A hybrid method to trace technology evolution pathways: a case study of 3D printing

Abstract

Whether it be for countries to improve the ability to undertake independent innovation or for enterprises to enhance their international competitiveness, tracing historical progression and forecasting future trends of technology evolution is essential for formulating technology strategies and policies. In this paper, we apply co-classification analysis to reveal the technical evolution process of a certain technical field, using co-word analysis to extract implicit or unknown patterns and topics, and main path analysis to discover significant clues about technology hotspots and development prospects. We illustrate this hybrid approach with 3D printing, referring to various technologies and processes used to synthesize a three-dimensional object. Results show how our method offers technical insights and traces technology evolution pathways, and then help decision-makers guide technology development.

Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study

“…Related approaches include keyword-based analysis (Lee et al 2009;Zhou et al 2014), citation analysis (Choi & Park 2009), subject-action-object-based semantic analysis (Zhang et al 2014b), diffusion modeling (Cunningham & Kwakkel 2014), and the combination of certain above approaches (Li 2015;Guo et al 2016). Further, such approaches have already been applied to a number of industry sectors, in particular emerging sectors, such as electric vehicles (Huang et al 2014), dye-sensitized solar cells (Zhang et al 2014c), energy industry (Daim & Oliver 2008;Kajikawa et al 2008;Daim et al 2017), and 3D printing (Huang et al 2017b). In parallel, based on the citation linkages between scientific articles, main path analysis (Lucio-Arias & Leydesdorff 2008) and hybrid models with both citation and co-citation statistics (Small et al 2014) are exploited to identify emerging topics and trace technological evolution as well.…”

“…Phaal et al (2004), Daim and Oliver (2008), and Daim et al 20172 Emphasizing the involvement of quantitative approaches (in particular bibliometric analysis) in gaining insights, with limited use of expert knowledge: This is an emergent area that investigates technological evolution through bibliometrics. Choi and Park (2009), Zhou et al (2014), Cunningham and Kwakkel (2014), and Huang et al (2017b) 3. Methodology and Data…”

Exploring the characteristics of 3D printing global industry chain and value chain innovation network

“…International research on the 3D printing industry focuses on evolutionary trends and business models. Huang (2017) traced the historical progression and forecast future trends of 3D printing technology evolution. Wright (2000) believed that the development of the 3D printing industry is unstoppable, and its growth rate is amazing.…”

Technology of Application of Software Tools for Energy Technology Forecasting

“…The largest contribution to Text Mining is made by American scientists and is mainly focused on the development of these methods in relation to social media [18,19]. And Tech Mining is more developed by Chinese scientists for the tasks of scientific and technological forecasting [20][21][22].…”