Evolution of high-quality economic development: A bibliometric analysis
DOI:
https://doi.org/10.24191/jeeir.v13i2.4471Keywords:
High-quality economic development (HQED), VOSviewer, Bibliometric analysis, Keyword co-occurence, Research clustersAbstract
China's current development focuses on high-quality economic development (HQED), which aims to enhance the efficiency and quality
of growth while simultaneously advancing social, economic, and environmental progress. This approach not only improves the quality of life but also increases national wealth. Despite its significance, HQED has not garnered much global attention. To address this gap, this study employs bibliometric methods and VOS viewer software to analyse the evolution and primary research hotspots of HQED. The findings reveal that the evolution of HQED research can be divided into two distinct periods: (i) from 2018 to 2020, when HQED was still in its infancy, and (ii) from 2021 to 2023, which saw a rapid increase in the number of HQED publications. China has emerged as the leading contributor to HQED research. The journal "Sustainability" serves as the main outlet, while the Chinese Academy of Sciences is the most active institution in HQED studies. The most cited author is Zhang Wei. The research is organised into several key clusters: Cluster 1 focuses on research methods used in HQED studies, while Clusters 2 and 3 introduce more green elements and onsiderations of environmental quality. Cluster 4 emphasises the importance of innovation and financial development. Clusters 5 and 6 address topics related to the digital economy, digital finance, and digital transformation, whereas Cluster 7 highlights China's focus on high-quality development. broaden the scope of HQED to include areas such as green innovation, digital economies, and human capital.
References
Amanov, F., & Pradeep, A. (2023). The significance of artificial intelligence in the second scientific revolution - A review. In 15th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2023 – Proceedings (pp.1-5). https://doi.org/10.1109/ECAI58194.2023.10194056
Borokhovich, K. A., Bricker, R. J., Brunarski, K. R., & Simkins, B. J. (1995). Finance research productivity and influence. The Journal of Finance, 50(5), 1691-1717. https://doi.org/10.1111/j.1540-6261.1995.tb05193.x
Cao, C., Xiao, G., Xu, S., & Zhou, X. (2022). The impact of population aging on high-quality economic development-based on the perspective of fiscal sustainability. Finance Theory and Practice, 43, 114-122. https://doi.org/10.16339/j.cnki.hdxbcjb.2022.01.015
Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359-377. https://doi.org/10.1002/asi.20317
Chen, Y., Chen, C., Liu, Z., Hu, Z., & Wang, X. (2015). The methodology function of Cite Space mapping knowledge domains. Studies in Science of Science, 33(2), 242-253. https://doi.org/10.16192/j.cnki.1003-2053.2015.02.009
Du, L., Tian, M., Cheng, J., Chen, W., & Zhao, Z. (2022). Environmental regulation and green energy efficiency: An analysis of spatial Durbin model from 30 provinces in China. Environmental Science and Pollution Research, 29(44), 67046-67062. https://doi.org/10.1007/s11356-022-20551-0
Duvvuru, A., Kamarthi, S., & Sultornsanee, S. (2012). Undercovering research trends: Network analysis of keywords in scholarly articles. In JCSSE 2012 - 9th International Joint Conference on Computer Science and Software Engineering (pp.265-270). https://doi.org/10.1109/JCSSE.2012.6261963
Fengze, Y. (2022). A theoretical and empirical studies on the high-quality development of China’s economy. International Journal of English Literature and Social Sciences, 7(6), 282-298. https://doi.org/10.22161/ijels.76.41
Full text of Xi Jinping’s report at 19th CPC National Congress. (2017, October 18). Xinhua News Agency. http://www.xinhuanet.com//english/special/2017-11/03/c_136725942.htm
Gao, J., Wu, D., Xiao, Q., Randhawa, A. A., Liu, Q., & Zhang, T. (2023). Green finance, environmental pollution and high-quality economic development—A study based on China’s provincial panel data. Environmental Science and Pollution Research, 30(11), 31954-31976. https://doi.org/10.1007/s11356-022-24428-0
Ge, H., & Wu, F. (2022). Digital economy enabling high quality economic development: Theoretical mechanism and empirical evidence. Frontiers of Economics in China, 17(4), 643-668. https://doi.org/10.3868/s060-015-022-0027-7
Ghosh, A. (2024). Global warming and the future generation. International Journal of Innovative Science and Research Technology, 9(3), 290-292. https://doi.org/10.38124/ijisrt/ijisrt24mar191
Guo, Y. M., Huang, Z. L., Guo, J., Guo, X. R., Li, H., Liu, M. Y., Ezzeddine, S., & Nkeli, M. J. (2021). A bibliometric analysis and visualization of blockchain. Future Generation Computer Systems, 116, 316-332. https://doi.org/10.1016/j.future.2020.10.023
Hamidi, A., & Ramavandi, B. (2020). Evaluation and scientometric analysis of researches on air pollution in developing countries from 1952 to 2018. Air Quality, Atmosphere and Health, 13(7), 797-806. https://doi.org/10.1007/s11869-020-00836-4
Ito, A. (2022). Digital China: Policy initiatives, progress, and challenges. In X. Ma, X., & C. Tang (Eds.), Growth mechanisms and sustainable development of the Chinese economy (pp. 97-123). Palgrave Macmillan. https://doi.org/10.1007/978-981-19-3858-0_4
Jiang, C., & Si, H. (2023). Research on the impact of population aging and technological innovation on high-quality economic development - An empirical analysis based on provincial panel data. Journal of Jiangsu Institute of Technology, 29, 38-51. https://doi.org/10.19831/j.cnki.2095-7394.2023.05.009
Kamran, M., Khan, H. U., Nisar, W., Farooq, M., & Rehman, S. U. (2020). Blockchain and internet of things: A bibliometric study. Computers and Electrical Engineering, 81, 106525. https://doi.org/10.1016/j.compeleceng.2019.106525
Li, C., Chen, Z., Wu, Y., Zuo, X., Jin, H., Xu, Y., Zeng, B., Zhao, G., & Wan, Y. (2022). Impact of green finance on China’s high-quality economic development, environmental pollution, and energy consumption. Frontiers in Environmental Science, 10, 1032586. https://doi.org/10.3389/fenvs.2022.1032586
Li, C., Wan, J., Xu, Z., & Lin, T. (2021). Impacts of green innovation, institutional constraints and their interactions on high-quality economic development across China. Sustainability, 13(9), 5277. https://doi.org/10.3390/su13095277
Li, J., Zhang, G., Ned, J. P., & Sui, L. (2023). How does digital finance affect green technology innovation in the polluting industry? Based on the serial two-mediator model of financing constraints and research and development (R&D) investments. Environmental Science and Pollution Research, 30(29), 74141-74152. https://doi.org/10.1007/s11356-023-27593-y
Li, W., Lin, X., Wang, H., & Wang, S. (2022). High-quality economic development, green credit and carbon emissions. Frontiers in Environmental Science, 10, 992518. https://doi.org/10.3389/FENVS.2022.992518/BIBTEX
Liu, L., & Li, X. (2024). A study on the impact of green finance on the high-quality economic development of Beijing–Tianjin–Hebei region. Sustainability, 16(6), 2433. https://doi.org/10.3390/su16062433
Liu, Z., Lai, B., Wu, S., Liu, X., Liu, Q., & Ge, K. (2022). Growth targets management, regional competition and urban land green use efficiency according to evidence from China. International Journal of Environmental Research and Public Health, 19(10), 6250. https://doi.org/10.3390/ijerph19106250
Lozano, S., Calzada-Infante, L., Adenso-Díaz, B., & García, S. (2019). Complex network analysis of keywords co-occurrence in the recent efficiency analysis literature. Scientometrics, 120(2), 609-629. https://doi.org/10.1007/s11192-019-03132-w
Luo, C., Wei, D., Su, W., & Lu, J. (2023). Association between regional digitalization and high-quality economic development. Sustainability, 15(3), 1909. https://doi.org/10.3390/su15031909
Luo, G., Guo, J., Yang, F., & Wang, C. (2023). Environmental regulation, green innovation and high-quality development of enterprise: Evidence from China. Journal of Cleaner Production, 418, 138112. https://doi.org/10.1016/j.jclepro.2023.138112
Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106(1), 213-228. https://doi.org/10.1007/s11192-015-1765-5
Narong, D. K., & Hallinger, P. (2023). A keyword co-occurrence analysis of research on service learning: Conceptual foci and emerging research trends. Education Sciences, 13(4), 339. https://doi.org/10.3390/educsci13040339
Nightingale, J. M., & Marshall, G. (2013). Citation analysis as a measure of article quality, journal influence and individual researcher performance. Nurse Education in Practice, 13(5), 429-436. https://doi.org/10.1016/j.nepr.2013.02.005
Ozek, B., Lu, Z., Pouromran, F., Radhakrishnan, S., & Kamarthi, S. (2023). Analysis of pain research literature through keyword Co-occurrence networks. PLOS Digital Health, 2(9), e0000331. https://doi.org/10.1371/journal.pdig.0000331
Pang, J., Jiao, F., & Zhang, Y. (2022). An analysis of the impact of the digital economy on high-quality economic development in China - A study based on the effects of supply and demand. Sustainability, 14(24), 16991. https://doi.org/10.3390/su142416991
Parthasarathy, G., Tomar, D.C. (2015). Trends in citation analysis. In L. Jain, S. Patnaik, & N. Ichalkaranje (Eds.), Intelligent computing, communication and devices. Advances in intelligent systems and computing (Vol. 308, pp. 813-821). Springer. https://doi.org/10.1007/978-81-322-2012-1_88
Perianes-Rodriguez, A., Waltman, L., & van Eck, N. J. (2016). Constructing bibliometric networks: A comparison between full and fractional counting. Journal of Informetrics, 10(4), 1178-1195. https://doi.org/10.1016/j.joi.2016.10.006
Sha, Y. (2019). Scientifically grasp the connotation relationship between population development and high-quality economic development. Population and Social, 35, 23-29. https://doi.org/10.14132/j.2095-7963.2019.01.004
Stremersch, S., Verniers, I., & Verhoef, P. C. (2007). The quest for citations: Drivers of article impact. In Journal of Marketing, 71(3), 171-193. https://doi.org/10.1509/jmkg.71.3.171
Tan, Y. L., Yiew, T. H., Habibullah, M. S., Chen, J. E., Mat Kamal, S. N. I., & Saud, N. A. (2023). Research trends in biodiversity loss: A bibliometric analysis. Environmental Science and Pollution Research, 30(2), 2754-2770. https://doi.org/10.1007/s11356-022-22211-9
The Central Committee of the Communist Party of China issues the 13th five-year plan proposal. (2015, November 3). Xinhua News Agency. https://www.gov.cn/xinwen/2015-11/03/content_5004118.htm
Trivedi, K. K. (2021). A study on global warming- A threat to biodiversity and universal health. International Journal of Advanced Research in Science, Communication and Technology, 6(2), 1525-1528. https://doi.org/10.48175/ijarsct-1585
Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
Van Eck, N. J., & Waltman, L. (2017). Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics, 111(2), 1053-1070. https://doi.org/10.1007/s11192-017-2300-7
van Nunen, K., Li, J., Reniers, G., & Ponnet, K. (2018). Bibliometric analysis of safety culture research. Safety Science, 108, 248-258. https://doi.org/10.1016/j.ssci.2017.08.011
Wang, R., & Wang, F. (2022). Exploring the role of green finance and energy development towards high-quality economic development: Application of spatial durbin model and intermediary effect model. International Journal of Environmental Research and Public Health, 19(14), 8875. https://doi.org/10.3390/ijerph19148875
Wang, S., Xiao, S., Lu, X., & Zhang, Q. (2023). North–south regional differential decomposition and spatiotemporal dynamic evolution of China’s industrial green total factor productivity. Environmental Science and Pollution Research, 30(13), 37706-37725. https://doi.org/10.1007/s11356-022-24697-9
Xie, T., Zhang, Y., & Song, X. (2024). Research on the spatiotemporal evolution and influencing factors of common prosperity in China. Environment, Development and Sustainability, 26(1), 1851-1877. https://doi.org/10.1007/s10668-022-02788-4
Xu, S., Chen, Y., Lyulyov, O., & Pimonenko, T. (2023). Green technology innovation and high-quality economic development: Spatial spillover effect. Prague Economic Papers, 32(3), 292-319. https://doi.org/10.18267/j.pep.833
Yadav, J., Shukla, S., Sharma, K., Soni, N., Agarwal, S., & Pathak, P. C. (2022). Frontiers in artificial intelligence and applications. In Proceedings - 2022 3rd International Conference on Computation, Automation and Knowledge Management, ICCAKM 2022 (pp.1-6). https://doi.org/10.1109/ICCAKM54721.2022.9990098
Yan, E., & Ding, Y. (2012). Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other. Journal of the American Society for Information Science and Technology, 63(7), 1313-1326. https://doi.org/10.1002/asi.22680
Yang, Y., Su, X., & Yao, S. (2021). Nexus between green finance, fintech, and high-quality economic development: Empirical evidence from China. Resources Policy, 74, 102445. https://doi.org/10.1016/j.resourpol.2021.102445
You, T., Yoon, J., Kwon, O. H., & Jung, W. S. (2021). Tracing the evolution of physics with a keyword co-occurrence network. Journal of the Korean Physical Society, 78(3), 236-243. https://doi.org/10.1007/s40042-020-00051-5
Yu, D., Yang, L., & Xu, Y. (2022). The impact of the digital economy on high-quality development: An analysis based on the national big data comprehensive test area. Sustainability, 14(21), 14468. https://doi.org/10.3390/su142114468
Yu, Y. (2023). Digital finance enables green innovation in new energy companies. BCP Business & Management, 38, 220-230. https://doi.org/10.54691/bcpbm.v38i.3691
Yuan, B., & Li, C. (2021). Research on innovation-driven high-quality economic development in China-Moderating effect of economic policy uncertainty. Macro Quality Research, 9, 45-57. https://doi.org/10.13948/j.cnki.hgzlyj.2021.01.004
Zhan, J., Liu, S., Su, H., & Zhang, F. (2022). Solutions to high-quality development: Theories and practices in ecological aspects. Frontiers in Environmental Science, 10, 1028676. https://doi.org/10.3389/fenvs.2022.1028676
Zhang, J., Yang, X., Hu, X., & Li, T. (2019). Author cooperation network in biology and chemistry literature during 2014-2018: Construction and structural characteristics. Information, 10(7), 236. https://doi.org/10.3390/info10070236
Zhang, W., Li, G., & Guo, F. (2022). Does carbon emissions trading promote green technology innovation in China? Applied Energy, 315, 119012. https://doi.org/10.1016/j.apenergy.2022.119012
Zhao, X., Long, L., & Yin, S. (2023). Regional common prosperity level and its spatial relationship with carbon emission intensity in China. Scientific Reports, 13(1), 17035. https://doi.org/10.1038/s41598-023-44408-9
Zhao, X., Nakonieczny, J., Jabeen, F., Shahzad, U., & Jia, W. (2022). Does green innovation induce green total factor productivity? Novel findings from Chinese city level data. Technological Forecasting and Social Change, 185, 122021. https://doi.org/10.1016/j.techfore.2022.122021
Zupic, I., & Cater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429-472. https://doi.org/10.1177/1094428114562629
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