Research on the Impact of Executives with Overseas Backgrounds on Corporate ESG Performance: Evidence from Chinese A-Share Listed Companies
Abstract
1. Introduction
2. Literature Review and Research Hypotheses
2.1. Executives with Overseas Backgrounds and Corporate ESG Performance
2.2. Executives with Overseas Backgrounds, Corporate Green Technological Innovation, and ESG Performance
2.3. Executives with Overseas Backgrounds, the Quality of Internal Control, and ESG Performance
2.4. Executives with Overseas Backgrounds, Corporate Risk-Taking Levels, and ESG Performance
2.5. Executives with Overseas Backgrounds, Corporate Digital Transformation, and ESG Performance
3. Research Design
3.1. Data Sources
3.2. Variable Definitions
3.2.1. Dependent Variable
3.2.2. Independent Variable
3.2.3. Mediating Variables
3.2.4. Moderating Variable
3.2.5. Control Variables
3.3. Econometric Models
4. Empirical Analysis
4.1. Descriptive Statistics
4.2. Regression Results
4.3. Robustness Tests
4.3.1. Replacing the Dependent Variable
4.3.2. Lagging the Independent Variable by One Period
4.3.3. Sample Selection Bias
4.3.4. Heterogeneity Analysis
5. Mechanism Tests
5.1. The Mediating Role of Corporate Green Technological Innovation
5.2. The Mediating Role of the Quality of Internal Control
5.3. The Mediating Role of Corporate Risk-Taking Levels
5.4. The Moderating Role of Corporate Digital Transformation
6. Research Conclusions and Implications
6.1. Conclusions
6.2. Policy and Managerial Implications
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Wang, F.L.; Guo, Y.H.; Li, S.Q. How Does Pro-Clean Government-Business Relationship Affect Corporate ESG Performance. Contemp. Financ. Econ. 2024, 8, 100. [Google Scholar]
- Bi, D.T.; Huang, W.X.; Wang, L.; Shao, B. How does city digital economy development affect the enterprise ESG performance?—A new path of green and high-quality city—Enterprise collaboration. Stud. Sci. Sci. 2024, 42, 594–604. [Google Scholar]
- Ozili, P.K. Green Finance Research around the World: A Review of Literature. Int. J. Green Econ. 2022, 16, 56–75. [Google Scholar] [CrossRef]
- Sethi, L.; Behera, B.; Sethi, N. Do Green Finance, Green Technology Innovation, and Institutional Quality Help Achieve Environmental Sustainability? Evidence from the Developing Economies. Sustain. Dev. 2024, 32, 2709–2723. [Google Scholar] [CrossRef]
- Hossin, M.S. Interest Rate Deregulation, Financial Development and Economic Growth: Evidence from Bangladesh. Glob. Bus. Rev. 2023, 24, 690–703. [Google Scholar] [CrossRef]
- Cohen, A.; Vakharia, S.P.; Netherland, J.; Frederique, K. How the War on Drugs Impacts Social Determinants of Health beyond the Criminal Legal System. Focus 2024, 22, 515–526. [Google Scholar] [CrossRef] [PubMed]
- Zhu, H.; Zhang, Y.; Bai, R.; Sun, X. Happiness and Executive Team Stability. Financ. Res. Lett. 2023, 57, 104286. [Google Scholar] [CrossRef]
- Le, H.N.M.; O’Connell, B.T.; Safari, M. The Influence of Overseas Study and Work Experience on Corporate Environmental Disclosures: Evidence from Vietnam. Meditari Account. Res. 2022, 30, 524–561. [Google Scholar] [CrossRef]
- Ofir, M. Controlling Non-Controlling Shareholders: The Case of Effective Control. Theor. Inq. Law 2024, 25, 187–230. [Google Scholar] [CrossRef]
- Krueger, P.; Sautner, Z.; Starks, L.T. The Importance of Climate Risks for Institutional Investors. Rev. Financ. Stud. 2020, 33, 1067–1111. [Google Scholar] [CrossRef]
- Tomičić Furjan, M.; Tomičić-Pupek, K.; Pihir, I. Understanding Digital Transformation Initiatives: Case Studies Analysis. Bus. Syst. Res. Int. J. Soc. Adv. Innov. Res. Econ. 2020, 11, 125–141. [Google Scholar]
- Fernández, A.; Gómez, B.; Binjaku, K.; Meçe, E.K. Digital Transformation Initiatives in Higher Education Institutions: A Multivocal Literature Review. Educ. Inf. Technol. 2023, 28, 12351–12382. [Google Scholar] [CrossRef] [PubMed]
- Fatima, S.; Abbas, S.; Rebi, A.; Ying, Z. Sustainable Forestry and Environmental Impacts: Assessing the Economic, Environmental, and Social Benefits of Adopting Sustainable Agricultural Practices. Ecol. Front. 2024, 44, 1119–1127. [Google Scholar] [CrossRef]
- Colli, M.; Stingl, V.; Waehrens, B. V Making or Breaking the Business Case of Digital Transformation Initiatives: The Key Role of Learnings. J. Manuf. Technol. Manag. 2022, 33, 41–60. [Google Scholar] [CrossRef]
- Bezerra, R.R.R.; Martins, V.W.B.; Macedo, A.N. Validation of Challenges for Implementing ESG in the Construction Industry Considering the Context of an Emerging Economy Country. Appl. Sci. 2024, 14, 6024. [Google Scholar] [CrossRef]
- Onyekwelu, N.P.; Ezeafulukwe, C.; Owolabi, O.R.; Asuzu, O.F.; Bello, B.G.; Onyekwelu, S.C. Ethics and Corporate Social Responsibility in HR: A Comprehensive Review of Policies and Practices. Int. J. Sci. Res. Arch. 2024, 11, 1294–1303. [Google Scholar] [CrossRef]
- Zheng, J.; Khurram, M.U.; Chen, L. Can Green Innovation Affect ESG Ratings and Financial Performance? Evidence from Chinese GEM Listed Companies. Sustainability 2022, 14, 8677. [Google Scholar] [CrossRef]
- Aydoğmuş, M.; Gülay, G.; Ergun, K. Impact of ESG Performance on Firm Value and Profitability. Borsa Istanb. Rev. 2022, 22, S119–S127. [Google Scholar] [CrossRef]
- Mishchuk, H.; Bilan, Y.; Androniceanu, A.; Krol, V. Social Capital: Evaluating Its Roles in Competitiveness and Ensuring Human Development. J. Compet. 2023, 15, 1–17. [Google Scholar]
- Abernethy, M.A.; Li, W.; Zhang, Y.; Shi, H. Firm Culture and Internal Control System. Account. Financ. 2023, 63, 3095–3123. [Google Scholar] [CrossRef]
- Kothandapani, H.P. Emerging Trends and Technological Advancements in Data Lakes for the Financial Sector: An in-Depth Analysis of Data Processing, Analytics, and Infrastructure Innovations. Q. J. Emerg. Technol. Innov. 2023, 8, 62–75. [Google Scholar]
- Chege, S.M.; Wang, D.; Suntu, S.L. Impact of Information Technology Innovation on Firm Performance in Kenya. Inf. Technol. Dev. 2020, 26, 316–345. [Google Scholar] [CrossRef]
Variable Type | Variable Name | Symbol | Definition |
---|---|---|---|
Dependent Variable | Corporate ESG Performance | ESG | Huazheng ESG ratings from C to AAA assigned values 1–9; annual average calculated. |
Independent Variable | Executives with Overseas Background | oversea_1 | Whether the firm has appointed executives with overseas backgrounds (1 = yes, 0 = no). |
Proportion of Overseas Background Executives | oversea_ratio | Proportion of executives with overseas backgrounds within the management team. | |
Mediating Variable | Green Technological Innovation | Ginn | Natural log of (number of green patent applications +1). |
Internal Control Quality | inctr | Dibo China Listed Company Internal Control Index. | |
Corporate Risk-Taking Level | Risk1 | Earnings volatility calculated over rolling three-year periods. | |
Moderating Variable | Digital Transformation | dig | Natural log of (sum of keyword occurrences from text analysis +1). |
Control Variable | Firm Size | Size | Natural log of (year-end total assets +1). |
Firm Age | Age | Natural log of (years since establishment +1). | |
Revenue Growth Rate | Growth | (Current period revenue − prior period revenue)/prior period revenue. | |
Leverage Ratio | Lever | Total liabilities/total assets. | |
Proportion of Independent Directors | Indep | Number of independent directors/total number of board members. | |
CEO Duality | Dual | Equals 1 if the chairman concurrently serves as general manager, 0 otherwise. | |
Ownership Concentration | Top1 | Shareholding ratio of the largest shareholder. | |
Board Size | Board | Natural log of the number of board members of the listed company. |
Variable | Sample Number | Mean | Standard Deviation | Min | Max |
---|---|---|---|---|---|
ESG | 34,299 | 4.151 | 1.009 | 1 | 6.75 |
oversea_1 | 34,299 | 0.261 | 0.439 | 0 | 1 |
oversea ratio | 34,299 | 0.063 | 0.128 | 0 | 1 |
Ginn | 34,299 | 2.817 | 22.716 | 0 | 1166 |
inctr | 33,757 | 636.482 | 131.197 | 0 | 995.36 |
Risk1 | 33,068 | 0.033 | 0.039 | 0 | 0.511 |
dig | 34,299 | 1.429 | 1.406 | 0 | 6.301 |
Size | 34,299 | 22.25 | 1.295 | 19.585 | 26.452 |
Age | 34,299 | 2.152 | 0.824 | 0 | 3.401 |
Growth | 34,299 | 0.164 | 0.409 | −0.658 | 4.024 |
Lev | 34,299 | 0.424 | 0.205 | 0.032 | 0.908 |
Board | 34,299 | 2.119 | 0.197 | 1.609 | 2.708 |
Indep | 34,299 | 37.682 | 5.382 | 28.57 | 60 |
Dual | 34,299 | 0.287 | 0.452 | 0 | 1 |
Top1 | 34,299 | 33.901 | 14.796 | 8.02 | 75.779 |
Variable | (1) | (2) | (3) | (4) |
---|---|---|---|---|
ESG | ESG | ESG | ESG | |
oversea_1 | 0.054 *** (0.013) | 0.033 ** (0.013) | ||
oversea_ratio | 0.208 *** (0.048) | 0.132 *** (0.047) | ||
Size | 0.317 *** (0.010) | 0.317 *** (0.010) | ||
Age | −0.119 *** (0.017) | −0.120 *** (0.017) | ||
Growth | −0.0209 ** (0.009) | −0.021 ** (0.009) | ||
Lev | −0.931 *** (0.039) | −0.931 *** (0.039) | ||
Board | 0.0585 (0.043) | 0.060 (0.043) | ||
Indep | 0.0112 *** (0.001) | 0.011 *** (0.001) | ||
Dual | −0.0328 ** (0.013) | −0.033 *** (0.013) | ||
Top1 | 0.007 *** (0.001) | 0.007 *** (0.001) | ||
Constant | 4.130 *** (0.016) | 4.131 *** (0.016) | −2.922 *** (0.234) | −2.919 *** (0.234) |
Observations | 34,299 | 34,299 | 34,299 | 34,299 |
R2 | 0.015 | 0.015 | 0.066 | 0.066 |
Variable | (1) | (2) | (3) | (4) | (5) | (6) |
---|---|---|---|---|---|---|
ESG | ESG | PESG | PESG | SESG | SESG | |
Loversea_1 | 0.0352 ** (0.015) | |||||
Loversea_ratio | 0.155 *** (0.055) | |||||
oversea_ratio | 1.431 *** (0.555) | 0.348 ** (0.157) | ||||
oversea_1 | 0.287 ** (0.142) | 0.0796 ** (0.039) | ||||
Size | 0.327 *** (0.011) | 0.324 *** (0.011) | 1.242 *** (0.113) | 1.235 *** (0.114) | 0.394 *** (0.059) | 0.394 *** (0.059) |
Age | −0.272 *** (0.026) | −0.272 *** (0.026) | 0.560 ** (0.240) | 0.557 ** (0.240) | −0.0557 (0.093) | −0.0574 (0.093) |
Growth | −0.0108 (0.010) | −0.0106 (0.010) | 0.0733 (0.099) | 0.0707 (0.099) | −0.103 *** (0.039) | −0.103 *** (0.039) |
Lev | −0.835 *** (0.043) | −0.830 *** (0.043) | −3.848 *** (0.466) | −3.852 *** (0.466) | −0.610 *** (0.200) | −0.616 *** (0.200) |
Board | 0.0218 (0.047) | 0.0181 (0.047) | 1.298 *** (0.435) | 1.324 *** (0.435) | 0.0407 (0.145) | 0.0532 (0.145) |
Indep | 0.0114 *** (0.001) | 0.0114 *** (0.001) | 0.0553 *** (0.013) | 0.0548 *** (0.013) | 0.00744 * (0.004) | 0.00749 * (0.004) |
Dual | −0.0382 *** (0.014) | −0.0416 *** (0.014) | 0.0117 (0.148) | 0.00821 (0.148) | −0.0452 (0.050) | −0.0475 (0.050) |
Top1 | 0.00489 *** (0.001) | 0.00476 *** (0.001) | 0.0209 *** (0.007) | 0.0208 *** (0.007) | 0.00253 (0.003) | 0.00243 (0.003) |
Constant | −2.677 *** (0.264) | −2.602 *** (0.264) | −13.24 *** (2.665) | −13.12 *** (2.666) | −4.713 *** (1.401) | −4.733 *** (1.400) |
Observations | 29,285 | 29,257 | 10,979 | 10,979 | 4204 | 4204 |
R2 | 0.066 | 0.066 | 0.698 | 0.698 | 0.320 | 0.320 |
Variable | Sample | Mean | Standardized Bias % | Reduction in Bias % | t-Test | V(T)/ V(C) | ||
---|---|---|---|---|---|---|---|---|
Treatment Group | Control Group | t | p > |t| | |||||
size | U | 21.999 | 22.160 | −13.200 | −7.140 | 0.000 | 0.87 * | |
M | 21.999 | 21.977 | 1.7 | 86.800 | 0.810 | 0.418 | 0.980 | |
age | U | 1.974 | 2.087 | −14.600 | −7.920 | 0.000 | 0.90 * | |
M | 1.974 | 1.963 | 1.4 | 90.300 | 0.640 | 0.525 | 0.91 * | |
growth | U | 0.177 | 0.172 | 1.2 | 0.650 | 0.518 | 0.980 | |
M | 0.177 | 0.179 | −0.500 | 54.500 | −0.240 | 0.811 | 0.94 * | |
lever | U | 0.405 | 0.419 | −7.100 | −3.910 | 0.000 | 0.990 | |
M | 0.405 | 0.405 | −0.300 | 96.500 | −0.110 | 0.909 | 1.020 | |
indep | U | 0.378 | 0.376 | 3.3 | 1.820 | 0.069 | 0.990 | |
M | 0.378 | 0.379 | −1.500 | 55.400 | −0.660 | 0.507 | 0.990 | |
dual | U | 0.315 | 0.284 | 6.9 | 3.830 | 0.000 | 1.060 | |
M | 0.315 | 0.308 | 1.7 | 75.800 | 0.740 | 0.458 | 1.010 | |
top1 | U | 0.330 | 0.348 | −12.300 | −6.650 | 0.000 | 0.87 * | |
M | 0.330 | 0.332 | −1.100 | 91.300 | −0.490 | 0.625 | 0.94 * | |
board | U | 2.100 | 2.125 | −12.700 | −6.910 | 0.000 | 0.93 * | |
M | 2.100 | 2.101 | −0.300 | 97.400 | −0.150 | 0.881 | 0.960 |
Variable | (1) | (2) |
---|---|---|
ESG | ESG | |
oversea_1 | 0.0728 ** (0.033) | |
oversea_ratio | 0.398 *** (0.120) | |
Controls | YES | YES |
Constant | 4.997 *** (0.654) | 5.045 *** (0.673) |
Observations | 6407 | 6490 |
R2 | 0.017 | 0.016 |
Pollution Attribute | Production Attribute | Factor Intensity | |||||
---|---|---|---|---|---|---|---|
Heavily Polluting | Non-Heavily Polluting | Manufacturing | Non-Manufacturing | Labor-Intensive | Capital-Intensive | Technology-Intensive | |
oversea_ ratio | 0.216 (0.173) | 0.293 *** (0.092) | 0.249 ** (0.098) | 0.282 * (0.149) | 0.265 (0.187) | 0.439 *** (0.166) | 0.186 * (0.111) |
Constant | 5.301 *** (0.685) | 5.346 *** (0.437) | 4.896 *** (0.452) | 6.417 *** (0.642) | 7.088 *** (0.749) | 4.719 *** (0.702) | 4.882 *** (0.544) |
Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
N | 4917 | 11,150 | 10,588 | 5479 | 4158 | 4716 | 7193 |
R2 | 0.022 | 0.023 | 0.019 | 0.024 | 0.028 | 0.020 | 0.022 |
Variable | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Ginn | ESG | Ginn | ESG | |
oversea_1 | 0.281 *** (0.095) | 0.0344 * (0.021) | ||
oversea_ratio | 1.088 *** (0.369) | 0.223 *** (0.081) | ||
Ginn | 0.00853 *** (0.002) | 0.00852 *** (0.002) | ||
Controls | YES | YES | YES | YES |
Constant | −5.347 *** (1.554) | 5.442 *** (0.368) | −5.699 *** (1.554) | 5.445 *** (0.368) |
Observations | 15,967 | 16,067 | 15,967 | 16,067 |
R2 | 0.019 | 0.019 | 0.019 | 0.019 |
Variable | (1) | (2) | (3) | (4) |
---|---|---|---|---|
inctr | ESG | inctr | ESG | |
oversea_1 | 7.599 ** (3.525) | 0.0428 ** (0.021) | ||
oversea_ratio | 42.89 *** (14.184) | 0.294 *** (0.082) | ||
inctr | 0.000759 *** (0.000) | 0.000750 *** (0.000) | ||
Controls | YES | YES | YES | YES |
Constant | 859.3 *** (61.967) | 4.706 *** (0.368) | 861.0 *** (62.834) | 4.833 *** (0.368) |
Observations | 16,007 | 16,007 | 16,007 | 16,007 |
R2 | 0.040 | 0.033 | 0.040 | 0.034 |
Variable | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Risk1 | ESG | Risk1 | ESG | |
oversea_1 | 0.00287 *** (0.001) | 0.0353 * (0.021) | ||
oversea_ratio | 0.0119 *** (0.004) | 0.198 ** (0.083) | ||
Risk1 | 0.568 *** (0.215) | 0.510 *** (0.197) | ||
Controls | YES | YES | YES | YES |
Constant | −0.00946 (0.016) | 5.215 *** (0.365) | −0.00810 (0.017) | 5.284 *** (0.376) |
Observations | 15,966 | 13,686 | 15,966 | 13,356 |
R2 | 0.050 | 0.019 | 0.058 | 0.021 |
Variable | ESG | |
---|---|---|
(1) | (2) | |
oversea_1 | 0.0624 ** (0.028) | |
dig | 0.0376 *** (0.009) | 0.0303 *** (0.009) |
oversea_1 × dig | 0.0298 ** (0.012) | |
oversea_ratio | 0.227 ** (0.112) | |
oversea_ratio × dig | 0.0912 * (0.049) | |
Controls | YES | YES |
Constant | 5.411 *** (0.368) | 5.424 *** (0.368) |
Observations | 16,067 | 16,067 |
R2 | 0.018 | 0.019 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Feng, L.; Ma, Z. Research on the Impact of Executives with Overseas Backgrounds on Corporate ESG Performance: Evidence from Chinese A-Share Listed Companies. Sustainability 2025, 17, 7683. https://doi.org/10.3390/su17177683
Feng L, Ma Z. Research on the Impact of Executives with Overseas Backgrounds on Corporate ESG Performance: Evidence from Chinese A-Share Listed Companies. Sustainability. 2025; 17(17):7683. https://doi.org/10.3390/su17177683
Chicago/Turabian StyleFeng, Lele, and Zhiqiang Ma. 2025. "Research on the Impact of Executives with Overseas Backgrounds on Corporate ESG Performance: Evidence from Chinese A-Share Listed Companies" Sustainability 17, no. 17: 7683. https://doi.org/10.3390/su17177683
APA StyleFeng, L., & Ma, Z. (2025). Research on the Impact of Executives with Overseas Backgrounds on Corporate ESG Performance: Evidence from Chinese A-Share Listed Companies. Sustainability, 17(17), 7683. https://doi.org/10.3390/su17177683