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Abstract
While innovation is generally accepted as one of the drivers of economic growth, most innovation metrics are qualitative and have a relatively lesser impact on policymaking than their quantitative counterparts. With this challenge, this paper presents another quantitative metric: the Fluidity of Innovation applied in the Philippines from 2001 to 2021. The study analyses data from public government reports and reputable private entities using the contextualized Reynolds Number from fluid mechanics. The findings reveal a significant transformation in the Philippines' innovation, moving from a laminar (smooth and predictable) to a turbulent (rapid and complex) phase; this indicates the country has a growing capacity to cater to rapid development in technology such as Artificial Intelligence and Quantum Computers. Since the Philippines is leaning towards a turbulent flow of innovation, some technology will be felt as Radical Innovation instead of Disruptive Innovation across the industries that allow the labor force to experience empowerment rather than a complete layoff. This research contributes to the broader understanding of innovation's role in the Philippine economy and fiscal policies, particularly those for innovation and technology.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Jose, D. S. (2024). Philippines’ Fluidity of Innovation from 2001 to 2021: Interpretations and Implications. International Journal of Multidisciplinary: Applied Business and Education Research, 5(1), 169-182. https://doi.org/10.11594/ijmaber.05.01.17
References
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Balakrishnan, R., & Milberg, W. (2019). Firm innovation and capitalist dialectics: The economics of Nina Shapiro. The Economic and Labour Relations Review, 30(4), 467–477. https://doi.org/10.1177/1035304619880473
Bigliardi, B., Ferraro, G., Filippelli, S., & Galati, F. (2020). The past, present and future of open innovation. European Journal of In-novation Management, 24(4), 1130–1161. https://doi.org/10.1108/EJIM-10-2019-0296
Buskens, V. (2020). Spreading information and developing trust in social networks to ac-celerate diffusion of innovations. Trends in Food Science & Technology, 106, 485–488. https://doi.org/10.1016/j.tifs.2020.10.040
Degenhardt, F., Seifert, S., & Szymczak, S. (2019). Evaluation of variable selection methods for random forests and omics data sets. Briefings in Bioinformatics, 20(2), 492–503. https://doi.org/10.1093/bib/bbx124
Fossen, F., & Sorgner, A. (2019). Mapping the Future of Occupations: Transformative and Destructive Effects of New Digital Technologies on Jobs. Foresight and STI Governance, 13(2), 10–18. https://doi.org/10.17323/2500-2597.2019.2.10.18
Funk, G. N. S., Jeffrey. (2021, March 19). Why We Need to Stop Relying On Patents to Measure Innovation. ProMarket. https://www.promarket.org/2021/03/19/patents-bad-measure-innovation-new-metric/
Gault, F., & Soete, L. (2022). Innovation Indica-tors. In F. Gault & L. Soete, Oxford Re-search Encyclopedia of Business and Management. Oxford University Press. https://doi.org/10.1093/acrefore/9780190224851.013.331
Giorgi, F. M., Ceraolo, C., & Mercatelli, D. (2022). The R Language: An Engine for Bioinformatics and Data Science. Life, 12(5), 648. https://doi.org/10.3390/life12050648
Harada, T. (2018). Endogenous innovation un-der New Keynesian dynamic stochastic general equilibrium model. Economics of Innovation and New Technology, 27(4), 361–376. https://doi.org/10.1080/10438599.2017.1362797
Isomäki, A. (2018, November 29). Open Inno-vation – What It Is and How to Do It. Vii-ma. https://www.viima.com/blog/open-innovation
Javaherchian, J., Moosavi, A., & Tabatabaei, S. A. (2023). Numerical analysis of pressure drop reduction of bubbly flows through hydrophobic microgrooved channels. Scientific Reports, 13(1), Article 1. https://doi.org/10.1038/s41598-023-45260-7
Kumar, V., & Sundarraj, R. P. (2018). The Eco-nomic Impact of Innovation. In V. Kumar & R. P. Sundarraj (Eds.), Global Innova-tion and Economic Value (pp. 49–93). Springer India. https://doi.org/10.1007/978-81-322-3760-0_2
Mineiro, A. A. da C., Assis de Souza, T., & Car-valho de Castro, C. (2021). The quadruple and quintuple helix in innovation envi-ronments (incubators and science and technology parks). Innovation & Man-agement Review, 18(3), 292–307. https://doi.org/10.1108/INMR-08-2019-0098
Momeni, F., Arab Mazar Yazdi, A., & Najafi, S. M. S. (2019). Changing economic systems and institutional dimensions of the Triple Helix model. Journal of Innovation and Entrepreneurship, 8(1), 1. https://doi.org/10.1186/s13731-018-0096-1
Olah, D., & Alpek, B. L. (2021). The theoretical model of spatial production for innova-tion. Journal of Innovation and Entrepre-neurship, 10(1), 37. https://doi.org/10.1186/s13731-021-00182-4
Orlenko, A., & Moore, J. H. (2021). A compari-son of methods for interpreting random forest models of genetic association in the presence of non-additive interactions. BioData Mining, 14(1), 9. https://doi.org/10.1186/s13040-021-00243-0
Park, M., Leahey, E., & Funk, R. J. (2023). Pa-pers and patents are becoming less dis-ruptive over time. Nature, 613(7942), Ar-ticle 7942. https://doi.org/10.1038/s41586-022-05543-x
Poertner, M., & Zhang, N. (2023). The effects of combating corruption on institutional trust and political engagement: Evidence from Latin America. Political Science Re-search and Methods, 1–10. https://doi.org/10.1017/psrm.2023.4
Pugliese, E., Cimini, G., Patelli, A., Zaccaria, A., Pietronero, L., & Gabrielli, A. (2019). Un-folding the innovation system for the de-velopment of countries: Coevolution of Science, Technology and Production. Sci-entific Reports, 9(1), Article 1. https://doi.org/10.1038/s41598-019-52767-5
Radziszewski, P. (2020). Exploring the devel-opment of an innovation metric—From hypothesis to initial use. Journal of Inno-vation and Entrepreneurship, 9(1), 10. https://doi.org/10.1186/s13731-020-00118-4
Radziwon, A., & Vanhaverbeke, W. (2024). Open Innovation in Small and Medium-Sized Enterprises. In H. Chesbrough, A. Radziwon, W. Vanhaverbeke, & J. West (Eds.), The Oxford Handbook of Open In-novation. Oxford University Press.
Razumovskaia, E., Yuzvovich, L., Kniazeva, E., Klimenko, M., & Shelyakin, V. (2020). The Effectiveness of Russian Government Pol-icy to Support SMEs in the COVID-19 Pandemic. Journal of Open Innovation: Technology, Market, and Complexity, 6(4), 160. https://doi.org/10.3390/joitmc6040160
Sabol, M. A., & Winton, B. G. (2022). Examining the Impacts of Trust and Creativity on In-novation Focused Promotive Voice. In-ternational Journal of Innovation Man-agement, 26(04), 2250024. https://doi.org/10.1142/S1363919622500244
Selva Babu, S., Kiruthika, A., Ragapriya, V., Monika, M. I., Anandhi, V., & Saranya, N. (2022). Review on Applications of R pro-gramming in Biological Data Analysis. Madras Agricultural Journal, 109. https://doi.org/10.29321/MAJ.10.000684
Steinbruch, F. K., Nascimento, L. da S., & de Menezes, D. C. (2021). The role of trust in innovation ecosystems. Journal of Busi-ness & Industrial Marketing, 37(1), 195–208. https://doi.org/10.1108/JBIM-08-2020-0395
Suherlan, S., & Okombo, M. O. (2023). Techno-logical Innovation in Marketing and its Effect on Consumer Behaviour. Technol-ogy and Society Perspectives (TACIT), 1(2), 94–103. https://doi.org/10.61100/tacit.v1i2.57
The Heritage Foundation. (2024). Philippines Economy: Population, GDP, Inflation, Business, Trade, FDI, Corruption. Herit-age.Org/Index. https://www.heritage.org/index/country/philippines
Trivellato, B., Martini, M., & Cavenago, D. (2021). How Do Organizational Capabili-ties Sustain Continuous Innovation in a Public Setting? The American Review of Public Administration, 51(1), 57–71. https://doi.org/10.1177/0275074020939263
Tseng, W.-T., Liu, Y.-T., Hsu, Y.-T., & Chu, H.-C. (2024). Revisiting the effectiveness of study abroad language programs: A mul-ti-level meta-analysis. Language Teach-ing Research, 28(1), 156–200. https://doi.org/10.1177/1362168820988423
Ulhøi, J. P. (2021). From innovation-as-usual towards unusual innovation: Using nature as an inspiration. Journal of Innovation and Entrepreneurship, 10(1), 2. https://doi.org/10.1186/s13731-020-00138-0
UNESCO. (2024). World Bank Open Data. World Bank Open Data. https://data.worldbank.org
Van de Walle, S., & Migchelbrink, K. (2022). Institutional quality, corruption, and im-partiality: The role of process and out-come for citizen trust in public admin-istration in 173 European regions. Jour-nal of Economic Policy Reform, 25(1), 9–27. https://doi.org/10.1080/17487870.2020.1719103
World Intellectual Property Organization., Dutta, Soumitra. Editor., Lanvin, Bruno. Editor., Rivera León, Lorena. Editor., &
Wunsch-Vincent, Sacha. Editor. (2023). Global Innovation Index 2023: Innovation in the face of uncertainty (16th edition.). Geneva, Switzerland : World Intellectual Property Organization, 2023. https://doi.org/10.34667/TIND.48220
Yazıcı, A. M.s (2023). The Quintuple Helix, In-dustrial 5.0, and Society 5.0. In B. Akkaya, S. Andreea Apostu, E. Hysa, & M. Panait (Eds.), Digitalization, Sustainable Devel-opment, and Industry 5.0 (pp. 317–336). Emerald Publishing Limited. https://doi.org/10.1108/978-1-83753-190-520231016
Zhao, L., Xu, Y., & Xu, X. (2023). The effects of trust and platform innovation character-istics on consumer behaviors in social commerce: A social influence perspec-tive. Electronic Commerce Research and Applications, 60, 101284. https://doi.org/10.1016/j.elerap.2023.101284