Research on the Influence of Technological Innovation Capability of Enterprises on Financial Performance under Financial Intelligence
Keywords:
financial intelligence, digital transformation, enterprise technology innovation
Abstract
Based on the data of A-share listed companies in Shanghai and Shenzhen from 2017 to 2020, this paper empirically examines the impact of corporate technological innovation capability on financial performance under financial intelligence. It is found that technological innovation capability significantly improves financial performance, and performance increases by 7.07% for every 1% increase in R&D expenditure. Preceding financial performance forms a dynamic gain effect by driving innovation, and the intensity of the effect decreases to 2.97% after endogenous correction. Heterogeneity analysis shows that the effect of SOEs is weaker than that of non-SOEs (0.0611 vs 0.119), the effect is stronger in the East and West due to resource adaptation and policy tilt (0.102, 0.135), and the Northeast is not significant due to structural constraints. It is suggested that enterprises should strengthen R&D investment and data integration, optimize business-finance synergy and capital risk control based on intelligent technology, and formulate appropriate strategies based on regional and organizational differences. The conclusion provides theoretical and practical support for the transformation of corporate finance in the era of digital economy.
References
[1] Shanghai National Accounting Institute. (2021). 2021 survey report on the status of financial intelligence in Chinese enterprises.
[2] Yang, Y., Zhao, J., & Lv, X. (2021). Analysis of the current situation and development trend of intelligent finance application in Chinese enterprises: Example based on questionnaire data. Accounting Newsletter, 11, 140–146, 151.
[3] Liu, Q. (2021). Knowledge management and human-computer collaboration in smart finance. Finance and Accounting Monthly, 24, 15–19.
[4] Liu, Q., & Yang, Y. (2018). Discussion on the system architecture, realization path and application trend of intelligent finance. Management Accounting Research, 1(1), 84–90, 96.
[5] Lin, Y.-E., Chen, S.-L., Sun, W., Sui, J.-L., Yin, C., & Xu, D.-C. (2020). A study on the application of text analytics in financial reporting analysis. In Q. Liu, Z. Wu, et al. (Eds.), Blue book of intelligent finance research (First series) (pp. 280–307). Shanghai, China: Lixin Accounting Press.
[6] Larson, D., & Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36(5), 700–710. https://doi.org/10.1016/j.ijinfomgt.2016.04.013
[7] Ada, Ş., & Ghaffarzadeh, M. (2015). Decision making based on management information system and decision support system. Evropejskij Issledovatelʹ, 93(4), 260–270.
[8] Sun, R., Gao, L., Li, Y., Shao, L., Li, F., Zhong, X., & Wang, D. (2017). The development and breakthrough of management accounting in the era of smart finance—Based on the perspective of administrative institutions. Finance and Accounting, 24, 67–72.
[9] Zhang, C., Xiao, C., Zhu, W., Chen, X., & Li, Z. (2019). Financial intelligence visualization analysis and literature review. Finance and Accounting Monthly, 3, 24–32.
[10] Mansfield, E. (1988). The speed and cost of industrial innovation in Japan and the United States: External vs. internal technology. Management Science, 34(10), 1157–1168. https://doi.org/10.1287/mnsc.34.10.1157
[11] Zhu, Q., Zhao, W., Zhang, B., & Xie, S. (2022). The impact of independent innovation capability on firm performance—Based on the moderating role of technology-based directors and intellectual property protection. Friends of Accounting, 1, 82–89.
[12] Zhu, H., Zhou, L., & Xie, T. (2020). Research on the application of deep learning technology in financial analysis and forecasting. In Q. Liu, Z. Wu, et al. (Eds.), Intelligent finance research blue book (First series) (pp. 253–279). Shanghai, China: Lixin Accounting Press.
[13] Zhang, C. (2021). Empirical research on the impact of corporate technological innovation on financial performance (Doctoral dissertation, Nanjing University of Posts and Telecommunications, Nanjing, China).
[14] Yang, H., & Zhang, W. (2020). The impact of energy enterprises’ technological innovation capability on financial performance—A study on the threshold effect based on enterprise size. Technical Economy, 39(8), 1–9, 34.
[15] Shanghai National Accounting Institute. (2021). Top ten information technology outcomes affecting Chinese accounting practitioners.
[16] Liu, Q., & Yang, Y. (2019). China’s accounting informatization in 40 years of reform and opening up: Review and prospect. Accounting Research, 2, 26–34.
[17] Liu, Q. (2020). Exploration of the development system of intelligent finance and its core link. Finance and Accounting, 10, 11–14.
[18] Zhao, W., & Zhang, H. (2021). Enterprise size, R&D investment and innovation performance—Taking GEM listed companies as an example. Productivity Research, 11, 156–160.
[19] Yang, Y., Liu, Q., & Huang, H. (2020). Analysis of influential factors on corporate finance transformation and value creation—A multi-case study of financial shared service center based on the perspective of force field model. Accounting Research, 7, 23–37.
[20] Yang, Y., Liu, Q., & Huang, H. (2020). Research on corporate finance intelligent transformation: System architecture and path process. Friends of Accounting, 20, 145–150.
[21] Tong, Z., Li, P., Yang, L., & Wang, S. (2023). The impact of matching business model innovation and technological innovation on the performance of latecomer enterprises—An empirical study from annual report text analysis. Science and Technology Progress and Countermeasures, 40(1), 1–9.
[22] Yang, J., Zhang, Y., Han, W., & Ye, W. (2020). Can executive teams shape the competitive advantages of new firms through business model innovation?—An empirical study based on CPSED Ⅱ database. Management World, 36(7), 55–77, 88.
[23] Zhao, X. (2021). The impact of government science and technology investment on enterprise innovation output—An empirical analysis based on panel fixed-effects model. China Agricultural Accounting, 8, 22–23.
[24] Liu, Q., Shang, H., et al. (2020). Intelligent finance to create a new world of financial management in the digital era. Beijing, China: China Finance & Economy Press.
[25] Graham, J. R., Harvey, C. R., & Rajgopal, S. (2005). The economic implications of corporate financial reporting. Journal of Accounting and Economics, 40(1), 3–73. https://doi.org/10.1016/j.jacceco.2005.01.002
[26] Luo, K. (2006). An empirical study on the correlation between corporate R&D expenses and corporate capital structure and corporate growth (Doctoral dissertation, Chongqing University, Chongqing, China).
[27] Shiller, R. J. (2003). From efficient markets theory to behavioral finance. Journal of Economic Perspectives, 17(1), 83–104. https://doi.org/10.1257/089533003321164967
[28] Price, S. M., Doran, J. S., Peterson, D. R., & Bliss, B. A. (2012). Earnings conference calls and stock returns: The incremental informativeness of textual tone. Journal of Banking and Finance, 36(4), 992–1011. https://doi.org/10.1016/j.jbankfin.2011.10.021
[29] Ke, S., & Zhao, Y. (2014). Industrial structure, city size and urban productivity in China. Economic Research, 49(4), 76–88, 115.
[30] Chang, E. C., Lin, T.-C., & Ma, X. (2019). Does short-selling threat discipline managers in mergers and acquisitions decisions? Journal of Accounting and Economics, 68(1), Article 101223. https://doi.org/10.1016/j.jacceco.2019.04.002
[31] Deng, J. (2020). Deficiencies in the application of DuPont analysis in manufacturing companies and its improvement. China Foreign Investment, 22, 51–52.
[32] Wang, Z., Wang, Z., Qiong, M., & Wang, H. (2020). Risk analysis of enterprise management accounting based on big data association rule algorithm. Journal of Physics: Conference Series, 1631(1), Article 012087. https://doi.org/10.1088/1742-6596/1631/1/012087
[33] Li, X., Long, B., Li, X., & Xiao, S. (2021). Government subsidies, equity structure and financial performance of agribusiness enterprises: An empirical study based on a double fixed-effects model. Agricultural Technology and Economics, 12, 127–144.
[34] Zhao, T., & Sun, W. (2022). Government support, innovation environment and R&D of industrial enterprises. Economic Issues, 3, 62–73.
[35] Di, L., & Bu, D. (2021). The impact of heterogeneous majority shareholders on corporate innovation investment in the context of mixed ownership reform system: A comparative analysis based on state-owned enterprises and non-state-owned enterprises. Research and Development Management, 33(4), 152–168.
[36] Yao, L., Guarda, T., Lopes, I., & Rocha, Á. (2019). Financial accounting intelligence management of internet of things enterprises based on data mining algorithm. Journal of Intelligent & Fuzzy Systems, 37(5), 5917–5926. https://doi.org/10.3233/JIFS-179289
[37] Lu, T., & Zhu, Z. (2021). Does artificial intelligence reduce labor income shares—A test based on fixed effects model and panel quartile model. Journal of Shanxi University of Finance and Economics, 43(11), 29–41.
[38] Jaffe, A. B., Peterson, S. R., Portney, P. R., & Stavins, R. N. (1995). Environmental regulation and the competitiveness of U.S. manufacturing: What does the evidence tell us? Journal of Economic Literature, 33(1), 132–163.
[39] Jaffe, A. B., & Stavins, R. N. (1995). Dynamic incentives of environmental regulations: The effects of alternative policy instruments on technology diffusion. Journal of Environmental Economics and Management, 29(3), S43–S63. https://doi.org/10.1006/jeem.1995.1060
[40] Zhang, D.-M., Yang, J., & Liu, Z.-M. (2021). Empirical analysis of the impact of heterogeneous environmental policies on the technological innovation capability of enterprises—Based on two-way fixed effects model. Business Research, 4, 68–74.
[2] Yang, Y., Zhao, J., & Lv, X. (2021). Analysis of the current situation and development trend of intelligent finance application in Chinese enterprises: Example based on questionnaire data. Accounting Newsletter, 11, 140–146, 151.
[3] Liu, Q. (2021). Knowledge management and human-computer collaboration in smart finance. Finance and Accounting Monthly, 24, 15–19.
[4] Liu, Q., & Yang, Y. (2018). Discussion on the system architecture, realization path and application trend of intelligent finance. Management Accounting Research, 1(1), 84–90, 96.
[5] Lin, Y.-E., Chen, S.-L., Sun, W., Sui, J.-L., Yin, C., & Xu, D.-C. (2020). A study on the application of text analytics in financial reporting analysis. In Q. Liu, Z. Wu, et al. (Eds.), Blue book of intelligent finance research (First series) (pp. 280–307). Shanghai, China: Lixin Accounting Press.
[6] Larson, D., & Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36(5), 700–710. https://doi.org/10.1016/j.ijinfomgt.2016.04.013
[7] Ada, Ş., & Ghaffarzadeh, M. (2015). Decision making based on management information system and decision support system. Evropejskij Issledovatelʹ, 93(4), 260–270.
[8] Sun, R., Gao, L., Li, Y., Shao, L., Li, F., Zhong, X., & Wang, D. (2017). The development and breakthrough of management accounting in the era of smart finance—Based on the perspective of administrative institutions. Finance and Accounting, 24, 67–72.
[9] Zhang, C., Xiao, C., Zhu, W., Chen, X., & Li, Z. (2019). Financial intelligence visualization analysis and literature review. Finance and Accounting Monthly, 3, 24–32.
[10] Mansfield, E. (1988). The speed and cost of industrial innovation in Japan and the United States: External vs. internal technology. Management Science, 34(10), 1157–1168. https://doi.org/10.1287/mnsc.34.10.1157
[11] Zhu, Q., Zhao, W., Zhang, B., & Xie, S. (2022). The impact of independent innovation capability on firm performance—Based on the moderating role of technology-based directors and intellectual property protection. Friends of Accounting, 1, 82–89.
[12] Zhu, H., Zhou, L., & Xie, T. (2020). Research on the application of deep learning technology in financial analysis and forecasting. In Q. Liu, Z. Wu, et al. (Eds.), Intelligent finance research blue book (First series) (pp. 253–279). Shanghai, China: Lixin Accounting Press.
[13] Zhang, C. (2021). Empirical research on the impact of corporate technological innovation on financial performance (Doctoral dissertation, Nanjing University of Posts and Telecommunications, Nanjing, China).
[14] Yang, H., & Zhang, W. (2020). The impact of energy enterprises’ technological innovation capability on financial performance—A study on the threshold effect based on enterprise size. Technical Economy, 39(8), 1–9, 34.
[15] Shanghai National Accounting Institute. (2021). Top ten information technology outcomes affecting Chinese accounting practitioners.
[16] Liu, Q., & Yang, Y. (2019). China’s accounting informatization in 40 years of reform and opening up: Review and prospect. Accounting Research, 2, 26–34.
[17] Liu, Q. (2020). Exploration of the development system of intelligent finance and its core link. Finance and Accounting, 10, 11–14.
[18] Zhao, W., & Zhang, H. (2021). Enterprise size, R&D investment and innovation performance—Taking GEM listed companies as an example. Productivity Research, 11, 156–160.
[19] Yang, Y., Liu, Q., & Huang, H. (2020). Analysis of influential factors on corporate finance transformation and value creation—A multi-case study of financial shared service center based on the perspective of force field model. Accounting Research, 7, 23–37.
[20] Yang, Y., Liu, Q., & Huang, H. (2020). Research on corporate finance intelligent transformation: System architecture and path process. Friends of Accounting, 20, 145–150.
[21] Tong, Z., Li, P., Yang, L., & Wang, S. (2023). The impact of matching business model innovation and technological innovation on the performance of latecomer enterprises—An empirical study from annual report text analysis. Science and Technology Progress and Countermeasures, 40(1), 1–9.
[22] Yang, J., Zhang, Y., Han, W., & Ye, W. (2020). Can executive teams shape the competitive advantages of new firms through business model innovation?—An empirical study based on CPSED Ⅱ database. Management World, 36(7), 55–77, 88.
[23] Zhao, X. (2021). The impact of government science and technology investment on enterprise innovation output—An empirical analysis based on panel fixed-effects model. China Agricultural Accounting, 8, 22–23.
[24] Liu, Q., Shang, H., et al. (2020). Intelligent finance to create a new world of financial management in the digital era. Beijing, China: China Finance & Economy Press.
[25] Graham, J. R., Harvey, C. R., & Rajgopal, S. (2005). The economic implications of corporate financial reporting. Journal of Accounting and Economics, 40(1), 3–73. https://doi.org/10.1016/j.jacceco.2005.01.002
[26] Luo, K. (2006). An empirical study on the correlation between corporate R&D expenses and corporate capital structure and corporate growth (Doctoral dissertation, Chongqing University, Chongqing, China).
[27] Shiller, R. J. (2003). From efficient markets theory to behavioral finance. Journal of Economic Perspectives, 17(1), 83–104. https://doi.org/10.1257/089533003321164967
[28] Price, S. M., Doran, J. S., Peterson, D. R., & Bliss, B. A. (2012). Earnings conference calls and stock returns: The incremental informativeness of textual tone. Journal of Banking and Finance, 36(4), 992–1011. https://doi.org/10.1016/j.jbankfin.2011.10.021
[29] Ke, S., & Zhao, Y. (2014). Industrial structure, city size and urban productivity in China. Economic Research, 49(4), 76–88, 115.
[30] Chang, E. C., Lin, T.-C., & Ma, X. (2019). Does short-selling threat discipline managers in mergers and acquisitions decisions? Journal of Accounting and Economics, 68(1), Article 101223. https://doi.org/10.1016/j.jacceco.2019.04.002
[31] Deng, J. (2020). Deficiencies in the application of DuPont analysis in manufacturing companies and its improvement. China Foreign Investment, 22, 51–52.
[32] Wang, Z., Wang, Z., Qiong, M., & Wang, H. (2020). Risk analysis of enterprise management accounting based on big data association rule algorithm. Journal of Physics: Conference Series, 1631(1), Article 012087. https://doi.org/10.1088/1742-6596/1631/1/012087
[33] Li, X., Long, B., Li, X., & Xiao, S. (2021). Government subsidies, equity structure and financial performance of agribusiness enterprises: An empirical study based on a double fixed-effects model. Agricultural Technology and Economics, 12, 127–144.
[34] Zhao, T., & Sun, W. (2022). Government support, innovation environment and R&D of industrial enterprises. Economic Issues, 3, 62–73.
[35] Di, L., & Bu, D. (2021). The impact of heterogeneous majority shareholders on corporate innovation investment in the context of mixed ownership reform system: A comparative analysis based on state-owned enterprises and non-state-owned enterprises. Research and Development Management, 33(4), 152–168.
[36] Yao, L., Guarda, T., Lopes, I., & Rocha, Á. (2019). Financial accounting intelligence management of internet of things enterprises based on data mining algorithm. Journal of Intelligent & Fuzzy Systems, 37(5), 5917–5926. https://doi.org/10.3233/JIFS-179289
[37] Lu, T., & Zhu, Z. (2021). Does artificial intelligence reduce labor income shares—A test based on fixed effects model and panel quartile model. Journal of Shanxi University of Finance and Economics, 43(11), 29–41.
[38] Jaffe, A. B., Peterson, S. R., Portney, P. R., & Stavins, R. N. (1995). Environmental regulation and the competitiveness of U.S. manufacturing: What does the evidence tell us? Journal of Economic Literature, 33(1), 132–163.
[39] Jaffe, A. B., & Stavins, R. N. (1995). Dynamic incentives of environmental regulations: The effects of alternative policy instruments on technology diffusion. Journal of Environmental Economics and Management, 29(3), S43–S63. https://doi.org/10.1006/jeem.1995.1060
[40] Zhang, D.-M., Yang, J., & Liu, Z.-M. (2021). Empirical analysis of the impact of heterogeneous environmental policies on the technological innovation capability of enterprises—Based on two-way fixed effects model. Business Research, 4, 68–74.
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2025-05-23
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