Hide
Раскрыть

ISSN 2587-814X (print),
ISSN 2587-8158 (online)

Russian version: ISSN 1998-0663 (print),
ISSN 2587-8166 (online)

Konstantin Nagaev 1, Elena Kurbatova  1
  • 1 National Research University Higher School of Economics, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation

Technology roadmapping. Method for gathering and consolidation expert opinions

2014. No. 1 (27). P. 52–60 [issue contents]

Konstantin Nagaev - Senior Researcher, Center for Information Analysis Applications, Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: knagaev@hse.ru

Elena Kurbatova - Junior Researcher, Center for Information Analysis Applications, Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: ekurbatova@hse.ru

     The paper discusses the problems related to data collection, processing and expert opinions evaluating in terms of a specified knowledge domain. Methods for expert data processing based on computer systems are presented. The results are used in foresight projects, long-term forecasting and in technology road mapping. The main advantage of proposed methods is the consideration of expert competence degrees. Additionally, expert datasets are adapted to aspects of the knowledge domain in accordance with a customer’s interest area.
     The proposed method provides obtaining subsets of expert data for a required version of expert polls, or expert data values effective on a specified date. An additional driver of expert data model flexibility is metadata for expert competence identification in different aspects: science, technology, business and governance. The metadata is designed to run evaluation of various analytic indicators for foresight investigations, for example, for weak signals and wild cards. The method gives accent to the opinion of a high-competence expert which may diverge significantly from the major opinion. This very property of the method is extremely important for weak signal retrieval. Wild cards are founded with an estimation of realization probability of a roadmap element with high influence rate in an interest area.
     Another area of the method applications is the development of different forecasts of knowledge domain’s evolution taking into account the  importance of properties in special contexts (economic, political, ecological and technological). Joint analysis of these data and experts’ competence data allows generating improved specific questionnaires for distinct expert groups automatically.
     The methods described here have been implemented in the software system “Interactive roadmap with feedback link” and tested in two pilot projects: “Catalytic cracking” and “Biotechnologies medical”.

Citation: Nagaev Konstantin Vladimirovich, Kurbatova Elena Mikhaylovna (2014) Avtomatizatsiya proektirovaniya tekhnologicheskikh dorozhnykh kart. Sbor informatsii i konsolidatsiya ekspertnykh mneniy [Technology roadmapping. Method for gathering and consolidation expert opinions] Biznes-informatika, 1 (27), pp. 52-60 (in Russian)
BiBTeX
RIS
 
 
Rambler's Top100 rss