This thesis aims to offer practical guidance for organisational change to successfully implement the Digital Product Passport (DPP). Additionally, it aims to identify specific AI-Nudges that can foster the DPP implementation. The DPP, as proposed by the European Commission, is a unified tool designed to capture and store comprehensive product lifecycle data. It should promote sustainability and circularity in products by ensuring traceability, transparency, and accountability across the entire supply chain. Despite its potential, successful implementation of the DPP requires organisational change and overcoming a significant challenge: the Knowing-Doing Gap. This means that knowledge is not translated into action. A qualitative research approach was used with semi-structured interviews with behavioural economics, AI and organisational change experts and thematic analysis. The findings revealed that while many organisations are aware of the DPP, fewer have progressed to actual implementation. The analysis supported the existence of the Knowing-Doing Gap, highlighting barriers such as resource constraints, abstract goals, and insufficient technological infrastructure. To overcome these barriers, Kotter’s 8-Step Model of Change was contextualised, offering actionable steps for organisations, including interdisciplinary collaboration, stakeholder engagement, data management, and establishing new norms. Additionally, the study exemplified specific AI-Nudges that can support the implementation of the DPP. These included a Reminder-Tracking AI-Nudge for the project team and employees, a Data Usage AI-Nudge for project teams, an Decision-Making AI-Nudge for purchasing departments, and a Recommendation AI-Nudge for consumers. As a result, this study provided a theoretical framework and process model for the DPP implementation.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mau-67877 |
Date | January 2024 |
Creators | Grünewald, Lilly, Huvermann, Frederike |
Publisher | Malmö universitet, Institutionen för Urbana Studier (US) |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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