• Title/Summary/Keyword: 생태계모델

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사회적 혁신 기반 소셜벤처 생태계 활성화 전략

  • Choe, Yong-Seok;Baek, Bo-Hyeon
    • 한국벤처창업학회:학술대회논문집
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    • 2019.11a
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    • pp.51-59
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    • 2019
  • 현대사회가 당면한 다양한 문제를 해결하는 주체로 '제4섹터(the fourth sector)'가 주목받고 있다. 제4섹터는 사회적경제 기업으로 대표되는 제3섹터의 지나친 정부 의존도와 서비스 모델 동형화의 문제점을 해결하고자 등장하였다(Meadows, 1972; Howaldt and Schwarz, 2010). 이러한 제4섹터의 핵심 주체로서 소셜벤처가 언급되고 있다(경기연구원, 2018). 그러나 아직까지 소셜벤처에 대한 학술적 및 정책적 개념이 모호한 실정이다. 따라서 본 연구에서는 사회의 포용적 성장을 도모하기 위해 제4섹터로서의 소셜벤처 정의와 특성을 명확히 하고, 소셜벤처 생태계 활성화를 위한 발전전략을 연구하고자 한다.

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A Study on the Problems and Policy Implementation for Open-Source Software Industry in Korea: Soft System Methodology Approach (소프트시스템 모델 방법론을 통해 진단한 국내 공개 SW 산업의 문제점과 정책전략 연구)

  • Kang, Songhee;Shim, Dongnyok;Pack, Pill Ho
    • The Journal of Society for e-Business Studies
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    • v.20 no.4
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    • pp.193-208
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    • 2015
  • In knowledge based society, information technology (IT) has been playing a key role in economic growth. In recent years, it is surprisingly notable that the source of value creation moved from hardware to software in IT industry. Especially, among many kinds of software products, the economic potential of open source was realized by many government agencies. Open source means software codes made by voluntary and open participation of worldwide IT developers, and many policies to promote open source activities were implemented for the purpose of fast growth in IT industry. But in many cases, especially in Korea, the policies promoting open source industry and its ecosystem were not considered successful. Therefore, this study provides the practical reasons for the low performance of Korean open source industry and suggests the pragmatic requisites for effective open source policy. For this purpose, this study applies soft system model (SSM) which is frequently used in academy and industry as a methodology for problem-solving and we link the problems with corresponding policy solutions based on SSM. Given concerns which Korean open source faces now, this study suggests needs for the three different kinds of government policies promoting multiple dimensions of industry: research and development (R&D)-side, supply-side, and computing environment-side. The implications suggested by this research will contribute to implement the practical policy solutions to boost open source industry in Korea.

Distributed Identity Management Model using SAML in Digital Ecosystem (디지털 생태계에서 SAML을 이용한 분산 아이디 관리모델)

  • Jang, In-Yong;Youm, Heung-Youl
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.9 no.6
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    • pp.141-154
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    • 2009
  • Digital Ecosystem is a new word for dynamic IT business environments. Digital Ecosystem can consist of various enterprise federations such as competing, collaborating and stable or unstable ones. They make it difficult to implement identity management for the environment. Existing solutions are either too restricting and inflexible to support the dynamic nature of ecosystems since they are too complex and difficult to adopt. This paper is to propose an distributed identity management model for automated processing of identity information between ecosystems. It is featured with being practical, clear and easy to deploy. And it is based on the new OASIS SAML3.0 standard to provide interoperability between existing identity technologies. This paper presents the basic and extended identity model for single service and multiple services. The model presented in this paper can be applied to enterprise context easily.

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Simulation of wetland storage volume using a classification-based artificial intelligence prediction model (분류 기반의 인공지능 예측 모델을 이용한 습지 저류량 모의)

  • Ji yu Seo;Ha eun Jung;Jeong Hoon Lee;Sang Dan Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.270-270
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    • 2023
  • 습지 생태계는 복잡한 물리적 생지화학적 프로세스의 상호작용이 있으나, 습지 생태계의 건강성 회복을 위한 첫 번째 단계는 습지 생태계에서의 물순환에 대한 정확한 이해일 것이다. 또한 지역적인 물 균형 및 생태계 보전에서 습지를 활용하기 위해서도 습지 물순환에 대한 정량적인 이해는 필수적이다. 그러나, 습지 물순환의 이해를 위해 필수적인 관측 자료들은 현장 측정으로 획득하기 어려운 자료이거나 비용적인 문제로 인하여 관측이 어려운 실정이다. 이에 본 연구에서는 Sentinel-2 위성 자료를 활용하여 습지의 유입량을 추정하기 위한 절차를 제시하고자 한다. 이를 위해 한반도 동남부의 낙동강에 위치한 주요 다목적댐의 자료를 활용한 분류 기반의 인공지능 모델이 설계된다. 인공지능의 학습을 위한 입력자료는 아래와 같은 절차에 의해 만들어진다. 1) 다목적댐의 수위-물 체적 관계를 이용하여 수위-수표면적 관계 곡선 도출. 2) 수위-수표면적 관계 곡선과 DEM을 활용하여 물과 육지 영역을 구분하는 식별자를 도출. 3) Sentinel-2 위성 정보와 물-육지 식별자를 비교하는 랜덤 포레스트 모델을 설계. 4) 위성 정보의 물-육지 정보로부터 미계측 습지 지역의 물과 육지를 식별할 수 있는 식별자 도출. 이러한 과정을 경유하여 추정된 습지의 수표면적과 습지 지역의 DEM을 결합함으로써 습지의 수위-수표면적-물 체적 관계 곡선이 산정되어, 최종적으로 습지의 유입량이 모의된다. 모의된 습지 유입량은 다양한 수문 모델의 매개변수를 추정하는데 활용될 수 있을 것이며, 검증된 수문 모델을 활용하여 습지의 물순환의 이해도를 증진시킬 수 있을 것으로 기대된다.

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A Study on e-Healthcare Business Model: Focusing on Business Ecosystem Approach (e헬스케어 비즈니스모델에 관한 연구: 비즈니스생태계 접근 중심으로)

  • Kim, Youngsoo;Jung, Jai-Jin
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.14 no.1
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    • pp.167-185
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    • 2019
  • As most G-20 countries expect medical spending to grow rapidly over the next few decades, the burden of healthcare costs continues to grow globally due to an increase in the elderly population and chronic illnesses, and the ongoing quality improvement of health care services. However, under the rapidly changing technological environment of healthcare and IT convergence, the problem may become even bigger if not properly recognized and not properly prepared. In the context of the paradigm shift and the increasing problem of the medical field, complex responses in technical, institutional and business aspects are urgently needed. The key is to derive a business model that is appropriate for businesses that integrate IT in the medical field. With the arrival of the era of the 4th industrial revolution, new technologies such as Internet of Things have been applied to eHealthcare, and the need for new business models has emerged.In the e-healthcare of the Internet era, it became a traditional firm-based business model. However, due to the characteristics of dynamics and complexity of things Internet in the Internet of things, A business ecosystem-based approach is needed. In this paper, we present and analyze the major success factors of the ecosystem based on the 3 - layer structure of the e - healthcare business ecosystem as a result of research on e - healthcare business ecosystem based on emerging technology such as Internet of things. The three-layer business ecosystem was defined as (1) Infrastructure Layer, (2) Character Layer, and (3) Stakeholder Layer. As the key success factors for the eHealthCare business ecosystem, the following four factors are suggested: (1) introduction of the iHealthcare concept, (2) expansion of the business ecosystem, (3) business ecosystem change process innovation, and (4) business ecosystem leadership innovation.

Characterization of Ecological Networks on Wetland Complexes by Dispersal Models (분산 모형에 따른 습지경관의 생태 네트워크 특성 분석)

  • Kim, Bin;Park, Jeryang
    • Journal of Wetlands Research
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    • v.21 no.1
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    • pp.16-26
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    • 2019
  • Wetlands that provide diverse ecosystem services, such as habitat provision and hydrological control of flora and fauna, constitute ecosystems through interaction between wetlands existing in a wetlandscape. Therefore, to evaluate the wetland functions such as resilience, it is necessary to analyze the ecological connectivity that is formed between wetlands which also show hydrologically dynamic behaviors. In this study, by defining wetlands as ecological nodes, we generated ecological networks through the connection of wetlands according to the dispersal model of wetland species. The characteristics of these networks were then analyzed using various network metrics. In the case of the dispersal based on a threshold distance, while a high local clustering is observed compared to the exponential dispersal kernel and heavy-tailed dispersal model, it showed a low efficiency in the movement between wetlands. On the other hand, in the case of the stochastic dispersion model, a low local clustering with high efficiency in the movement was observed. Our results confirmed that the ecological network characteristics are completely different depending on which dispersal model is chosen, and one should be careful on selecting the appropriate model for identifying network properties which highly affect the interpretation of network structure and function.