Forecasting technology trends using text mining of the gaps between science and technology: The case of perovskite solar cell technology

How to detect and identify the future trends of emerging technologies as early as possible is crucial for government R&D strategic planning and enterprises' practices. To avoid the weakness of using only scientific papers or patents to study the development trends of emerging technologies, this paper proposes a framework that uses scientific papers and patents as data resources and integrates the text mining and expert judgment approaches to identify technology evolution paths and forecast technology development trends within the short term. The perovskite solar cell technology is selected as a case study. In this case, the text mining and expert judgment methods are applied to analyze the technology evolution path, and gaps analysis between science and technology is used to forecast the technology development trend. This paper will contribute to the technology forecasting and foresight methodology, and will be of interest to solar photovoltaic technology R&D experts.

[1]  Jean Pierre Courtial,et al.  Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry , 1991, Scientometrics.

[2]  Sungjoo Lee,et al.  Applying technology road‐maps in project selection and planning , 2008 .

[3]  Ronald N. Kostoff,et al.  Literature-related discovery (LRD): Water purification , 2008 .

[4]  Hsu-Hao Tsai,et al.  Global data mining: An empirical study of current trends, future forecasts and technology diffusions , 2012, Expert Syst. Appl..

[5]  Alan L. Porter,et al.  Identification of technology development trends based on subject–action–object analysis: The case of dye-sensitized solar cells , 2015 .

[6]  Tugrul U. Daim,et al.  Product and process innovation in manufacturing firms: a 30-year bibliometric analysis , 2017, Scientometrics.

[7]  Sungjoo Lee,et al.  Technological Forecasting & Social Change Business planning based on technological capabilities : Patent analysis for technology-driven roadmapping ☆ , 2009 .

[8]  Ichiro Sakata,et al.  Extracting the commercialization gap between science and technology — Case study of a solar cell , 2010 .

[9]  Tugrul U. Daim,et al.  Research Forecasting for Health Information Technology (HIT), using technology intelligence , 2012 .

[10]  Xin Li,et al.  Integrating bibliometrics and roadmapping methods: A case of dye-sensitized solar cell technology-based industry in China , 2015 .

[11]  Ozcan Saritas,et al.  A methodology for technology trend monitoring: the case of semantic technologies , 2016, Scientometrics.

[12]  Jing Xu,et al.  Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis: a case study in LTE technology , 2014, Scientometrics.

[13]  Yongtae Park,et al.  Monitoring the organic structure of technology based on the patent development paths , 2009 .

[14]  Stefano Breschi,et al.  Tracing the links between science and technology: An exploratory analysis of scientists' and inventors' networks , 2010 .

[15]  Y. Kajikawa,et al.  Citation network analysis of organic LEDs , 2009 .

[16]  Pei-Chun Lee,et al.  Quantitative mapping of patented technology — The case of electrical conducting polymer nanocomposite , 2009, Technological Forecasting and Social Change.

[17]  Mercedes Úbeda-García,et al.  The intellectual structure of research in hospitality management: A literature review using bibliometric methods of the journal International Journal of Hospitality Management , 2016 .

[18]  Ronald N. Kostoff,et al.  Science and technology roadmaps , 2001, IEEE Trans. Engineering Management.

[19]  Byungun Yoon,et al.  A systematic approach for identifying technology opportunities: Keyword-based morphology analysis , 2005 .

[20]  Alan L. Porter,et al.  Four dimensional Science and Technology planning: A new approach based on bibliometrics and technology roadmapping , 2014 .

[21]  Alan L. Porter,et al.  Technology opportunities analysis , 1995 .

[22]  Francis Narin,et al.  Is technology becoming science? , 1985, Scientometrics.

[23]  Alan L. Porter,et al.  Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research , 2016 .

[24]  Xiang Liu,et al.  Collective dynamics in knowledge networks: Emerging trends analysis , 2013, J. Informetrics.

[25]  Yoshiyuki Takeda,et al.  Structure of research on biomass and bio-fuels: A citation-based approach , 2008 .

[26]  Dongwoo Kang,et al.  An SAO-based text mining approach to building a technology tree for technology planning , 2012, Expert Syst. Appl..

[27]  Kwangsoo Kim,et al.  Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks , 2011, Scientometrics.

[28]  Yoshiyuki Takeda,et al.  Detecting emerging research fronts based on topological measures in citation networks of scientific publications , 2008 .

[29]  Jeremy Rifkin,et al.  The third industrial revolution : how lateral power is transforming energy, the economy, and the world , 2011 .

[30]  Robert Phaal,et al.  Technology roadmapping—A planning framework for evolution and revolution , 2004 .

[31]  Ronald N. Kostoff,et al.  The use and misuse of citation analysis in research evaluation , 1998, Scientometrics.

[32]  S. N. Singh,et al.  Mapping the intellectual structure of scientometrics: a co-word analysis of the journal Scientometrics (2005–2010) , 2014, Scientometrics.

[33]  Jia Hao,et al.  Knowledge map-based method for domain knowledge browsing , 2014, Decis. Support Syst..

[34]  Alan L. Porter,et al.  Innovation forecasting , 1997, Innovation in Technology Management. The Key to Global Leadership. PICMET '97.

[35]  Mu-Hsuan Huang,et al.  Identifying and visualizing technology evolution: A case study of smart grid technology , 2012 .

[36]  Robert Phaal,et al.  A framework for mapping industrial emergence , 2011 .

[37]  Fefie Dotsika,et al.  Identifying potentially disruptive trends by means of keyword network analysis , 2017 .

[38]  Farshad Madani,et al.  The evolution of patent mining: Applying bibliometrics analysis and keyword network analysis , 2016 .

[39]  Heeyong Noh,et al.  Identifying emerging core technologies for the future , 2016 .

[40]  Alan L. Porter,et al.  A hybrid visualisation model for technology roadmapping: bibliometrics, qualitative methodology and empirical study , 2013, Technol. Anal. Strateg. Manag..

[41]  R. Tijssen.  Global and domestic utilization of industrial relevant science: patent citation analysis of science-technology interactions and knowledge flows , 2001 .

[42]  Guangquan Zhang,et al.  Topic-based technological forecasting based on patent data: A case study of Australian patents from 2000 to 2014 , 2017 .

[43]  Chao-Chan Wu,et al.  Examining the trends of technological development in hydrogen energy using patent co-word map analysis , 2014 .

[44]  Michael I. Jordan,et al.  Hierarchical Dirichlet Processes , 2006 .

[45]  David L. Deeds,et al.  An Analysis of the Critical Role of Public Science in Innovation: The Case of Biotechnology , 2000 .

[46]  Choi Jae-woo,et al.  Themes and Trends in Korean Educational Technology Research: A Social Network Analysis of Keywords★ , 2014 .

[47]  Chaomei Chen,et al.  Dynamic topic detection and tracking: A comparison of HDP, C‐word, and cocitation methods , 2014, J. Assoc. Inf. Sci. Technol..

[48]  Kwangsoo Kim,et al.  TrendPerceptor: A property-function based technology intelligence system for identifying technology trends from patents , 2012, Expert Syst. Appl..

[49]  Alan L. Porter,et al.  Technology roadmapping for competitive technical intelligence , 2016 .

[50]  Rcgm Roel Loonen,et al.  Science foresight using life-cycle analysis, text mining and clustering: A case study on natural ventilation , 2017, Technological Forecasting and Social Change.

[51]  Jinho Choi,et al.  Patent keyword network analysis for improving technology development efficiency , 2014 .

[52]  André Leme Fleury,et al.  An overview of the literature on technology roadmapping (TRM): Contributions and trends , 2013 .

[53]  Türkay Dereli,et al.  Patent analysis of wind energy technology using the patent alert system , 2012 .

[54]  Dawid Weiss,et al.  A concept-driven algorithm for clustering search results , 2005, IEEE Intelligent Systems.

[55]  Chao-Chan Wu,et al.  Using patent analyses to monitor the technological trends in an emerging field of technology: a case of carbon nanotube field emission display , 2009, Scientometrics.

[56]  Yoshiyuki Takeda,et al.  Tracking emerging technologies in energy research : toward a roadmap for sustainable energy , 2008 .

[57]  Efstathios Tapinos,et al.  Scenario-driven roadmapping for technology foresight , 2017 .

[58]  Yuen-Hsien Tseng,et al.  Text mining techniques for patent analysis , 2007, Inf. Process. Manag..

[59]  Türkay Dereli,et al.  Classifying technology patents to identify trends: Applying a fuzzy-based clustering approach in the Turkish textile industry , 2009 .

[60]  Nathalie Sick,et al.  Identifying trends in battery technologies with regard to electric mobility: evidence from patenting activities along and across the battery value chain , 2015 .

[61]  Shih-Chieh Fang,et al.  Exploring technological opportunities by mining the gaps between science and technology: Microalgal biofuels , 2015 .

[62]  Gaizka Garechana,et al.  TeknoRoadmap, an approach for depicting emerging technologies , 2017 .

[63]  Sungjoo Lee,et al.  Keyword selection and processing strategy for applying text mining to patent analysis , 2015, Expert Syst. Appl..

[64]  Ola Olsson,et al.  Technological Opportunity and Growth , 2005 .

[65]  Tugrul U. Daim,et al.  Forecasting emerging technologies: Use of bibliometrics and patent analysis , 2006 .