Overconfident CEOs, Greenwashing Firms: Why a Decade of Corporate Finance Never Connected Them

Sarah Sentika; Herry  Achmad Buchory; Ramadhi Ramadhi; Raden  Muhammad Arya Pratama

doi:10.55227/ijhess.v6i2.2589

Authors

Sarah Sentika Universitas Satu
Herry Achmad Buchory Widyatama University
Ramadhi Ramadhi Widyatama University
Raden Muhammad Arya Pratama Widyatama University

DOI:

https://doi.org/10.55227/ijhess.v6i2.2589

Keywords:

Behavioral corporate finance, Strategic diagram, Managerial overconfidence, Greenwashing, OpenAlex

Abstract

Behavioral corporate finance promised to explain how the beliefs and biases of managers and investors distort investment, financing, and payout decisions. Corporate finance research has since expanded and turned toward sustainability, yet no study has examined whether behavioral explanations followed. This study maps 2,405 journal articles published between 2016 and 2026 from OpenAlex. It combines performance indicators with a co-occurrence analysis of 167 keywords in VOSviewer, a strategic diagram, and a joint reading of keyword recency and normalised citations. The results show that the corpus received 22,293 citations (9.27 per article; h-index 66) and that annual output grew from 85 articles in 2016 to 551 in 2025. China produced 773 articles (40.7% of those with country data) with a relative citation impact of 1.29, while the United States (2.98) and Australia (2.97) recorded the highest impact. Indonesia ranked third in output (180 articles) but had the lowest relative citation impact (0.19) and the smallest share of international co-authorship (5.0%) among the ten leading countries. Six of the ten most cited articles belong to the sustainability stream and only one to behavioral corporate finance. Four clusters emerged: governance, disclosure, and behavioral biases (54 keywords); financing constraints and the green transition (48); capital structure and financing decisions (43); and agency, managerial traits, and investment efficiency (22). The green transition cluster is the most cohesive (density 79.6), the newest (mean year 2024.3), and the most cited (normalised citations 1.83), yet the least connected to the rest of the field. All ten core behavioral keywords fall below the citation average of their publication years (0.23 to 0.63), and investor biases such as overconfidence, loss aversion, and herding send less than 2% of their links to the green cluster. The study sets out research questions that bring managerial and investor biases into research on greenwashing, ESG, and green finance

References

Alperin, J. P., Portenoy, J., Demes, K., Larivière, V., & Haustein, S. (2024). An analysis of the suitability of OpenAlex for bibliometric analyses. ArXiv. https://doi.org/10.48550/arXiv.2404.17663

Arena, C., Michelon, G., & Trojanowski, G. (2018). Big egos can be green: A study of CEO hubris and environmental innovation. British Journal of Management, 29(2), 316–336. https://doi.org/10.1111/1467-8551.12250

Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007

Arissaputra, R., Gaffar, V., Sultan, M. A., Andriana, D., Abror, A., Sentika, S., & Christiyanto, W. W. (2025). Muslim tourists as role models for environmental responsibility: key factors in memorable nature-based tourism, place attachment, and environmental concern. Journal of Islamic Marketing, 16(12), 3657–3681.

Arissaputra, R., Sultan, M. A., Hurriyati, R., Gaffar, V., Asmara, M. A., & Sentika, S. (2024). Positive vs. negative E-WOM: understanding the more significant role in mediating E-commerce quality on online impulse buying. Jurnal Aplikasi Manajemen, 22(2), 444–458.

Baker, M., & Wurgler, J. (2013). Behavioral corporate finance: An updated survey. In G. M. Constantinides, M. Harris, & R. M. Stulz (Eds.), Handbook of the Economics of Finance (Vol. 2, pp. 357–424). Elsevier. https://doi.org/10.1016/B978-0-44-453594-8.00005-7

Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics, 22(1), 155–205. https://doi.org/10.1007/BF02019280

Chen, P., & Dagestani, A. A. (2023). Greenwashing behavior and firm value: From the perspective of board characteristics. Corporate Social Responsibility and Environmental Management, 30(5), 2330–2343. https://doi.org/10.1002/csr.2488

Christensen, H. B., Hail, L., & Leuz, C. (2021). Mandatory CSR and sustainability reporting: Economic analysis and literature review. Review of Accounting Studies, 26(3), 1176–1248. https://doi.org/10.1007/s11142-021-09609-5

Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of Informetrics, 5(1), 146–166. https://doi.org/10.1016/j.joi.2010.10.002

Costa, D. F., Carvalho, F. de M., & Moreira, B. C. de M. (2019). Behavioral economics and behavioral finance: A bibliometric analysis of the scientific fields. Journal of Economic Surveys, 33(1), 3–24. https://doi.org/10.1111/joes.12262

Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070

Gennaioli, N., Ma, Y., & Shleifer, A. (2016). Expectations and investment. NBER Macroeconomics Annual, 30, 379–442. https://doi.org/10.1086/685965

Khan, A., Goodell, J. W., Hassan, M. K., & Paltrinieri, A. (2022). A bibliometric review of finance bibliometric papers. Finance Research Letters, 47, 102520. https://doi.org/10.1016/j.frl.2021.102520

Kumar, S., Colombage, S., & Rao, P. (2017). Research on capital structure determinants: A review and future directions. International Journal of Managerial Finance, 13(2), 106–132. https://doi.org/10.1108/IJMF-09-2014-0135

Kumar, S., Rao, S., Goyal, K., & Goyal, N. (2022). Journal of Behavioral and Experimental Finance: A bibliometric overview. Journal of Behavioral and Experimental Finance, 34, 100652. https://doi.org/10.1016/j.jbef.2022.100652

Kumar, S., Sharma, D., Rao, S., Lim, W. M., & Mangla, S. K. (2025). Past, present, and future of sustainable finance: Insights from big data analytics through machine learning of scholarly research. Annals of Operations Research, 345(2), 1061–1104. https://doi.org/10.1007/s10479-021-04410-8

Li, J., Lian, G., & Xu, A. (2023). How do ESG affect the spillover of green innovation among peer firms? Mechanism discussion and performance study. Journal of Business Research, 158, 113648. https://doi.org/10.1016/j.jbusres.2023.113648

Lim, W. M., Kumar, S., & Ali, F. (2022). Advancing knowledge through literature reviews: ‘What’, ‘why’, and ‘how to contribute.’ The Service Industries Journal, 42(7–8), 481–513. https://doi.org/10.1080/02642069.2022.2047941

Lyon, T. P., & Montgomery, A. W. (2015). The means and end of greenwash. Organization & Environment, 28(2), 223–249. https://doi.org/10.1177/1086026615575332

Malmendier, U. (2018). Behavioral corporate finance. In NBER Working Paper (Vol. 25162). National Bureau of Economic Research. https://doi.org/10.3386/w25162

Malmendier, U., & Tate, G. (2015). Behavioral CEOs: The role of managerial overconfidence. Journal of Economic Perspectives, 29(4), 37–60. https://doi.org/10.1257/jep.29.4.37

McCarthy, S., Oliver, B., & Song, S. (2017). Corporate social responsibility and CEO confidence. Journal of Banking & Finance, 75, 280–291. https://doi.org/10.1016/j.jbankfin.2016.11.024

Mukherjee, D., Lim, W. M., Kumar, S., & Donthu, N. (2022). Guidelines for advancing theory and practice through bibliometric research. Journal of Business Research, 148, 101–115. https://doi.org/10.1016/j.jbusres.2022.04.042

Priem, J., Piwowar, H., & Orr, R. (2022). OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts. ArXiv. https://doi.org/10.48550/arXiv.2205.01833

Rao, N. (2016). Do tax credits stimulate R&D spending? The effect of the R&D tax credit in its first decade. Journal of Public Economics, 140, 1–12. https://doi.org/10.1016/j.jpubeco.2016.05.003

Seo, H. (2021). Peer effects in corporate disclosure decisions. Journal of Accounting and Economics, 71(1), 101364. https://doi.org/10.1016/j.jacceco.2020.101364

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

Visser, M., van Eck, N. J., & Waltman, L. (2021). Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic. Quantitative Science Studies, 2(1), 20–41. https://doi.org/10.1162/qss_a_00112

Xia, F., Chen, J., Yang, X., Li, X., & Zhang, B. (2023). Financial constraints and corporate greenwashing strategies in China. Corporate Social Responsibility and Environmental Management, 30(4), 1770–1781. https://doi.org/10.1002/csr.2453

Xu, A., Zhu, Y., & Wang, W. (2023). Micro green technology innovation effects of green finance pilot policy: From the perspectives of action points and green value. Journal of Business Research, 159, 113724. https://doi.org/10.1016/j.jbusres.2023.113724

Zahera, S. A., & Bansal, R. (2018). Do investors exhibit behavioral biases in investment decision making? A systematic review. Qualitative Research in Financial Markets, 10(2), 210–251. https://doi.org/10.1108/QRFM-04-2017-0028