Weiteng Shen
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Weiteng Shen has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
Shunbin Zhong
School of Business, Minnan Normal University, Zhangzhou, China
3 shared publicationsHaoran Ge
2 shared publicationsXuan Yu
Ningbo University Donghai Academy, Ningbo, China
2 shared publicationsAndrianarivo Andriandafiarisoa Rali Avotra
1 shared publication- Jintao Ma
School of Business, Ningbo University, Ningbo 315211, China
1 shared publication Junyao Bao
1 shared publication
Latest Publications
- Open Access
- 3 November 2025
- Published by Springer Nature in Humanities and Social Sciences Communications
- Vol. 12 (1) , 1-14
The effect of digitalization on total factor productivity: a dynamic capabilities perspective
- 3 November 2025
- Published by Springer Nature in Humanities and Social Sciences Communications
- Vol. 12 (1) , 1-14
Open AccessThe effect of digitalization on total factor productivity: a dynamic capabilities perspective
- Open Access
- 1 July 2025
- Published by Frontiers Media SA in Frontiers in Marine Science
- Vol. 12, 1587019
The effects of digitalization on the quality of marine economic development: evidence from a micro-level perspective
Digitalization is transforming the marine economy at an accelerating pace, yet its effects on the Quality of Marine Economic Development (QMED) and the pathways driving these changes are underexplored. This study investigates these dynamics using an unbalanced panel of 168 A-share listed marine firms in China over the period 2003–2023. We apply a two-way fixed effects model to estimate the effect of digitalization on QMED and explore its mechanisms, complemented by heterogeneity analyses across firm sizes, industry types, government attention, and human capital levels. The results show that digitalization improves QMED, with a 0.01 rise in the digitalization index—about one-fifth of its mean—lifting Total Factor Productivity (TFP) of marine firms by roughly 0.599, or 6.85% of the average TFP. Digitalization boosts QMED by enhancing firms’ resource allocation efficiency and spurring technological innovation. Larger firms benefit more than smaller ones, while labor-intensive industries outpace capital-intensive ones in QMED gains. Higher human capital levels weaken digitalization’s positive effect on QMED. These findings suggest practical strategies for practitioners, such as adopting cost-effective digital tools like automation and big data analytics in labor-intensive sectors and providing subsidies or financing to support smaller firms’ digitalization. These insights highlight digitalization’s uneven effects and provide a foundation for targeted policy design to enhance marine economic development.
- 1 July 2025
- Published by Frontiers Media SA in Frontiers in Marine Science
- Vol. 12, 1587019
Open AccessThe effects of digitalization on the quality of marine economic development: evidence from a micro-level perspective
Digitalization is transforming the marine economy at an accelerating pace, yet its effects on the Quality of Marine Economic Development (QMED) and the pathways driving these changes are underexplored. This study investigates these dynamics using an unbalanced panel of 168 A-share listed marine firms in China over the period 2003–2023. We apply a two-way fixed effects model to estimate the effect of digitalization on QMED and explore its mechanisms, complemented by heterogeneity analyses across firm sizes, industry types, government attention, and human capital levels. The results show that digitalization improves QMED, with a 0.01 rise in the digitalization index—about one-fifth of its mean—lifting Total Factor Productivity (TFP) of marine firms by roughly 0.599, or 6.85% of the average TFP. Digitalization boosts QMED by enhancing firms’ resource allocation efficiency and spurring technological innovation. Larger firms benefit more than smaller ones, while labor-intensive industries outpace capital-intensive ones in QMED gains. Higher human capital levels weaken digitalization’s positive effect on QMED. These findings suggest practical strategies for practitioners, such as adopting cost-effective digital tools like automation and big data analytics in labor-intensive sectors and providing subsidies or financing to support smaller firms’ digitalization. These insights highlight digitalization’s uneven effects and provide a foundation for targeted policy design to enhance marine economic development.
- Open Access
- 15 February 2025
- Published by Elsevier in International Review of Economics & Finance
- Vol. 99
The effects of internet infrastructure on carbon neutrality
- 15 February 2025
- Published by Elsevier in International Review of Economics & Finance
- Vol. 99
Open AccessThe effects of internet infrastructure on carbon neutrality
- Open Access
- 7 November 2023
- Published by Frontiers Media SA in Frontiers in Sustainable Food Systems
- Vol. 7, 1281366
Green total factor productivity growth and its driving forces in China’s fisheries sector
The rapid development of China’s fisheries sector has brought about significant environmental problems, which are detrimental to the sustainable development of the sector. Balancing environmental protection while promoting fisheries development has become an urgent issue in China. Based on data from 30 provincial-level administrative regions in China from 2004 to 2019, this study utilizes the Epsilon-based Measure (EBM) model considering undesirable outputs and the global Malmquist-Luenberger (GML) index to measure the green total factor productivity (GTFP) growth in China’s fisheries sector. Furthermore, it explores the spatiotemporal evolution and driving forces of fisheries GTFP growth using spatial Durbin model (SDM). The results indicate that ignoring the resource and environmental costs in fisheries production would overestimate the growth of total factor productivity (TFP) by 1.3%. The growth of fishery output primarily comes from the increase in input factors, exhibiting extensive characteristics that have been gradually diminishing over time. During the sample period, the provinces with the fastest growth in GTFP shifted from being mainly concentrated in the central and western regions to the eastern region. The local driving forces behind the improvement of fisheries GTFP include internet penetration rate, transportation convenience, education level of rural residents. The driving forces from economically similar provinces include the positive spatial interplay between provinces, fishery disaster rate, fisherman training, fishery trade openness, and urbanization rate. Overall, these finds offer a novel approach to reexamine the growth of China’s fisheries and provide valuable insights for the future fisheries development.
- 7 November 2023
- Published by Frontiers Media SA in Frontiers in Sustainable Food Systems
- Vol. 7, 1281366
Open AccessGreen total factor productivity growth and its driving forces in China’s fisheries sector
The rapid development of China’s fisheries sector has brought about significant environmental problems, which are detrimental to the sustainable development of the sector. Balancing environmental protection while promoting fisheries development has become an urgent issue in China. Based on data from 30 provincial-level administrative regions in China from 2004 to 2019, this study utilizes the Epsilon-based Measure (EBM) model considering undesirable outputs and the global Malmquist-Luenberger (GML) index to measure the green total factor productivity (GTFP) growth in China’s fisheries sector. Furthermore, it explores the spatiotemporal evolution and driving forces of fisheries GTFP growth using spatial Durbin model (SDM). The results indicate that ignoring the resource and environmental costs in fisheries production would overestimate the growth of total factor productivity (TFP) by 1.3%. The growth of fishery output primarily comes from the increase in input factors, exhibiting extensive characteristics that have been gradually diminishing over time. During the sample period, the provinces with the fastest growth in GTFP shifted from being mainly concentrated in the central and western regions to the eastern region. The local driving forces behind the improvement of fisheries GTFP include internet penetration rate, transportation convenience, education level of rural residents. The driving forces from economically similar provinces include the positive spatial interplay between provinces, fishery disaster rate, fisherman training, fishery trade openness, and urbanization rate. Overall, these finds offer a novel approach to reexamine the growth of China’s fisheries and provide valuable insights for the future fisheries development.
- Open Access
- 30 December 2022
- Published by Elsevier in SSRN Electronic Journal
The Emerging Driving Force of Productivity: Does Digital Transformation Work?
The deep integration of manufacturing and digital technology has become an important means to promote the high-quality development of manufacturing. Based on the data of China's listed manufacturing companies from 2007 to 2020, this study uses a panel fixed-effect model to empirically test the effect of digital transformation on the total factor productivity of enterprises. It found that digital transformation has significantly improved the total factor productivity of China's listed manufacturing companies. This conclusion still holds true when considering the endogeneity problem and carrying out a series of robustness tests. The results of the heterogeneity analysis showed that the promotion effect of digital transformation on total factor productivity exists only in samples receiving low government subsidies, samples with low industry concentration and samples of large-scale enterprises. In addition, this study also found that technological innovation, human capital and inventory management efficiency are important mechanisms for digital transformation to improve the total factor productivity of enterprises.
- 30 December 2022
- Published by Elsevier in SSRN Electronic Journal
Open AccessThe Emerging Driving Force of Productivity: Does Digital Transformation Work?
The deep integration of manufacturing and digital technology has become an important means to promote the high-quality development of manufacturing. Based on the data of China's listed manufacturing companies from 2007 to 2020, this study uses a panel fixed-effect model to empirically test the effect of digital transformation on the total factor productivity of enterprises. It found that digital transformation has significantly improved the total factor productivity of China's listed manufacturing companies. This conclusion still holds true when considering the endogeneity problem and carrying out a series of robustness tests. The results of the heterogeneity analysis showed that the promotion effect of digital transformation on total factor productivity exists only in samples receiving low government subsidies, samples with low industry concentration and samples of large-scale enterprises. In addition, this study also found that technological innovation, human capital and inventory management efficiency are important mechanisms for digital transformation to improve the total factor productivity of enterprises.
- Open Access
Influence of the Evolution of Marine Industry Structure on the Green Total Factor Productivity of Marine Economy
The 14th five-year plan emphasizes the importance of marine ecology and environmental protection, and the green concept is incorporated into the high-quality development system of the marine economy. This research used the data of 11 coastal provinces and cities in China from 2006 to 2016, based on the super-efficiency slack-based measure model and global Malmquist index model. The objective was to calculate the green total factor productivity (GTFP) of the marine economy, to study the impact of the evolution of the marine industrial structure on marine economic GTFP. The study found the following: (1) in general, the upgrade of marine industrial structure promoted the growth of marine economic GTFP and presented an inverted “U” trend of initially promoting and then suppressing. Spatially, only the advancement and rationalization of industrial structure in the Yellow and Bohai Sea regions inhibited the growth of marine economic GTFP. In terms of time, the advanced marine industrial structure promoted the growth of GTFP from 2006 to 2010, whereas that of industrial structure inhibited the growth of GTFP from 2011 to 2016. (2) The GTFP of the marine economy showed an increasing trend, but the conversion rate of production technology is low. Falling into the “efficiency trap” of highly advanced technology input and low-efficiency technology output should be avoided. (3) Affected by the mismatch of regional resources or industrial structure, government intervention showed an “opposite” mechanism in areas with different marine economic strengths. Government intervention in areas with higher marine economic strength was conducive to GTFP growth, whereas government intervention in areas with weaker marine economic strength would hinder GTFP growth.
Open AccessInfluence of the Evolution of Marine Industry Structure on the Green Total Factor Productivity of Marine Economy
The 14th five-year plan emphasizes the importance of marine ecology and environmental protection, and the green concept is incorporated into the high-quality development system of the marine economy. This research used the data of 11 coastal provinces and cities in China from 2006 to 2016, based on the super-efficiency slack-based measure model and global Malmquist index model. The objective was to calculate the green total factor productivity (GTFP) of the marine economy, to study the impact of the evolution of the marine industrial structure on marine economic GTFP. The study found the following: (1) in general, the upgrade of marine industrial structure promoted the growth of marine economic GTFP and presented an inverted “U” trend of initially promoting and then suppressing. Spatially, only the advancement and rationalization of industrial structure in the Yellow and Bohai Sea regions inhibited the growth of marine economic GTFP. In terms of time, the advanced marine industrial structure promoted the growth of GTFP from 2006 to 2010, whereas that of industrial structure inhibited the growth of GTFP from 2011 to 2016. (2) The GTFP of the marine economy showed an increasing trend, but the conversion rate of production technology is low. Falling into the “efficiency trap” of highly advanced technology input and low-efficiency technology output should be avoided. (3) Affected by the mismatch of regional resources or industrial structure, government intervention showed an “opposite” mechanism in areas with different marine economic strengths. Government intervention in areas with higher marine economic strength was conducive to GTFP growth, whereas government intervention in areas with weaker marine economic strength would hinder GTFP growth.