Leogrande, Angelo and Drago, Carlo and Mallardi, Giulio and Costantiello, Alberto and Magaletti, Nicola (2024): Patenting Propensity in Italy: A Machine Learning Approach to Regional Clustering.
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Abstract
This article focuses on the propensity to patent across Italian regions, considering data from ISTAT-BES between 2004 and 2019 to contribute to analyzing regional gaps and determinants of innovative performances. Results show how the North-South gap in innovative performance has persisted over time, confirming the relevance of research intensity, digital infrastructure, and cultural employment on patenting activity. These relations have been analyzed using the panel data econometric model. It allows singling out crucial positive drivers like R&D investment or strongly negative factors, such as limited mobility of graduates. More precisely, given the novelty of approaches applied in the used model, the following contributions are represented: first, the fine grain of regional differentiation, from which the sub-national innovation system will be observed. It also puts forward a set of actionable policy recommendations that would contribute to more substantial inclusive innovation, particularly emphasizing less-performing regions. By focusing on such dynamics, this study will indirectly address how regional characteristics and policies shape innovation and technological competitiveness in Italy. Therefore, it contributes to the debate on regional systems of innovation and their possible role in economic development in Europe since the economic, institutional, and technological conditions are differentiated between various areas in Italy.
Item Type: | MPRA Paper |
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Original Title: | Patenting Propensity in Italy: A Machine Learning Approach to Regional Clustering |
English Title: | Patenting Propensity in Italy: A Machine Learning Approach to Regional Clustering |
Language: | English |
Keywords: | Innovation, Innovation and Invention, Management of Technological Innovation and R&D, Technological Change, Intellectual Property and Intellectual Capital |
Subjects: | O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O30 - General O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O31 - Innovation and Invention: Processes and Incentives O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O32 - Management of Technological Innovation and R&D O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O33 - Technological Change: Choices and Consequences ; Diffusion Processes O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O34 - Intellectual Property and Intellectual Capital O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O35 - Social Innovation O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O38 - Government Policy |
Item ID: | 123081 |
Depositing User: | Dr Angelo Leogrande |
Date Deposited: | 06 Jan 2025 08:34 |
Last Modified: | 06 Jan 2025 08:34 |
References: | Abdulhameed, T. Z., Yousif, S. A., Samawi, V. W., & Al-Shaikhli, H. I. (2024). SS-DBSCAN: Semi-Supervised Density-Based Spatial Clustering of Applications with Noise for Meaningful Clustering in Diverse Density Data. IEEE Access. Aguiar-Hernandez, C., & Breetz, H. L. (2024). The adverse effects of political instability on innovation systems: The case of Mexico's wind and solar sector. Technovation, 136, 103083. Ali, M. A. (2024). Modeling regional innovation in Egyptian governorates: Regional knowledge production function approach. Regional Science Policy & Practice, 16(3), 12450. Al-Khatib, A. W., & Al-ghanem, E. M. (2022). Radical innovation, incremental innovation, and competitive advantage, the moderating role of technological intensity: evidence from the manufacturing sector in Jordan. European Business Review, 34(3), 344-369. Alnafrah, I. (2024). Identifying innovation roadblocks: unveiling knowledge and innovation patterns that hinder commercialisation. Technology Analysis & Strategic Management, 1-21. Anouze, A. L., Al Khalifa, M. M., & Al-Jayyousi, O. R. (2024). Reevaluating national innovation systems: An index based on dynamic-network data envelopment analysis. Socio-Economic Planning Sciences, 95, 102003. Ar, I. M., Temel, S., Dabic, M., Howells, J., Mert, A., & Yesilay, R. B. (2021). The role of supporting factors on patenting activities in emerging entrepreneurial universities. IEEE transactions on engineering management, 70(6), 2293-2304. Ashari, P. A., Blind, K., & Koch, C. (2023). Knowledge and technology transfer via publications, patents, standards: Exploring the hydrogen technological innovation system. Technological Forecasting and Social Change, 187, 122201. Ashari, P. A., Oh, H., & Koch, C. (2024). Pathways to the hydrogen economy: A multidimensional analysis of the technological innovation systems of Germany and South Korea. international journal of hydrogen energy, 49, 405-421. Barra, C., & Ruggiero, N. (2022). How do dimensions of institutional quality improve Italian regional innovation system efficiency? The Knowledge production function using SFA. Journal of Evolutionary Economics, 32(2), 591-642. Bechini, A., Marcelloni, F., & Renda, A. (2020). TSF-DBSCAN: A novel fuzzy density-based approach for clustering unbounded data streams. IEEE Transactions on Fuzzy Systems, 30(3), 623-637. Berman, A., Marino, A., & Mudambi, R. (2020). The global connectivity of regional innovation systems in Italy: A core–periphery perspective. Regional Studies, 54(5), 677-691. Bharill, N., Patel, O. P., Tiwari, A., Mu, L., Li, D. L., Mohanty, M., ... & Prasad, M. (2019). A generalized enhanced quantum fuzzy approach for efficient data clustering. IEEE Access, 7, 50347-50361. Bianchi, C., Galaso, P., & Palomeque, S. (2021). The tradeoffs of brokerage in innovation networks: a study of Latin American cities. Serie Documentos de Trabajo; 21/21. Binz, C., & Truffer, B. (2020). The governance of global innovation systems: Putting knowledge in context. Knowledge for governance, 397-414. Block, J., Fisch, C., Ikeuchi, K., & Kato, M. (2022). Trademarks as an indicator of regional innovation: evidence from Japanese prefectures. Regional Studies, 56(2), 190-209. Braunerhjelm, P., Ding, D., & Thulin, P. (2020). Labour market mobility, knowledge diffusion and innovation. European Economic Review, 123, 103386. Burhan, M., Singh, A. K., & Jain, S. K. (2017). Patents as proxy for measuring innovations: A case of changing patent filing behavior in Indian public funded research organizations. Technological Forecasting and Social Change, 123, 181-190. Cappellano, F., Sohn, C., Makkonen, T., & Kaisto, V. (2022). Bringing borders back into cross-border regional innovation systems: Functions and dynamics. Environment and Planning A: Economy and Space, 54(5), 1005-1021. Caviggioli, F., Colombelli, A., De Marco, A., Scellato, G., & Ughetto, E. (2023). The impact of university patenting on the technological specialization of European regions: a technology-level analysis. Technological Forecasting and Social Change, 188, 122216. Cefis, E., Grassano, N., & Tubiana, M. (2024). Firms’ patenting and collective cumulative knowledge: evidence from the largest R&D investors in the world. Industry and Innovation, 1-36. Cheng, H., Yu, Y., Zhang, L., & Zhang, Z. (2022). The effect of subsidies on cultural and creative Enterprise performance: mediating role of patents. Engineering Economics, 33(2), 188-199. Christensen, J. L., Gregersen, B., Holm, J. R., & Lorenz, E. (Eds.). (2021). Globalisation, new and emerging technologies, and sustainable development: The Danish innovation System in Transition. Christopoulos, G., & Wintjes, R. (2024). Identifying Clusters as Local Innovation Systems. Journal of the Knowledge Economy, 15(2), 9784-9823. Ciołek, D., & Golejewska, A. (2022). Efficiency determinants of regional innovation systems in Polish subregions. Gospodarka Narodowa. The Polish Journal of Economics, 311(3), 24-45. Cooke, P., Heidenreich, M., & Braczyk, H. J. (2024). Introduction: Regional innovation systems–an evolutionary approach. In Regional innovation systems (pp. 1-18). Routledge. Crespi, F., & Guarascio, D. (2019). The demand-pull effect of public procurement on innovation and industrial renewal. Industrial and Corporate Change, 28(4), 793-815. D’Adamo, I., Di Carlo, C., Gastaldi, M., Rossi, E. N., & Uricchio, A. F. (2024). Economic Performance, Environmental Protection and Social Progress: A Cluster Analysis Comparison towards Sustainable Development. Sustainability, 16(12), 5049. Dhulipala, L., Dong, X., Gowda, K. N., & Gu, Y. (2024). Optimal Parallel Algorithms for Dendrogram Computation and Single-Linkage Clustering. arXiv preprint arXiv:2404.19019. Di Comite, F., Diukanova, O., Mandras, G., & Gómez Prieto, J. (2018). The RHOMOLO economic impact assessment of the R&I and Low-Carbon ERDF Investment programme in Apulia, Italy (No. 04/2018). JRC Working Papers on Territorial Modelling and Analysis. Dong, Y., Wei, Z., Liu, T., & Xing, X. (2020). The impact of R&D intensity on the innovation performance of artificial intelligence enterprises-based on the moderating effect of patent portfolio. Sustainability, 13(1), 328. Drago, C., Di Nallo, L., & Russotto, M. L. (2024). Measuring and classifying the social sustainability of European banks: An analysis using interval-based composite indicators. Environmental Impact Assessment Review, 105, 107434. Drago, C., Minnetti, F., Di Nallo, L., & Manzari, A. (2025). Uncovering patterns of fintech behavior in Italian banks: A multidimensional statistical analysis. Research in International Business and Finance, 73, 102598. Errichiello, L., & Drago, C. (2024). Destinations’ environmental orientation: a symbolic cluster analysis based on hotel employees’ environmental knowledge, awareness, and concern. Journal of Sustainable Tourism, 32(8), 1471-1491. Ervits, I. (2024). The effect of co-patenting as a form of knowledge meta-integration on technological differentiation at Siemens. European Journal of Innovation Management, 27(8), 2575-2596. Fang, L., & Li, Z. (2024). Corporate digitalization and green innovation: Evidence from textual analysis of firm annual reports and corporate green patent data in China. Business Strategy and the Environment. Fernandes, C., Farinha, L., Ferreira, J. J., Asheim, B., & Rutten, R. (2021). Regional innovation systems: what can we learn from 25 years of scientific achievements?. Regional studies, 55(3), 377-389. Filippopoulos, N., & Fotopoulos, G. (2022). Innovation in economically developed and lagging European regions: A configurational analysis. Research Policy, 51(2), 104424. Forner, D., & Ozcan, S. (2023). Examination of overlapping boundaries of innovation systems using deep neural network and natural language processing. IEEE Transactions on Engineering Management. Franco, S., Gianelle, C., Kleibrink, A., & Murciego, A. (2020). Learning from similar regions: how to benchmark innovation systems beyond rankings. In Quantitative Methods for Place-Based Innovation Policy (pp. 162-194). Edward Elgar Publishing. Fritsch, M., Greve, M., & Wyrwich, M. (2023). Shades of a Socialist Legacy? Innovation Activity in East and West Germany 1877-2014. Fu, Y., Liu, X., Sarkar, S., & Wu, T. (2021). Gaussian mixture model with feature selection: An embedded approach. Computers & Industrial Engineering, 152, 107000. Galaso, P., & Kovářík, J. (2021). Collaboration networks, geography and innovation: Local and national embeddedness. Papers in Regional Science, 100(2), 349-378. Ganau, R., & Grandinetti, R. (2021). Disentangling regional innovation capability: what really matters?. Industry and Innovation, 28(6), 749-772. Ganguly, M. (2024). Stronger patent regime, innovation and scientist mobility. Research in Economics, 78(4), 101004. Ghazal, S., Aziz, T., Tabash, M. I., & Drachal, K. (2024). The Linkage between Corporate Research and Development Intensity and Stock Returns: Empirical Evidence. Journal of Risk and Financial Management, 17(5), 180. Gutiérrez, C., Roa P, V., & Smith, J. (2021). The Chilean sectoral innovation systems: An approach from the National Innovation Survey. Journal of technology management & innovation, 16(1), 3-13. Han, J. (2017). Technology commercialization through sustainable knowledge sharing from university-industry collaborations, with a focus on patent propensity. Sustainability, 9(10), 1808. Hazarika, N. (2021). R&D intensity and its curvilinear relationship with firm profitability: Perspective from the alternative energy sector. Sustainability, 13(9), 5060. Heidenreich, M. (2024). Conclusion: the dilemmas of regional innovation systems. In Regional innovation systems (pp. 363-389). Routledge. Houdouin, P., Ollila, E., & Pascal, F. (2023, June). Regularized EM algorithm. In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 1-5). IEEE. Howoldt, D. (2024). Characterising innovation policy mixes in innovation systems. Research Policy, 53(2), 104902. Ikotun, A. M., & Ezugwu, A. E. (2022). Improved SOSK-means automatic clustering algorithm with a three-part mutualism phase and random weighted reflection coefficient for high-dimensional datasets. Applied Sciences, 12(24), 13019. Im, H. J., Park, Y. J., & Shon, J. (2015). Product market competition and the value of innovation: Evidence from US patent data. Economics Letters, 137, 78-82. Innocenti, N., Capone, F., & Lazzeretti, L. (2020). Knowledge networks and industrial structure for regional innovation: An analysis of patents collaborations in Italy. Papers in Regional Science, 99(1), 55-73. Javadian, M., Vaziri, R., Haghzad Klidbary, S., & Malekzadeh, A. (2020). Refining membership degrees obtained from fuzzy C-means by re-fuzzification. Iranian Journal of Fuzzy Systems, 17(4), 85-104. Jovanović, M., Savić, G., Cai, Y., & Levi-Jakšić, M. (2022). Towards a Triple Helix based efficiency index of innovation systems. Scientometrics, 127(5), 2577-2609. Karna, A., & Gibert, K. (2022). Automatic identification of the number of clusters in hierarchical clustering. Neural Computing and Applications, 34(1), 119-134. Kim, H., Kim, H. K., & Cho, S. (2020). Improving spherical k-means for document clustering: Fast initialization, sparse centroid projection, and efficient cluster labeling. Expert Systems with Applications, 150, 113288. Kim, J., & Lee, K. (2022). Local–global interface as a key factor in the catching up of regional innovation systems: Fast versus slow catching up among Taipei, Shenzhen, and Penang in Asia. Technological Forecasting and Social Change, 174, 121271. Kim, J., & Lee, K. (2022). Varieties of Regional Innovation Systems around the World and Catch-up by Latecomers. Utrecht University, Human Geography and Planning. Kitaisky, V., Revinsky, G., Revinsky, O., & Shvedova, V. (2021). Industry preferences for foreign patenting of Russian innovation enterprises. Economic Annals-XXI/Ekonomìčnij Časopis-XXI, 189. Klincewicz, K., & Szumiał, S. (2022). Successful patenting—not only how, but with whom: the importance of patent attorneys. Scientometrics, 127(9), 5111-5137. Kryukov, V., & Tokarev, A. (2022). Spatial trends of innovation in the Russian oil and gas sector: What does patent activity in Siberia and the Arctic reflect?. Regional Science Policy & Practice, 14(1), 127-146. Lee, S., Lee, H., & Lee, C. (2020). Open innovation at the national level: Towards a global innovation system. Technological Forecasting and Social Change, 151, 119842. Lepore, D., Micozzi, A., & Spigarelli, F. (2021). Industry 4.0 accelerating sustainable manufacturing in the COVID-19 era: assessing the readiness and responsiveness of Italian regions. Sustainability, 13(5), 2670. Li, Y., Wei, Y., Li, Y., Lei, Z., & Ceriani, A. (2022). Connecting emerging industry and regional innovation system: Linkages, effect and paradigm in China. Technovation, 111, 102388. Longi, H., Niemelä, S., & Leppänen, T. (2020). Bridging the innovation system and industry development: experiments from Northern Finland. International Journal of Innovation and Regional Development, 9(2), 85-101. Lu, H., Du, D., & Qin, X. (2022). Assessing the dual innovation capability of national innovation system: Empirical evidence from 65 countries. Systems, 10(2), 23. Maasoumi, E., Heshmati, A., & Lee, I. (2021). Green innovations and patenting renewable energy technologies. Empirical economics, 60(1), 513-538. Manuylenko, V. V., Ermakova, G. A., Gryzunova, N. V., Koniagina, M. N., Milenkov, A. V., Setchenkova, L. A., & Ochkolda, I. I. (2022). Generation and assessment of intellectual and informational capital as a foundation for corporations’ digital innovations in the “open innovation” system. International Journal of Advanced Computer Science and Applications, 13(9). Matricano, D. (2020). The effect of R&D investments, highly skilled employees, and patents on the performance of Italian innovative startups. Technology Analysis & Strategic Management, 32(10), 1195-1208. Mazlumi, S. H. H., & Kermani, M. A. M. (2022). Investigating the structure of the internet of things patent network using social network analysis. IEEE Internet of Things Journal, 9(15), 13458-13469. McCaw, Z. R., Aschard, H., & Julienne, H. (2022). Fitting Gaussian mixture models on incomplete data. BMC bioinformatics, 23(1), 208. Meetei, L. A., Bhattacharjya, B., & Bhowmick, B. (2024). The role of universities in the innovation systems in the developing countries. Foresight and STI Governance, 18(1), 58-67. Mi, T., Zhong, L., Huang, Y., Liu, Y., & Yu, G. (2023, November). A Grid-Based Fuzzy C-Means Clustering Algorithm with Unknown Number of Clusters. In 2023 5th International Conference on Artificial Intelligence and Computer Applications (ICAICA) (pp. 182-185). IEEE. Montenegro, R. L. G., Ribeiro, L. C., & Britto, G. (2021). The effects of environmental technologies: evidences of different national innovation systems. Journal of Cleaner Production, 284, 124742. Muna, U. M., Biswas, S., Zarif, S. A. A. M., & Farid, D. M. (2023, December). Ameliorating Performance of Random Forest using Data Clustering. In 2023 26th International Conference on Computer and Information Technology (ICCIT) (pp. 1-6). IEEE. Ndicu, S., Ngui, D., & Barasa, L. (2024). Technological catch-up, innovation, and productivity analysis of national innovation systems in developing countries in Africa 2010–2018. Journal of the knowledge economy, 15(2), 7941-7967. Nguyen, P. N. D., & Nguyen, H. H. (2024). Examining the Role of Family in Shaping Digital Entrepreneurial Intentions in Emerging Markets. SAGE Open, 14(1), 21582440241239493. Nuccio, M., & Bertacchini, E. (2023). Data-driven arts and cultural organizations: opportunity or chimera?. In Rethinking Culture and Creativity in the Digital Transformation (pp. 31-48). Routledge. Önder, A. S., Schweitzer, S., & Tcaci, O. (2024). Innovation and Regional Development: The Impact of Patenting on Labor Market Outcomes. Available at SSRN 5010957. Ortega, A. M., & Serna, M. (2020). Determinants of innovation performance of organizations in a regional innovation system from a developing country. International Journal of Innovation Science, 12(3), 345-362. Ottone, V., & Barbieri, M. (2022). Research & innovation policy in the Italian NRRP: an evalutation of emerging challenges for multi-level governance. Contemporary Italian Politics, 14(4), 409-423. ÖZen, B. S., & Baycan, T. (2022). Comparison of Innovation Strategies of Regional Development Agencies in Turkey. Ekonomicheskie i Sotsialnye Peremeny, 15(3), 236-258. Pan, X., Li, J., Shen, Z., & Song, M. (2023). Life cycle identification of China's regional innovation systems based on entropy weight disturbing attribute model. Habitat International, 131, 102725. Paunov, C., & Rollo, V. (2016). Has the internet fostered inclusive innovation in the developing world?. World Development, 78, 587-609. Petrosillo, I., Lovello, E. M., Drago, C., Magazzino, C., & Valente, D. (2024). Global environmental sustainability trends: A temporal comparison using a new interval-based composite indicator. Environmental and Sustainability Indicators, 24, 100482. Portillo-Tarragona, P., Scarpellini, S., & Marín-Vinuesa, L. M. (2024). ‘Circular patents’ and dynamic capabilities: new insights for patenting in a circular economy. Technology Analysis & Strategic Management, 36(7), 1571-1586. Puri, D., & Gupta, D. (2024, May). Enhancing K-Means Clustering with Data-Driven Initialization and Adaptive Distance Measures. In 2024 International Conference on Emerging Innovations and Advanced Computing (INNOCOMP) (pp. 570-574). IEEE. Radosevic, S. (2022). Techno-economic transformation in Eastern Europe and the former Soviet Union–A neo-Schumpeterian perspective. Research Policy, 51(1), 104397. Rahko, J. (2017). Knowledge spillovers through inventor mobility: the effect on firm-level patenting. The Journal of Technology Transfer, 42(3), 585-614. Rhodes, J. S., Cutler, A., & Moon, K. R. (2023). Geometry-and accuracy-preserving random forest proximities. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(9), 10947-10959. Ruhrmann, H., Fritsch, M., & Leydesdorff, L. (2022). Synergy and policy-making in German innovation systems: Smart Specialisation Strategies at national, regional, local levels?. Regional Studies, 56(9), 1468-1479. Samara, E., Kilintzis, P., Katsoras, E., Martnidis, G., & Kosti, P. (2024). A system dynamics approach for the development of a Regional Innovation System. Journal of Innovation and Entrepreneurship, 13(1), 26. Scherngell, T., Schwegmann, K., & Zahradnik, G. (2023). The geographical dynamics of global R&D collaboration networks in robotics: Evidence from co-patenting activities across urban areas worldwide. Plos one, 18(4), e0281353. Shahwan, R., & Zaman, T. (2023). Role of universities as knowledge Creators in a national innovation system: an open innovation paradigm. In Industry clusters and innovation in the Arab world: Challenges and opportunities (pp. 259-280). Emerald Publishing Limited. Song, M., Jung, H., Lee, S., Kim, D., & Ahn, M. (2021). Diagnostic classification and biomarker identification of Alzheimer’s disease with random forest algorithm. Brain sciences, 11(4), 453. Stek, P. E. (2021). Identifying spatial technology clusters from patenting concentrations using heat map kernel density estimation. Scientometrics, 126(2), 911-930. Stojčić, N. (2021). Collaborative innovation in emerging innovation systems: Evidence from Central and Eastern Europe. The Journal of Technology Transfer, 46(2), 531-562. Su, Y., Jiang, X., & Lin, Z. (2021). Simulation and relationship strength: characteristics of knowledge flows among subjects in a regional innovation system. Science, Technology and Society, 26(3), 459-481. Suominen, A., Deschryvere, M., & Narayan, R. (2023). Uncovering value through exploration of barriers-A perspective on intellectual property rights in a national innovation system. Technovation, 123, 102719. Tahmooresnejad, L., & Turkina, E. (2023). Economic geography of innovation: The effect of gender-related aspects of co-inventor networks on country and regional innovation. Plos one, 18(7), e0288843. Volchik, V. V., Maslyukova, E. V., & Panteeva, S. A. (2021). Investigating the approaches to national innovation systems modeling. Ekonomicheskie i Sotsialnye Peremeny, 14(5), 135-150. Wagner, C., Poland, K. B., & Yan, X. (2021). Flows and Networks in Global Innovation System among Top R&D Nations. Global Innovation and National Interests Project: Working Paper, 7, 2016-2021. Wang, J., Chandra, K., Du, C., Ding, W., & Wu, X. (2021). Assessing the Potential of Cross-border regional innovation Systems: A case study of the Hong Kong-Shenzhen region. Technology in Society, 65, 101557. Wibisono, E. (2024). THE ROLE OF LOCAL GOVERNMENT IN IMPROVING REGIONAL INNOVATION CAPABILITY: A CRITICAL LITERATURE REVIEW IN THE CONTEXT OF THE ASIAN REGION. Jurnal Khazanah Intelektual, 8(1), 1-28. Wirkierman, A. L., Ciarli, T., & Savona, M. (2023). A taxonomy of European innovation clubs. Economia Politica, 40(1), 1-34. Wong, C. Y., & Lee, K. (2022). Evolution of innovation systems of two industrial districts in East Asia: transformation and upgrade from a peripheral system and the role of the core firms, Samsung and TSMC. Journal of Evolutionary Economics, 32(3), 955-990. Wong, C. Y., Sheu, J., & Lee, K. (2023). Dynamics or dilemma: Assessing the innovation systems of three satellite platform regions (Singapore, Dublin and Penang). Eurasian Geography and Economics, 64(5), 589-628. Yan, S., Zou, L., Growe, A., & Wang, Q. (2024). Propositions for place-based policies in making regional innovation systems. Evidence from six high-tech industrial development zones in China. Cities, 154, 105322. Yao, L., Li, J., & Li, J. (2020). Urban innovation and intercity patent collaboration: A network analysis of China’s national innovation system. Technological Forecasting and Social Change, 160, 120185. Yu, S., Wang, Y., Gu, Y., Dhulipala, L., & Shun, J. (2021). Parchain: A framework for parallel hierarchical agglomerative clustering using nearest-neighbor chain. arXiv preprint arXiv:2106.04727. Yuan, X., & Li, X. (2021). Mapping the technology diffusion of battery electric vehicle based on patent analysis: A perspective of global innovation systems. Energy, 222, 119897. Zhao, R., Zhang, H., Zhang, M. Y., Qu, F., & Xu, Y. (2023). Competitor-weighted centrality and small-world clusters in competition networks on firms’ innovation ambidexterity: Evidence from the wind energy industry. International Journal of Environmental Research and Public Health, 20(4), 3339. Zhao, X., & Tan, J. (2021). The performance implications of patenting–the moderating effect of informal institutions in emerging economies. R&D Management, 51(5), 468-483. Zhou, Q., Cheng, C., Fang, Z., Zhang, H., & Xu, Y. (2024). How does the development of the digital economy affect innovation output? Exploring mechanisms from the perspective of regional innovation systems. Structural Change and Economic Dynamics, 70, 1-17. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/123081 |