• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.140-141
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• 2017

Big data analysis, in the large amount of data stored as the data warehouse which it refers the process of discovering meaningful new correlations, patterns, trends and creating new values. Thus, Big data analysis is an effective analysis of various big data that exist all over the world such as social big data, machine to machine (M2M) sensor data, and corporate customer relationship management data. In the big data era, it has become more important to effectively analyze not only structured data that is well organized in the database, but also unstructured big data such as the internet, social network services, and explosively generated web documents, e-mails, and social data in mobile environments. By the way, a meta analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. We reviewed a total of 750 samples among 50 studies published on the topic related as IDT between 2000 and 2017 in Korea.

• Proceedings of the Technology Innovation Conference
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• 2002.02a
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• pp.133-149
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• 2002

This study aims to investigate the impact of wide use of digital technology, in particular, the Internet, on innovation process and corporate strategy in electronics industry. The introduction of digital technology has changed innovation process, business model and organizational structure of the electronics companies. With the introduction of digital technology, the entire value chain of electronics industry from procurement, sales, and marketing to R&D and manufacturing has been restructured. E-commerce has been a major agenda for e-business. Recently, collaboration among electronics companies through e-marketplace has emerged as an important issue. A web-based e-commerce standard, so called RosettaNet, has been developed for facilitating e-transactions of electronics firms. The development of digital technology has dramatically increased the processing speed and sophisticated the virtual reality technology. As simulation becomes easier and more effective, the uncertainty and risk involved in R&D has decreased significantly. Another positive impact is closer cooperation between R&D and manufacturing functions. Taking advantage of automated and flexible production technology, has a new type of firm, so called, EMS (Electronics Manufacturing Services) emerged, whose strategic focus is on manufacturing only. The EMS can be seen as a kind of innovative organization, that is, a modular organization for production function. Digital technology has made convergence of computer and communication possible at early years but right now the convergence has been accelerated in extensive areas of communication, broadcasting, information appliances, software, contents, and services. Firms' effort for an innovative product and service has been intensified and the competition for a new standard product and service has become severe in electronics industry. Business activities are always realized in a specific organizational context. Accordingly building up innovation-friendly organization has emerged as a critical concern. Due to the striking decrease of transaction cost, a network type of organization has proliferated, and a business function turns into a modular organization. As a whole, digital technology has pushed electronics firms into developing their own business model, which takes consideration of standardization of business platform and their core competency.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.390-396
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• 2021

In this research, design and fabrication of marine repeater capable to extend communication coverage in monitoring system of fishing gear automatic identification, which is one of implementation method of the real-name electric fishing gear system declared by Ministry of Oceans and Fisheries in 2016, is reported. The proposed marine repeater is fabricated in a form of RF repeater with interference cancellation system (ICS), which can cancel the oscillation due to feedback signal between service antenna and link antenna. In design process, we secure the isolation of 30 dB between service antenna and link antenna. It is confirmed that when the level of feedback signal into repeater input be lower of 15 dB than repeater gain, error vector magnitude due to oscillation can be lower than the performance criterion of 6%, from the test verification. It is expected that the service coverage will be extended by applying the developed marine ICS RF repeater into marine IoT network including monitoring system of fishing gear automatic identification.

• Journal of Preventive Medicine and Public Health
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• v.54 no.5
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• pp.330-339
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• 2021

Objectives: Tobacco control in Indonesia is very lenient compared to international standards. This study explored the perspectives of tobacco control stakeholders (TCSs) on the likelihood of advancing tobacco marketing regulation in Indonesia. Methods: Data were collected from TCSs who were members of the Indonesia Tobacco Control Network group in a modified Delphi study. We collected the data in 2 waves using a questionnaire that comprised a set of closed and open-ended questions. For this paper, we analysed 2 of the 3 sections of the questionnaire: (1) tobacco advertising, promotions, and sponsorship (TAPS) bans, and (2) marketing and retailing regulations. We conducted a descriptive analysis of the scores using Stata/IC.13 and summarised the comments for each item. Results: The TCSs viewed the measures/strategies across all aspects of TAPS and tobacco marketing regulation as highly desirable, but provided varied responses on their feasibility. They rated political feasibility lower than technical feasibility for most measures. Advancing TAPS measures and prohibition of selling to minors were considered more attainable by sub-national governments, while prohibition of tobacco corporate social responsibility was considered as the least feasible measure in the next 5 years. Conclusions: Despite little optimism for substantial national-level change, there is a positive expectation that sub-national governments will strengthen their tobacco control regulation. It is paramount that the government reduce tobacco industry leverage by implementing Article 5.3 of the World Health Organization Framework Convention on Tobacco Control. Extending advocacy networks beyond tobacco control groups and framing tobacco control more effectively are necessary steps.

• Journal of Technology Innovation
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• v.29 no.4
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• pp.59-93
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• 2021

This article discusses the innovation activities of firms that aim for system transformation from the perspective of 'Transformative Innovation Policies'. Here, for the sustainable transformation of our society, a firm that finds the 'purpose' of business activities in solving social problems and implements a new business model is defined as a 'transition-oriented firm'. The main characteristics of a transition-oriented firm are examined in terms of 1) transition vision and mission setting, 2) business model innovation for transition, 3) network formation for system transition, and 4) securing legitimacy of transition. And through case studies, the approach, significance, and limitations of the transition-oriented corporate innovation theory are discussed. The case study is from a Eisai Korea, which aims for an integrated prevention, treatment, and care system centered on residents and citizens.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1558-1564
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• 2019

Corporate business clusters create a borderless business network through value chains and value creation activities. Clusters in the IT sector are crossing regional boundaries because of their rapid technological development and short product life cycle. To investigate this phenomenon, we examined the value activities of IT companies. As a result, the global expansion of the case companies was limited, but they had business clusters that exceeded the regional boundaries. However, because the order of business clusters is not advanced, value activities are focused on productivity rather than innovation. Given the rapidly evolving nature of IT, it is necessary to evolve into a business cluster that can create new value. Companies must design and implement value-creating processes to develop new technologies or enter new markets, which can lead to cluster growth. Companies must design and implement value-creating processes to develop new technologies or enter new markets, which can lead to cluster growth.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.75-85
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• 2021

In this paper, we present a deep neural network-based prediction model that processes and analyzes the corporate credit and personal credit information of individual business owners as a new method to predict the default rate of individual business more accurately. In modeling research in various fields, feature selection techniques have been actively studied as a method for improving performance, especially in predictive models including many features. In this paper, after statistical verification of macroeconomic indicators (macro variables) and credit information (micro variables), which are input variables used in the default rate prediction model, additionally, through the credit information feature selection method, the final feature set that improves prediction performance was identified. The proposed credit information feature selection method as an iterative & hybrid method that combines the filter-based and wrapper-based method builds submodels, constructs subsets by extracting important variables of the maximum performance submodels, and determines the final feature set through prediction performance analysis of the subset and the subset combined set.

• Journal of Korea Trade
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• v.24 no.3
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• pp.20-36
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• 2020

Purpose - As the global product network expands through both internationalization and diversification of the multimodal transportation system, corporate strategies have shifted to emphasize the importance of a high value-added international logistics system. To guide policies and strategies to attract relevant industries, this study aims to analyze the location competitiveness of regional logistics distribution center to serve Northeast Asia. Design/methodology - Multi-criteria techniques are considered to offer a promising framework for evaluating decision-making factors. This paper employed an analytic hierarchy process to analyze the hierarchal structure of determinants for selecting the location of a regional logistics distribution center. Adopting both qualitative and quantitative evaluations, this study suggest political implications for a regional logistics distribution center development, such as the direction of political support, service differentiation and infrastructure development. Findings - This study developed a location competitiveness evaluation model, based on the case study of the major port-cities in Northeast Asia. Evaluation model incorporates five factors underpinning 17 components extracted using factor analysis. The results revealed that the logistics factor is the most significant factor for evaluating the competitiveness of a regional logistics distribution center. The remaining factors were market, costs, and services environment. Comparing qualitative and quantitative evaluations, results provide useful insights for a regional logistics distribution center development in Northeast Asia. Originality/value - This study revealed differences between qualitative and quantitative evaluations. The finding implies that prior works on evaluation models of competitiveness has not successfully measured the gap between quantitative data and expert' evaluations. To overcome this limitation, this paper considered both actual data such as actual distance, cost, the number of companies located, and expert opinions.

• The Journal of Information Systems
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• v.31 no.4
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• pp.75-100
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• 2022

Purpose Recently, hyper-realistic virtual influencers have received much attention in the field of corporate marketing. However, there is a lack of research that suggests specific processes affecting behavioral intentions through trust and attachment between virtual influencers and consumers. In addition, previous studies have failed to consider the characteristics of hyper-realistic virtual influencers. Therefore, this study investigates the effects of trust and attachment to hyper-realistic virtual influencers on consumers' behavioral intentions based on the trust-building model. Design/methodology/approach Based on the previous research, seven antecedent factors for trust-building were derived: Reality, Attractiveness, Awareness, Interactivity, Professionalism, Social Presence, and Predictability. Next, the survey was conducted on Chinese people who had experienced interacting with hyper-realistic virtual influencers on social network services within the last 3 months at the time of data collection. A total of 326 respondents were used for the final analysis and hypotheses were tested using a structural equation model technique. Findings The results of this study are as follows. First, this study confirmed that reality, attractiveness, awareness, social presence, and predictability as antecedent factors for trust-building of hyper-realistic virtual influencers have a positive effect on trust. Second, this study confirmed that trust in hyper-realistic virtual influencers has a significant positive effect on attachment. Lastly, this study confirmed that trust and attachment to the hyper-realistic virtual influencer significantly and positively affect relationship retention and purchase intentions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.267-277
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• 2022

Due to the increasing proportion of cloud and remote working environments, various information security incidents are occurring. Insider threats have emerged as a major issue, with cases in which corporate insiders attempting to leak confidential data by accessing it remotely. In response, insider threat detection approaches based on machine learning have been developed. However, existing machine learning methods used to detect insider threats do not take biases and variances into account, which leads to limited performance. In this paper, boosting-type ensemble learning algorithms are applied to verify the performance of malicious insider detection, conduct a close analysis, and even consider the imbalance in datasets to determine the final result. Through experiments, we show that using ensemble learning achieves similar or higher accuracy to other existing malicious insider detection approaches while considering bias-variance tradeoff. The experimental results show that ensemble learning using bagging and boosting methods reached an accuracy of over 98%, which improves malicious insider detection performance by 5.62% compared to the average accuracy of single learning models used.