Text mining of information resources to inform Forecasting Innovation Pathways

被引：46

作者：

Guo, Ying ^{[1
]}

Ma, Tingting ^{[1
]}

Porter, Alan L. ^{[2
]}

Huang, Lu ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China

[2] Georgia Inst Technol, Technol Policy & Assessment Ctr, Atlanta, GA 30332 USA

来源：

TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT | 2012年 / 24卷 / 08期

基金：

美国国家科学基金会;

关键词：

Forecasting Innovation Pathways; Newand Emerging Science and Technologies; Tech Mining; nanotechnology; dye-sensitised solar cells; technology intelligence; TECHNOLOGY; ENERGY; FRAMEWORK; SYSTEMS; SCIENCE;

D O I：

10.1080/09537325.2012.715491

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

Highly uncertain dynamics of New and Emerging Science and Technologies pose special challenges to traditional forecasting tools. This paper explores the systematisation of the 'Forecasting Innovation Pathways'analytical approach through the application of Tech Mining. Once a set of multi-database, emerging technology search results has been obtained, we devise a means to help extract intelligence on key technology components and functions, major stakeholders, and potential applications. We present results pertaining to the development of dye-sensitised solar cells.

引用

页码：843 / 861

页数：19

共 34 条

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