Weathering the media storm over the sustainability crisis

When facing sustainability backlash, strategic communication and transparency are key, a new study finds

Featured faculty: Zhang Qi
Written by Putro Harnowo

The global community is increasingly taking a stand on climate change. In July this year, the World Court called out countries failing to meet goals outlined in the Paris Agreement as violating international law, supporting the decision made by the Inter-American Court on Human Rights that a healthy climate is a human right.

While these advisory opinions are not legally binding, a growing number of climate change-related lawsuits are emerging worldwide. Businesses are held accountable for their contributions to or inaction on greenhouse gas emissions and for making false claims about their net zero commitments, a practice known as “greenwashing.”

Recent cases include a US$1.16 million fine imposed on online fashion retailer Shein by an Italian regulator for misleading environmental claims, and legal actions by the Australian consumer watchdog against the producer of popular sunscreen brands, Hawaiian Tropic and Banana Boat, over the claims of reef-friendly products.

These trends signal businesses to double down on or, at the very least, remain mindful of their environmental, social and governance (ESG) efforts. “Reputational damage unfolds quickly as negative climate news sparks public scrutiny, spreading rapidly across the media,” says Zhang Qi, Assistant Professor of Accounting at the Chinese University of Hong Kong (CUHK) Business School.

When facing an ESG crisis, Professor Zhang notes that issuing public statements in a timely manner is critical for businesses to mitigate the damage. However, companies often face challenges in weighing their options. Some prefer to disclose detailed information, and others choose vague messages, corporate lingo or even remain silent. “Negative news amplifies criticism and forces firms to respond, but the responses can either benefit or backfire,” he adds.

In a paper titled Responding to climate change crises: firms’ trade-offs, Professor Zhang and his co-authors underline that sharing information early is crucial for maintaining public trust, and disclosing verified information, such as audited reports, can enhance credibility and lower the risk of further damage. “Without credible, substantive information directly addressing the environmental incident, firms risk losing stakeholder trust, facing boycotts, or experiencing sustained negative sentiment.”

Although giving out detailed information is effective, firms may strategically balance it with a softer approach. For instance, when the consequences of giving less detailed information are negligible, the firm’s established reputation can substantiate allusive statements, but this only works if such reputation exists through the history of publishing ESG reports. So, how to tailor a media strategy that effectively addresses environmental crises threatening a company’s reputation?

Machine learning and social media can help

Along with Felix Fritsch of the University of Mannheim and Xiang Zheng of Nanyang Business School, Professor Zhang leverages machine learning to look at how companies balance different approaches when deciding what to say about climate issues after negative media coverage. For this purpose, social media provides an ideal setting for examining corporate climate-related disclosures, due to its speed, reach and flexibility.

Specifically, the researchers turned to Twitter, which later rebranded to X in July 2023, and developed Climate-TwitterBERT that combines a keyword discovery algorithm with bidirectional encoder representations from transformers (BERT), a language model developed by Google. The researchers then analysed tweets posted by various firms from 2007 to 2020 and were able to pick 136,899 tweets relevant to climate change crises.

“We cover all US public companies with active corporate Twitter accounts, which naturally includes many well-known brands experiencing environmental incidents related to greenhouse gas emissions, global and local pollution, biodiversity or landscape impacts, and waste management,” says Professor Zhang.

“Reputational damage unfolds quickly as negative climate news sparks public scrutiny, spreading rapidly across the media.”

Professor Zhang Qi

The language model was further fine-tuned to categorise tweets into three types: hard responses, soft responses and promotional tweets. Hard responses provide verifiable and measurable information, such as emission reports detailing specific emissions data and quantitative progress toward climate targets. Soft responses reflect vague messages, including aspirational remarks about a commitment to sustainability without specific data and statements on moral positioning on climate issues. Promotional tweets focus on marketing green products and are excluded from analyses.

Their analyses found hard responses generate greater engagement, as measured by number of likes, retweets and replies, suggesting that the public appreciates empirical evidence the most. “Firms in the utilities, consumer cyclicals and basic materials sectors are most likely to issue hard climate disclosures,” he adds. “These industries face higher climate exposure and stakeholder scrutiny, increasing the incentive to provide verifiable information.”

Different problems require bespoke solutions

To understand the distinct approaches employed by the firms, the researchers classify environmental incidents based on media attention. An incident is of low influence if small NGOs, local media and local government report it. Medium-influence are covered by national media and government, as well as international NGOs. Highly influential ones are those covered by international media.

Soft responses typically follow low-influence incidents, but medium-influence crises prompt hard responses. High-influence disasters trigger both responses, supporting the idea that high-profile cases pressure firms to act across multiple fronts. Firms are 37 per cent more likely to disclose hard responses within three days of the incidents, particularly driven by medium and high influences.

Furthermore, having previously published ESG reports gives firms a higher degree of flexibility in deploying hard and soft responses. In contrast, firms that never issued ESG reports tend to avoid providing soft responses, but are also very unlikely to provide hard responses, making the best use of silence.

Firms with ESG reports dealing with low-influence problems tend to use soft responses to provide a quick and straightforward approach. When medium-influence incidents arise, these firms prefer to elicit a hard response as the public expects a substantive explanation. Sustainability reports act as a buffer, allowing firms to respond with initial messages that may be irrelevant and provide more detailed information later.

It is worth noting that not all ESG reports are assured by a credible third party, such as an accounting or audit firm. Firms with assured reports have higher chances of issuing hard responses compared to those with unassured reports. Third-party verification strengthens the substantive messages to deal with medium and high-influence crises.

Interestingly, firms with unassured ESG reports are more likely to respond to non-environmental issues with hard responses on climate change to showcase their commitment to sustainability. However, firms with verified ESG reports tend to respond to non-environmental issues simply with soft responses.

Strengthening ESG disclosures with AI

While the study was conducted using social media data, Professor Zhang believes that the findings can be applied to broader platforms, although the magnitude may differ. “The underlying mechanism should apply across media channels,” he says. “Incidents covered by national or international media outlets tend to elicit hard responses, but whether traditional channels like broadcast and print media exert a stronger effect than social media remains uncertain.”.

ESG issues comprise three core elements. While climate action is powered largely by the environmental piece, ignoring the social and governance sides would be a costly blind spot. As the machine learning model used in the study now focuses on environmental issues, further refinement will be extended to analyse disclosures across wider aspects. “Our model is a general BERT-based framework that can be adapted to other ESG topics. While our current study focuses on Twitter and US firms, future work will extend the approach to different ESG dimensions such as labour practices and diversity.”

Amid the increasing scrutiny on sustainability issues and the advancement of technology, the study opens a higher possibility of applying artificial intelligence (AI) to improve ESG disclosure practices and identify greenwashing. Having said that, achieving greenwashing detection with AI requires clear terminologies and categories, robust fact-claim training datasets and refined models, which means much more needs to be done to make automated greenwashing detection feasible.

As recent large language models can further link the company’s ESG claims to external evidence, such as news articles, financial reports and regulatory filings, enabling scalable fact-checking, Professor Zhang anticipates that these technological breakthroughs will eventually provide easier access for stakeholders to monitor firms’ disclosure practices, forcing companies to provide truthful and high-quality ESG information.