• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.241-250
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• 2005

New product development (NPD) is defined as the transformation of a market opportunity and a set of assumptions about product technology into a product available for sale. Managers charged with project selection decisions in the NPD process, such as go/no-go choices and specific resource allocation decisions, are faced with a complicated problem. Therefore, the ability to develop new successful products has identifies as a major determinant in sustaining a firm's competitive advantage. The purpose of this study is to develop a new evaluation model for NPD project selection in the high -tech industry using support vector machines (SYM). The evaluation model is developed through two phases. In the first phase, binary (go/no-go) classification prediction model, i.e. SVM for high-tech NPD project selection is developed. In the second phase. using the predicted output value of SVM, feasibility grade is calculated for the final NPD project decision making. In this study, the feasibility grades are also divided as three level grades. We assume that the frequency of NPD project cases is symmetrically determined according to the feasibility grades and misclassification errors are partially minimized by the multiple grades. However, the horizon of grade level can be changed by firms' NPD strategy. Our proposed feasibility grade method is more reasonable in NPD decision problems by considering particularly risk factor of NPD in viewpoints of future NPD success probability. In our empirical study using Korean NPD cases, the SVM significantly outperformed ANN and logistic regression as benchmark models in hit ratio. And the feasibility grades generated from the predicted output value of SVM showed that they can offer a useful guideline for NPD project selection.

• Korean Medical Education Review
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• v.18 no.2
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• pp.51-57
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• 2016

This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.

• Health Policy and Management
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• v.31 no.4
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• pp.387-398
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• 2021

Moon Jae-in Care can be seen as a 2.0 version of Roh Moo-Hyun Care. Just as Roh Care failed to achieve its coverage rate goal and 30% share of public beds, Moon Care also failed to achieve its expected goal. The reason is that it followed Roh Care's failed strategy. Failure to control non-covered services has led to a long way to achieve a 70% coverage rate and induced the expansion of voluntary indemnity insurance, resulting in increased public burden. The universal coverage of non-covered services caused an immediate backlash from doctors. And Moon government also failed to control the private insurance market. The expansion of publicly owned beds has not become realized and has not obtained public support. Above all, it failed to overcome the resistance of doctors and failed to obtain consent from budget power groups in the cabinet for public investment. It was also insufficient to win the support of civic groups. Communication with interested groups failed and the role of private health care providers was neglected. The next government should also continue to strengthen health care coverage, but it should prioritize preventing medical poor and create a consensus with both medical providers and consumers for the control of non-covered services. Ahead of the super-aged society, the establishment of linkage between medical services and long-term care and visiting health care or welfare services is an important task. All public and private provisions and resources should be utilized in the view of a comprehensive public health perspective, and public investment should be input in sectors where public medical institutions can perform more effective functions. The next government, which will be launched in 2022, should design a new paradigm for health care in the face of a period of transformation, such as the coming super-aged society in 2026 and the Fourth Industrial Revolution, and recognize that the capabilities of the health care system represent the nation's overall capacity.

• Fashion & Textile Research Journal
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• v.21 no.5
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• pp.574-585
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• 2019

The acceleration of digital transformation (DX) has resulted in SNS influencer marketing trends becoming the mainstream of the new market. SNS influencers act as early adopters in the process of new products being accepted. Chinese consumers are most affected by Hallyu, which increases interest in K-beauty products. This study analyzes how K-beauty SNS influencers are related to Chinese consumers. A survey was conducted among Chinese millennial consumers after watching videos provided by K-beauty SNS influencer; subsequently, 456 responses were used for data analysis. As a result, the analysis based on the Elaboration Likelihood Model (ELM) distinguishes the central route and the peripheral route in the process of Chinese consumers accepting new SNS products. The study findings suggested that information quality, credibility, accuracy, and usefulness had significant effects on acceptance intention for new products among central route factors, and similarity, trustworthiness, pleasure, expertise, and attractiveness also had significant effects on the acceptance intention of new product among peripheral route factors. It was found that variables of the central route, rather than those of peripheral route, had stronger effects on the acceptance intention for new products. Consequently, the central route of K-beauty SNS influencer is more important to Chinese consumers' acceptance of new products. It is expected that this study will offer beauty influencer marketing-based cosmetics brands efficient consumer management suggestions.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.186-198
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• 2021

The introduction of digital technologies affects most socio-economic processes and activities in the economy, from agriculture to public services. Even though the world is currently only in the early stages of digital transformation, the digital economy is growing rapidly, especially in developing countries. Shortly, digital platforms will be able to replace the "invisible hand" of the market and turn it into digital. Some digital platforms have already reached global reach in some sectors of the economy. The growing value of data and artificial intelligence is reflected in the high capitalization of these enterprises. Their growing role has far-reaching consequences for the organization of economic activity and integration into the field of e-business. However, their importance and level of development in different countries differ significantly. The main purpose of this article is an assessment of the level and trends of the digital economy in the world and the identification of homogeneous groups of states following the main trends in the development of its components from among the EU countries. The methodology of the conducted research is based on the use of general scientific research methods in the analysis of secondary sources and the application of statistical methods of correlation-regression and cluster analysis. Macroeconomic indicators and components of DESI (Digital Economy and Society Index) were used for the analysis. Results. Based on the analysis established that most developed countries have a medium level of digitalization of the business environment and a high level of digitalization of socially oriented public services, while countries with lower GDP focus their policies on building digital infrastructure and training qualified personnel. The study summarizes and analyzes current trends in digital technology, analyzes the level and dynamics of integration of digital technologies of the studied EU countries, the level of development of e-business and e-commerce. The conceptualization of mechanisms of creation of added value in the digital economy is offered and the possible consequences of digitalization of the economy of developing countries are generalized.

• Journal of Korea Trade
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• v.25 no.5
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• pp.110-128
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• 2021

Purpose - The essential purpose of this study is to analyze the possibility of substitution of an individual job resulting from technological development represented by the 4th Industrial Resolution, considering the different effects of digital transformation on the labor market. Design/methodology - In order to estimate the substitution probability, this study used two data sets which the job characteristics data for individual occupations provided by KEIS and the information on occupational status of substitution provided by Frey and Osborne(2013). In total, 665 occupations were considered in this study. Of these, 80 occupations had data with labels of substitution status. The primary goal of estimation was to predict the degree of substitution for 607 of 665 occupations (excluding 58 with markers). It utilized three methods a principal component analysis, an unsupervised learning methodology of machine learning, and Ridge and Lasso from supervised learning methodology. After extracting significant variables based on the three methods, this study carried out logistics regression to estimate the probability of substitution for each occupation. Findings - The probability of substitution for other occupational groups did not significantly vary across individual models, and the rank order of the probabilities across occupational groups were similar across models. The mean of three methods of substitution probability was analyzed to be 45.3%. The highest value was obtained using the PCA method, and the lowest value was derived from the LASSO method. The average substitution probability of the trading industry was 45.1%, very similar to the overall average. Originality/value - This study has a significance in that it estimates the job substitution probability using various machine learning methods. The results of substitution probability estimation were compared by industry sector. In addition, This study attempts to compare between trade business and industry sector.

• Journal of Surface Science and Engineering
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• v.55 no.6
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• pp.368-375
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• 2022

YSZ (Yttria Stabilized Zirconia) is used as a thermal barrier coating material for gas turbines due to its low thermal conductivity and high fracture toughness. However, the operating temperature of the gas turbine is rising according to the market demand, and the problem that the coating layer of YSZ is peeled off due to the volume change due to the phase transformation at a high temperature of 1400℃ or higher is emerging. To solve this problem, various studies have been carried out to have phase stability, low thermal conductivity, and high fracture toughness in a high temperature environment of 1400℃ or higher by doping trivalent and tetravalent oxides to YSZ. In this study, the monoclinic phase formation behavior and crystallinity were comparatively analyzed according to the total doping amount of oxides by controlling the doping amounts of Sc₂O₃ and Gd₂O₃, which are trivalent oxides, and TiO₂, which are tetravalent oxides, in YSZ. Through comparative analysis of monoclinic phase formation and crystallinity, the thermal conductivity of the thermal barrier coating layer according to the amount of doping was predicted.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1280-1287
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• 2020

This paper proposes a vision-based food recognition method for automated production of custom cakes. A small camera module mounted on a food art printer recognizes objects' shape and estimates their center points through image processing. Through the perspective transformation, the top-view image is obtained from the original image taken at an oblique position. The line and circular hough transformations are applied to recognize square and circular shapes respectively. In addition, the center of gravity of each figure are accurately detected in units of pixels. The test results show that the shape recognition rate is more than 98.75% under 180 ~ 250 lux of light and the positioning error rate is less than 0.87% under 50 ~ 120 lux. These values sufficiently meet the needs of the corresponding market. In addition, the processing delay is also less than 0.5 seconds per frame, so the proposed algorithm is suitable for commercial purpose.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.89-101
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• 2022

COVID-19 is significantly changing consumers' demand and habits. In order to understand consumer characteristics and find effective advertising directions in the post-COVID-19 era, this study set young consumers who are more sensitive to market changes and technological transformation from a subjective perspective of advertising audiences. Through the Q methodology, the advertising development model in the post-COVID-19 era was derived exploratively by examining their cognitive status of advertisements in the post-COVID-19 era. The model consists of three types of advertisements: "demand mining online ads" that value consumer demand and adapt to online shopping paths, "added value creation experiential ads" that value derived value and consumer experiences, and "practical and sentimental value creative ads" based on pragmatism and emotional values. In addition, this study also suggested for the sustainable practice of advertising in the post-COVID-19 era in various aspects, such as "seeking multidimensional values," "expanding consumer experience," and "mining and leading demand.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.294-306
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• 2021

In the era of brand economy, companies fulfill their social responsibilities to enhance consumers' brand trust, thereby enhancing brand loyalty. On the other hand, the current Covid-19 epidemic has accelerated the pace of digital transformation of enterprises and has also made consumers pay more attention to the online reputation of enterprises. Based on the Chinese consumer market, this paper studies the corporate social responsibility, Internet word-of-mouth, brand trust, and brand loyalty of electronic product companies. To verify the impact of corporate social responsibility on brand loyalty through Internet word-of-mouth and brand trust, this paper issued a questionnaire survey to Chinese consumers. A total of 469 questionnaires were used for empirical analysis, and SPSS21.0 was used to analyze the collected data. The results are summarized as follows: (1) CSR has a positive impact on brand trust. (2) CSR has a positive impact on brand loyalty. (3) Brand trust has a positive impact on brand loyalty. (4) Brand trust and e-WOM play an intermediary role in CSR and brand loyalty.