• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.141-152
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• 2015

Our agriculture and rural villages have faced negative conditions in many reasons. To overcome this situation, a new change is needed by the 6th industrialization. Many agriculture and rural villages in Korea are pursuing the 6th industrialization through the convergence of the primary, secondary, and tertiary industries to vitalize agriculture and rural villages. But there are several problems with the 6th industrialization. There is a limit to the capacity building of the members of the rural organization and Korean agricultural base primary, secondary, and tertiary industries are weak all. In addition, it has been insufficient research for value chain management of the region as a whole; there has been no study of information sharing across the region for the 6th industrialization. This study is about value chain management model for successful the 6th industry with Quick Response System and the big data technology. In this study to provide the efficiency of 6th industry value chain management with customer's needs analysis using big data and research for the information share between the industries in the region through the information pipeline theory of the QR System. We hope that our study is helped to proceed successfully on the 6th industrialization in Korea.

• KDI Journal of Economic Policy
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• v.14 no.3
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• pp.23-48
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• 1992

The Korea's Consumer electronics industry has exhibited a spectacular growth in the last three decades, expanding into one of the most important industries in Korea in many respects. One interesting aspect of the industry is the dominant role played by the Big Three of the industry, Gumsung, Samsung, and Daewoo. Since 1984, the three companies have accounted for about 90% of the sales in key items such as color TV, VTRs, refrigerators, and washers. The Big Three not only dominated the manufacturing stage, but also the distribution stage of the industry through their networks of exclusive dealers that constitute the major part of the distribution market. In this study, we analyzed the effects of the exclusive dealing by the Big Three on the efficiency of the Korean economy. We find that exclusive dealing by the Big Three could seriously constrain competition in both the manufacturing and distribution stages of the industry. Exclusive dealing by the Big Three effectively forcecloses the market for most other manufacturers as well as deterring entry into the manufacturing stage by potential entrants. Further, it impedes the growth of distributors that achieve the economies of scale and scope and restricts competition by the Big Three. In contrast, we could find little evidence that exclusive dealing by the Big Three is pro-competitive or enhances welfare. As a remedy to this problem, we suggest that the Fair Trade Commission of Korea should regulate the exclusive dealing by the Big Three, thus opening the door for the growth of distributors that are not bound by an exclusive dealing relationship with any of the Big Three. Put differently, we urge the Korean Fair Trade Commission to apply the Article 23 (5) to the exclusive dealing by the Big Three. Article 23 (5) that states that unfair restrictive dealing is illegal has never been clarified by the FTC. We believe that our analysis could also serve as a basic for the clarification of the article in general.

• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.2
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• pp.105-113
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• 2022

Purpose - An increase in automation has been as a result of digital technologies. The data will be instrumental in the determination of the services that are more necessary so that more resources can be allocated for them. The purpose of the current research is to investigate how big data utilization will help increase the profitability in the industry 4.0 era. Research design, Data, and methodology - The present research has conducted the comprehensive literature content analysis. Quantitative approaches allow respondents to decide, but qualitative methods allow them to offer more information. In the next step, respondents are given data collection equipment, and information is collected. Result - The According to qualitative literature analysis, there are five ways in which big data utilization will help increase the profitability in the industry 4.0 era. The five solutions are (1) Better Customer Insight, (2) Increased Market Intelligence, (3) Smarter Recommendations and Audience Targeting, (4) Data-driven innovation, (5) Improved Business Operations. Conclusion - Modern companies have been seeking a competitive advantage so that they can have the edge over other companies in the same industries providing the same services and products. Big data is that technology that businesses have always wanted for an extended period of time to revolutionize their operations, making their businesses more profitable.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.270-275
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• 2024

Introduction. In this study, purpose is to analize the types of golf tourism, inbound or outbound, by using big data and see how movement of industry is being changed and what changes have been made during and after Covid-19 in golf industry. Method Using Textom, a big data analysis tool, "golf tourism" and "Covid-19" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 1 st January, 2023 to 31st December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "golf tourism" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, top 36 keywords with the highest relevance and search frequency were selected and applied to this study. The top 36 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. Results By using big data analysis, it was found out option of oversea golf tourism is affecting on inbound golf travel. "Golf", "Tourism", "Vietnam", "Thailand" showed high frequencies, which proves that oversea golf tour is now the re-coming trends.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.139-151
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• 2023

This study aims to gain insights into ChatGPT, which has recently received significant attention. The study utilized a mixed method involving case studies and news big data analysis. ChatGPT can be described as an optimized language model for dialogue. The question arises whether ChatGPT will replace Google search services, posing a potential threat to Google. It could hurt Google's advertising business, which is the foundation of its profits. With AI-based chatbots like ChatGPT likely to disrupt the web search industry, Google is establishing a new AI strategy. The study used the BIG KINDS service and analyzed 2,136 articles over six months, from August 23, 2022, to February 22, 2023. Thirty of these articles were written in 2022, while 2,106 have been reported recently as of February 22, 2023. Also, the study examined the contents of ChatGPT by utilizing literature research, news big data analysis, and use cases. Despite limitations such as the potential for false information, analyzing news big data and use cases suggests that ChatGPT is worth using.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.51-58
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• 2016

In the area of hotel and tourism sector, various research are analyzed using big data. Big data is being generated by any digital devices around us all the times. All the digital process and social media exchange produces the big data. In this paper, we analyzed the de-identification method of big data to use the personal information of hotel guests. Through the analysis of these big data, hotel can provide differentiated and diverse services to hotel guests and can improve the service and support the marketing of hotels. If the hotel wants to use the information of the guest, the private data should be de-identified. There are several de-identification methods of personal information such as pseudonymisation, aggregation, data reduction, data suppression and data masking. Using the comparison of these methods, the pseudonymisation is discriminated to the suitable methods for the analysis of information for the hotel guest. Also, among the pseudonymisation methods, the t-closeness was analyzed to the secure and efficient method for the de-identification of personal information in hotel.

• The Journal of Bigdata
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• v.3 no.1
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• pp.33-40
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• 2018

With the advent of the fourth industrial revolution, each industry has been innovated with new concepts. New concept of each industry takes advantage of new information technologies based on big data infra. Thus quality control of big data is becoming more important. In this paper, we try to develop a framework of big data service quality through a case study. A 'Legal Tech' service was selected for the case study. Especially a big data quality framework was developed for a living law service in the Ministry of Justice.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.77-85
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• 2017

Due to the expansion of accommodation space caused by increase of population along with lifestyle changes, most of people spend their time indoor except for the travel time. Because of this, environmental change of indoor is very important, and it affects people's health and economy in resources. But, most of people don't acknowledge the importance of indoor environment. Thus, monitoring system for sustaining and managing indoor environment systematically is needed, and big data clusters should be used in order to save and manage numerous sensor data collected from many spaces. In this paper, we design a big data cluster for the indoor environment monitoring in order to store the sensor data and monitor unit of the huge building Implementation design big data cluster-based system for the analysis, and a distributed file system and building a Hadoop, HBase for big data processing. Also, various sensor data is saved for collection, and effective indoor environment management and health enhancement through monitoring is expected.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.77-88
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• 2021

The development history of China's big data is relatively short, and it has only been ten years so far. Although the application level of big data in real life is not high, some achievements have been made in the supply chain. Various kinds of data will be generated in the actual operation of the supply chain. If these data can be effectively classified and used, the "bullwhip effect" of the operation of the supply chain can be also effectively improved. Thus this paper proposes the development of a supply chain collaborative inventory management model and application framework using big data. In this study, we analyzed the supply chain of beer industry, which is the most prominent consumption industry with "bullwhip effect", and further established a big data collaborative inventory management model for the supply chain of beer industry based on system dynamics. We used the Vensim software for simulation and sensitivity test and after appling our model, we found that the inventory fluctuations of the participants in the beer industry supply chain became significantly smaller, which verified the effectiveness of the model. Our study can be also applied to the possible problems of the large data supply chain collaborative inventory management model, and gives certain countermeasures and suggestions.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.109-121
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• 2023

This study aims to address the literature gap by examining the direct relationship between big data analytics capability, marketing innovation, and organizational innovations. Additionally, this study would examine big data analytics capability as the antecedent for both innovation types and how these relationships influence firm performance. The research model is developed based on the integration of resource-based view and knowledge-based view theories. The quantitative method is used as the research methodology for this study. Based on a purposive sampling method, a total of 115 questionnaires were obtained from managers in star-rated hotels located in Malaysia. Partial least square structural equation modeling (PLS-SEM) is utilized for the data analysis. The result shows that big data analytics capability positively affects marketing and organizational innovations. The findings show that big data analytics capability and organizational innovation positively influence firm performance. Nonetheless, the result revealed that marketing innovation is not positively related to firm performance. The findings also indicate to hotel managers the importance of big data analytic capability and the resources required to build and develop this capability. The contributions from this study enrich the literature on big data and innovation, which is particularly limited in the hospitality and tourism context.