CSU Pueblo professors are helping companies predict the hidden value of sustainability investments

When people hear “green initiatives,” they think recycling programs, electric vehicles, and maybe LED lights. He-Boong Kwon, Ph.D. at Colorado State University Pueblo has discovered something far more complex lurking beneath these surface-level efforts. His custom neural network modeling approach reveals that the real power of environmental programs lies not in what they do alone, but in how they interact with a company’s other strategies in ways no spreadsheet analysis could ever detect.

“Rather than finding out yes or no, I try to find out how much and what shape,” Kwon explains from his office at the Hasan School of Business. “That’s why the study is very new.”

For years, companies have wrestled with a basic question: Does going green help or hurt the bottom line? Some studies suggest environmental initiatives drain resources. Others argue they boost profits. Kwon’s research, co-authored with colleague Brad Gilbreath, Ph.D., was recently published in Annals of Operations Research – a peer-reviewed journal – and suggests both camps have been asking the wrong question entirely.

Beyond the Green Debate

Traditional research has examined environmental, operational, and innovation strategies in isolation. Think of it like studying the ingredients of a recipe separately instead of understanding how they work together. Kwon realized that companies don’t operate in silos. Their green initiatives interact with research and development efforts and operational efficiencies in complex, often unpredictable ways.

“Many researchers studied the isolated impact,” Kwon notes. “They neglected how much they interact together.”

This insight led him to develop what he calls a “dual network approach” using artificial intelligence. Unlike conventional spreadsheet analysis that might show whether something is good or bad, Kwon’s algorithm detects hidden synergy patterns. It reveals not just whether combinations of strategies work, but exactly how much impact companies can expect and what that impact looks like over time.

The Power of Prediction

The algorithm’s strength lies in its ability to think like a human brain, learning from data patterns across more than 300 companies. Where traditional methods might miss subtle interactions between, say, sustainability investments and R&D spending, the AI identifies complex, non-linear relationships that can dramatically affect a company’s market value.

“By having  combinations of green initiatives, R&D investments, and operations-improvement programs appropriate for their organization, companies can expect a (definitive) potential outcome in the future,” Kwon explains. “Prediction is the key word; our approach enables finding the sweet spot of initiatives and investments.”

For local manufacturers, this could be transformative. Consider CS Wind, the South Korean company that purchased Vestas’ wind turbine facility in Pueblo in 2021. Using Kwon’s approach, such a company could predict how investments in emissions control might interact with its existing operational efficiency to impact stock value and profitability.

The algorithm goes beyond crunching numbers. It provides specific guidance based on each company’s unique situation. A railroad company like those operating through Pueblo might discover its existing operational excellence creates opportunities for green investments that wouldn’t make sense for a smaller competitor.

One Size Doesn’t Fit All

This personalized approach addresses what Kwon sees as the biggest misconception about environmental initiatives: that they’re universally good or bad for business.

“It really depends on the company’s situation, the company’s potential capability,” he emphasizes. “That’s why one size doesn’t fit all.”

Some companies have resource slack that makes green investments profitable. Others operate so efficiently that additional environmental spending might actually reduce returns. The algorithm helps distinguish between these scenarios, providing managers with precise predictions rather than generic advice.

This nuanced understanding could benefit Pueblo’s diverse industrial base. Manufacturing companies, energy producers, and logistics firms each face different constraints and opportunities. Kwon’s research suggests that cookie-cutter approaches to sustainability often fail because they ignore these fundamental differences.

Breaking Down Silos

Beyond predicting outcomes, the research highlights a structural problem many companies face: departmental silos. Environmental teams, R&D groups, and operations managers often work independently, missing opportunities for synergy.

“Companies don’t know how much impact they can expect,” Kwon observes. “That’s why that type of approach was somewhat very rare up to this point.”

His algorithm encourages cross-functional thinking. Instead of asking whether to invest in green technology or operational improvements, companies can optimize combinations of both. The AI might reveal that a modest investment in emissions control, combined with existing R&D capabilities, generates returns that neither strategy would achieve alone.

Local Innovation on the Global Stage

The research emerges from an unlikely setting. CSU Pueblo, a regional comprehensive university, isn’t typically associated with cutting-edge business analytics. Yet Kwon’s work is drawing attention from others who study operations management and efficiency  and could influence how companies worldwide approach sustainability.

“I hope companies start working with people like Kwon to learn about these ideas a bit more,” says co-researcher Gilbreath. “We’re always talking about the lack of communication between academia and industry. The approach Dr. Kwon originated, while complex, is important and can be impactful.

The collaboration represents exactly the kind of practical research that could benefit local businesses. Southern Colorado’s economy includes manufacturing, energy, and transportation companies that could all use more precise tools for evaluating sustainability investments.

Looking Forward

Kwon plans to extend his research to medium-sized companies and focus on specific environmental initiatives like waste control and emissions reduction. The goal is making the algorithm more accessible to businesses that can’t afford extensive consulting but need better decision-making tools.

The implications extend beyond individual companies. As environmental regulations tighten and consumer preferences shift toward sustainable products, businesses need sophisticated ways to navigate these changes. Kwon’s algorithm offers a data-driven approach that moves beyond simple cost-benefit analysis.

For Pueblo’s business community, the research represents an opportunity to lead rather than follow. Companies that understand how to optimize combinations of environmental, operational, and innovation strategies may find competitive advantages their peers miss.

“Some great new innovations and ideas can come out of green initiatives,” Gilbreath notes. “You might just be working on green initiatives, but you might come up with ideas that will affect your other operations.”

In a region where manufacturing meets environmental responsibility, that kind of insight could prove invaluable. The question isn’t whether businesses should invest in sustainability. It’s how to do it smartly, with the kind of precision that generative artificial intelligence can provide.

This research was conducted at Colorado State University Pueblo’s Hasan School of Business. Dr. Kwon has been a faculty member since 2012, focusing on performance analysis, sustainability, and technology management.