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Logistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap

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  • Koopo Kwon

    (Department of Industrial and Management Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Korea
    Department of Shipping and Air Cargo & Drone Logistics, Youngsan University, 142 Bansongsunhwan-ro, Haeundae-gu, Busan 48015, Korea)

  • Sungchan Jun

    (Department of Industrial and Management Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Korea)

  • Yong-Jae Lee

    (Department of Industrial and Management Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Korea)

  • Sanghei Choi

    (Vice President for Research, Korea Maritime Institute, 26, Haeyang-ro 301 beon-gil, Yeongdo-gu, Busan 49111, Korea)

  • Chulung Lee

    (School of Industrial and Management Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea)

Abstract

The rapid advancement of digital technologies has fundamentally changed the competitive dynamics of the logistics industry. For players in the logistics industry, digitization has become an unavoidable situation to achieve survival and sustainable competitiveness. A technology strategy is essential for digitization, and identifying opportunities and threats of technology development through technology trend exploration is important for technology strategy. In addition, to enable the implementation of the technology strategy, it is necessary to detect the change in technology and search for the technology that is expected to have a practical development effect. The purpose of this study is to identify opportunities and areas for technology development through patent data in establishing technology strategies. Previous research mainly relied on the expert interview method, and there was also a patent analysis study based on topic modeling, but only to grasp technology trends. This paper aims to propose a new framework for the extension to the stage for establishing a technology roadmap. By using the Word2Vec algorithm, we will investigate the patent search formula that reflects the trend, the prediction of changes in logistics technology through LDA (Latent Dirichlet Allocation) clustering of patent data, and the derivation of vacant technology by experimental methods. The proposed framework is expected to be utilized for predicting technological change and deriving promising technologies for establishing technology roadmaps in logistics companies.

Suggested Citation

  • Koopo Kwon & Sungchan Jun & Yong-Jae Lee & Sanghei Choi & Chulung Lee, 2022. "Logistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5430-:d:806675
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    References listed on IDEAS

    as
    1. Coccia, Mario, 2019. "The theory of technological parasitism for the measurement of the evolution of technology and technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 289-304.
    2. Loet Leydesdorff & Duncan Kushnir & Ismael Rafols, 2014. "Interactive overlay maps for US patent (USPTO) data based on International Patent Classification (IPC)," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1583-1599, March.
    3. Donghyun Choi & Bomi Song, 2018. "Exploring Technological Trends in Logistics: Topic Modeling-Based Patent Analysis," Sustainability, MDPI, vol. 10(8), pages 1-26, August.
    4. David J. Teece, 2003. "Competition, Cooperation, and Innovation Organizational Arrangements for Regimes of Rapid Technological Progress," World Scientific Book Chapters, in: Essays In Technology Management And Policy Selected Papers of David J Teece, chapter 16, pages 447-474, World Scientific Publishing Co. Pte. Ltd..
    5. Dong-Hui Jin & Hyun-Jung Kim, 2018. "Integrated Understanding of Big Data, Big Data Analysis, and Business Intelligence: A Case Study of Logistics," Sustainability, MDPI, vol. 10(10), pages 1-15, October.
    6. Bo Wang & Shengbo Liu & Kun Ding & Zeyuan Liu & Jing Xu, 2014. "Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis: a case study in LTE technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 685-704, October.
    7. Wang, Chang & Geng, Hongjun & Sun, Rui & Song, Huiling, 2022. "Technological potential analysis and vacant technology forecasting in the graphene field based on the patent data mining," Resources Policy, Elsevier, vol. 77(C).
    8. Cho, Youngsang & Hwang, Junseok & Lee, Daeho, 2012. "Identification of effective opinion leaders in the diffusion of technological innovation: A social network approach," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 97-106.
    9. Chen, P. & Redner, S., 2010. "Community structure of the physical review citation network," Journal of Informetrics, Elsevier, vol. 4(3), pages 278-290.
    10. Bouzon, Marina & Govindan, Kannan & Rodriguez, Carlos M.Taboada & Campos, Lucila M.S., 2016. "Identification and analysis of reverse logistics barriers using fuzzy Delphi method and AHP," Resources, Conservation & Recycling, Elsevier, vol. 108(C), pages 182-197.
    11. Yunkoo Cho & Young Jae Han & Jumi Hwang & Jiwon Yu & Sangbaek Kim & Chulung Lee & Sugil Lee & Kyung Pyo Yi, 2021. "Identifying Technology Opportunities for Electric Motors of Railway Vehicles with Patent Analysis," Sustainability, MDPI, vol. 13(5), pages 1-13, February.
    12. Cheng, An-Chin & Chen, Chia-Yon, 2008. "The Technology Forecasting Of New Materials: The Example Of Nanosized Ceramic Powders," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(4), pages 88-110, December.
    13. Shiu-Wan Hung & An-Pang Wang, 2010. "Examining the small world phenomenon in the patent citation network: a case study of the radio frequency identification (RFID) network," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 121-134, January.
    14. Chang, Shann-Bin, 2012. "Using patent analysis to establish technological position: Two different strategic approaches," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 3-15.
    15. 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.
    16. Jia Zheng & Zhi-yun Zhao & Xu Zhang & Dar-zen Chen & Mu-hsuan Huang, 2014. "International collaboration development in nanotechnology: a perspective of patent network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 683-702, January.
    17. Sunghae Jun & Sangsung Park & Dongsik Jang, 2015. "A Technology Valuation Model Using Quantitative Patent Analysis: A Case Study of Technology Transfer in Big Data Marketing," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(5), pages 963-974, September.
    18. Eunsuk Chun & Sungchan Jun & Chulung Lee, 2021. "Identification of Promising Smart Farm Technologies and Development of Technology Roadmap Using Patent Map Analysis," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    19. Yu-Jing Chiu & Tao-Ming Ying, 2012. "A Novel Method for Technology Forecasting and Developing R&D Strategy of Building Integrated Photovoltaic Technology Industry," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-24, July.
    20. Junic Kim & Jaewook Yoo, 2019. "Science and Technology Policy Research in the EU: From Framework Programme to HORIZON 2020," Social Sciences, MDPI, vol. 8(5), pages 1-10, May.
    21. Woo Jin Lee & Won Kyung Lee & So Young Sohn, 2016. "Patent Network Analysis and Quadratic Assignment Procedures to Identify the Convergence of Robot Technologies," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-16, October.
    22. Sang M. Lee & DonHee Lee, 2020. "“Untact”: a new customer service strategy in the digital age," Service Business, Springer;Pan-Pacific Business Association, vol. 14(1), pages 1-22, March.
    23. Gómez, Daniel & Figueira, José Rui & Eusébio, Augusto, 2013. "Modeling centrality measures in social network analysis using bi-criteria network flow optimization problems," European Journal of Operational Research, Elsevier, vol. 226(2), pages 354-365.
    24. Ernst, Holger, 2003. "Patent information for strategic technology management," World Patent Information, Elsevier, vol. 25(3), pages 233-242, September.
    25. Feindt, Sylvie & Jeffcoate, Judith & Chappell, Caroline, 2002. "Identifying Success Factors for Rapid Growth in SME E-commerce," Small Business Economics, Springer, vol. 19(1), pages 51-62, August.
    26. Choi, Jinho & Hwang, Yong-Sik, 2014. "Patent keyword network analysis for improving technology development efficiency," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 170-182.
    27. Jiwon Yu & Jong-Gyu Hwang & Jumi Hwang & Sung Chan Jun & Sumin Kang & Chulung Lee & Hyundong Kim, 2020. "Identification of Vacant and Emerging Technologies in Smart Mobility Through the GTM-Based Patent Map Development," Sustainability, MDPI, vol. 12(22), pages 1-22, November.
    28. Butts, Carter T., 2008. "Social Network Analysis with sna," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i06).
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    Cited by:

    1. Jiwon Yu & Young Jae Han & Hyewon Yang & Sugil Lee & Gildong Kim & Chulung Lee, 2022. "Promising Technology Analysis and Patent Roadmap Development in the Hydrogen Supply Chain," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    2. Koopo Kwon & Jaeryong So, 2023. "Future Smart Logistics Technology Based on Patent Analysis Using Temporal Network," Sustainability, MDPI, vol. 15(10), pages 1-17, May.
    3. Sungyong Choi, 2023. "Special Issue on Advances in Operations and Supply Chain Management with Sustainability Considerations," Sustainability, MDPI, vol. 15(6), pages 1-4, March.
    4. Yong-Jae Lee & Young Jae Han & Sang-Soo Kim & Chulung Lee, 2022. "Patent Data Analytics for Technology Forecasting of the Railway Main Transformer," Sustainability, MDPI, vol. 15(1), pages 1-25, December.
    5. Adedotun Joseph Adenigbo & Joash Mageto & Rose Luke, 2023. "Adopting Technological Innovations in the Air Cargo Logistics Industry in South Africa," Logistics, MDPI, vol. 7(4), pages 1-16, November.

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