Integrating science and technology metrics into a competitive technology intelligence methodology
DOI:
https://doi.org/10.37380/jisib.v1i1.696Keywords:
Competitive intelligence, competitive technology intelligence, patentometrics, science and technology metrics, scientometricsAbstract
For years, the appropriate interpretation and application of metrics have enabled scientists to assess science and technology dynamics. Consequently, diverse disciplines have emerged, such as bibliometrics, scientometrics and patentometrics, offering important theoretical and methodological contributions. However, the current accelerated technological advances require researchers to implement a superior approach to detect continuous changes in the external environment identifying opportunities and vulnerabilities to strengthen the decision-making process regarding R&D and innovation. In this context, competitive technology intelligence (CTI) offers a strategic approach based on a continuous cycle where information is transformed into an actionable result. This research provides a broader scope to science and technology metrics, incorporating them into a CTI global methodology of eight steps. Metrics add value throughout the entire CTI process, from project planning to decision-making stages, having the most significant role in the information analysis stage, mainly to process information from sources such as scientific documents, patents, and social networks. Particularly, this approach considers recent studies in CTI in which quantitative tools such as patentometrics and scientometrics were successfully used. This proposal can be applied to predict upcoming technologies, movements of competitors, disrupting activities, market changes, and future trends. Accordingly, this research adds value to the assessment of science and technology dynamics, aiming to improve the decision-making process of R&D and innovation.
References
Amidon Rogers, Debra M. (1996). The challenge of fifth generation R&D. Research Technology Management, 39(4), 33-41. doi: 10.1080/08956308.1996.11671075.
Bollen, J., Van de Sompel, H., Hagberg, A., Chute, R., 2009. A Principal Component Analysis of 39 Scientific Impact Measures. PLoS ONE, 4(6): e6022. doi:10.1371/journal.pone.0006022
Cronin, B., Sugimoto, C.R. (2014). Beyond bibliometrics: Harnessing multidimensional indicators of scholarly impact. Cambridge, United States: The MIT Press.
Dou, H., Juillet, A., Clerc, P. (2019). Strategic Intelligence for the Future 1: A New Strategic and Operational Approach. Hoboken, United States: Wiley.
Du Toit, A.B. (2015). Competitive intelligence research: an investigation of trends in the literature. Journal of Intelligence Studies in Business. 5(2). doi: 10.37380/jisib.v5i2.127
European Union (2017). Next-generation metrics: Responsible metrics and evaluation for open science. Luxembourg: Publications Office of the European Union. doi: 10.2777/337729.
Fitzpatrick, W., Burke, D. (2003). Competitive Intelligence, corporate security and the virtual organization. Advances in Competitiveness Research, 11(1), 20-45.
Garcia-Garcia, L. A., Rodriguez-Salvador, M. (2018a). Uncovering 3D bioprinting research trends: A keyword network mapping analysis. International Journal of Bioprinting, 4(2), 147-154. doi: 10.18063/IJB.v4i2.147
Garcia-Garcia, L. A., Rodriguez-Salvador, M. (2018b). Additive manufacturing knowledge incursion on orthopedic devices: The case of hand orthoses. Proceedings of the 3rd International Conference on Progress in Additive Manufacturing (Pro-AM 2018), 571-
doi: 10.25341/D4388H
Hernandez-Quintanar, L., Rodriguez-Salvador, M. (2019). Discovering New 3D Bioprinting Applications: Analyzing the Case of Optical Tissue Phantoms. International Journal of Bioprinting, 5(1), 178-189. doi: 10.18063/ijb.v5i1.178.
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: 10.1016/j.techfore.2018.10.031.
Luu, T. T. (2015). From cultural intelligence to supply chain performance. The International Journal of Logistics Management, 27(1). doi: 10.1108/IJLM-01-2014-0009
Michán, L., Muñoz-Velasco, I. (2013). Cienciometría para ciencias médicas: definiciones, aplicaciones y perspectivas. Investigación En Educación Médica, 2(6), 100-106. doi:10.1016/s2007-5057(13)72694-2
Niven, P. R. (2006). Balanced Scorecard Step-by- step: Maximizing Performance and Maintaining Results. Hoboken, United States: Wiley.
Porter, A. L. (2019). Data Analytics for Better Informed Technology & Engineering Management. IEEE Engineering Management Review, 47(3), 29-32. doi: 10.1109/EMR.2019.2928265.
Priem, J., Piwowar, H., Hemminger, B. (2012). Altmetrics in the wild: Using social media to explore scholarly impact. arXiv:1203.4745
Qiu, J., Zhao, R., Yang, S., Dong, K. (2017). Informetrics: Theory, Methods and Applications. Singapore: Springer.
Rodriguez-Salvador, M. (2006). Innovación y creatividad. En Ingeniería concurrente: Una metodología integradora, 137-145. Barcelona, Spain: Universitat Politècnica de Catalunya, Edicions UPC.
Rodriguez-Salvador, M., Eddy-Valdez A., Garza- Cavazos, R. (2002). Industry/university cooperative research in competitive technical intelligence: a case of identifying technological trends for a Mexican steel manufacturer. Research Evaluation, 11(3), 165–173. doi: 10.3152/147154402781776835
Rodriguez-Salvador, M., Garcia-Garcia, L. (2018). Additive Manufacturing in Healthcare. Foresight and STI Governance, 12(1), 47-55. doi: 10.17323/2500-2597.2018.1.47.55
Rodriguez-Salvador, M., Lopez-Martinez, R. E. (2000). Cognitive Structure of Research: Scientometric Mapping in Sintered Materials. Research Evaluation, 9(3), 189-200. doi: 10.3152/147154400781777214
Rodriguez-Salvador, M., Rio-Belver, R. M., Garechana-Anacabe, G. (2017). Scientometric and patentometric analyses to determine the knowledge landscape in innovative technologies: The case of 3D bioprinting. PLoS ONE, 12(6): e0180375. doi: 10.1371/journal.pone.0180375
Rodriguez-Salvador, M., Ruiz-Cantu, L. (2019). Revealing Emerging Science and Technology Research for Dentistry Applications of 3D Bioprinting. International Journal of
Bioprinting, 5(1), 170-176. doi: 10.18063/ijb.v5i1.170
Rodriguez-Salvador, M., Villarreal-Garza, D., Alvarez, M., Trujillo-de Santiago, G. (2019). Analysis of the Knowledge Landscape of 3D Bioprinting in Latin America. International Journal of Bioprinting, 5(2.2), 16-25. doi:10.18063/ijb.v5i2.3.240
Rothberg, H. N., & Erickson, G. S. (2017). Big data systems: knowledge transfer or intelligence insights? Journal of Knowledge Management, 21(1), 92–112. doi:10.1108/jkm-07-2015-0300
Shaitura, S.V., Ordov, K.V., Lesnichaya, I.G., Romanova, Y.D., Khachaturova, S.S. (2018). Services and mechanisms of competitive intelligence on the Internet. Revista ESPACIOS. Vol. 39 (No 45).
Smirnova, K., Golkar, A., Vingerhoeds, R. (2018). Competition-driven figures of merit in technology roadmap planning. 2018 IEEE International Systems Engineering Symposium (ISSE), 1-6. doi: 10.1109/SysEng.2018.8544407.
Staudt, J., Yu, H., Light, R.P., Marschke, G., Börner, K., Weinberg, B. A. (2018) High- impact and transformative science (HITS) metrics: Definition, exemplification, and comparison. PLoS ONE, 13(7): e0200597. doi: 10.1371/journal.pone.0200597.
Verlander, E. G. (2012). The Practice of Professional Consulting. San Francisco, United States: Wiley.
Wilsdon, J., Allen, L., Belfiore, E., Campbell, P., Curry, S., Hill, S., Jones, R.A.L., Kain, R., Kerridge, S., Thelwall, M., Tinkler, J., Viney, I., Wouters, P., Hill, J., Johnson, B. (2015). The metric tide: report of the independent review of the role of metrics in research assessment and management. London, United Kingdom: Higher Education Funding Council for England. doi: 10.13140/RG.2.1.4929.1363.
Zhang, Y., Robinson, D.K.R., Porter, A.L., Zhu, D., Zhang, G., Lu, J. (2016). Technology roadmapping for competitive technical intelligence. Technological Forecasting and Social Change, 110, 175-186. doi: 10.1016/j.techfore.2015.11.029
Zhang, Y., Zhang, G., Chen, H., Porter, A. L., Zhu, D., Lu, J. (2016). Topic Analysis and Forecasting for Science, Technology and Innovation: Methodology and a Case Study focusing on Big Data Research. Technological Forecasting and Social Change. 105, 179-191. doi: 10.1016/j.techfore.2016.01.015.
Zeid, A. (2014). Business Transformation: A Roadmap for Maximizing Organizational Insights. Cary, United States: Wiley.
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