• Title/Summary/Keyword: platform-based knowledge ecosystems

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Organizing knowledge ecosystems: The influence of organizational capabilities of platform leaders on multi-firm collaborations for knowledge creation (지식생태계의 조직화: 플랫폼 리더의 조직역량이 지식창출을 위한 기업간 협력의 확장에 미치는 영향)

  • Jung, Dongil;Park, Sangchan;Kim, Bokyung
    • Knowledge Management Research
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    • v.16 no.2
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    • pp.1-27
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    • 2015
  • This paper presents a knowledge-based view of platform-centered collaborations among multiple organizations. Studies of technological innovation and knowledge creation have broadened beyond their initial emphasis on internal development within an organization or simple exchange of ideas between two parties toward complex collaboration among many organizations at the level of platform-based knowledge ecosystems. Platforms serve as an interface between different groups of producers and consumers in a variety of multi-sided knowledge markets such as smartphone operating systems and video games industries. This study is an exploratory examination to offer theoretical understanding of how the organizational capabilities of platform leaders help expand a network of platform participants. The growth of platform participants is particularly important in the early stage of any platforms as the concept of network effects suggests that the platform with the largest number of participants will capture entire markets. Building upon organization studies and network economics theory on multisided markets, this paper focuses on the role of platform leaders in expanding platform-based collaboration. In our view, platform leaders develop varying levels of three organizational capabilities to discern quality of potential participants, to attract them to actually participate in collaboration, and to maintain long-term exchange relations in the ecosystem. We suggest that the capabilities of platform leaders will have a positive effect on the expansion of platform participants to secure network effects, and also examine several contextual factors that moderate the relationship between a platform leader's capacity and platform expansion.

Platform Based of The Major Attribute Research for The Service Ecosystem Construction (플랫폼 기반의 서비스 생태계 구축을 위한 주요 속성 연구)

  • Kwon, Hyeog-In;Na, Yun-Bin;Park, Jong-Suk
    • Journal of Information Technology Services
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    • v.12 no.4
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    • pp.461-472
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    • 2013
  • Today, In the Service Industry are more getting a lot of convergence of IT utilization. And global IT companies are strengthening that platform based Services Ecosystems. These business in the field, Ecosystem Competitive strategy is difficult to imitate. And this strategy is generated organic Business Model that a by Competitive-Predominance to brings. In addition, the added value of the Service Industry is taken, a new type of job creation by the ripple-effect is huge. However, existing the Ecosystem Theory of Business is a lack of research on the use. Thus, Ecosystem Construction conditions is very difficult. This study is try to successful Platform Case's Analysis such as Apple, Google, Amazon, eBay's. These Ecosystems is that want to know the Major attributes. At first, would be analyzing to previous research, the Service and Knowledge Services' major attributes and Ecosystem studies' major attributes to grasp. Then, from a Group of Experts is to assess the importance. Finally, according to each Platform, examined the Correlation of Major Attributes.

A Machine Learning-Driven Approach for Wildfire Detection Using Hybrid-Sentinel Data: A Case Study of the 2022 Uljin Wildfire, South Korea

  • Linh Nguyen Van;Min Ho Yeon;Jin Hyeong Lee;Gi Ha Lee
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.175-175
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    • 2023
  • Detection and monitoring of wildfires are essential for limiting their harmful effects on ecosystems, human lives, and property. In this research, we propose a novel method running in the Google Earth Engine platform for identifying and characterizing burnt regions using a hybrid of Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (multispectral photography) images. The 2022 Uljin wildfire, the severest event in South Korean history, is the primary area of our investigation. Given its documented success in remote sensing and land cover categorization applications, we select the Random Forest (RF) method as our primary classifier. Next, we evaluate the performance of our model using multiple accuracy measures, including overall accuracy (OA), Kappa coefficient, and area under the curve (AUC). The proposed method shows the accuracy and resilience of wildfire identification compared to traditional methods that depend on survey data. These results have significant implications for the development of efficient and dependable wildfire monitoring systems and add to our knowledge of how machine learning and remote sensing-based approaches may be combined to improve environmental monitoring and management applications.

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Analysis on Dynamics of Korea Startup Ecosystems Based on Topic Modeling (토픽 모델링을 활용한 한국의 창업생태계 트렌드 변화 분석)

  • Heeyoung Son;Myungjong Lee;Youngjo Byun
    • Knowledge Management Research
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    • v.23 no.4
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    • pp.315-338
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    • 2022
  • In 1986, Korea established legal systems to support small and medium-sized start-ups, which becomes the main pillars of national development. The legal systems have stimulated start-up ecosystems to have more than 1 million new start-up companies founded every year during the past 30 years. To analyze the trend of Korea's start-up ecosystem, in this study, we collected 1.18 million news articles from 1991 to 2020. Then, we extracted news articles that have the keywords "start-up", "venture", and "start-up". We employed network analysis and topic modeling to analyze collected news articles. Our analysis can contribute to analyzing the government policy direction shown in the history of start-up support policy. Specifically, our analysis identifies the dynamic characteristics of government influenced by external environmental factors (e.g., society, economy, and culture). The results of our analysis suggest that the start-up ecosystems in Korea have changed and developed mainly by the government policies for corporation governance, industrial development planning, deregulation, and economic prosperity plan. Our frequency keyword analysis contributes to understanding entrepreneurial productivity attributed to activities among the networked components in industrial ecosystems. Our analyses and results provide practitioners and researchers with practical and academic implications that can help to establish dedicated support policies through forecast tasks of the economic environment surrounding the start-ups. Korean entrepreneurial productivity has been empowered by growing numbers of large companies in the mobile phone industry. The spectrum of large companies incorporates content startups, platform providers, online shopping malls, and youth-oriented start-ups. In addition, economic situational factors contribute to the growth of Korean entrepreneurial productivity the economic, which are related to the global expansions of the mobile industry, and government efforts to foster start-ups. Our research is methodologically implicative. We employ natural language processes for 30 years of media articles, which enables more rigorous analysis compared to the existing studies which only observe changes in government and policy based on a qualitative manner.