How Have Corporate Codes of Ethics Responded to an Era of Increased Scrutiny?
Saved in:
| Title: | How Have Corporate Codes of Ethics Responded to an Era of Increased Scrutiny? |
|---|---|
| Authors: | Loughran, Tim1 (AUTHOR) Loughran.9@nd.edu, McDonald, Bill1 (AUTHOR), Otteson, James R.1 (AUTHOR) |
| Source: | Journal of Business Ethics. Apr2023, Vol. 183 Issue 4, p1029-1044. 16p. 9 Charts. |
| Subject Terms: | *Corporations, Organizational ethics, Scandals, Environmental responsibility, Sustainability, Corporate governance, Social responsibility of business |
| Abstract: | Over the past decade, corporate scandals have proliferated. These scandals, along with the emergence of the #MeToo movement and Environmental, Social, and Corporate Governance (ESG) mandates, have increased the scrutiny of corporations' ethics culture. How have companies responded in terms of the language appearing in their public ethics documents? We compare the Code of Ethics in 2008 versus 2019 for a sample of S&P 500 firms. For the vast majority of firms, their Code of Ethics lengthened, with the average 2019 code having 29% more words (about 1760 words) than the 2008 average. The language of the codes has also changed. Words such as bribery, corruption, sustainability, speak up, bullying, slavery, and human rights all saw significantly higher usage in the later period. We review possible reasons for the dramatic changes and suggest what questions remain about the motivations behind them. Whether the changes we observe are primarily intrinsically motivated or simply market responses to public pressures is yet to be determined. What is clear from our findings is that society seems to be entering a new age of increasingly moral—or, at least, moralized—corporate governance. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Business Ethics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
