Logistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap

Koopo Kwon, Sungchan Jun, Yong Jae Lee, Sanghei Choi, Chulung Lee

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


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.

Original languageEnglish
Article number5430
JournalSustainability (Switzerland)
Issue number9
Publication statusPublished - 2022 May 1

Bibliographical note

Funding Information:
Funding: This work was supported by Jungseok Logistics Foundation. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2020R1F1A1076812). This research was supported by Brain Korea 21 FOUR.

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.


  • clustering
  • latent dirichlet allocation
  • patent analysis
  • retail logistics
  • technology roadmap
  • time series

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Building and Construction
  • Environmental Science (miscellaneous)
  • Energy Engineering and Power Technology
  • Hardware and Architecture
  • Computer Networks and Communications
  • Management, Monitoring, Policy and Law


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