Fulltekst

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstrakt

As innovative technology is being developed at an accelerated rate, the identification of technology opportunities is especially critical for both companies and governments. Among various approaches to search for opportunities, one of the most frequently used is to discover technology opportunity from patent data. In line with it, this paper aims to propose a hybrid approach based on morphological analysis (MA) and unified structured inventive thinking (USIT) for technology opportunity discovery (TOD) through patent analysis using text mining and Word2Vec clustering analysis to explore the intrinsic links of innovation elements. A basic morphology matrix is constructed according to patent information and then is extended using the innovation algorithms that are reorganized from USIT. Technology opportunities are analyzed at two layers to generate new technical ideas. To illustrate the research process and validate its utility, this paper selects the technology of coalbed methane (CBM) extraction as a use case. This hybrid approach contributes by suggesting a semi-autonomous and systematic procedure to perform MA for TOD. By integrating the innovation algorithms, this approach improves the procedure of value extension in MA.

Detaljer

Tittel
Discovering Technology Opportunity by Keyword-Based Patent Analysis: A Hybrid Approach of Morphology Analysis and USIT
Forfatter
Lijie Feng 1 ; Niu, Yuxiang 2   VIAFID ORCID-logo  ; Liu, Zhenfeng 3   VIAFID ORCID-logo  ; Wang, Jinfeng 3 ; Zhang, Ke 2   VIAFID ORCID-logo 

 School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China; ljfeng@shmtu.edu.cn (L.F.); yuxiangniucyn@gmail.com (Y.N.); kezhang2019zzu@gmail.com (K.Z.); School of Economic & Management, Shanghai Maritime University, Shanghai 201306, China; wangjinfeng@shmtu.edu.cn 
 School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China; ljfeng@shmtu.edu.cn (L.F.); yuxiangniucyn@gmail.com (Y.N.); kezhang2019zzu@gmail.com (K.Z.) 
 School of Economic & Management, Shanghai Maritime University, Shanghai 201306, China; wangjinfeng@shmtu.edu.cn 
Første side
136
Utgivelsesår
2020
Utgivelsesdato
2020
Utgiver
MDPI AG
e-ISSN
20711050
Kildetype
Vitenskapelig journal
Utgivelsesspråk
English
ProQuest-dokument-ID
2441209896
Opphavsrett
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.