Identification of Promising Vacant Technologies for the Development of Truck on Freight Train Transportation Systems
| Autor: | Jumi Hwang, Jiwon Yu, Sungchan Jun, Chulung Lee, Sangbaek Kim, Seong Ho Han |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Truck
Trademark Computer science Rail freight transport ComputingMilieux_LEGALASPECTSOFCOMPUTING 02 engineering and technology truck on flatcar or truck on freight train lcsh:Technology Field (computer science) lcsh:Chemistry 0502 economics and business 0202 electrical engineering electronic engineering information engineering General Materials Science Macro patent analysis Instrumentation network analysis lcsh:QH301-705.5 Fluid Flow and Transfer Processes business.industry lcsh:T Process Chemistry and Technology 05 social sciences General Engineering Manufacturing engineering lcsh:QC1-999 Computer Science Applications Patent map ComputingMilieux_GENERAL Identification (information) lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 time series analysis 020201 artificial intelligence & image processing business lcsh:Engineering (General). Civil engineering (General) patent map 050203 business & management Patent classification lcsh:Physics promising vacant technology |
| Zdroj: | Applied Sciences, Vol 11, Iss 499, p 499 (2021) Applied Sciences Volume 11 Issue 2 |
| ISSN: | 2076-3417 |
| Popis: | In this study, we identify promising, currently vacant technologies for a Truck on Flatcar or Truck on Freight Train (TFTFT) system by analyzing the relevant patent information. We then apply network analysis from macro- and microperspectives to establish technology development strategies. We first researched the patent database from the United States Patent and Trademark Office (USPTO) by extracting relevant keywords for the TFTFT system. We then preprocessed the patent data to develop a patent-International Patent Classification (IPC) matrix and a patent-keyword matrix. Next, we developed a generative topographic mapping (GTM)-based patent map using the patent-IPC matrix and detected any patent vacuums. Then, in order to confirm the promising patent vacuums, we technically examined criticality and trend analyses. Finally, we designed an IPC-based network and a keyword network with promising patent vacuums to derive a technology development strategy from a macro- and microperspective for the TFTFT system. As a result, we confirmed two promising patent vacuums. The patent vacuums found were defined as the technical field of rail vehicles suitable for TFTFT systems and the technical field of equipment and systems for freight transfer to rail vehicles. The proposed procedure and analysis method provide useful insights for developing a research and development (R& D) strategy and technology development strategy for a TFTFT system. |
| Databáze: | OpenAIRE |
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