Logistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap

Koopo Kwon, Sungchan Jun, Yong-Jae Lee, Sanghei Choi and Chulung Lee
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Koopo Kwon: Department of Industrial and Management Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, 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

Sustainability, 2022, vol. 14, issue 9, 1-30

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.

Keywords: retail logistics; technology roadmap; patent analysis; time series; clustering; latent dirichlet allocation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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