• Information Systems Review
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• v.14 no.2
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• pp.21-46
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• 2012

Organizations that make widely use of information technologies can be more efficient. But, the dependence of information technologies leads to an increase in threat of security. This is the reason why organizations are investing in security risk management (SRM) which is designed to protect of information assets. Noting a lack of empirical research in SRM, we investigate the key factors having a direct effect on performance of SRM. Particularly, this study focused on identifying factors influencing awareness of SRM and Intention to develop SRM in Organization. Based on relevant literature review, six motivating factors, including Behavior for Security Management, Compliance with Security Policy, perceived Benefits, Perceived Sacrifice, Social Pressure, Experience of Security Risks, were initially identified. The results indicated that most perception factors were positively related to Organization's intention to develop SRM and awareness of SRM, which then had positive impact on performance of SRM. But Perceived Sacrifice was not significantly related to two variables which is Organization's intention to develop SRM and awareness of SRM.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.109-111
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• 2006

본 논문은 애니메이터로 하여금 얼굴 표정들의 공간으로부터 일련의 표정을 선택하게 함으로써 3차원 아바타의 표정을 실시간적으로 제어할 수 있도록 하기 위한 표정공간의 생성방법에 관하여 기술한다. 본 시스템에서는 약 2400여개의 얼굴 표정 프레임을 이용하여 표정공간을 구성하였다. 본 기법에서는 한 표정을 표시하는 상태표현으로 얼굴특징 점들 간의 상호거리를 표시하는 거리행렬을 사용한다. 이 거리행렬의 집합을 표정공간으로 한다. 그러나 이 표정공간은 한 표정이 다른 표정까지 이동할 때 두 표정간의 직선경로를 통해 이동할 수 있는 그런 공간이 아니다. 본 기법에서는 한 표정에서 다른 표정까지 거쳐 갈 수 있는 경로를 캡쳐된 표정 데이터로부터 근사적으로 유추한다. 우선, 각 표정상태를 표현하는 거리행렬간의 거리가 일정 값 이하인 경우 두 표정을 인접해 있다고 간주한다. 임의의 두 표정 상태가 일련의 인접표정들의 집합으로 연결되어 있으면 두 표정간에 경로가 존재한다고 간주한다. 한 표정에서 다른 표정으로 변화할 때 두 표정간의 최단경로를 통해 이동한다고 가정한다. 두 표정간의 최단거리를 구하기 위해 다이내믹 프로그래밍 기법을 이용한다. 이 거리행렬의 집합인 표정공간은 다차원 공간이다. 3차원 아바타의 얼굴 표정 제어는 애니메이터들이 표정공간을 항해할 때 실시간적으로 수행된다. 이를 도와주기 위해 표정공간을 차원 스케일링 기법을 이용하여 2차원 공간으로 가시화하였고, 애니메이터들로 하여금 본 시스템을 사용하여 실시간 표정 제어를 수행하게 했는데, 본 논문은 그 결과를 평가한다.참여하는 빈들 간의 관계를 분석하여 워크플로우에 대한 성능 측정이 가능하도록 한다. 또한 제안된 메트릭을 통하여 EJB 어플리케이션의 성능 향상을 도모할 수 있도록 한다.로 표면 위로 자라났고, 부종은 창상 밑 조직까지 감소하였으며, 육아조직은 교원질 섬유로 대체되었다. 창상 유발 21일 후, 다른 창상에 비해, HG 처치창은 유의적으로 창상 표면이 거의 재생성 상피로 덮였으며, 육아조직은 창상 유발 14일 후와 비교해서 유의적으로 교원질 섬유로 대체되었다. 위의 모든 결과에서 보듯이, 개에서 전층피부 창상의 처치 시 HG의 사용은 HC와 생리 식염수에 비해 창상치유 복구기의 치유 속도를 촉진하는 것으로 사료된다.시범학교의 자녀를 들 부모들은 환경관련문제에 대한 의식 및 환경관련 제품에 대한 구매행동의 변화가 두드러지게 나타났다.EX>$d^{2+}$ + SA처리구는 두 화합물의 이중 효과에 의해 전반적인 생리 활성을 억제하여, 결국에는 식물의 고사를 유도하는 것으로 사료된다.목에 대한 보안'이 가장 중요한 것으로 나타났다. 본 연구에서는 솔루션 선정요인에 관한 중요도를 e-마켓플레이스의 유형과 산업 별로 평가해보았는데, 여기에서 밝혀진 중요도를 통해 e 마켓플레이스를 구축하고 자 하는 기업은 솔루션을 자체 개발하거나 구입할 때 올바른 의사결정을 할 수 있다. 그리고 솔루션을 제공하려는 기업측면에서는 e-마켓플레이스를 구축하고자 하는 기업에게 유형과 산업별로 적절한 솔루션을 제공할 수 있다.순환이 뇌대사 및 수술 후 신경학적 결과에 보다 유익한 효과를 제공해 줄 수 있음

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.987-993
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• 2002

최근 들어 전자상거래의 급속한 발달로 전 세계적으로 수송 물동량이 급격히 증대되고 있고, 이로 인해 택배사업이 대단히 활성화되고 있다. 출발지와 목적지가 서로 상이한 무수히 만은 수송 요구가 들어오면 수송 요구화물의 신속한 집배송을 위한 배차계획 및 수송계획을 세우는 것이 택배회사의 주요 업무이다. 이러한 배차 계획 및 수송 계획을 어떻게 수립하느냐에 따라 전체 수송비용뿐만 아니라 고객들의 서비스 수준에 상당한 영향을 미치게 된다. 그러나 이러한 운영적 차원에서의 의사결정 이전에 훨씬 중요하게 고려해야 할 내용이 택배네트워크의 설계 문제이다. 이러한 택배네트워크의 설계에는 터미널 개수 및 위치를 결정하는 전략적 문제와 영업소들을 터미널에 할당하는 전술적 문제로 구분될 수 있다. 현재 우리 국내에는 크고 작은 수많은 택배사업자들이 있으나, 그 중에서 비교적 규모가 큰 주요 택배회사들은 대부분 전국에 걸쳐 다수의 터미널을 설치하여 두고 수송화물의 집배송을 위한 물류거점으로 운영하고 있다. 이와 같은 터미널 위치 및 개수가 정해진 상태에서 전국에 걸쳐 분포되어 있는 영업소들을 어떤 터미널에 할당하여 처리되도록 하느냐의 여부는 수송비용 측면에서뿐만 아니라 고객들에 대한 서비스 측면에서 대단히 중요한 의사결정 중의 하나이다. 본 연구에서는 비용과 시간을 고려하여 전국에 걸쳐 분포되어 있는 영업소들을 어떤 터미널에 할당해야 하는지를 결정하기 위한 수리적 모형을 제시하고, 이에 대한 탐색적 해법을 제시하며, 국내의 택배회사 사례를 대상으로 모형을 적용해 보고자 한다.무가 많이 발생하는 유통 분야의 프랜차이즈 산업을 대상으로 기업정보시스템 구현 및 경쟁력 강화를 뒷받침하기 위해서, 기업간 프로세스 협업(collaboration) 부분의 데이터 및 서식, 이를 취급하는 기능과 프로세스에 대란 분석을 통해 업무 프로세스 모델링 방법론과 관련한 모델링 지침 및 메타모델을 이용한 표준 업무 프로세스 모델을 개발하여 기업간 업무 프로세스 표준화에 대한 체계적인 관리에 대한 방안을 연구하고자 한다.의Bullwhip effect를 감소시킬 수 있는 장점이 있다. 동시에 이것은 향후 e-Business 시스템 구축을 위한 기본 인프라 역할을 수행할 수 있게 된다. 많았고 년도에 따른 변화는 보이지 않았다. 스키손상의 발생빈도는 초기에 비하여 점차 감소하는 경향을 보였으며, 손상의 특성도 부위별, 연령별로 다양한 변화를 나타내었다.해가능성을 가진 균이 상당수 검출되므로 원료의 수송, 김치의 제조 및 유통과정에서 병원균에 대한 오염방지에 유의하여야 할 것이다. 확인할 수 있었다. 이상의 결과에 의하면 고농도의 유기물이 함유된 음식물쓰레기는 Hybrid Anaerobic Reactor (HAR)를 이용하여 HRT 30일 정도에서 충분히 직접 혐기성처리가 가능하며, 이때 발생된 $CH_{4}$를 회수하여 이용하면 대체에너지원으로 활용 가치가 높은 것으로 판단된다./207), $99.2\%$(238/240), $98.5\%$(133/135) 및 $100\%$ (313)였다. 각

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.1
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• pp.133-158
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• 2011

In 2030s, as we enter in to the era of BT (Bio-Technology) market opening up, technologies in all areas such as IT, data analysis, IC and biochemistry are necessitated. New development in technology will be based on "Convergence", especially between IT and BT. In order to have synergy effects from the convergence, those related industries and universities should be physically inter-related in an appropriate location. Until 2009, 819 industrial clusters where many Korean industries and firms are concentrated have been constructed in Korea. They have had supports from various institutions and facilities. However, few systems designed to assist "intellectual property (IP) service" for technology convergence are found in Korea. Thus, by analyzing current problems and challenges of the Korean industrial clusters, this paper suggests a possible answer to maximize the synergy from technology convergence through organic cooperation among companies in industrial clusters. This paper finds that the Korean industrial clusters need to establish IP service supporting center while suggesting its function and concept on organization structure, and work flow, which help firms to develop IP strategies. In addition, the paper provides a direction for current IP system and policies implemented by the Korean government to be more effective to small-and-medium-sized companies located in the industrial clusters.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.163-176
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• 2019

The purpose of this study is to examine the impact of PM consultant leadership competence on consulting repurchase intention and the impact of SME CEO participation on consulting repurchase intention. The validity of the measurement model was secured through CFA (Confirmative Factor Analysis) for the questionnaire data, and consistency was secured through the same method convenience, and significant results were obtained. In other words, not only the ability of PM consultant in repurchase of consulting is important, but also confirms that repurchase intention differs according to the participation of manager. Therefore, the performance that manager feels depends on the degree of manager's interest in repurchase and plays an important role in repurchase. As a result, it is important for PM to report to manager and / or make the manager participate in consulting process so that manager can be interested. In this study, it is difficult to generalize the relationship between PM's leadership role and manager's involvement in the repurchase intention. However, it is meaningful that PM's competence as well as management's participation are very important, and that this study figured out which drection PM's leadership should focus on. The purpose of this study is to investigate the effect of the variables on the repurchase intention.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.397-404
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• 2021

The web-based crowdfunding platform provides small-cap companies the opportunity to reduce financial risks and to reliably produce new products through pre-orders. Meanwhile, crowdfunding projects are also helping companies as a channel to test new products before mass production. Despite these advantages, from the point of view of businesses and consumers, it is true that web-based crowdfunding platforms have limitations in the retail environment. For example, the limited social elements of a web-based platform are somewhat in conflict with the basic characteristics of crowdfunding projects - which inevitably demand high social influences for the success. As such, understanding the mechanisms of social factors of crowdfunding platforms from the consumers' perspective is important. Therefore, in this study, we empirically tested the effect of social factors of crowdfunding platform on consumer participation and evaluation. Based on the Social Influence Theory and Social Presence Theory, we developed a conceptual framework where the social group size and social presence of other backers were the independent variables and the purchaser's intention to participate as the dependent variable. In the results, the size of the social group size and the perceived social presence have a significant positive effect on purchaser's participation intent. In addition, the social presence had a greater influence on the purchaser's intention to participate than the size of the sponsor's social group. We believe that our findings contribute to the extant literature by empirically demonstrating the valid effect of social factors of crowdfunding platforms on consumer evaluations.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.163-172
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• 2022

This study investigates the IPI (Information Protection Intention) of DHS (Digital Healthcare Service) providers by introducing PMT (Protection Motivation Theory). This study examines the effects of protection motivation, such as threat appraisal and coping appraisal, on IPI, such as ICI(Induction Control Intention) and SDI(Self Defense Intention). The research model, based on the PMT, adopted severity, vulnerability, reaction efficacy and self-efficacy as independent variables. The research model was validated through quantitative research, a survey of 222 DHS providers in South Korea, using structural equation modeling. The results show that (1) a clear awareness of the consequences of security threats increases the understanding of DHS providers on the severity of closure of healthcare information, and thus may decreases abuse of DHS by providers; (2) user confidence and satisfaction on the security system may make them be confident that they can handle the closure of healthcare information by themselves; and (3) although DHS providers are realizing the consequences of closure of healthcare information, they think that they are unlikely to encounter such situations. As a result of this study, venture companies that provide DHS need to provide contents that can continuously increase providers' security level in order to increase providers' information protection intention. It suggests that IPI is important through trust of healthcare service providers.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.15-23
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• 2014

A Case Study on Venture and Small-Business Executives' Use of Strategic Intuition in the Decision Making Process This paper is a case study on how Venture and Small-Business Executives managers can take advantage of their intuitions in situations where the business environment is increasingly uncertain, a novel situation occurs without any data to reflect on, when rational decision-making is not possible, and when the business environment changes. The case study is based on a literature review, in-depth interviews with 16 business managers, and an analysis of Klein, G's (1998) "Generic Mental Simulation Model." The "intuition" discussed in this analysis is classified into two types of intuition: the Expert Intuition which is based on one's own experiences, and Strategic Intuition which is based on the experience of others. Case study strategic management intuition and intuition, the experts were utilized differently. Features of professional intuition to work quickly without any effort by, while the strategic intuition, is time-consuming. Another feature that has already occurred, one expert intuition in decision-making about the widely used strategic intuition was used a lot in future decision-making. The case study results revealed that managers were using expert intuition and strategic intuition differentially. More specifically, Expert Intuition was activated effortlessly, while strategic intuition required more time. Also, expert intuition was used mainly for making judgments about events that have already happened, while strategic intuition was used more often for judgments regarding events in the future. The process of strategic intuition involved (1) Strategic concerns, (2) the discovery of medium, (3) Primary mental simulation, (4) The offsetting of key parameters, (5) secondary mental simulation, and (6) the decision making process. These steps were used to develop the "Strategic Intuition Decision-making Model" for Venture and Small-Business Executives. The case study results further showed that firstly, the success of decision-making was determined in the "secondary mental simulation' stage, and secondly, that more difficulty in management was encountered when expert intuition was used more than strategic intuition and lastly strategic intuition is possible to be educated.

• 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.