• Journal of Family Resource Management and Policy Review
• /
• v.27 no.1
• /
• pp.13-24
• /
• 2023

The 4th industrial revolution came deep into family life and changed the way of housework and care. The change in the family caused by the technological change of the 4th industrial revolution is remarkable in terms of socialization of housework. In this study, the socialization of housework, which is accelerating in the era of the 4th industrial revolution, was examined focusing on the change in the aspect of "household service" through the "platform". Since 2015, when technological changes in the 4th industrial revolution began to decline, related newspaper articles were extracted for daily and economic newspapers nationwide and analyzed big data. The results of big data analysis show that the platform economy using the 4th industrial revolution technology is rapidly spreading the socialization of housework not only at the business level but also at the public policy level. It has been confirmed that support for household services through the platform is growing into a new business area of companies, and at the public policy level, it is being treated as an important policy task in supporting work-family balance or responding to infectious diseases. This study is meaningful in that it provided an opportunity to reflect on the roles and tasks of the family, market, and state for housework and care in the future through changes in housework and care caused by the 4th industrial revolution technology.

• Knowledge Management Research
• /
• v.24 no.3
• /
• pp.95-125
• /
• 2023

As the aviation industry has rapidly been grown, there are more factors for customers to consider when choosing an airline. In response, airlines are trying to increase customer value by providing high-quality services and differentiated experiential value. While early customer value research centered on utilitarian value, which is the trade-off between cost and benefit in terms of utility for products and services, the importance of experiential value has recently been emphasized. However, experiential value needs to be studied in a specific context that fully represents customer preferences because what constitutes customer value changes depending on the product or service context. In addition, customer value has an important influence on customers' decision-making, so it is necessary for airlines to accurately understand what constitutes customer value. In this study, we collected customer reviews and ratings from Skytrax, a website specializing in airlines, and utilized the BERTopic technique to derive factors of customer value. The results revealed nine factors that constitute customer value in airlines, and six of them are related to customer satisfaction. This study proposes a new methodology that enables a granular understanding of customer value and provides airlines with specific directions for improving service quality.

• Health Policy and Management
• /
• v.27 no.2
• /
• pp.167-176
• /
• 2017

Background: This study aimed to analyze the impact of community health care resources on the place of death of older adults with dementia compared to those with cancer in South Korea, using public administrative big data. Methods: Based on a literature review, we selected person- and community-level variables that can affect older people's decisions about where to die. Data on place-of-death and person-level attributes were obtained from the 2013 death certification micro data from Statistics Korea. Data on the population and economic and health care resources in the community where the older deceased resided were obtained from various open public administrative big data including databases on the local tax and resident population statistics, health care resources and infrastructure statistics, and long-term care (LTC) insurance statistics. Community-level data were linked to the death certificate micro data through the town (si-gun-gu) code of the residence of the deceased. Multi-level logistic regression models were used to simultaneously estimate the impacts of community as well as individual-level factors on the place of death. Results: In both the dementia (76.1%) and cancer (87.1%) decedent groups, most older people died in the hospital. Among the older deceased with dementia, hospital death was less likely to occur when the older person resided in a community with a higher supply of LTC facility beds, but hospital death was more likely to occur in communities with a higher supply of LTC hospital beds. Similarly, among the cancer group, the likelihood of a hospital death was significantly lower in communities with a higher supply of LTC facility beds, but was higher in communities with a higher supply of acute care hospital beds. As for individual-level factors, being female and having no spouse were associated with the likelihood of hospital death among older people with dementia. Conclusion: More than three in four older people with dementia die in the hospital, while home is reported to be the place of death preferred by Koreans. To decrease this gap, an increase in the supply of end-of-life (EOL) care at home and in community-based service settings is necessary. EOL care should also be incorporated as an essential part of LTC. Changes in the perception of EOL care by older people and their families are also critical in their decisions about the place of death, and should be supported by public education and other related non-medical, social approaches.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.6
• /
• pp.651-659
• /
• 2014

With the popularization of big data environment, big data have been highlighted as a key information strategy to establish national spatial data infrastructure for a scientific land policy and the extension of the creative economy. Especially interesting from our point of view is the cadastral information is a core national information source that forms the basis of spatial information that leads to people's daily life including the production and consumption of information related to real estate. The purpose of our paper is to suggest the scheme of big data analytics with respect to the articles of cadastral resurvey project in order to approach cadastral information in terms of spatial data integration. As specific research method, the TM (Text Mining) package from R was used to read various formats of news reports as texts, and nouns were extracted by using the KoNLP package. That is, we searched the main keywords regarding cadastral resurvey, performing extraction of compound noun and data mining analysis. And visualization of the results was presented. In addition, new reports related to cadastral resurvey between 2012 and 2014 were searched in newspapers, and nouns were extracted from the searched data for the data mining analysis of cadastral information. Furthermore, the approval rating, reliability, and improvement of rules were presented through correlation analyses among the extracted compound nouns. As a result of the correlation analysis among the most frequently used ones of the extracted nouns, five groups of data consisting of 133 keywords were generated. The most frequently appeared words were "cadastral resurvey," "civil complaint," "dispute," "cadastral survey," "lawsuit," "settlement," "mediation," "discrepant land," and "parcel." In Conclusions, the cadastral resurvey performed in some local governments has been proceeding smoothly as positive results. On the other hands, disputes from owner of land have been provoking a stream of complaints from parcel surveying for the cadastral resurvey. Through such keyword analysis, various public opinion and the types of civil complaints related to the cadastral resurvey project can be identified to prevent them through pre-emptive responses for direct call centre on the cadastral surveying, Electronic civil service and customer counseling, and high quality services about cadastral information can be provided. This study, therefore, provides a stepping stones for developing an account of big data analytics which is able to comprehensively examine and visualize a variety of news report and opinions in cadastral resurvey project promotion. Henceforth, this will contribute to establish the foundation for a framework of the information utilization, enabling scientific decision making with speediness and correctness.

• The Journal of Bigdata
• /
• v.1 no.1
• /
• pp.53-60
• /
• 2016

Data of central government and local government was collected automatically from the public data portal. And we did the multidimensional analysis based on various perspective like file format and present condition of public data. To complete this work, we constructed Data Warehouse based on the other countries' evaluation index case. Finally, the result from service level evaluation by using multidimensional analysis was used to display each area, establishment, fields.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.1
• /
• pp.301-311
• /
• 2020

With the recent global urban issues such as climate change, urbanization, and energy problems, the smart city was proposed as one of the solutions in urban planning. This study introduces the smart city initiatives of South Korea by examining the recent history of smart city policies and their limitations. This case study reflects the experience of one of the countries which thrived to building smart cities as their national key industries to drive economic growth. It also analyzes the trends of the smart city using big data analysis techniques. Although there are obstacles such as economic recession, failing to differentiate from the U-city, low service level than expected smart functionality, We could recognize the current status of the smart city policies in South Korea such as 1) Korean smart city development projects are actively implemented, 2) public consensus suggests that applying advanced technology and the active role of government need, 3) a comprehensive and strategic approach with the integration and application of advanced technologies is required as well, 4) investment by both private and public sectors need to deliver social improvements. This study suggests future direction of smart city polity in South Korea in the conclusion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.115-117
• /
• 2017

R has become a popular analytics platform as it provides powerful analytic functions as well as visualizations. However, it has a weakness in which scalability is limited. As an alternative, the RHadoop package facilitates distributed processing of R programs under the Hadoop platform. This paper investigates usefulness of the RHadoop package when analyzing healthcare big data that is widely open in the internet space. To do this, this paper has compared analytic performances of R and RHadoop using the medical treatment records of year 2015 provided by National Health Insurance Service. The result shows that RHadoop effectively enhances processing performance of healthcare big data compared with R.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.511-513
• /
• 2022

Digital Health Care is the convergence of ICT and (non)medical technology, emphasizing the importance of prevent and monitoring health management in terms of new challenging medical paradigm: predictive, preventive, personalized and participatory. Beyond the limited medical industry of long-term care insurance, it is emerging that AI, IoT, Big Data related new services with new technologies in the 4^th revolution era. It is also noted that business field based on test bed is emergent; Caring Robot, wearable devices need to be launched in the market. Diverse service is possible with Big Data and AI etc.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.2
• /
• pp.218-223
• /
• 2021

The five elements of big data are said to be Volume, Variety, Velocity, Veracity, and Value. Among them, data lacking the Veracity of the data or fake data not only makes an error in decision making, but also hinders the creation of value. This study analyzed YouTube's revenue structure to focus the effect of data integrity on data valuation among these five factors. YouTube is one of the OTT service platforms, and due to COVID-19 in 2020, YouTube creators have emerged as a new profession. Among the revenue-generating models provided by YouTube, the process of generating advertising revenue based on click-based playback was analyzed. And, analyzed the process of subtracting the profits generated from invalid activities that not the clicks due to viewers' pure interests, then paying the final revenue. The invalid activity in YouTube's revenue structure is Raw Data, not pure viewing activity of viewers, and it was confirmed a direct impact on revenue generation. Through the analysis of this process, the new Data Value Chain was proposed.

• Information Systems Review
• /
• v.20 no.2
• /
• pp.63-85
• /
• 2018

Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.