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A Network Analysis Model for Selecting Sustainable Technology

Author

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  • Sangsung Park

    (Graduate School of Management of Technology, Korea University, Seoul 136-701, Korea)

  • Seung-Joo Lee

    (Department of Statistics, Cheongju University, Chungbuk 363-764, Korea)

  • Sunghae Jun

    (Department of Statistics, Cheongju University, Chungbuk 363-764, Korea)

Abstract

Most companies develop technologies to improve their competitiveness in the marketplace. Typically, they then patent these technologies around the world in order to protect their intellectual property. Other companies may use patented technologies to develop new products, but must pay royalties to the patent holders or owners. Should they fail to do so, this can result in legal disputes in the form of patent infringement actions between companies. To avoid such situations, companies attempt to research and develop necessary technologies before their competitors do so. An important part of this process is analyzing existing patent documents in order to identify emerging technologies. In such analyses, extracting sustainable technology from patent data is important, because sustainable technology drives technological competition among companies and, thus, the development of new technologies. In addition, selecting sustainable technologies makes it possible to plan their R&D (research and development) efficiently. In this study, we propose a network model that can be used to select the sustainable technology from patent documents, based on the centrality and degree of a social network analysis. To verify the performance of the proposed model, we carry out a case study using actual patent data from patent databases.

Suggested Citation

  • Sangsung Park & Seung-Joo Lee & Sunghae Jun, 2015. "A Network Analysis Model for Selecting Sustainable Technology," Sustainability, MDPI, vol. 7(10), pages 1-16, September.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:10:p:13126-13141:d:56384
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Eungchan Kim & Young Seok Ock & Seung-Jun Shin & Wonchul Seo, 2018. "An Approach to Generating Reference Information for Technology Evaluation," Sustainability, MDPI, vol. 10(9), pages 1-19, September.
    2. Sangsung Park & Sunghae Jun, 2017. "Technology Analysis of Global Smart Light Emitting Diode (LED) Development Using Patent Data," Sustainability, MDPI, vol. 9(8), pages 1-15, August.
    3. Junhyeog Choi & Sunghae Jun & Sangsung Park, 2016. "A Patent Analysis for Sustainable Technology Management," Sustainability, MDPI, vol. 8(7), pages 1-13, July.
    4. Vasile Gherheș & Ciprian Obrad, 2018. "Technical and Humanities Students’ Perspectives on the Development and Sustainability of Artificial Intelligence (AI)," Sustainability, MDPI, vol. 10(9), pages 1-16, August.
    5. Kulkarni, Shruti, 2020. "Using Machine Learning to Analyze Climate Change Technology Transfer (CCTT)," SocArXiv zyb3j, Center for Open Science.
    6. Kim, Gabjo & Bae, Jinwoo, 2017. "A novel approach to forecast promising technology through patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 228-237.
    7. Sunghae Jun, 2019. "Bayesian Structural Time Series and Regression Modeling for Sustainable Technology Management," Sustainability, MDPI, vol. 11(18), pages 1-12, September.
    8. Gyula Dörgő & Viktor Sebestyén & János Abonyi, 2018. "Evaluating the Interconnectedness of the Sustainable Development Goals Based on the Causality Analysis of Sustainability Indicators," Sustainability, MDPI, vol. 10(10), pages 1-26, October.
    9. Juhwan Kim & Sunghae Jun & Dongsik Jang & Sangsung Park, 2018. "Sustainable Technology Analysis of Artificial Intelligence Using Bayesian and Social Network Models," Sustainability, MDPI, vol. 10(1), pages 1-12, January.
    10. Ning Huang & Libiao Bai & Hailing Wang & Qiang Du & Long Shao & Jingtao Li, 2018. "Social Network Analysis of Factors Influencing Green Building Development in China," IJERPH, MDPI, vol. 15(12), pages 1-16, November.
    11. Li, Shuying & Garces, Edwin & Daim, Tugrul, 2019. "Technology forecasting by analogy-based on social network analysis: The case of autonomous vehicles," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    12. Daiho Uhm & Jea-Bok Ryu & Sunghae Jun, 2017. "An Interval Estimation Method of Patent Keyword Data for Sustainable Technology Forecasting," Sustainability, MDPI, vol. 9(11), pages 1-19, November.
    13. Jumi Hwang & Kyung Hee Kim & Jong Gyu Hwang & Sungchan Jun & Jiwon Yu & Chulung Lee, 2020. "Technological Opportunity Analysis: Assistive Technology for Blind and Visually Impaired People," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
    14. Sunghae Jun, 2018. "Bayesian Count Data Modeling for Finding Technological Sustainability," Sustainability, MDPI, vol. 10(9), pages 1-12, September.
    15. Jaehyun Choi & Dongsik Jang & Sunghae Jun & Sangsung Park, 2015. "A Predictive Model of Technology Transfer Using Patent Analysis," Sustainability, MDPI, vol. 7(12), pages 1-21, December.
    16. Alina Steblyanskaya & Xu Qingchao & Svetlana Razmanova & Nikolay Steblyanskiy & Artem Denisov, 2021. "China and Russia Energy Strategy Development: Arctic LNG," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 450-460.
    17. Eun Jin Han & So Young Sohn, 2017. "Firms’ Negative Perceptions on Patents, Technology Management Strategies, and Subsequent Performance," Sustainability, MDPI, vol. 9(3), pages 1-15, March.
    18. Dongwook Kim & Sungbum Kim, 2017. "The Role of Mobile Technology in Tourism: Patents, Articles, News, and Mobile Tour App Reviews," Sustainability, MDPI, vol. 9(11), pages 1-45, November.
    19. Lu Zhang & Xiaochao Guo & Zhimei Lei & Ming K. Lim, 2019. "Social Network Analysis of Sustainable Human Resource Management from the Employee Training’s Perspective," Sustainability, MDPI, vol. 11(2), pages 1-20, January.
    20. Tsouchnika, Maria & Smolyak, Alex & Argyrakis, Panos & Havlin, Shlomo, 2022. "Patent collaborations: From segregation to globalization," Journal of Informetrics, Elsevier, vol. 16(1).
    21. Jong-Min Kim & Bainwen Sun & Sunghae Jun, 2019. "Sustainable Technology Analysis Using Data Envelopment Analysis and State Space Models," Sustainability, MDPI, vol. 11(13), pages 1-19, June.
    22. BangRae Lee & DongKyu Won & Jun-Hwan Park & LeeNam Kwon & Young-Ho Moon & Han-Joon Kim, 2016. "Patent-Enhancing Strategies by Industry in Korea Using a Data Envelopment Analysis," Sustainability, MDPI, vol. 8(9), pages 1-17, September.
    23. Azimi, Sasan & Rahmani, Rouhollah & Fateh-rad, Mahdi, 2019. "Investment cost optimization for industrial project portfolios using technology mining," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 243-253.
    24. Sungchul Kim & Dongsik Jang & Sunghae Jun & Sangsung Park, 2015. "A Novel Forecasting Methodology for Sustainable Management of Defense Technology," Sustainability, MDPI, vol. 7(12), pages 1-17, December.
    25. Sangsung Park & Sunghae Jun, 2017. "Statistical Technology Analysis for Competitive Sustainability of Three Dimensional Printing," Sustainability, MDPI, vol. 9(7), pages 1-16, June.

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