Why Digital Materials Passports Succeed or Fail: It Comes Down to Human Behavior

Every manufactured product carries a hidden story—where its raw materials came from, how they were processed, how they can be recovered and reused at the end of their life. Digital Materials Passports, or DMPs, are electronic data sets designed to record exactly that story, tracking the geographical, ecological, technical, and usage properties of materials throughout their lifespan. Accessed through data carriers and shared among supply chain businesses, authorities, and consumers, these digital identity documents for materials promise to transform manufacturing: improving recyclability, speeding up procurement, increasing transparency and traceability, and boosting product quality. Yet a new position paper published in Frontiers in Manufacturing Technology argues that the technology itself is only half the story. The success or failure of DMPs, the researchers contend, hinges on something far messier—human behavior.

The study, led by Vladislav Hristov Grozev and colleagues at the Sheffield University Management School, tackles a gap that has been largely ignored in the rush toward digitalization. While research on DMP implementation has focused overwhelmingly on technical questions—data standards, interoperability, regulatory compliance—the human and organizational side of the change has received far less attention. This is a serious omission, the authors argue, because implementing DMPs across a supply chain is not merely a software installation. It is a large-scale digital change that can reshape business models, organizational structures, and everyday work processes, touching everyone from raw material providers to manufacturers, logistics firms, and recycling companies.

To understand why this matters, the researchers applied a socio-technical systems approach, a framework that treats organizations as networks of six interconnected systems: stakeholders, culture, structure, processes, goals, and technology. The core insight is that these systems cannot be optimized in isolation. Introducing DMP technology does not just change the technical subsystem; it ripples outward, requiring extra training for employees, creating new ways of working, generating new jobs, and demanding shifts in organizational mindset and priorities. When social and technical elements are misaligned, socio-technical challenges emerge—and these, rather than technical failures, may be what derails digital change initiatives.

The team paired this framework with the IGLOO model, which holds that organizational support must operate simultaneously at five levels: individual, group, leader, organizational, and omnibus—the interorganizational level that spans entire supply chains. This multi-level lens is essential for DMPs because their whole purpose is to enable data sharing across multiple companies. A support strategy confined within one organization’s walls simply cannot deliver the interorganizational coordination that DMPs require.

From this foundation, the researchers developed seven propositions, each grounded in established theories of human behavior at work. The first three tackle perhaps the most stubborn obstacle: resistance to sharing data. Employees are unlikely to share information through DMPs if interorganizational trust has not been built, if organizations operate in silos, or if sharing threatens competitive advantage. The social identity literature offers a remedy: creating conditions of common fate—a sense that ‘we are all in this together’—can forge a shared social identity across the supply chain. Practical methods include developing shared interorganizational goals, opening communication channels between leadership and teams across companies, and helping employees understand how their DMP work affects others at different stages of the manufacturing process. Evidence from other domains supports this logic: multi-agency emergency response teams during the UK COVID-19 response showed that shared difficult experiences and contact between responders increased digital interoperability between organizations.

Trust itself is the second pillar. Drawing on the integrated model of organizational trust, the paper identifies three characteristics that make data sharing feel less risky: ability, benevolence, and integrity. Employees need confidence that colleagues in other organizations can make sense of DMP data, that those partners act in the interests of the whole supply chain rather than themselves alone, and that the data exchanged will be accurate and principled. Where direct trust is hard to establish, the researchers propose creating an intermediary body—a neutral third party that controls and shares DMP data. They point to a striking real-world example from the Dutch flower sector, where traders established a not-for-profit foundation that collected payment data from all organizations, kept member details private, and provided anonymized data for informed decision-making, protecting everyone’s competitive advantage in the process.

The remaining propositions address changes within organizations. Introducing DMPs often means new business models, new key performance indicators, and new jobs—changes that can feel psychologically threatening, especially for employees worried about job security. The HERO model of healthy and resilient organizations suggests a path forward: providing systematic, planned, proactive resources such as autonomy, feedback, teamwork, and supportive leadership builds positive psychological states like engagement and trust, which in turn motivate employees to meet new goals. Leadership style matters enormously here. Transformational leaders—those who demonstrate idealized influence, articulate inspiring visions, stimulate intellectual challenge, and attend to individual needs—can sustain employee motivation and optimism throughout the upheaval. Research on small and medium German enterprises found that employees whose leaders exhibited transformational behaviors showed a greater desire to adopt digital technologies precisely because that style boosted their motivation to engage.

Work design offers another lever. To break down silos and extract real value from DMP data, employees need an integrated understanding of processes beyond their own narrow specialization. Work design theory suggests that enriching roles with skill variety, task identity, and task significance—incorporating new data skills, complete identifiable tasks, and awareness of environmental impact—fosters meaningfulness and motivation. Social characteristics such as interdependence and feedback from others can build team trust and cohesion, particularly when data specialists must collaborate with strategy specialists. And because new roles demand new competencies, the seventh proposition calls for rigorous training needs analysis combined with formal programs, self-directed learning, and informal experiential learning. Organizations that invest in a learning-oriented culture not only build digital confidence but also foster open-mindedness toward new technologies.

Timing and adaptation are critical, the authors emphasize. For large-scale changes, trust-building actions must start early, since preparing employees and organizations takes time. Learning needs should be identified and updated as technology and regulations evolve, and some propositions can be repeated or refined over time. The propositions are also adaptable to different organizational realities: companies controlling multiple production steps may implement DMPs more easily because their processes are already integrated, while smaller enterprises might roll out DMPs across all processes at once, making transformational leadership and training support especially crucial. Organizations moving slowly can initially rely on external services to create and maintain DMP data while they redesign roles and analyze training needs in the interim.

Perhaps the most important thread running through the paper is stakeholder involvement. Participatory approaches—in which employees, certification bodies, higher education institutions, customers, and industrial digital technology providers help shape the change—promote understanding, buy-in, and ownership. Employees can identify which skills they need; certification bodies can help agree on what data should be collected to build trust without sacrificing commercial secrets; technology providers can design DMP interfaces that embed task significance and social support. The authors see this human-centered approach as a stepping stone toward Industry 5.0, the emerging paradigm defined by human centricity, resilience, and sustainability. If organizations implement DMPs while ensuring both employee and organizational goals are met, the digital passport becomes more than a compliance tool—it becomes a vehicle for positive, human-centered transformation of structure, processes, goals, and culture across entire supply chains. The propositions now await real-world testing, but their message is already clear: the circular economy will not be built by technology alone, but by people who trust, engage, and learn together.

Subject of Research: Human and organizational factors in the implementation of digital materials passports across supply chains

Article Title: Behavior at work: propositions for optimizing the human and organizational challenges of digital materials passports

Article References: Grozev, V. H., Axtell, C., Zhang, H., & Nielsen, K. (2025). Behavior at work: propositions for optimizing the human and organizational challenges of digital materials passports. Frontiers in Manufacturing Technology, 5, Article 1511735. https://doi.org/10.3389/fmtec.2025.1511735

Image Credits: AI Generated

DOI: 10.3389/fmtec.2025.1511735

Keywords: digital materials passports, circular economy, socio-technical systems, organizational trust, transformational leadership, work design, training needs analysis, Industry 5.0, supply chain, digital transformation, social identity, employee involvement