The Competitive Technical Intelligence Methodology For Emerging Technology

Strategic emerging industry has become one of the key issues for national sustainability and core competitiveness since the coming economic globalization. The “Innovation-driven Development Strategy” was announced officially in China’s 18 th National Congress, and the development of strategic emerging industry has been listed in the government’s schedule. At this stage, this essay constructs a Competitive Technical Intelligence(CTI) methodology for emerging technology to retrieve core technological components, discover hot topics, identify relationships among the components and topics, describe the evolutionary pathway of emerging technology, and explore the value-added information to support the decision making process for national R&D planning and strategic management.The CTI methodology for emerging technology includes a “CTI Retrieval Model,” a “CTI Analysis Model,” and a “CTI Visualization Model.” The empirical study focuses on China’s Dye Sensitized Solar Cell industry, the results of which indicate the feasibility and effectively of our methodology and also hold interests for governments, academia, and industries. The significances of this essay are given as below:(1) To build up a CTI Retrieval Model for emerging technologyThe CTI Retrieval Model includes a “Search Strategy Refining Approach for Science, Technology, & Innovation(ST&I) Data” and a “Term Clumping Approach”. This Model, based on quantitative approaches and aiding with expert knowledge, takes ST&I data and the features of specific emerging technology into consideration and provides stepwise process to collect accurate target data and clean, consolidate, and cluster terms and phrases for core technological component retrieval. The CTI Retrieval Model establishes the data foundation for CTI methodology for emerging technology.(2) To build up a CTI Analysis Model for emerging technologyThe CTI Analysis Model emphasizes both statistic and sematic approaches. In the statistic part, a “Data-driven K-Means-based Text Clustering Approach” is proposed, which has a high accuracy for ST&I data and a K local optimum function. In the semantic part, the combination of “Subject – Action – Object” analysis and the Contradiction Matrix of TRIZ theory is involved in the “Problem & Solution(P&S) Pattern-based Semantic TRIZ Approach,” which holds the ability to identify the underlying relationships between technological components. The CTI Analysis Model is the main part of the CTI methodology for emerging technology.(3) To build up a CTI Visualization Model for emerging technologyThe CTI Visualization Model concentrates on Technology Roadmapping(TRM) approaches, which includes a “TRM Composing Approach” and a “Criterion for TRM Selection and Evaluation.” We construct three TRM composing functions with diverse foci, 1) the Term/Topic-based TRM composing function aims to describe the technological components in detail, 2) the P&S pattern-based TRM composing function pays more attention to follow the relationships of P&S patterns to trace problem-solving trends, and 3) the semi-automatic TRM composing function introduces Fuzzy Set to transfer vague expert knowledge to defined numeric values and improves the performance for TRM automatic generation. The discussion on the criterion for TRM selection and evaluation provides benefit for TRM’s actual applications. The CTI Visualization Model is the core panel and the output of the CTI methodology for emerging technology.