Multivariate multiple regression modelling for technology analysis
- Authors
- Jun, Sunghae; Wood, Jacob; Park, Sangsung
- Issue Date
- 2018
- Publisher
- ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
- Keywords
- Multivariate multiple regression; technology analysis; three-dimensional printing; management of technology
- Citation
- TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT, v.30, no.3, pp.311 - 323
- Indexed
- SSCI
SCOPUS
- Journal Title
- TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT
- Volume
- 30
- Number
- 3
- Start Page
- 311
- End Page
- 323
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/80846
- DOI
- 10.1080/09537325.2017.1309015
- ISSN
- 0953-7325
- Abstract
- Technology analysis is important for technology management areas such as research and development strategy and new product development. So many studies on technology analysis have been used across a diverse array of fields. Most of these were based on patent analysis, which analyses patent documents using text mining and statistics. The studies on conventional patent analyses constructed models consisting of various independent variables (technologies) and one dependent variable. But in reality, we have to consider a model that includes several dependent variables at the same time, because most technologies influence each other. In this paper, we propose a methodology for patent analysis that reflects the various response technologies simultaneously. We perform multivariate multiple regression modelling in order to efficiently conduct our technology analysis. To show how our modelling can be applied to realistic context, we carry out a case study using the patent documents related to three-dimensional printing technology.
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Collections - Graduate School > Graduate School of management of technology > 1. Journal Articles
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