Прогнозирование технологических трендов с учетом временных интервалов между научными публикациями и патентами
PDF
PDF (English)

Ключевые слова

технологическое прогнозирование
текст-майнинг
тенденции технологического развития
траектория технологического развития
электронная торговля
программное обеспечение как услуга
SaaS
патентное цитирование

Как цитировать

ДаймТ., БухариЭ., БакриД., ВанХуисД., ЯлсинХ., & ВангС. (2021). Прогнозирование технологических трендов с учетом временных интервалов между научными публикациями и патентами. Форсайт, 15(2), 12-24. https://doi.org/10.17323/2500-2597.2021.2.12.24

Аннотация

Выявление технологических трендов — ключевой фактор конкурентоспособности, позволяющий воспользоваться потенциалом новых разработок еще до их появления. Освоение инструментов прогнозирования позволяет быть на несколько шагов впереди при создании новых продуктов и услуг. В статье представлен метод, комбинирующий интеллектуальный анализ текста (текст-майнинг) с экспертной оценкой для изучения краткосрочных тенденций технологического развития. В качестве примера для апробации выбрана бизнес-модель «программное обеспечение как услуга» (software-as-a-service, SaaS). Долгосрочные тренды выявляются путем анализа временных интервалов между научными исследованиями и прикладными разработками. Новый подход вносит вклад в развитие методологии технологического прогнозирования. Представлены пять основных направлений эволюции рассматриваемой области: виртуальные сети, гибридное облако, методы моделирования, мобильные и веб-приложения,  свидетельствующие о переходе информационных систем в онлайн-формат. Наряду с бессрочным лицензированием получает распространение схема пользования программным обеспечением по подписке. Ускоренная разработка продуктов на основе мобильных решений преобразует подходы к хранению информации, прежде всего в базах данных.

https://doi.org/10.17323/2500-2597.2021.2.12.24
PDF
PDF (English)

Литература

Angelou K., Maragakis M., Argyrakis P. (2019) A structural analysis of the patent citation network by the k-shell decomposition method. Physica A: Statistical Mechanics and Its Applications, 521, 476-483. DOI: https://doi.org/10.1016/j.physa.2019.01.063

Bengisu M., Nekhili R. (2006) Forecasting emerging technologies with the aid of science and technology databases. Technological Forecasting and Social Change, 73(7), 835-844. DOI: https://doi.org/10.1016/j.techfore.2005.09.001

Bildosola I., Rio-Belver R.M., Garechana G., Cilleruelo E. (2017) TeknoRoadmap: An approach for depicting emerging technologies. Technological Forecasting and Social Change, 117, 25-37. DOI: https://doi.org/10.1016/j.techfore.2017.01.015

Boyack K.W., van Eck N.J., Colavizza G., Waltman L. (2018) Characterizing in-text citations in scientific articles: A large-scale analysis. Journal of Informetrics, 12(1), 59-73. DOI: https://doi.org/10.1016/j.joi.2017.11.005

Chen C. (1998) Bridging the gap: The use of pathfinder networks in visual navigation. Journal of Visual Languages & Computing, 9(3), 267-286. DOI: https://doi.org/10.1006/jvlc.1998.0083

Chen C.M., Ibekwe?SanJuan F., Hou J. H. (2010) The Structure and Dynamics of Cocitation Clusters: A Multiple-Perspective Cocitation Analysis. Journal of the American Society for Information Science and Technology, 61(7), 1386-1409. DOI: https://doi.org/10.1002/asi.21309

Chen H., Zhang G., Zhu D., Lu J. (2017) Topic-based technological forecasting based on patent data: A case study of Australian patents from 2000 to 2014. Technological Forecasting and Social Change, 119(7), 39-52. DOI: https://doi.org/10.1016/j.techfore.2017.03.009

Chen W., Shen B.J., Qi Z.W. (2011) Research and implementation of business logic customization framework for SaaS applications. Jisuanji Yingyong Yanjiu, 28(1), 155-158.

Choi S., Park H., Kang D., Lee J.Y., Kim K. (2012) An SAO-based text mining approach to building a technology tree for technology planning. Expert Systems with Applications, 39(13), 11443-11455. DOI: https://doi.org/10.1016/j.eswa.2012.04.014

Christensen C.M. (1997) The innovator's dilemma: When new technologies cause great firms to fail, Boston, MA: Harvard Business School Press.

Coates V., Farooque M., Klavans R., Lapid K., Linstone H.A., Pistorius C., Porter A.L. (2001) On the Future of Technological Forecasting. Technological Forecasting and Social Change, 67(1), 1-17. DOI: https://doi.org/10.1016/S0040-1625(00)00122-0

Cusumano M.A. (2008) The changing software business: Moving from products to services. Computer, 41(1), 20-27. https://doi.ieeecomputersociety.org/. DOI: https://doi.org/10.1109/MC.2008.29

Daim T., Bukhari E., Bakry D., VanHuis J., Yalcin H., Wang X. (2021) Forecasting Technology Trends through the Gap Between Science and Technology: The Case of Software as an E-Commerce Service. Foresight and STI Governance, 15(2), 12-24.

Elfatatry A., Layzell P. (2002) Software as a service: A negotiation perspective. In: Proceedings of the 26th Annual International Conference on Computer Software and Applications, 26-29 August 2002, Oxford, UK (ed. D.C. Martin), Piscataway, NJ: IEEE, pp. 501-506. https://ieeexplore.ieee.org/document/1045054, accessed 06.04.2021.

Garcia-Lillo F., Claver-Cortes E., Marco-Lajara B., Ubeda-Garcia M. (2019) Identifying the ‘knowledge base' or ‘intellectual structure' of research on international business, 2000-2015: A citation/co-citation analysis of JIBS. International Business Review, 28(4), 713-726. DOI: https://doi.org/10.1016/j.ibusrev.2019.02.001

Ghazinoory S., Ameri F., Farnoodi S. (2013) An application of the text mining approach to select technology centers of excellence. Technological Forecasting and Social Change, 80(5), 918-931. DOI: https://doi.org/10.1016/j.techfore.2012.09.001

Graham R.L., Hell P. (1985) On the history of the minimum spanning tree problem. Annals of the History of Computing, 7(1), 43-57. DOI: https://doi.org/10.1109/MAHC.1985.10011

Hasner C., de Lima A.A., Winter E. (2019) Technology advances in sugarcane propagation: A patent citation study. World Patent Information, 56, 9-16. DOI: https://doi.org/10.1016/j.wpi.2018.09.001

Huang L., Zhang Y., Guo Y., Zhu D.H., Porter A.L. (2014) Four-dimensional Science and Technology Planning: A New Approach Based on Bibliometrics and Technology Roadmapping. Technological Forecasting and Social Change, 81(1), 39-48. DOI: https://doi.org/10.1016/j.techfore.2012.09.010

Huang Y., Porter A.L., Zhang Y., Lian X., Guo Y. (2018) An assessment of technology forecasting: Revisiting earlier analyses on dye-sensitized solar cells (DSSCs). Technological Forecasting and Social Change, 146, 831-843. DOI: https://doi.org/10.1016/j.techfore.2018.10.031

Kim G., Bae J. (2017) A novel approach to forecast promising technology through patent analysis. Technological Forecasting and Social Change, 117, 228-237. DOI: https://doi.org/10.1016/j.techfore.2016.11.023

Kim H.J., Jeong Y.K., Song M. (2016) Content- and proximity-based author co-citation analysis using citation sentences. Journal of Informetrics, 10(4), 954-966. DOI: https://doi.org/10.1016/j.joi.2016.07.007

Kose T., Sakata I. (2018) Identifying technology convergence in the field of robotics research. Technological Forecasting and Social Change. DOI: https://doi.org/10.1016/j.techfore.2018.09.005

Laplante P.A., Zhang J., Voas J. (2008) What's in a Name? Distinguishing between SaaS and SOA. IT Professional, 10(3), 46-50. https://doi.ieeecomputersociety.org/. DOI: https://doi.org/10.1109/MITP.2008.60

Lee H., Lee S., Yoon B. (2011) Technology clustering based on evolutionary patterns: The case of information and communications technologies. Technological Forecasting and Social Change, 78(6), 953-967. DOI: https://doi.org/10.1016/j.techfore.2011.02.002

Li X., Xie Q., Daim T., Huang L. (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. DOI: https://doi.org/10.1016/j.techfore.2019.01.012

Ma D. (2007) The business model of Software-as-a-Service. In: Proceedings of the IEEE International Conference on Services Computing (SCC 2007), Salt Lake City, UT, 9-13 July 2007, Hoboken, NJ: IEEE, pp. 701-702. http://doi.ieeecomputersociety.org/. DOI: https://doi.org/10.1109/SCC.2007.118

Madani F., Weber C. (2016) The evolution of patent mining: Applying bibliometrics analysis and keyword network analysis. World Patent Information, 46, 32-48. DOI: https://doi.org/10.1016/j.wpi.2016.05.008

Olsson O. (2005) Technological opportunity and growth. Journal of Economic Growth, 10(1), 31-53. DOI: https://doi.org/10.1007/s10887-005-1112-4

Park C., Yong T. (2017) Prospect of Korean nuclear policy change through text mining. Energy Procedia, 128, 72-78. DOI: https://doi.org/10.1016/j.egypro.2017.09.017

Porter A.-L., Detampel M.J. (1995) Technology opportunities analysis. Technological Forecasting and Social Change, 49(3), 237-255. DOI: https://doi.org/10.1016/0040-1625(95)00022-3

Porter A.L., Cunningham S.W. (2004) Tech Mining: Exploiting New Technologies for Competitive Advantage, Hoboken, NJ: Wiley.

Rezaeian M., Montazeri H., Loonen R.C.G.M. (2017) Science foresight using life-cycle analysis, text mining and clustering: A case study on natural ventilation. Technological Forecasting and Social Change, 118, 270-280. DOI: https://doi.org/10.1016/j.techfore.2017.02.027

Rongying Z., Limin X. (2010) The Knowledge Map of the Evolution and Research Frontiers of the Bibliometrics. Journal of Library Science in China, 5, 60-68. https://en.cnki.com.cn/Article_en/CJFDTotal-ZGTS201005007.htm, accessed 06.04.2021.

SIIA (2001) Software as a Serice: Strategic Backgrounder. Washington, D.C.: Software & Information Industry Association.

Shibata N., Kajikawa Y., Sakata I. (2010) Extracting the commercialization gap between science and technology - Case study of a solar cell. Technological Forecasting and Social Change, 77(7), 1147-1155. DOI: https://doi.org/10.1016/j.techfore.2010.03.008

Teufel S., Siddharthan A., Tidhar D. (2009) An annotation scheme for citation function. In: SigDIAL '06: Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue (eds. J. Alexandersson, A. Knott), Stroudsburg, PA: Association for Computational Linguistics, pp. 80-87. http://dl.acm.org/citation.cfm?id=1654595.1654612, accessed 06.04.2021.

Wang M.-Y., Fang S.-C., Chang Y.-H. (2015) Exploring technological opportunities by mining the gaps between science and technology: Microalgal biofuels. Technological Forecasting and Social Change, 92, 182-195. DOI: https://doi.org/10.1016/j.techfore.2014.07.008

Yoon B., Park I., Coh B. (2014) Exploring technological opportunities by linking technology and products: Application of morphology analysis and text mining. Technological Forecasting and Social Change, 86, 287-303. DOI: https://doi.org/10.1016/j.techfore.2013.10.013

Yoon B., Park Y. (2005) A systematic approach for identifying technology opportunities: keyword-based morphology analysis. Technological Forecasting and Social Change, 72 (2), 145-160. DOI: https://doi.org/10.1016/j.techfore.2004.08.011

Лицензия Creative Commons

Это произведение доступно по лицензии Creative Commons «Attribution» («Атрибуция») 4.0 Всемирная.

Скачивания

Данные скачивания пока не доступны.