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TeknoRoadmap, an approach for depicting emerging technologies

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  • Bildosola, Iñaki
  • Río-Bélver, Rosa María
  • Garechana, Gaizka
  • Cilleruelo, Ernesto

Abstract

One of the biggest challenges for current enterprises is the adoption of emerging technologies as soon as these provide competitive improvements. In this sense, several types of technology forecasting and surveillance activities are present in their daily activity. From the academic point of view, technology forecasting activities involve the combination of methods of a diverse nature, with which the technology is depicted and its potential future paths are discussed. Within this conceptual framework, the present work aims at describing a novel approach, known as TeknoRoadmap, which combines bibliometrics and technology forecasting methods to depict emerging technologies. Thus, this contribution aims to widen the scope compared to those provided by previous works within the field, and to that end, the depiction of emerging technologies is provided based on two main elements, namely: the profile of the research activity; and a complete technology roadmap. The approach combines consolidated methods such as text mining and roadmapping, and novel ones such as web content mining, with special attention given to forecasting activities. The work provides a detailed description of the steps on which the approach is structured, as well as the results of one specific application to a cutting edge emerging technology: cloud computing.

Suggested Citation

  • Bildosola, Iñaki & Río-Bélver, Rosa María & Garechana, Gaizka & Cilleruelo, Ernesto, 2017. "TeknoRoadmap, an approach for depicting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 25-37.
    • Handle: RePEc:eee:tefoso:v:117:y:2017:i:c:p:25-37
    DOI: 10.1016/j.techfore.2017.01.015
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    1. van Eck, N.J.P. & Waltman, L., 2009. "How to Normalize Co-Occurrence Data? An Analysis of Some Well-Known Similarity Measures," ERIM Report Series Research in Management ERS-2009-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Gaizka Garechana & Rosa Rio-Belver & Ernesto Cilleruelo & Jaso Larruscain Sarasola, 2015. "Clusterization and mapping of waste recycling science. Evolution of research from 2002 to 2012," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(7), pages 1431-1446, July.
    3. Huang, Lu & Zhang, Yi & Guo, Ying & Zhu, Donghua & Porter, Alan L., 2014. "Four dimensional Science and Technology planning: A new approach based on bibliometrics and technology roadmapping," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 39-48.
    4. D. Thorleuchter & D. Van Den Poel, 2013. "Weak Signal Identification with Semantic Web Mining," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/860, Ghent University, Faculty of Economics and Business Administration.
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    2. Leonid Gokhberg & Ilya Kuzminov & Pavel Bakhtin & Elena Tochilina & Alexander Chulok & Anton Timofeev & Alina Lavrinenko, 2017. "Big-Data-Augmented Approach to Emerging Technologies Identification: Case of Agriculture and Food Sector," HSE Working papers WP BRP 76/STI/2017, National Research University Higher School of Economics.
    3. Sebastián Escobar & Margareth Santander & Pilar Useche & Carlos Contreras & Jader Rodríguez, 2020. "Aligning Strategic Objectives with Research and Development Activities in a Soft Commodity Sector: A Technological Plan for Colombian Cocoa Producers," Agriculture, MDPI, vol. 10(5), pages 1-32, April.
    4. Zamani, Mehdi & Yalcin, Haydar & Naeini, Ali Bonyadi & Zeba, Gordana & Daim, Tugrul U, 2022. "Developing metrics for emerging technologies: identification and assessment," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    5. Böhmecke-Schwafert, Moritz & García Moreno, Eduardo, 2023. "Exploring blockchain-based innovations for economic and sustainable development in the global south: A mixed-method approach based on web mining and topic modeling," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    6. Yuskevich, Ilya & Smirnova, Ksenia & Vingerhoeds, Rob & Golkar, Alessandro, 2021. "Model-based approaches for technology planning and roadmapping: Technology forecasting and game-theoretic modeling," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    7. Iñaki Bildosola & Gaizka Garechana & Enara Zarrabeitia & Ernesto Cilleruelo, 2020. "Characterization of strategic emerging technologies: the case of big data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 45-60, March.
    8. Li, Xin & Xie, Qianqian & Daim, Tugrul & Huang, Lucheng, 2019. "Forecasting technology trends using text mining of the gaps between science and technology: The case of perovskite solar cell technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 432-449.
    9. Seyed Mahmoud Zanjirchi & Mina Rezaeian Abrishami & Negar Jalilian, 2019. "Four decades of fuzzy sets theory in operations management: application of life-cycle, bibliometrics and content analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1289-1309, June.
    10. Kristóf Gyódi & Łukasz Nawaro & Michał Paliński & Maciej Wilamowski, 2023. "Informing policy with text mining: technological change and social challenges," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 933-954, February.
    11. Li, Xin & Wu, Yundi & Cheng, Haolun & Xie, Qianqian & Daim, Tugrul, 2023. "Identifying technology opportunity using SAO semantic mining and outlier detection method: A case of triboelectric nanogenerator technology," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    12. Zhang, Hao & Daim, Tugrul & Zhang, Yunqiu (Peggy), 2021. "Integrating patent analysis into technology roadmapping: A latent dirichlet allocation based technology assessment and roadmapping in the field of Blockchain," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    13. Samaneh Mohebalizadeh & Soroush Ghazinoori, 2021. "Developing a Technology Roadmap for Regenerative Medicine: A Participatory Action Research," Systemic Practice and Action Research, Springer, vol. 34(4), pages 377-397, August.

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