewing it. The purpose of this study is to examine the possibility of improvement in consideration of the risk factors related to the domestic construction industry registration industry classification system. To this end, we will conduct a case study on the construction industry classification system operated by overseas construction industry licenses or registration systems in Japan, the United States, and Australia, and compare it with the domestic industry classification system to derive implications and directions for improvement.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.169-181
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• 2016

Organizations in some industries are still hesitant to adopt the Enterprise Resource Planning (ERP) system due to its high risk of failures. This study examined how industry classification affects the successful implementation of the ERP system. To achieve this goal, we reinvestigated the existing ERP Success Model that was developed by Chung with the data from various industry sectors, since Chung validated the model only in the engineering and construction industries. In order to test to see if the Chung model can be applicable outside the engineering and construction industries, the relationships between the ERP success indicators and the critical success factors in the Chung model and those in the sample data collected from ten different industry sectors were compared and investigated. The ten industry sectors were selected based on the Global Industry Classification Standard (GICS). We found that the impact of success factors on the success of implementing an ERP system varied across industry sectors. This means that the success of ERP system implementation can be industry-specific. Thus, industry classification should be considered as another factor to help IT decision makers or top-management avoid ERP system failures when they plan to implement a new ERP system.

• Journal of Korea Trade
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• v.23 no.8
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• pp.110-131
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• 2019

Purpose - This paper investigates the implications for facilitating trade in the products of Industry 4.0. To identify the issues caused by the conflicts of policy objectives such as applying the tariff concession under the ITA and imposing the export control, by exploring the case of classification of drones. Design/methodology - We adopted a single case study method to gain a deeper understanding of the complex and multifaceted issues of Customs classification in the context of facilitating trade in the products of Industry 4.0. This study employs the case of drones to explore how these issues of Customs classification affect trade facilitation. We ensured the internal validity of the study by confirming the pattern of the results with the existing theories. Findings - Our main findings can be summarised as follows: the intrinsic nature of the products that converge several technologies causes issues in the classification. The inconsistency in product classification delays customs clearance by hindering the Customs risk-management system that pinpoints products subject to controls. To address the issues, therefore, we proposed fundamental reforms of Customs to empower themselves with management roles. Facilitating trade in the products of Industry 4.0 requires more enhanced Customs capability. Therefore, the reforms should include comprehensive capacity-building activities, such as changes in staff-trainings, promotion system, organisation and culture. Customs also need roles in robust designing of cooperative systems to compensate for the lacks of controls and to ensure concrete risk management for expedited Customs procedures. As well, by equipping the Single Window of Customs with crucial control functions of other ministries, Customs need to support the cooperation. The role of harmonising various preaudits of other ministries with its own is another essential role that ensures predictability of clearance procedure. Originality/value - There are scanty studies in the field of knowledge about what obstacles exist and what solution is available in the course of transforming to 'Industry 4.0'. In filling out the gap of knowledge, this paper is of academic significance in that it applies the research theory on trade facilitation for the specific cases of classification of the product of Industry 4.0 to verify its effectiveness and to extend the subject of the studies to the scope of Industry 4.0. It also has practical significance in that the results have provided implications for reforms of Customs procedures to facilitate trade in the products of Industry 4.0.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.265-268
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• 2001

As growing the electronic commerce there are significant changes in the products/services catalog into the on-line environment. Advertent of e-catalog business opportunity for their own product/services enlarges the market volume and there are diverse methods for the presentation of its product/services. A method for the presentation of product/services features one uses identification and classification system. This study constructs a classification system and database layout for the product/services classification system as a part of e-catalog system. We consider the specific method for the GDAS-based dataset and UNSPSC classification system in the distribution industry.

• Journal of Korea Technology Innovation Society
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• v.10 no.3
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• pp.531-554
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• 2007

This paper suggests a new model connecting various knowledge activities through classification systems such as classifications of research, technology, industry, major and job. Although research activities are linked to technology and industry areas or to education and job areas, there is no effort to link these kinds of activities. There are a few studies to link research and technology or research and education respectively. But, there have been no studies to connect technology-industry linkage and education-job linkage. This paper suggests that research area can be a basis of link between technology-industry linkage and education-job linkage. The methods building the links are not simple, but easy; 1) setting up new science/research classification system having two dimensions of research and application, 2) building electronic systems and databases allowing fields for several classification systems, and 3) making rules using multi-dimensional classification systems following the purpose of the programs. The model is designed to meet the needs of nationwide R&D and human resources policies, and for the preparation of knowledge society to grasp the relationship between sequential activities using knowledge. If we know the interactive relationships between various areas, we can trace related phenomena in different activities with restricted information.

• 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.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.79-95
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• 2024

In modern society, as data plays a crucial role at the levels of businesses, industries, and nations, the utilization of data becomes increasingly important. Consequently, governments are prioritizing the development and implementation of plans to cultivate data workforce, viewing the data industry as a cornerstone of national strategy. To enhance domestic capabilities and nurture workforce in the data industry, it is deemed necessary to conduct an objective comparative analysis with major foreign countries. Therefore, this study aims to analyze cases of domestic and international data industries and explore methods for quantitatively comparing data industry workforce across nations. Initially, the study distinguishes between "data industry workforce" and "data job-related workforce," particularly focusing on professionals handling data-related tasks. Subsequently, it compares the workforce sizes of data job-related workforce across nations, utilizing standardized occupational classification codes based on the International Standard Classification of Occupations(ISCO). However, it should be noted that countries employing their own unique occupational classification systems often require matching job titles with similar meanings for accurate comparison. Through this study, it is anticipated that policymakers will be able to establish future directions for cultivating data workforce based on comparable status.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.181-182
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• 2015

Lately, the importance of the marin industry is growing as current status and future trend. This change is being prompted for the development of the maritime industry such as resource depletion, climate change, the Arctic opens. The demand of new marine industry with IT and convergence is gradually increasing. A new understanding of the importance of the marine industry is needed. Therefore, the systematic classification system for the marin industry building for the marin industry is to assess the marine industry activity levels at the national level.

• Journal of Radiation Industry
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• v.8 no.3
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• pp.155-159
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• 2014

RI-Biomics is a new concept that combines radioisotopes (RI) and Biomics. For efficient collection of information, establishment of database for technical information system and its application to the system, there is an increasing need for constructing the standard classification system of technical information by its systematical classification. In this paper, we have summarized the development process of the standard classification system of technical information in the field of RI-Biomics and its application to the system. Constructing the draft version for the standard classification system of technical information was based on that standard classification one in national science and technology in Korea. The final classification system was then derived through the reconstruction and the feedback process based on the consultation from the 7 experts. These results were applied to the database of technical information system after transforming as standard code. Thus, the standard classification system were composed of 5 large classifications and 20 small classifications, and those classification are expected to establish the foundation of information system by achieving the circular structure of collection-analysis-application of information.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.103-117
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• 2023

This study focuses on the behavioural lexical classification for extracting animation character actions and the analysis of the character's upper and lower body movements. The behaviour and state of characters in the animation industry are crucial, and digital technology is enhancing the industry's value. However, research on animation motion application technology and behavioural lexical classification is still lacking. Therefore, this study aims to classify the predicates enabling animation motion, differentiate the upper and lower body movements of characters, and apply the behavioural lexicon's motion data. The necessity of this research lies in the potential contributions of advanced character motion technology to various industrial fields, and the use of the behavioural lexicon to elucidate and repurpose character motion. The research method applies a grammatical, behavioural, and semantic predicate classification and behavioural motion analysis based on the character's upper and lower body movements.