• Title/Summary/Keyword: University %26 Institute collaboration network analysis

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Development of a Collaboration Recommendation Model between Global Consulting Firms using Link Prediction

  • Yu, Young-su;Koo, Bon-sang
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.381-386
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    • 2020
  • Global construction and engineering consulting (E&C) firms are actively seeking entry into overseas markets based on loan projects from multilateral development banks to provide a basis for entry into overseas markets and sustainable growth. Bids on these projects are competitive between global top firms in terms of the technical level and price due to the limited number of projects; thus, developing a successful partnership to complement competence has become an essential element to win bids. In this regard, many studies have analyzed enterprises through characteristic analyses or the derivation of influential factors from the past social networks based on social network analysis (SNA). However, few studies have been conducted to reflect the process of changes to analyze collaborative relationships. Thus, this study aims to identify dynamic changes in past social networks and develop a model that can predict changes in the relationships between E&C firms based on similarities or differences between firms, presenting a methodology to target firms for appropriate collaboration. The analysis results demonstrate that the sensitivity of the developed prediction model was 70.26%, which could accurately predict 163 out of 232 actual cooperative cases.

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Business Ecosystem-focused Commercialization Strategy for Real-time Monitoring and Detection Technology for Landslides (실시간 산사태 모니터링 및 탐지기술에 대한 비즈니스 생태계 기반 기술사업화 전략 연구)

  • Sawng, Yeong-Wha;Lim, Dong-Hyun;Chae, Byung-Gon;Choi, Junghae
    • The Journal of Engineering Geology
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    • v.26 no.2
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    • pp.223-233
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    • 2016
  • This study establishes a commercialization strategy for technology that can monitor and detect landslides in real time. An effective commercialization strategy was sought through both qualitative and quantitative analyses. The qualitative analysis considered the business environment in detail, while the quantitative analysis examined technologically strong and weak areas by visualizing the links between IPC (International Patent Classification) code structure and patent applicants. The results from both analyses are considered together, with particular attention paid to the business environment. The resulting integrated analysis comprehensively explores the degree of technological development and the current state of real-time monitoring and detection technology for landslides. The integrated analysis identified complementary assets in the business environment, as there is strong development and many research entities in this area. This suggests positive reinforcement for commercialization with two sub-strategies: (1) exploring demand with complementary assets, and (2) providing technology information for explored demand, which should facilitate successful commercialization. Exploiting this positive reinforcement for technology commercialization could reduce the high uncertainty of the technology and the market, and thus increase the probability of successful commercialization. It is also expected to contribute to long-term success by strengthening collaboration between the supply and demand sides.