Digging into the digital shopper's mind – Constructor University researchers develop framework for ethical customer digital twins

As digital commerce continues to evolve, understanding the complex emotional and cognitive drivers behind consumer choices has become vital for sustainable development. A breakthrough study by researchers at Constructor University introduces an innovative, analytics-driven method for building ethical Customer Digital Twins (CDTs). Published in the March 2026 issue of the Decision Analytics Journal, the research pioneers a way to combine neuromarketing techniques with social media text analysis to model how consumers process ethical and sustainability-focused information during online shopping – laying the foundation for the future of eCommerce.

Developed by Constructor University alumna Ama Anomwaa Okyere Sefa, Mohammadreza Rezaei, Ph.D. researcher, and Prof. Dr. Omid Fatahi Valilai from the Emerging Technologies in Industrial Engineering (EITIE) research group, the study bridges data science and behavioral psychology. While traditional eCommerce analytics rely heavily on click rates and static surveys, this new framework supports the development of more realistic virtual representations of consumer states by analyzing both implicit neural activity and explicit text responses.

A fusion of brainwaves and language processing

To capture how consumers truly feel, the researchers designed an experiment within a fast-fashion e-commerce setting. Participants wore electroencephalography (EEG) headsets to monitor implicit indicators like mental workload, attention, and emotional valence in real-time. They were then exposed to ethically framed information such as sustainability cues, and provided written feedback, which was analyzed using advanced Natural Language Processing (NLP).

The results show that understanding consumer feelings requires considering both customers’ explicit written feedback and implicit EEG responses as complementary sources of insight. In some cases, what participants wrote did not fully align with what their brain activity suggested. By demonstrating this partial gap between expressed sentiment and physiological response, the paper highlights the need for more robust, temporally aware digital architectures that can better capture the complexity of consumer emotions and decision-making.

The future of sustainable industry 4.0

The project is rooted in the EITIE mini-lab's ongoing mission to analyze consumer behavior in Industry 4.0. To expand on these findings, the research team is already planning next-stage experimental approaches. These will incorporate Virtual Reality (VR) and Augmented Reality (AR) to build even more immersive and realistic testing environments. Ultimately, this foundational data will help designers and marketers build better intervention strategies, digital tools, and communications that encourage eco-friendly habits.

Furthermore, this research directly supports broader efforts toward transparent, circular value chains. By providing clear evidence on how consumers react to ethical information, the framework offers immediate value to ongoing European sustainability initiatives, such as the Textile Digital Product Passport under the EU HORIZON SORT4CIRC project. Linking consumer engagement with extended producer responsibility ensures that business actions can be aligned with circular-economy goals across the entire textile ecosystem.

Prof. Dr. Omid Fatahi Valilai emphasized the downstream societal value: “This paper demonstrates a practical basis for integrating neuroscience-informed signals with NLP sentiment analytics, supporting digital twins that are more realistic and responsible. As Primary Coordinator for the Textile Digital Product Passport in the EU HORIZON SORT4CIRC project, I see direct value here: better evidence on consumer reactions can inform design-for-circularity communication and help align business actions with circular-economy goals.”

A step toward an AI-supported digital ecosystem

Beyond technical data fusion, this work contributes to the EITIE research group’s broader path toward using AI tools, including LLM-based agents, under human oversight to support sustainability improvements in digital ecosystems. Such systems can use complementary information from written feedback and EEG-based indicators to support deeper analysis, prediction, and interpretation of customer behavior in response to sustainability-related information.

By detailing both the technical possibilities and the boundary conditions required for responsible deployment, Constructor University researchers have established an important baseline for the next generation of transparent, ethically aligned digital retail ecosystems. These insights can support future AI-assisted tools that help design better interventions, improve sustainability-related decision-making, and encourage more eco-conscious consumer behavior.

“Our findings show that written feedback and EEG signals provide complementary insights rather than a simple one-to-one match,” said Mohammadreza Rezaei. “This study is an important foundation for our broader research program. In the next stages, we will expand our experimental approaches, including the use of VR and AR, to create a stronger basis for designing tools that encourage more sustainability-related consumer behavior.”

The paper, “An analytics-driven method for building ethical customer digital twins using neuromarketing and social media data,” is available fully open-access in the Decision Analytics Journal, Volume 18, March 2026.