High-quality marine economic development in China from the perspective of green total factor productivity growth: dynamic changes and improvement strategies
Abstract
High-quality marine economic development (HMED) is regarded as a new development pattern of the marine economy in China. This paper aims to examine the dynamic changes and improvement strategies of HMED from the perspective of the green total factor productivity (GTFP) growth. First, the GTFP growth of the marine economy in China’s coastal regions for the period 2007–2020 is calculated using the bootstrapped Malmquist index. Second, the dynamic changes and spatial impacts of the GTFP growth are characterized using kernel density estimation (KDE). Moreover, a novel analytical framework to study the improvement strategies of the GTFP is developed. Within this framework, the fuzzy set qualitative comparative analysis (fsQCA) method is used to explore the paths to achieve HMED. The findings show that: (i) the GTFP growth for coastal regions shows significant fluctuations, suggesting that a stable pattern of marine economic development has yet to be established; (ii) the regional distribution of GTFP growth varies significantly, with provinces with fast GTFP growth gathering resources from neighboring provinces, resulting in a siphon effect; (iii) for coastal provinces that lack certain development conditions, the combined effect of other advantageous factors can be used to achieve HMED. Finally, this study presents policy recommendations for achieving HMED, which can provide insights into the design of China’s future marine economic policies.
First published online 10 September 2024
Keyword : marine economy, high-quality marine economic development, green total factor productivity, kernel density estimation, fuzzy set qualitative comparative analysis
How to Cite
Liu, P., Zhu, B., Yang, M., & De Baets, B. (2024). High-quality marine economic development in China from the perspective of green total factor productivity growth: dynamic changes and improvement strategies. Technological and Economic Development of Economy, 30(6), 1572–1597. https://doi.org/10.3846/tede.2024.22018
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Simar, L., & Wilson, P. W. (1998). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management Science, 44(1), 49–61. https://doi.org/10.1287/mnsc.44.1.49
Simar, L., & Wilson, P. W. (1999). Estimating and bootstrapping Malmquist indices. European Journal of Operational Research, 115(3), 459–471. https://doi.org/10.1016/S0377-2217(97)00450-5
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Xia, F., & Xu, J. T. (2020). Green total factor productivity: A re-examination of quality of growth for provinces in China. China Economic Review, 62, Article 101454. https://doi.org/10.1016/j.chieco.2020.101454
Ye, F., Quan, Y. B., He, Y. X., & Lin, X. F. (2021). The impact of government preferences and environmental regulations on green development of China’s marine economy. Environmental Impact Assessment Review, 87, Article 106522. https://doi.org/10.1016/j.eiar.2020.106522
Zhang, Y. L. (2021). The regional disparity of influencing factors of technological innovation in China: evidence from high-tech industry. Technological and Economic Development of Economy, 27(4), 811–832. https://doi.org/10.3846/tede.2021.14828
Ding, L. L., Yang, Y., Wang, L., & Calin, A. C. (2020a). Cross efficiency assessment of China’s marine economy under environmental governance. Ocean & Coastal Management, 193, Article 105245. https://doi.org/10.1016/j.ocecoaman.2020.105245
Ding, L. L., Lei, L., Wang, L., Zhang, L. F., & Calin, A. C. (2020b). A novel cooperative game network DEA model for marine circular economy performance evaluation of China. Journal of Cleaner Production, 253, Article 120071. https://doi.org/10.1016/j.jclepro.2020.120071
Estache, A., de la Fe, B. T., & Trujillo, L. (2004). Sources of efficiency gains in port reform: A DEA decomposition of a Malmquist TFP index for Mexico. Utilities Policy, 12(4), 221–230. https://doi.org/10.1016/j.jup.2004.04.013
Fiss, P. C. (2011). Building better causal theories: A fuzzy set approach to typologies in organization research. Academy of Management Journal, 54(2), 393–420. https://doi.org/10.5465/amj.2011.60263120
Frambach, R. T., Fiss, P. C., & Ingenbleek, P. T. (2016). How important is customer orientation for firm performance? A fuzzy set analysis of orientations, strategies, and environments. Journal of Business Research, 69(4), 1428–1436. https://doi.org/10.1016/j.jbusres.2015.10.120
Jiang, H. L., Jiang, P. C., Wang, D., & Wu, J. H. (2021). Can smart city construction facilitate green total factor productivity? A quasi-natural experiment based on China’s pilot smart city. Sustainable Cities and Society, 69, Article 102809. https://doi.org/10.1016/j.scs.2021.102809
Jiang, X. Z., Liu, T. Y., & Su, C. W. (2014). Chin’s marine economy and regional development. Marine Policy, 50, 227–237. https://doi.org/10.1016/j.marpol.2014.06.008
Karim, N. H., Rahman, N. S. F. A., & Shah, S. F. S. S. J. (2018). Empirical evidence on failure factors of warehouse productivity in Malaysian logistic service sector. The Asian Journal of Shipping and Logistics, 34(2), 151–160. https://doi.org/10.1016/j.ajsl.2018.06.012
Kraus, S., Ribeiro-Soriano, D., & Schüssler, M. (2018). Fuzzy-set qualitative comparative analysis (fsQCA) in entrepreneurship and innovation research – the rise of a method. International Entrepreneurship and Management Journal, 14, 15–33. https://doi.org/10.1007/s11365-017-0461-8
Lee, K. H., Noh, J., & Khim, J. S. (2020). The blue economy and the United Nations’ sustainable development goals: Challenges and opportunities. Environment International, 137, Article 105528. https://doi.org/10.1016/j.envint.2020.105528
Li, G., Zhou, Y., Liu, F., & Tian, A. R. (2021). Regional difference and convergence analysis of marine science and technology innovation efficiency in China. Ocean & Coastal Management, 205, Article 105581. https://doi.org/10.1016/j.ocecoaman.2021.105581
Li, K., Qu, J. Y., Wei, P., Ai, H. S., & Jia, P. R. (2020). Modelling technological bias and productivity growth: A case study of China’s three urban agglomerations. Technological and Economic Development of Economy, 26(1), 135–164. https://doi.org/10.3846/tede.2020.11329
Li, Y., Wu, Y. J., Chen, Y. Q., & Huang, Q. B. (2021). The influence of foreign direct investment and trade opening on green total factor productivity in the equipment manufacturing industry. Applied Economics, 53(57), 6641–6654. https://doi.org/10.1080/00036846.2021.1947961
Liang, C., Wang, S. J., Foley, M., & Ma, G. H. (2023). The path selection on improving the quality of environmental information disclosure–configuration analysis based on fsQCA. Applied Economics, 55(19), 2207–2222. https://doi.org/10.1080/00036846.2022.2102134
Liu, P. D., & Zhu, B. Y. (2022). Temporal-spatial evolution of green total factor productivity in China’s coastal cities under carbon emission constraints. Sustainable Cities and Society, 87, Article 104231. https://doi.org/10.1016/j.scs.2022.104231
Liu, P. D., Zhu, B. Y., & Yang, M. Y. (2021). Has marine technology innovation promoted the high-quality development of the marine economy? – Evidence from coastal regions in China. Ocean & Coastal Management, 209, Article 105695. https://doi.org/10.1016/j.ocecoaman.2021.105695
Liu, P. D., Zhu, B. Y., Yang, M. Y., & Chu, X. (2022). ESG and financial performance: A qualitative comparative analysis in China’s new energy companies. Journal of Cleaner Production, 379, Article 134721. https://doi.org/10.1016/j.jclepro.2022.134721
Llopis-Albert, C., Palacios-Marqués, D., & Simón-Moya, V. (2021). Fuzzy set qualitative comparative analysis (fsQCA) applied to the adaptation of the automobile industry to meet the emission standards of climate change policies via the deployment of electric vehicles (EVs). Technological Forecasting and Social Change, 169, Article 120843. https://doi.org/10.1016/j.techfore.2021.120843
Makieła, K., Wojciechowski, L., & Wach, K. (2021). Effectiveness of FDI, technological gap and sectoral level productivity in the Visegrad Group. Technological and Economic Development of Economy, 27(1), 149–174. https://doi.org/10.3846/tede.2020.14017
Ministry of Natural Resources. (2020). China marine statistical yearbook. Beijing, China.
National Bureau of Statistics. (2020a). China regional economic statistical yearbook. Beijing, China.
National Bureau of Statistics. (2020b). China statistical yearbook. Beijing, China.
Pastor, J. T., & Lovell, C. K. (2005). A global Malmquist productivity index. Economics Letters, 88(2), 266–271. https://doi.org/10.1016/j.econlet.2005.02.013
Prokop, V., Hajek, P., & Stejskal, J. (2021). Configuration paths to efficient national innovation ecosystems. Technological Forecasting and Social Change, 168, Article 120787. https://doi.org/10.1016/j.techfore.2021.120787
Quah, D. T. (1997). Empirics for growth and distribution: Stratification, polarization, and convergence clubs. Journal of Economic Growth, 2(1), 27–59. https://doi.org/10.1023/A:1009781613339
Ragin, C. C. (2009). Redesigning social inquiry: Fuzzy sets and beyond. University of Chicago Press.
Ren, W. H., & Ji, J. Y. (2021). How do environmental regulation and technological innovation affect the sustainable development of marine economy: New evidence from China’s coastal provinces and cities. Marine Policy, 128, Article 104468. https://doi.org/10.1016/j.marpol.2021.104468
Ren, W. H., Wang, Q., & Ji, J. Y. (2018). Research on China’s marine economic growth pattern: An empirical analysis of China’s eleven coastal regions. Marine Policy, 87, 158–166. https://doi.org/10.1016/j.marpol.2017.10.021
Santos, A. M., Salvador, R., Dias, J. C. Q., & Soares, C. G. (2018). Assessment of port economic impacts on regional economy with a case study on the Port of Lisbon. Maritime Policy & Management, 45(5), 684–698. https://doi.org/10.1080/03088839.2018.1471536
Schneider, C. Q., & Wagemann, C. (2012). Set-theoretic methods for the social sciences: A guide to qualitative comparative analysis. Cambridge University Press.
Simar, L., & Wilson, P. W. (1998). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management Science, 44(1), 49–61. https://doi.org/10.1287/mnsc.44.1.49
Simar, L., & Wilson, P. W. (1999). Estimating and bootstrapping Malmquist indices. European Journal of Operational Research, 115(3), 459–471. https://doi.org/10.1016/S0377-2217(97)00450-5
Solís, D., Agar, J. J., & del Corral, J. (2015). IFQs and total factor productivity changes: The case of the Gulf of Mexico red snapper fishery. Marine Policy, 62, 347–357. https://doi.org/10.1016/j.marpol.2015.06.001
Su, C. W., Song, Y., & Umar, M. (2021). Financial aspects of marine economic growth: From the perspective of coastal provinces and regions in China. Ocean & Coastal Management, 204, Article 105550. https://doi.org/10.1016/j.ocecoaman.2021.105550
Tekic, Z., & Tekic, A. (2024). Complex patterns of ICTs’ effect on sustainable development at the national level: The triple bottom line perspective. Technological Forecasting and Social Change, 198, Article 122969. https://doi.org/10.1016/j.techfore.2023.122969
Wang, L. L., Su, M., Kong, H., & Ma, Y. X. (2021). The impact of marine technological innovation on the upgrade of China’s marine industrial structure. Ocean & Coastal Management, 211, Article 105792. https://doi.org/10.1016/j.ocecoaman.2021.105792
Wang, S. H., Lu, B. B., & Yin, K. D. (2021). Financial development, productivity, and high-quality development of the marine economy. Marine Policy, 130, Article 104553. https://doi.org/10.1016/j.marpol.2021.104553
Wei, X. Y., Hu, Q. G., Shen, W. T., & Ma, J. T. (2021). Influence of the evolution of marine industry structure on the green total factor productivity of marine economy. Water, 13(8), Article 1108. https://doi.org/10.3390/w13081108
Xia, F., & Xu, J. T. (2020). Green total factor productivity: A re-examination of quality of growth for provinces in China. China Economic Review, 62, Article 101454. https://doi.org/10.1016/j.chieco.2020.101454
Ye, F., Quan, Y. B., He, Y. X., & Lin, X. F. (2021). The impact of government preferences and environmental regulations on green development of China’s marine economy. Environmental Impact Assessment Review, 87, Article 106522. https://doi.org/10.1016/j.eiar.2020.106522
Zhang, Y. L. (2021). The regional disparity of influencing factors of technological innovation in China: evidence from high-tech industry. Technological and Economic Development of Economy, 27(4), 811–832. https://doi.org/10.3846/tede.2021.14828