Dare to Cheat? The Liabilities of Newness and Foreignness in Containing Sustainability Fraud in China

As stakeholder pressure to protect the environment grows dramatically, sustainability fraud—fraud and misconduct committed with sustainability data—has become a growing concern in operations and supply chain management. Many large corporations have been found guilty of making deceptive claims of being environmentally compliant.

Why do some companies cheat when reporting their environmental data, while others do not? This is the question Mei Li, associate professor of supply chain management at the University of Oklahoma, set out to answer through a research study focused on activities in China.

Li presented her findings at the August 24 Distinguished Lecture Series. She opened by sharing a personal story about what motivated her to focus the research on China, even though sustainability fraud exists at a global level.

Li’s parents retired to Boston after living and working their entire lives in Beijing. Following their move, they maintained strong social ties with friends and colleagues in China. Sadly, it wasn’t long before they began to receive what Li describes as “death calls,” or those dreaded calls about the untimely passing of a dear friend or colleague.

“Eight out of 10 times those deaths were related to some form of cancer,” said Li. “So, they strongly believe the polluted water they drank and the polluted air they breathed in, it’s a serious problem for the Chinese people.”

To the Chinese government’s credit, it, too, recognized and acknowledged the dire pollution problem. In 2015, through the Ministry of Ecology and Environment of China (MEEC), the country issued a mandate that every pollutant-producing facility in the country must install a Continuous Emission Monitoring System (CEMS) to track pollutants going into the air and water.

“So, technically, once you install these CEMS devices, the Chinese government will know exactly how much pollutants you’re putting in the air or into the water.  A big problem is solved, right? But that’s not what happened,” Li said.

When the mandate kicked in, air pollutant levels dropped drastically. However, soon after, the levels went back up again.

“According to MEEC, the information reported to them from the mandated CEMS systems said the companies were not putting excessive pollutants in the air,” Li said. “However, according to satellite images, which cannot be manipulated, the levels of pollutants went back up close to the old levels. So, something didn’t add up.”

Making sense of bad data

The Chinese government approached Li and her project team with a request that they make sense out of the data. The Ecology and Environment Ministry gave the researchers the output from each pollutant-producing facility.

“The challenge for us is that you can’t trust the data,” Li said. “You suspect there’s something funny going on with the data, but you have to make trustworthy, accurate predictions of who are the environmental violators.”

To get to the bottom of it, the team used machine learning to predict who the cheaters would be. 

“We used feature engineering, and we actually operated on the metadata, or the manner in which they were reporting, and we came up with an index to compute the data quality value,” she said. “That value can predict who is cheating on their reported data.”

Based on the prediction model, the team was able to create a list of companies they highly suspected were cheating. They gave that list to MEEC.

“The ministry sent people to manually inspect every single facility on our list, and guess what? Every single facility on our list, except one, was found to be making fraudulent claims on their data,” said Li. “The one exception facility had done the right thing; they had made the investment to improve their machines and standards.”

As an example of how the factories cheated, the environmental agents at one site found a hole cut into the intake area of the CEMS device to introduce fresh air, which diluted the polluted air. As a result, the factory’s CEMS reading seemed acceptable. 

It’s all about the Guanxi

After completing this study, Li wanted to investigate what types of firms are more or less likely to commit sustainability fraud. She developed another research study comparing newer firms with older firms and local companies with foreign companies. 

She also looked at the moderating effects of the social/political and economic environments in which the firms operate. For instance, in China firms are categorized as either monitored by the state-level agency (state controlled) or by local agencies (non-state controlled). And economic development differs between coastal provinces and inland provinces. Li examined how those factors might impact a firm’s tendency to cheat on sustainability measures.

”Older, more established firms tend to cheat more,” Li concluded from her study. “And foreign firms tend to cheat less in China.”

Li attributes the reason to a Chinese concept that derives from imperial, dynastic China and is still practiced today. It is known as Guanxi, which means social ties. Guanxi refers to social ties used to build connections with government authorities as well as to secure favors in interpersonal relationships. The concept applies to relations between organizations as well.

“Guanxi is a crucial social capital to receive more favorable treatments and resource allocations from the government authorities,” explained Li.

Guanxi also can be used to get away with unethical behavior, she noted. That’s why young firms and foreign firms are less likely to cheat on their sustainability data. They have the liability of not having the social ties needed to escape accountability.

“If it’s an older firm, they probably tell their buddy, ‘Hey, I did this, the government didn’t catch me, so go ahead, you do that, too.’ A younger firm, without establishing that network, doesn’t get that insider information of how to cheat,” Li explained. “Therefore, they wouldn’t be able to learn that trick, right or wrong.”

The social/political and economic environment are also important factors influencing sustainability fraud, the study revealed. For example, when firms are state controlled, they have less opportunity to capitalize on their social capital, or Guanxi, and thus are less likely to cheat. 

“We found that state attention does matter,” Li said. So, the difference between foreign firms and local firms, the difference between new firms and young firms, will be lessened if the firm is under state control.”

She also found that foreign firms are less likely to commit sustainability fraud when the local economy is more developed. Li suggested that is partly because better-developed areas can afford to spend more on monitoring the environment. But economic development does not make a difference in whether new or older firms cheat.

Doing good, saying good and cheating good

In concluding her presentation, Li talked about the contributions of the research both to theory and practice. One theoretical contribution is to corporate social responsibility literature. Past research has examined what Li calls “doing good” and “saying good.” 

Doing good is true corporate social responsibility. Saying good includes practices such as greenwashing and brownwashing, when firms decouple their actual sustainability practices from what they say. 

“The construct we’re trying to study is different from doing good or saying good,” Li said. “It’s actually ‘cheating good.’ You’re cheating by saying you meet a standard. 

“It’s a separate concept because it’s a much more extreme case, where the firm has to violate environmental regulations. And on top of that, they’re masking their misconduct.”

Another contribution the study makes is introducing the concepts of the liability of newness and liability of foreignness into the supply chain literature. Li suggests that those liabilities—from lacking important social networks—may also apply in various supply chain functions.

“Does liability of newness play a role in sourcing?,” Li questioned. “That means that new firms actually have a harder time sourcing from suppliers than established firms. In operations management, can the new firm operate as effectively as older firms due to their lack of social capital? Does a newer firm have a harder time establishing their distribution channels?”

Li said these are all good questions for future research. 

From an applied perspective, the study is enlightening for emerging economies where the legal and regulatory systems are not yet stable, Li noted. The lack of regulation leaves room for informal mechanisms to intervene with business operations and possibly encourage fraud. 

For policymakers, Li cautioned that her findings should make them mindful of Gresham’s Law, which states that bad money drives out good money. In a sustainability context, it applies when older and local firms get away with fraud, while newer and foreign firms incur extra costs complying with regulations.

“If the policymaker does not intervene and lets this go,” Li said, “eventually the firms who can survive, the firms who stay, are those bad firms. So bad firms drive out good-behaving firms.”

About the speaker:

Meo Li
Mei Li

Mei Li is an associate professor of supply chain management at the University of Oklahoma. Her research has been published in a variety of leading journals, including the Journal of Marketing, Journal of Operations Management, Journal of Supply Chain Management and Journal of Business Logistics, among others.

Li earned her PhD in supply chain management from Arizona State University. She served on the faculty of Lehigh University, University of Notre Dame and Michigan State University before moving to Oklahoma in 2020.

She serves as associate editor for Data Science and Management Journal and is a member of the CARISCA Academic Board.




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