Asia-Pacific companies integrate ESG metrics into executive incentive plans amid demands to promote sustainable business practices
- Bias Rating
10% Center
- Reliability
80% ReliableGood
- Policy Leaning
10% Center
- Politician Portrayal
N/A
Continue For Free
Create your free account to see the in-depth bias analytics and more.
Continue
Continue
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates. Already a member: Log inBias Score Analysis
The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
10% Positive
- Liberal
- Conservative
Sentence | Sentiment | Bias |
---|---|---|
Unlock this feature by upgrading to the Pro plan. |
Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative
Contributing sentiments towards policy:
59% : "Metrics related to human capital and reduction of carbon emissions received the most attention across all ESG categories in Asia-Pacific, according to WTW.53% : "More companies are incorporating executive incentives with ESG measures, and pay committees see this as an important tool to ensure alignment with the interests of all stakeholders, including long-term interests of shareholders," he said.Publicly listed companies that have declared their social ambitions, established foundations, endorsed the United Nations Sustainable Development Goals, or are subject to regulatory frameworks are particularly proactive in adopting these metrics, said Hays' Smith.
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.