Study Identifies ‘Neural Loyalty’ as Key to Bridging Gap Between Sustainable Intentions and Consumer Action

A recent study published in the journal Sustainability explores the neurocognitive mechanisms that shape sustainable consumer behavior.

sustainable shopping label, recycled materials

Image Credit: Black Salmon/Shutterstock.com

By examining how emotional and cognitive processes work together to influence green purchasing intentions, researchers introduced a new model grounded in dual-process theory and neuromarketing. Central to this framework is the concept of neural loyalty - a key mediator that helps translate pro-environmental intentions into actual behavior. The goal was to offer a fresh approach to closing the persistent gap between what consumers intend to do and what they actually do when it comes to making sustainable choices.

Rethinking How We Understand Consumer Behavior

With environmental concerns becoming more urgent, research on consumer behavior is shifting away from purely rational models toward those that also factor in emotional and neurocognitive influences. Traditional approaches often fall short in explaining why people who care deeply about the environment don’t always make eco-friendly choices - a disconnect driven by both cognitive and emotional barriers.

Recent advances in neuromarketing and cognitive neuroscience show that our decisions are shaped by a mix of conscious reasoning and subconscious emotion. Dual-process theory offers a useful lens here, distinguishing between fast, emotion-driven thinking (System 1) and slower, analytical reasoning (System 2). For pro-environmental intentions to turn into real behavior, both systems need to be engaged.

Mapping the Emotional and Cognitive Drivers of Green Buying

To better understand this interplay, researchers developed and validated a dual-process neurocognitive model. They focused on three main factors:

  • Neurocognitive Emotional Processing (NEP)
  • Neurocognitive Cognitive Control (NCC)
  • Emotional Engagement with Ecological Stimuli (EEE)

Each of these was hypothesized to influence green purchase intention (GPI), either directly or through neural loyalty (NLG) - a construct that captures the emotional-cognitive bond consumers form with green products.

To test the model, the team used partial least squares structural equation modeling (PLS-SEM), a method well-suited to complex, multi-variable analyses. They surveyed 276 consumers across Romania, Poland, and the Czech Republic - countries actively moving toward more sustainable consumption. Participants were selected based on their engagement with eco-friendly products like organic foods and biodegradable detergents.

The survey drew on established neuromarketing and sustainability literature, using 5-point Likert scales to measure affective (e.g., empathy, pride) and cognitive (e.g., trust in environmental certifications) dimensions.

Key Findings: Emotions and Logic Work Hand in Hand

The results confirmed the model’s validity. All structural paths were statistically significant (p < 0.05), and the model showed strong explanatory power, with R² values of 0.68 for GPI and 0.72 for NLG.

  • NEP had a direct, significant impact on both NLG and GPI. Visual and symbolic cues - like clean nature imagery or sustainability labels - triggered emotional responses that strengthened brand attachment and moral satisfaction.
  • NCC also played a crucial role. Consumers who took time to assess sustainability claims - such as long-term environmental impact - were more likely to trust and prefer green brands, reducing their susceptibility to misleading marketing.
  • EEE emerged as a strong predictor of NLG and GPI. Emotions such as pride, empathy, and concern for future generations deepened consumers' psychological connection to sustainable products and increased their willingness to pay premium prices.

Crucially, NLG was found to mediate the effects of all three drivers on GPI. This suggests that emotional and cognitive reinforcements, over time, can solidify one-off green choices into lasting habits.

Practical Takeaways for Green Marketing

The findings offer clear guidance for marketers aiming to promote sustainable products. It’s not enough to simply provide information. Campaigns need to stir emotions - like empathy - while also delivering transparent, fact-based claims. For instance, visual storytelling that links individual actions to global outcomes can build emotional investment, while credible labels and certifications reinforce rational trust.

This approach helps foster neural loyalty, encouraging repeat purchases and deeper commitment to sustainability.

Beyond marketing, the model has applications for policymakers and NGOs. By appealing to both emotional and rational drivers, behavioral interventions can be more effective in encouraging lasting change and narrowing the gap between intention and action.

Conclusion and What’s Next

This study marks a meaningful step forward in applying neuroscience to sustainable consumer behavior. By validating a dual-process model and introducing neural loyalty as a mediating force, the researchers offer a clearer picture of why good intentions don’t always lead to green actions - and what can be done about it.

Future research could take this further by using tools like functional magnetic resonance imaging (fMRI) to observe real-time brain activity, or by comparing results across cultures to see how emotional and cognitive factors vary globally.

Understanding how affective and rational processes work together - via neural loyalty - opens up new avenues for designing policies, products, and campaigns that genuinely move the needle on sustainable consumption.

Journal Reference

Petrescu, M. & et al. (2025, November). Dual-Process Neurocognitive Pathways Bridging the Intention-Behaviour Gap in Sustainable Consumer Decisions. Sustainability, 17(22), 10141. DOI: 10.3390/su172210141, https://www.mdpi.com/2071-1050/17/22/10141

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Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

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