Exploring the impact of digital transformation on productivity: the role of artificial intelligence technology, green technology, and energy technology
Abstract
The aim of this paper is to explore the technological innovation mechanism by which digital transformation (DT) influences total factor productivity (TFP). We take the Chinese listed firms from 2007 to 2020 as research samples, and con- tribute to the above goals based on fixed-effect models, instrumental variables, mediation effect, and moderating effect models. It has been found that (1) while DT contributes positively to productivity, the enhancement of TFP in current DT is primarily attributed to artificial intelligence (AI) technology rather than other techno- logical innovation. (2) From an innovation-directed perspective, the impact of DT on TFP may be offset by other forms of technological innovation, such as green and energy technology. Specifically, the non-AI direction of technological innovation may not align with the productivity implications of DT. (3) Intellectual property protection impedes the impact of DT on productivity and constrains the deployment of AI technology. Conversely, business strategic radicalism and corporate intangible asset have yielded favorable outcomes. This study not only verifies that the technological innovation channel of DT for enhancing TFP mainly stems from AI technology, but also implies that the current DT might exert a negative effect on other technologies.
First published online 12 February 2025
Keyword : digital transformation, artificial intelligence technology, green technology, energy technology, total factor productivity
How to Cite
Qu, F., Tang, Q., Li, C.-M., & Liu, J. (2025). Exploring the impact of digital transformation on productivity: the role of artificial intelligence technology, green technology, and energy technology . Technological and Economic Development of Economy, 1-32. https://doi.org/10.3846/tede.2025.23009
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Acemoglu, D., Aghion, P., Bursztyn, L., & Hemous, D. (2012). The environment and directed technical change. American Economic Review, 102(1), 131–166. https://doi.org/10.1257/aer.102.1.131
Ackerberg, D. A., Caves, K., & Frazer, G. (2015). Identification properties of recent production function estimators. Econometrica, 83(6), 2411–2451. https://doi.org/10.3982/ECTA13408
Aghion, P., Dechezleprêtre, A., Hémous, D., Martin, R., & Van Reenen, J. (2016). Carbon taxes, path dependency, and directed technical change: Evidence from the auto industry. Journal of Political Economy, 124(1), 1–51. https://doi.org/10.1086/684581
Ahmed, E. M., & Elfaki, K. E. (2024). Green technological progress implications on long-run sustainable economic growth. Journal of the Knowledge Economy, 15(2), 6860–6877. https://doi.org/10.1007/s13132-023-01268-y
Ahmed, E. M., & Kialashaki, R. (2021). FDI inflows spillover effect implications on the Asian-Pacific labour productivity. International Journal of Finance & Economics, 28(1), 575–588. https://doi.org/10.1002/ijfe.2437
Ayoko, O. B. (2021). Digital transformation, robotics, artificial intelligence, and innovation. Journal of Management and Organization, 27(5), 831–835. https://doi.org/10.1017/jmo.2021.64
Baruffaldi, S., Van Beuzekom, B., Dernis, H., Harhoff, D., Rao, N., Rosenfeld, D., & Squicciarini, M. (2020). Identifying and measuring developments in artificial intelligence: Making the impossible possible (OECD Science, Technology and Industry Working Paper No. 2020/05). OECD. https://doi.org/10.1787/5f65ff7e-en
Bentley-Goode, K. A., Omer, T. C., & Twedt, B. J. (2017). Does business strategy impact a firm’s information environment? Journal of Accounting, Auditing & Finance, 34(4), 563–587. https://doi.org/10.1177/0148558X17726893
Brynjolfsson, E., & Collis, A. (2019). How should we measure the digital economy? Harvard Business Review, 97(6), 140–148.
Buck, C., Clarke, J., Torres de Oliveira, R., Desouza, K. C., & Maroufkhani, P. (2023). Digital transformation in asset-intensive organisations: The light and the dark side. Journal of Innovation & Knowledge, 8(2), Article 100335. https://doi.org/10.1016/j.jik.2023.100335
Chatzistamoulou, N. (2023). Is digital transformation the Deus ex Machina towards sustainability transition of the European SMEs? Ecological Economics, 206(12), Article 107739. https://doi.org/10.1016/j.ecolecon.2023.107739
Cheng, Y., Zhou, X., & Li, Y. (2023). The effect of digital transformation on real economy enterprises’ total factor productivity. International Review of Economics and Finance, 85(1), 488–501. https://doi.org/10.1016/j.iref.2023.02.007
China Stock Market & Accounting Research Database (n.d.). Retrieved August 1, 2023, from https://data.csmar.com/
China Securities Regulatory Commission (n.d.). Retrieved December 31, 2023, from http://www.csrc.gov.cn/csrc/c100103/c1452025/content.shtml
China National Intellectual Property Administration. (n.d.-a). Open data [Database]. Retrieved August 1, 2023, from https://pss-system.cponline.cnipa.gov.cn/conventionalSearch
China National Intellectual Property Administration. (n.d.-b). Open data [Website]. Retrieved March 1, 2024, from https://www.cnipa.gov.cn/art/2024/3/1/art_93_190525.html
Du, K., & Li, J. (2019). Towards a green world: How do green technology innovations affect total-factor carbon productivity. Energy Policy, 131(4), 240–250. https://doi.org/10.1016/j.enpol.2019.04.033
Du, K., Cheng, Y., & Yao, X. (2021). Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities. Energy Economics, 98, Article 105247. https://doi.org/10.1016/j.eneco.2021.105247
Du, J., Shen, Z., Song, M., & Zhang, L. (2023). Nexus between digital transformation and energy technology innovation: An empirical test of A-share listed enterprises. Energy Economics, 120(2), Article 106572. https://doi.org/10.1016/j.eneco.2023.106572
Du, G., Zhou, C., & Zhang, M. (2024). Does digital transformation promote local-neighborhood green technology innovation? – Based on the panel data of Chinese a-share listed companies from 2011 to 2021. Journal of Cleaner Production, 466, Article 142809. https://doi.org/10.1016/j.jclepro.2024.142809
Fang, X., & Liu, M. (2024). How does the digital transformation drive digital technology innovation of enterprises? Evidence from enterprise’s digital patents. Technological Forecasting and Social Change, 204, Article 123428. https://doi.org/10.1016/j.techfore.2024.123428
Gaglio, C., Kraemer-Mbula, E., & Lorenz, E. (2022). The effects of digital transformation on innovation and productivity: Firm-level evidence of South African manufacturing micro and small enterprises. Technological Forecasting and Social Change, 182(3), Article 121785. https://doi.org/10.1016/j.techfore.2022.121785
Gong, C., & Ribiere, V. (2021). Developing a unified definition of digital transformation. Technovation, 102(12), Article 102217. https://doi.org/10.1016/j.technovation.2020.102217
Gregory, R. W., Wagner, H. T., Tumbas, S., & Drechsler, K. (2019, December 15–18). At the crossroads between digital innovation and digital transformation. In Proceedings of the 40th International Conference on Information Systems (ICIS). München, Germany.
Guo, X., Li, M., Wang, Y., & Mardani, A. (2023). Does digital transformation improve the firm’s performance? From the perspective of digitalization paradox and managerial myopia. Journal of Business Research, 163, Article 113868. https://doi.org/10.1016/j.jbusres.2023.113868
Guo, S., & Zhang, Z. X. (2023). Green credit policy and total factor productivity: Evidence from Chinese listed companies. Energy Economics, 128, Article 107115. https://doi.org/10.1016/j.eneco.2023.107115
Hao, Y., Ba, N., Ren, S., & Wu, H. (2021). How does international technology spillover affect China’s carbon emissions? A new perspective through intellectual property protection. Sustainable Production and Consumption, 25, 577–590. https://doi.org/10.1016/j.spc.2020.12.008
Hassler, J., Krusell, P., & Olovsson, C. (2021). Directed technical change as a response to natural resource scarcity. Journal of Political Economy, 129(11), 3039–3072. https://doi.org/10.1086/715849
Huang, J., Cai, X., Huang, S., Tian, S., & Lei, H. (2019). Technological factors and total factor productivity in China: Evidence based on a panel threshold model. China Economic Review, 54(11), 271–285. https://doi.org/10.1016/j.chieco.2018.12.001
Jiang, W. (2017). Have instrumental variables brought US closer to the truth. Review of Corporate Finance Studies, 6(2), 127–140. https://doi.org/10.1093/rcfs/cfx015
Karafillis, C., & Papanagiotou, E. (2011). Innovation and total factor productivity in organic farming. Applied Economics, 43(23), 3075–3087. https://doi.org/10.1080/00036840903427240
Kraus, S., Jones, P., Kailer, N., Weinmann, A., Chaparro-Banegas, N., & Roig-Tierno, N. (2021). Digital transformation: An overview of the current state of the art of research. SAGE Open, 11(3), Article 21582440211047576. https://doi.org/10.1177/21582440211047576
Levinsohn, J., & Petrin, A. (2003). Estimating production functions using inputs to control for unobservables. Review of Economic Studies, 70(2), 317–341. https://doi.org/10.1111/1467-937X.00246
Lei, Z., & Wang, D. (2023). Digital transformation and total factor productivity: Empirical evidence from China. PLoS ONE, 18(10), Article e0292972. https://doi.org/10.1371/journal.pone.0292972
Li, L. (2022). Digital transformation and sustainable performance: The moderating role of market turbulence. Industrial Marketing Management, 104, 28–37. https://doi.org/10.1016/j.indmarman.2022.04.007
Li, X., Wang, X., & Xu, W. (2022). The information technology revolution and structural labor change: Evidence from China. Economic Modelling, 115, Article 105956. https://doi.org/10.1016/j.econmod.2022.105956
Li, J., Lian, G., & Xu, A. (2023a). How do ESG affect the spillover of green innovation among peer firms? Mechanism discussion and performance study. Journal of Business Research, 158, Article 113648. https://doi.org/10.1016/j.jbusres.2023.113648
Li, S., Gao, L., Han, C., Gupta, B., Alhalabi, W., & Almakdi, S. (2023b). Exploring the effect of digital transformation on firms’ innovation performance. Journal of Innovation & Knowledge, 8(1), Article 100317. https://doi.org/10.1016/j.jik.2023.100317
Lipsey, R. G., & Carlaw, K. I. (2004). Total factor productivity and the measurement of technological change. Canadian Journal of Economics, 37(4), 1118–1150. https://doi.org/10.1111/j.0008-4085.2004.00263.x
Malik, H., Chaudhary, G., & Srivastava, S. (2022). Digital transformation through advances in artificial intelligence and machine learning. Journal of Intelligent and Fuzzy Systems, 42(2), 615–622. https://doi.org/10.3233/JIFS-189787
Maroufkhani, P., Desouza, K. C., Perrons, R. K., & Iranmanesh, M. (2022). Digital transformation in the resource and energy sectors: A systematic review. Resources Policy, 76, Article 102622. https://doi.org/10.1016/j.resourpol.2022.102622
McElheran, K. S., & Forman, C. (2019). Firm organization in the digital age: IT use and vertical transactions in U.S. manufacturing. SSRN. https://doi.org/10.2139/ssrn.3396116
Nagaoka, S., Motohashi, K., & Goto, A. (2010). Chapter 25 – Patent statistics as an innovation indicator. In B. H. Hall & N. Rosenberg (Eds.), Handbook of the economics of innovation (Vol. 2, pp. 1083–1127). Elsevier. https://doi.org/10.1016/S0169-7218(10)02009-5
Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy, 48(8), Article 103773. https://doi.org/10.1016/j.respol.2019.03.018
Nucci, F., Puccioni, C., & Ricchi, O. (2023). Digital technologies and productivity: A firm-level investigation. Economic Modelling, 128, Article 106524. https://doi.org/10.1016/j.econmod.2023.106524
Olley, G. S., & Pakes, A. (1996). The dynamanics of productivity in the telecommunications equipment industry. Econometrica, 64(6), 1263–1297. https://doi.org/10.2307/2171831
Pan, W., Xie, T., Wang, Z., & Ma, L. (2022). Digital economy: An innovation driver for total factor productivity. Journal of Business Research, 139, 303–311. https://doi.org/10.1016/j.jbusres.2021.09.061
Parteka, A., & Kordalska, A. (2023). Artificial intelligence and productivity: Global evidence from AI patent and bibliometric data. Technovation, 125, Article 102764. https://doi.org/10.1016/j.technovation.2023.102764
Peng, Y., & Tao, C. (2022). Can digital transformation promote enterprise performance? From the perspective of public policy and innovation. Journal of Innovation & Knowledge, 7(3), Article 100198. https://doi.org/10.1016/j.jik.2022.100198
Picazo Rodríguez, B., Verdú-Jover, A. J., Estrada-Cruz, M., & Gomez-Gras, J. M. (2023). Does digital transformation increase firms’ productivity perception? The role of technostress and work engagement. European Journal of Management and Business Economics, 33(2), 137–156. https://doi.org/10.1108/EJMBE-06-2022-0177
Qiu, Y., Han, W., & Zeng, D. (2023). Impact of biased technological progress on the total factor productivity of China’s manufacturing industry: The driver of sustainable economic growth. Journal of Cleaner Production, 409, Article 137269. https://doi.org/10.1016/j.jclepro.2023.137269
Qu, F., Xu, L., & He, C. (2023). Leverage effect or crowding out effect? Evidence from low-carbon city pilot and energy technology innovation in China. Sustainable Cities and Society, 91, Article 104423. https://doi.org/10.1016/j.scs.2023.104423
Saleem, H., Shahzad, M., Khan, M. B., & Khilji, B. A. (2019). Innovation, total factor productivity and economic growth in Pakistan: A policy perspective. Journal of Economic Structures, 8(1), Article 7. https://doi.org/10.1186/s40008-019-0134-6
Shen, L., Zhang, X., & Liu, H. (2022). Digital technology adoption, digital dynamic capability, and digital transformation performance of textile industry: Moderating role of digital innovation orientation. Managerial and Decision Economics, 43(6), 2038–2054. https://doi.org/10.1002/mde.3507
Song, M., Peng, L., Shang, Y., & Zhao, X. (2022). Green technology progress and total factor productivity of resource-based enterprises: A perspective of technical compensation of environmental regulation. Technological Forecasting and Social Change, 174, Article 121276. https://doi.org/10.1016/j.techfore.2021.121276
Su, J., Wei, Y., Wang, S., & Liu, Q. (2023). The impact of digital transformation on the total factor productivity of heavily polluting enterprises. Scientific Reports, 13(1), Article 6386. https://doi.org/10.1038/s41598-023-33553-w
Tang, M., Liu, Y., Hu, F., & Wu, B. (2023). Effect of digital transformation on enterprises’ green innovation: Empirical evidence from listed companies in China. Energy Economics, 128, Article 107135. https://doi.org/10.1016/j.eneco.2023.107135
Teece, D. J. (2018). Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world. Research Policy, 47(8), 1367–1387. https://doi.org/10.1016/j.respol.2017.01.015
Teng, Y., Du, A. M., & Lin, B. (2024). The mechanism of supply chain efficiency in enterprise digital transformation and total factor productivity. International Review of Financial Analysis, 96, Article 103583. https://doi.org/10.1016/j.irfa.2024.103583
Van Veldhoven, Z., & Vanthienen, J. (2022). Digital transformation as an interaction-driven perspective between business, society, and technology. Electronic Markets, 32, 629–644. https://doi.org/10.1007/s12525-021-00464-5
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Wang, H., Cui, H., & Zhao, Q. (2021). Effect of green technology innovation on green total factor productivity in China: Evidence from spatial durbin model analysis. Journal of Cleaner Production, 288, Article 125624. https://doi.org/10.1016/j.jclepro.2020.125624
Wang, J., Dong, X., & Dong, K. (2023a). Does renewable energy technological innovation matter for green total factor productivity? Empirical evidence from Chinese provinces. Sustainable Energy Technologies and Assessments, 55, Article 102966. https://doi.org/10.1016/j.seta.2022.102966
Wang, J., Liu, Y., Wang, W., & Wu, H. (2023b). How does digital transformation drive green total factor productivity? Evidence from Chinese listed enterprises. Journal of Cleaner Production, 406, Article 136954. https://doi.org/10.1016/j.jclepro.2023.136954
Wang, L. (2023). Digital transformation and total factor productivity. Finance Research Letters, 58, Article 104338. https://doi.org/10.1016/j.frl.2023.104338
WinGo textual analytics database (n.d.). Retrieved August 1, 2023, from http://www.wingodata.com/
World Intellectual Property Organization (n.d.). IPC Green Inventory. Retrieved March 16, 2024, from https://www.wipo.int/classifications/ipc/green-inventory/home
Wu, L., Lou, B., & Hitt, L. (2019). Data analytics supports decentralized innovation. Management Science, 65(10), 4863–4877. https://doi.org/10.1287/mnsc.2019.3344
Wu, K., Fu, Y., & Kong, D. (2022). Does the digital transformation of enterprises affect stock price crash risk? Finance Research Letters, 48, Article 102888. https://doi.org/10.1016/j.frl.2022.102888
Xing, X., Chen, T., Yang, X., & Liu, T. (2023). Digital transformation and innovation performance of China’s manufacturers? A configurational approach. Technology in Society, 75, Article 102356. https://doi.org/10.1016/j.techsoc.2023.102356
Xue, L., Zhang, Q., Zhang, X., & Li, C. (2022). Can digital transformation promote green technology innovation? Sustainability, 14(12), Article 7497. https://doi.org/10.3390/su14127497
Yang, C.-H. (2022). How artificial intelligence technology affects productivity and employment: Firm-level evidence from Taiwan. Research Policy, 51(6), Article 104536. https://doi.org/10.1016/j.respol.2022.104536
Yang, Y., Jin, Y., & Xue, Q. (2024). How does digital transformation affect corporate total factor productivity? Finance Research Letters, 67, Article 105850. https://doi.org/10.1016/j.frl.2024.105850
Yu, J., Xu, Y., Zhou, J., & Chen, W. (2024). Digital transformation, total factor productivity, and firm innovation investment. Journal of Innovation & Knowledge, 9(2), Article 100487. https://doi.org/10.1016/j.jik.2024.100487
Zaoui, F., & Souissi, N. (2020). Roadmap for digital transformation: A literature review. Procedia Computer Science, 175, 621–628. https://doi.org/10.1016/j.procs.2020.07.090
Zeng, G., & Lei, L. (2021). Digital transformation and corporate total factor productivity: Empirical evidence based on listed enterprises. Discrete Dynamics in Nature and Society, 2021, Article 9155861. https://doi.org/10.1155/2021/9155861 (Retraction published 2023, Discrete Dynamics in Nature and Society, 2023, Article 9871216)
Zhang, H., & Dong, S. (2023). Digital transformation and firms’ total factor productivity: The role of internal control quality. Finance Research Letters, 57, Article 104231. https://doi.org/10.1016/j.frl.2023.104231
Zhen, W., Xin-gang, Z., & Ying, Z. (2021). Biased technological progress and total factor productivity growth: From the perspective of China’s renewable energy industry. Renewable and Sustainable Energy Reviews, 146, Article 111136. https://doi.org/10.1016/j.rser.2021.111136
Zheng, Y., & Zhang, Q. (2023). Digital transformation, corporate social responsibility and green technology innovation- based on empirical evidence of listed companies in China. Journal of Cleaner Production, 424, Article 138805. https://doi.org/10.1016/j.jclepro.2023.138805
Zhu, C., Li, N., & Ma, J. (2024). Impact of CEO overconfidence on enterprise digital transformation: Moderating effect based on digital finance. Finance Research Letters, 59, Article 104688. https://doi.org/10.1016/j.frl.2023.104688
Ackerberg, D. A., Caves, K., & Frazer, G. (2015). Identification properties of recent production function estimators. Econometrica, 83(6), 2411–2451. https://doi.org/10.3982/ECTA13408
Aghion, P., Dechezleprêtre, A., Hémous, D., Martin, R., & Van Reenen, J. (2016). Carbon taxes, path dependency, and directed technical change: Evidence from the auto industry. Journal of Political Economy, 124(1), 1–51. https://doi.org/10.1086/684581
Ahmed, E. M., & Elfaki, K. E. (2024). Green technological progress implications on long-run sustainable economic growth. Journal of the Knowledge Economy, 15(2), 6860–6877. https://doi.org/10.1007/s13132-023-01268-y
Ahmed, E. M., & Kialashaki, R. (2021). FDI inflows spillover effect implications on the Asian-Pacific labour productivity. International Journal of Finance & Economics, 28(1), 575–588. https://doi.org/10.1002/ijfe.2437
Ayoko, O. B. (2021). Digital transformation, robotics, artificial intelligence, and innovation. Journal of Management and Organization, 27(5), 831–835. https://doi.org/10.1017/jmo.2021.64
Baruffaldi, S., Van Beuzekom, B., Dernis, H., Harhoff, D., Rao, N., Rosenfeld, D., & Squicciarini, M. (2020). Identifying and measuring developments in artificial intelligence: Making the impossible possible (OECD Science, Technology and Industry Working Paper No. 2020/05). OECD. https://doi.org/10.1787/5f65ff7e-en
Bentley-Goode, K. A., Omer, T. C., & Twedt, B. J. (2017). Does business strategy impact a firm’s information environment? Journal of Accounting, Auditing & Finance, 34(4), 563–587. https://doi.org/10.1177/0148558X17726893
Brynjolfsson, E., & Collis, A. (2019). How should we measure the digital economy? Harvard Business Review, 97(6), 140–148.
Buck, C., Clarke, J., Torres de Oliveira, R., Desouza, K. C., & Maroufkhani, P. (2023). Digital transformation in asset-intensive organisations: The light and the dark side. Journal of Innovation & Knowledge, 8(2), Article 100335. https://doi.org/10.1016/j.jik.2023.100335
Chatzistamoulou, N. (2023). Is digital transformation the Deus ex Machina towards sustainability transition of the European SMEs? Ecological Economics, 206(12), Article 107739. https://doi.org/10.1016/j.ecolecon.2023.107739
Cheng, Y., Zhou, X., & Li, Y. (2023). The effect of digital transformation on real economy enterprises’ total factor productivity. International Review of Economics and Finance, 85(1), 488–501. https://doi.org/10.1016/j.iref.2023.02.007
China Stock Market & Accounting Research Database (n.d.). Retrieved August 1, 2023, from https://data.csmar.com/
China Securities Regulatory Commission (n.d.). Retrieved December 31, 2023, from http://www.csrc.gov.cn/csrc/c100103/c1452025/content.shtml
China National Intellectual Property Administration. (n.d.-a). Open data [Database]. Retrieved August 1, 2023, from https://pss-system.cponline.cnipa.gov.cn/conventionalSearch
China National Intellectual Property Administration. (n.d.-b). Open data [Website]. Retrieved March 1, 2024, from https://www.cnipa.gov.cn/art/2024/3/1/art_93_190525.html
Du, K., & Li, J. (2019). Towards a green world: How do green technology innovations affect total-factor carbon productivity. Energy Policy, 131(4), 240–250. https://doi.org/10.1016/j.enpol.2019.04.033
Du, K., Cheng, Y., & Yao, X. (2021). Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities. Energy Economics, 98, Article 105247. https://doi.org/10.1016/j.eneco.2021.105247
Du, J., Shen, Z., Song, M., & Zhang, L. (2023). Nexus between digital transformation and energy technology innovation: An empirical test of A-share listed enterprises. Energy Economics, 120(2), Article 106572. https://doi.org/10.1016/j.eneco.2023.106572
Du, G., Zhou, C., & Zhang, M. (2024). Does digital transformation promote local-neighborhood green technology innovation? – Based on the panel data of Chinese a-share listed companies from 2011 to 2021. Journal of Cleaner Production, 466, Article 142809. https://doi.org/10.1016/j.jclepro.2024.142809
Fang, X., & Liu, M. (2024). How does the digital transformation drive digital technology innovation of enterprises? Evidence from enterprise’s digital patents. Technological Forecasting and Social Change, 204, Article 123428. https://doi.org/10.1016/j.techfore.2024.123428
Gaglio, C., Kraemer-Mbula, E., & Lorenz, E. (2022). The effects of digital transformation on innovation and productivity: Firm-level evidence of South African manufacturing micro and small enterprises. Technological Forecasting and Social Change, 182(3), Article 121785. https://doi.org/10.1016/j.techfore.2022.121785
Gong, C., & Ribiere, V. (2021). Developing a unified definition of digital transformation. Technovation, 102(12), Article 102217. https://doi.org/10.1016/j.technovation.2020.102217
Gregory, R. W., Wagner, H. T., Tumbas, S., & Drechsler, K. (2019, December 15–18). At the crossroads between digital innovation and digital transformation. In Proceedings of the 40th International Conference on Information Systems (ICIS). München, Germany.
Guo, X., Li, M., Wang, Y., & Mardani, A. (2023). Does digital transformation improve the firm’s performance? From the perspective of digitalization paradox and managerial myopia. Journal of Business Research, 163, Article 113868. https://doi.org/10.1016/j.jbusres.2023.113868
Guo, S., & Zhang, Z. X. (2023). Green credit policy and total factor productivity: Evidence from Chinese listed companies. Energy Economics, 128, Article 107115. https://doi.org/10.1016/j.eneco.2023.107115
Hao, Y., Ba, N., Ren, S., & Wu, H. (2021). How does international technology spillover affect China’s carbon emissions? A new perspective through intellectual property protection. Sustainable Production and Consumption, 25, 577–590. https://doi.org/10.1016/j.spc.2020.12.008
Hassler, J., Krusell, P., & Olovsson, C. (2021). Directed technical change as a response to natural resource scarcity. Journal of Political Economy, 129(11), 3039–3072. https://doi.org/10.1086/715849
Huang, J., Cai, X., Huang, S., Tian, S., & Lei, H. (2019). Technological factors and total factor productivity in China: Evidence based on a panel threshold model. China Economic Review, 54(11), 271–285. https://doi.org/10.1016/j.chieco.2018.12.001
Jiang, W. (2017). Have instrumental variables brought US closer to the truth. Review of Corporate Finance Studies, 6(2), 127–140. https://doi.org/10.1093/rcfs/cfx015
Karafillis, C., & Papanagiotou, E. (2011). Innovation and total factor productivity in organic farming. Applied Economics, 43(23), 3075–3087. https://doi.org/10.1080/00036840903427240
Kraus, S., Jones, P., Kailer, N., Weinmann, A., Chaparro-Banegas, N., & Roig-Tierno, N. (2021). Digital transformation: An overview of the current state of the art of research. SAGE Open, 11(3), Article 21582440211047576. https://doi.org/10.1177/21582440211047576
Levinsohn, J., & Petrin, A. (2003). Estimating production functions using inputs to control for unobservables. Review of Economic Studies, 70(2), 317–341. https://doi.org/10.1111/1467-937X.00246
Lei, Z., & Wang, D. (2023). Digital transformation and total factor productivity: Empirical evidence from China. PLoS ONE, 18(10), Article e0292972. https://doi.org/10.1371/journal.pone.0292972
Li, L. (2022). Digital transformation and sustainable performance: The moderating role of market turbulence. Industrial Marketing Management, 104, 28–37. https://doi.org/10.1016/j.indmarman.2022.04.007
Li, X., Wang, X., & Xu, W. (2022). The information technology revolution and structural labor change: Evidence from China. Economic Modelling, 115, Article 105956. https://doi.org/10.1016/j.econmod.2022.105956
Li, J., Lian, G., & Xu, A. (2023a). How do ESG affect the spillover of green innovation among peer firms? Mechanism discussion and performance study. Journal of Business Research, 158, Article 113648. https://doi.org/10.1016/j.jbusres.2023.113648
Li, S., Gao, L., Han, C., Gupta, B., Alhalabi, W., & Almakdi, S. (2023b). Exploring the effect of digital transformation on firms’ innovation performance. Journal of Innovation & Knowledge, 8(1), Article 100317. https://doi.org/10.1016/j.jik.2023.100317
Lipsey, R. G., & Carlaw, K. I. (2004). Total factor productivity and the measurement of technological change. Canadian Journal of Economics, 37(4), 1118–1150. https://doi.org/10.1111/j.0008-4085.2004.00263.x
Malik, H., Chaudhary, G., & Srivastava, S. (2022). Digital transformation through advances in artificial intelligence and machine learning. Journal of Intelligent and Fuzzy Systems, 42(2), 615–622. https://doi.org/10.3233/JIFS-189787
Maroufkhani, P., Desouza, K. C., Perrons, R. K., & Iranmanesh, M. (2022). Digital transformation in the resource and energy sectors: A systematic review. Resources Policy, 76, Article 102622. https://doi.org/10.1016/j.resourpol.2022.102622
McElheran, K. S., & Forman, C. (2019). Firm organization in the digital age: IT use and vertical transactions in U.S. manufacturing. SSRN. https://doi.org/10.2139/ssrn.3396116
Nagaoka, S., Motohashi, K., & Goto, A. (2010). Chapter 25 – Patent statistics as an innovation indicator. In B. H. Hall & N. Rosenberg (Eds.), Handbook of the economics of innovation (Vol. 2, pp. 1083–1127). Elsevier. https://doi.org/10.1016/S0169-7218(10)02009-5
Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy, 48(8), Article 103773. https://doi.org/10.1016/j.respol.2019.03.018
Nucci, F., Puccioni, C., & Ricchi, O. (2023). Digital technologies and productivity: A firm-level investigation. Economic Modelling, 128, Article 106524. https://doi.org/10.1016/j.econmod.2023.106524
Olley, G. S., & Pakes, A. (1996). The dynamanics of productivity in the telecommunications equipment industry. Econometrica, 64(6), 1263–1297. https://doi.org/10.2307/2171831
Pan, W., Xie, T., Wang, Z., & Ma, L. (2022). Digital economy: An innovation driver for total factor productivity. Journal of Business Research, 139, 303–311. https://doi.org/10.1016/j.jbusres.2021.09.061
Parteka, A., & Kordalska, A. (2023). Artificial intelligence and productivity: Global evidence from AI patent and bibliometric data. Technovation, 125, Article 102764. https://doi.org/10.1016/j.technovation.2023.102764
Peng, Y., & Tao, C. (2022). Can digital transformation promote enterprise performance? From the perspective of public policy and innovation. Journal of Innovation & Knowledge, 7(3), Article 100198. https://doi.org/10.1016/j.jik.2022.100198
Picazo Rodríguez, B., Verdú-Jover, A. J., Estrada-Cruz, M., & Gomez-Gras, J. M. (2023). Does digital transformation increase firms’ productivity perception? The role of technostress and work engagement. European Journal of Management and Business Economics, 33(2), 137–156. https://doi.org/10.1108/EJMBE-06-2022-0177
Qiu, Y., Han, W., & Zeng, D. (2023). Impact of biased technological progress on the total factor productivity of China’s manufacturing industry: The driver of sustainable economic growth. Journal of Cleaner Production, 409, Article 137269. https://doi.org/10.1016/j.jclepro.2023.137269
Qu, F., Xu, L., & He, C. (2023). Leverage effect or crowding out effect? Evidence from low-carbon city pilot and energy technology innovation in China. Sustainable Cities and Society, 91, Article 104423. https://doi.org/10.1016/j.scs.2023.104423
Saleem, H., Shahzad, M., Khan, M. B., & Khilji, B. A. (2019). Innovation, total factor productivity and economic growth in Pakistan: A policy perspective. Journal of Economic Structures, 8(1), Article 7. https://doi.org/10.1186/s40008-019-0134-6
Shen, L., Zhang, X., & Liu, H. (2022). Digital technology adoption, digital dynamic capability, and digital transformation performance of textile industry: Moderating role of digital innovation orientation. Managerial and Decision Economics, 43(6), 2038–2054. https://doi.org/10.1002/mde.3507
Song, M., Peng, L., Shang, Y., & Zhao, X. (2022). Green technology progress and total factor productivity of resource-based enterprises: A perspective of technical compensation of environmental regulation. Technological Forecasting and Social Change, 174, Article 121276. https://doi.org/10.1016/j.techfore.2021.121276
Su, J., Wei, Y., Wang, S., & Liu, Q. (2023). The impact of digital transformation on the total factor productivity of heavily polluting enterprises. Scientific Reports, 13(1), Article 6386. https://doi.org/10.1038/s41598-023-33553-w
Tang, M., Liu, Y., Hu, F., & Wu, B. (2023). Effect of digital transformation on enterprises’ green innovation: Empirical evidence from listed companies in China. Energy Economics, 128, Article 107135. https://doi.org/10.1016/j.eneco.2023.107135
Teece, D. J. (2018). Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world. Research Policy, 47(8), 1367–1387. https://doi.org/10.1016/j.respol.2017.01.015
Teng, Y., Du, A. M., & Lin, B. (2024). The mechanism of supply chain efficiency in enterprise digital transformation and total factor productivity. International Review of Financial Analysis, 96, Article 103583. https://doi.org/10.1016/j.irfa.2024.103583
Van Veldhoven, Z., & Vanthienen, J. (2022). Digital transformation as an interaction-driven perspective between business, society, and technology. Electronic Markets, 32, 629–644. https://doi.org/10.1007/s12525-021-00464-5
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Wang, H., Cui, H., & Zhao, Q. (2021). Effect of green technology innovation on green total factor productivity in China: Evidence from spatial durbin model analysis. Journal of Cleaner Production, 288, Article 125624. https://doi.org/10.1016/j.jclepro.2020.125624
Wang, J., Dong, X., & Dong, K. (2023a). Does renewable energy technological innovation matter for green total factor productivity? Empirical evidence from Chinese provinces. Sustainable Energy Technologies and Assessments, 55, Article 102966. https://doi.org/10.1016/j.seta.2022.102966
Wang, J., Liu, Y., Wang, W., & Wu, H. (2023b). How does digital transformation drive green total factor productivity? Evidence from Chinese listed enterprises. Journal of Cleaner Production, 406, Article 136954. https://doi.org/10.1016/j.jclepro.2023.136954
Wang, L. (2023). Digital transformation and total factor productivity. Finance Research Letters, 58, Article 104338. https://doi.org/10.1016/j.frl.2023.104338
WinGo textual analytics database (n.d.). Retrieved August 1, 2023, from http://www.wingodata.com/
World Intellectual Property Organization (n.d.). IPC Green Inventory. Retrieved March 16, 2024, from https://www.wipo.int/classifications/ipc/green-inventory/home
Wu, L., Lou, B., & Hitt, L. (2019). Data analytics supports decentralized innovation. Management Science, 65(10), 4863–4877. https://doi.org/10.1287/mnsc.2019.3344
Wu, K., Fu, Y., & Kong, D. (2022). Does the digital transformation of enterprises affect stock price crash risk? Finance Research Letters, 48, Article 102888. https://doi.org/10.1016/j.frl.2022.102888
Xing, X., Chen, T., Yang, X., & Liu, T. (2023). Digital transformation and innovation performance of China’s manufacturers? A configurational approach. Technology in Society, 75, Article 102356. https://doi.org/10.1016/j.techsoc.2023.102356
Xue, L., Zhang, Q., Zhang, X., & Li, C. (2022). Can digital transformation promote green technology innovation? Sustainability, 14(12), Article 7497. https://doi.org/10.3390/su14127497
Yang, C.-H. (2022). How artificial intelligence technology affects productivity and employment: Firm-level evidence from Taiwan. Research Policy, 51(6), Article 104536. https://doi.org/10.1016/j.respol.2022.104536
Yang, Y., Jin, Y., & Xue, Q. (2024). How does digital transformation affect corporate total factor productivity? Finance Research Letters, 67, Article 105850. https://doi.org/10.1016/j.frl.2024.105850
Yu, J., Xu, Y., Zhou, J., & Chen, W. (2024). Digital transformation, total factor productivity, and firm innovation investment. Journal of Innovation & Knowledge, 9(2), Article 100487. https://doi.org/10.1016/j.jik.2024.100487
Zaoui, F., & Souissi, N. (2020). Roadmap for digital transformation: A literature review. Procedia Computer Science, 175, 621–628. https://doi.org/10.1016/j.procs.2020.07.090
Zeng, G., & Lei, L. (2021). Digital transformation and corporate total factor productivity: Empirical evidence based on listed enterprises. Discrete Dynamics in Nature and Society, 2021, Article 9155861. https://doi.org/10.1155/2021/9155861 (Retraction published 2023, Discrete Dynamics in Nature and Society, 2023, Article 9871216)
Zhang, H., & Dong, S. (2023). Digital transformation and firms’ total factor productivity: The role of internal control quality. Finance Research Letters, 57, Article 104231. https://doi.org/10.1016/j.frl.2023.104231
Zhen, W., Xin-gang, Z., & Ying, Z. (2021). Biased technological progress and total factor productivity growth: From the perspective of China’s renewable energy industry. Renewable and Sustainable Energy Reviews, 146, Article 111136. https://doi.org/10.1016/j.rser.2021.111136
Zheng, Y., & Zhang, Q. (2023). Digital transformation, corporate social responsibility and green technology innovation- based on empirical evidence of listed companies in China. Journal of Cleaner Production, 424, Article 138805. https://doi.org/10.1016/j.jclepro.2023.138805
Zhu, C., Li, N., & Ma, J. (2024). Impact of CEO overconfidence on enterprise digital transformation: Moderating effect based on digital finance. Finance Research Letters, 59, Article 104688. https://doi.org/10.1016/j.frl.2023.104688