• Health Policy and Management
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• v.32 no.4
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• pp.380-388
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• 2022

Background: Emerging infectious diseases, such as Middle East respiratory syndrome or coronavirus disease 2019, pose a continuous threat to public health, making a risk assessment necessary for infectious disease control and prevention. Therefore, we aimed to investigate the risk assessment methods for infectious diseases used by major foreign countries and organizations. Methods: We conducted an investigation and comparative analysis of risk assessment and risk determination methods for infectious diseases. The risk assessment tools included the strategic toolkit for assessing risks, influenza risk assessment tool, pandemic severity assessment framework, and rapid risk assessment methodology. Results: The most frequently reported risk elements were disease severity, antiviral treatment, attack rate, population immunity, and basic productive ratio. The risk evaluation method was evaluated quantitatively and qualitatively by the stakeholders at each institution. Additionally, the final risk level was visualized in a matrix, framework, and x and y-axis. Conclusion: Considering the risk assessment tools, the risk element was classified based on the duplicate of each indicator, and risk evaluation and level of risk assessment were analyzed.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1122-1135
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• 2022

With the development of digital technology and the influence of the global pandemic, the metaverse, a three-dimensional virtual world, is receiving attention in society, economy and overall industry, and the manufacturing industry is also accepting it as a major strategic agenda for digital transformation. Therefore, in this study, the concept of the industry metaverse from the perspective of the manufacturing industry was defined, and the types of the industry metaverse were classified into four types by reflecting the characteristics of the manufacturing industry based on the general metaverse scenario presented in previous studies. These are Virtual behavior simulation, Augmented operation of business objects and Virtual experience simulation, Augmented decision of business subjects. In addition, through case analysis of solutions used in the manufacturing industry, it was confirmed that the central technology of the Industry Metaverse is the digital twin, and that it is being implemented by convergence with major digital technologies such as virtual reality, augmented reality, digital human, and AI. This study will be able to provide guidelines for future research on the metaverse from the perspective of the manufacturing industry and establishment of a digital transformation strategy for the industry.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.65-78
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• 2023

Investigations on information security factors re- main elusive at small and medium enterprises (SMEs), es- specially for custom-made software solutions. This article aims to investigate, classify, adopt factors from recent literature addressing information security resources. SMEs al- ready have information security in place, but they are not easy to adopt through the negotiation processes between the in-house software development companies and custom-made software clients at SMEs. This article proposes a strategic framework for implementing the process of adoption of the information security factors at SMEs after conducting a systematic snapshot approach for investigating and classifying the resources. The systematic snapshot was conducted using a search strategy with inclusion and exclusion criteria to retain 128 final reviewed papers from a large number of papers within the period of 2001-2022. These papers were analyzed based on a classification schema including management, organizational, development, and environmental categories in software development lifecycle (SDLC) phases in order to define new security factors. The reviewed articles addressed research gaps, trends, and common covered evidence-based decisions based on the findings of the systematic mapping. Hence, this paper boosts the broader cooperation between in-house software development companies and their clients to elicit, customize, and adopt the factors based on clients' demands.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.162-165
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• 2023

Power can be generated from either renewable or non-renewable sources. Renewable sources are liked to maintain a strategic distance from contamination emanation and rely on upon fossil energizes which is decreasing day by day. The proposed sun powered vitality transformation unit comprises of a sun oriented exhibit, Bidirectional DC-DC converter, single stage inverter and AC. The inverter changes over DC control from the PV board into AC power and offered it to the heap which is associated with the lattice. The photovoltaic sun powered vitality (PV) is the most direct approach to change over sunlight based radiation into power and depends on the photovoltaic impact. The most extreme power point following of the PV yield for all daylight conditions is a key to keep the yield control per unit cost low for fruitful PV applications. Framework associated PV frameworks dependably have an association with people in general power matrix by means of an appropriate inverter in light of the fact that a PV module conveys just dc power. This project presents the new design, Development and Performance Analysis of a Grid Connected PV Inverter. Demonstrate that the proposed framework can lessen the Energy Consumption radically from the power board and give a solid support to the Grid.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.204-206
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• 2022

The global economy and the air transport business have been affected since the spread of the COVID-19 pandemic. As countries tighten restrictions on international movements, the growing emphasis on air cargo puts pressure on airports to maintain and upgrade their cargo policies, facilities, and operations. Hence, ensuring the competitiveness of cargo airports becomes pivotal for airports survival under the volatile global demand. The study aims to evaluate the importance of the competitiveness factors for cargo airports and identify areas for further improvement. The study applies the Best-Worst Method (BWM) to assess the cargo airports' competitiveness factors: 'Transport Capacity,' 'Airport Operations and Facility Capacity,' 'Economic Growth,' 'Financial Performance,' and 'Airport Brand Value.' The selected airports include Heathrow Airport, Aéroport de Paris-Charles de Gaulle, Hong Kong International Airport, and Incheon International Airport. The results identify 'Transport Capacity' as the most significant competitiveness factor, and Hong Kong International Airport the best performing cargo airport. This research forms a reference framework for evaluating cargo airports' competitive position, which may help identify airports' relative strengths and weaknesses. Moreover, this framework can also serve as a tool facilitating the strategic design of airports that may accommodate both air cargo and passenger demand flexibly under the demand uncertainty.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.833-844
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• 2023

As technology convergence is recognized as a driver of innovation, the identification of technology convergence opportunities is critical to expanding a firm's technology portfolio. Recently, wearable technology has emerged as an important factor in creating new business opportunities and providing technology investment alternatives for firms in the era of Industry 4.0. Against this background, this study provides a new patent analysis framework for identifying and proposing technology convergence opportunities in the wearable field. Using 8,621 patents filed between 2011 and 2021, a case study was conducted to identify technological convergence opportunities by applying Word2Vec algorithm. The analysis framework can be divided into four stages, with the final stage recommending potential technology convergence opportunities for a specific candidate firm's technology area by calculating similarities between technology codes. This study aims to better understand the current status of wearable technology development as well as to propose a new methodology for capturing technology convergence opportunities in the wearable industry. The case study result suggests that the convergence of healthcare and ICT may provide new development opportunities. Furthermore, the results are expected to provide alternative perspectives on the development of new markets and technologies using wearable technology and can support the strategic decision-making on future technology planning in the wearable field.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.132-141
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• 2011

Australia has joined many governments to adopt public-private partnership (PPP) as a major strategy for procuring infrastructure for decades. However, failures have occurred although the market has been considered to be a mature and sophisticated one. Failures have typically been traced back to inappropriate economic evaluation and a lack of value-for-money. In particular, a literature review has identified that there was no holistic consideration on the evaluation of procurement transactions of PPP projects. The transaction costs of PPPs were not handled properly. In this paper, theories of transaction cost economics are proposed for the purpose of such a holistic institutional economic evaluation. These theories are analysed in order to identify potential critical success factors for a strategic infrastructure procurement framework. The potential critical success factors are identified and grouped into a number of categories that match the theories of transaction cost economics. These categories include (1) Asset Specificity, (2) Organizational Capability, (3) Transaction Frequency, (4) Behavioural Uncertainty, and (5) Environmental Uncertainty. These potential critical success factors may be subject to an empirical test in the future. The proposed framework will offer decision makers with an insight into project life cycle economic outcomes needed to successfully deliver PPPs.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.85-97
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• 2010

Internet communities are a typical space for knowledge creation and use on the Internet as people discuss their common interests within the internet communities. When we define 'Knowledge Communities' as internet communities that are related to knowledge creation and use, they are categorized into 4 different types such as 'Search Engine,' 'Open Communities,' 'Specialty Communities,' and 'Activity Communities.' Each type of knowledge community does not remain the same, for example. Rather, it changes with time and is also affected by the external business environment. Therefore, it is critical to develop processes for practical use of such changeable knowledge communities. Yet there is little research regarding a strategic framework for knowledge communities as a source of knowledge creation and use. The purposes of this study are (1) to find factors that can affect knowledge creation and use for each type of knowledge community and (2) to develop a strategic framework for practical use of the knowledge communities. Based on previous research, we found 7 factors that have considerable impacts on knowledge creation and use. They were 'Fitness,' 'Reliability,' 'Systemicity,' 'Richness,' 'Similarity,' 'Feedback,' and 'Understanding.' We created 30 different questions from each type of knowledge community. The questions included common sense, IT, business and hobbies, and were uniformly selected from various knowledge communities. Instead of using survey, we used these questions to ask users of the 4 representative web sites such as Google from Search Engine, NAVER Knowledge iN from Open Communities, SLRClub from Specialty Communities, and Wikipedia from Activity Communities. These 4 representative web sites were selected based on popularity (i.e., the 4 most popular sites in Korea). They were also among the 4 most frequently mentioned sitesin previous research. The answers of the 30 knowledge questions were collected and evaluated by the 11 IT experts who have been working for IT companies more than 3 years. When evaluating, the 11 experts used the above 7 knowledge factors as criteria. Using a stepwise linear regression for the evaluation of the 7 knowledge factors, we found that each factors affects differently knowledge creation and use for each type of knowledge community. The results of the stepwise linear regression analysis showed the relationship between 'Understanding' and other knowledge factors. The relationship was different regarding the type of knowledge community. The results indicated that 'Understanding' was significantly related to 'Reliability' at 'Search Engine type', to 'Fitness' at 'Open Community type', to 'Reliability' and 'Similarity' at 'Specialty Community type', and to 'Richness' and 'Similarity' at 'Activity Community type'. A strategic framework was created from the results of this study and such framework can be useful for knowledge communities that are not stable with time. For the success of knowledge community, the results of this study suggest that it is essential to ensure there are factors that can influence knowledge communities. It is also vital to reinforce each factor has its unique influence on related knowledge community. Thus, these changeable knowledge communities should be transformed into an adequate type with proper business strategies and objectives. They also should be progressed into a type that covers varioustypes of knowledge communities. For example, DCInside started from a small specialty community focusing on digital camera hardware and camerawork and then was transformed to an open community focusing on social issues through well-known photo galleries. NAVER started from a typical search engine and now covers an open community and a special community through additional web services such as NAVER knowledge iN, NAVER Cafe, and NAVER Blog. NAVER is currently competing withan activity community such as Wikipedia through the NAVER encyclopedia that provides similar services with NAVER encyclopedia's users as Wikipedia does. Finally, the results of this study provide meaningfully practical guidance for practitioners in that which type of knowledge community is most appropriate to the fluctuated business environment as knowledge community itself evolves with time.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8262-8273
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• 2015

Sources of innovation and a sustainable competitive advantage for market leading firms in a dynamic environment are major concerns for both firm managers and academic researchers. For this reason, the dynamic capability view (DCV), evolved from the resource-based view (RBV) is gaining popularity as a cornerstone for success of firms in a dynamic market. DCV proposes a number of new concepts and elements, but these are still under development. This study suggests a comprehensive constitution of dynamic capabilities by performing a systematic literature review of 59 conceptual research papers from 238 bodies of literature. For the integrative conceptual framework, the elements of the dynamic capabilities are segmented into organizational learning and strategic choices with sensing, seizing, and reconfiguring stages. In addition, our conceptual framework lays a foundation for further empirical studies, with investigating sources of competitive advantage of market leading firms.