Digital Product Passports (DPPs) are gradually being made mandatory under the European Union’s Ecodesign for Sustainable Products Regulation (ESPR). Whether they succeed in promoting sustainable consumption will depend on how well consumers engage with the information they provide. To date, regulatory and supply chain perspectives on DPPs have been widely researched. However, the emerging literature on DPPs from a consumer perspective remains fragmented with a predominantly single-country focus and few studies delivering insights into the psychological drivers of consumer acceptance of DPPs from a holistic perspective. This paper seeks to investigate drivers of consumer intention to use DPPs using the Extended Technology Acceptance Model. The model is extended to include Subjective Knowledge and Trust. An online cross-sectional consumer survey of 1488 respondents across four European markets (Denmark, Spain, Sweden and Switzerland) was analysed using Partial Least Squares-Structural Equation Modelling. Results show that DPPs are poorly known (22.4% of respondents were aware of them) but positively evaluative in most other dimensions. The Extended TAM explains a variance of 76% (R2=0.76) in Intention to Use. Trust has the strongest direct effect on Perceived Ease of Use (β=0.66). Trust also has an important effect on Usefulness. Subjective Knowledge has an effect on Usefulness through Trust. Perceived Usefulness has the strongest direct effect on Intention to Use. We posit that there is a sequence to information circulated, with awareness and credibility signals preceding usefulness. The paper provides cross-national evidence on DPP acceptance and finds Trust as an important adoption mechanism, broadening technology-acceptance theory and providing practical guidance for policymakers and firms on the sequencing of awareness, credibility and usefulness messaging within the framework of DPPs transitioning to mandatory implementation.
Wearable bioelectronics have emerged as indispensable platforms for next-generation personalized medicine, unlocking unprecedented capabilities for continuous, real-time physiological monitoring. As the vital bridge between rigid devices and soft tissues, hydrogel biointerfaces face a critical trilemma of sustainability, performance, and safety, as conventional petrochemical matrices often trigger environmental burdens, cytotoxicity, and interfacial instability. Addressing these challenges, this review explores the development of sustainable hydrogel biointerfaces, navigating their trajectory from green design to wearable healthcare applications. After briefly establishing foundational design principles based on renewable feedstocks and benign fabrication, we place our primary focus on their transformative healthcare applications. Specifically, we systematically evaluate recent breakthroughs in leveraging these sustainable hydrogel biointerfaces for non-invasive electrophysiological monitoring, motion monitoring and electronic skin, biochemical sensing, wound monitoring and therapy, and self-powered wearable systems. Finally, we highlight critical bottlenecks hindering clinical translation, providing forward-looking perspectives on engineering more degradable and clinically robust bioelectronic platforms.
Green growth has become an important pathway for reconciling economic development with environmental sustainability, increasing the need to understand how it is discussed and evaluated across digital communication environments. This study examines the cognitive and affective dimensions of stakeholder-related online discourse on green growth using social media analytics. The final analytical dataset comprises 1799 English-language posts collected from LinkedIn, Reddit, TikTok, Twitter/X, and YouTube. The methodological framework integrates lexicon-based sentiment and emotion analysis, Latent Dirichlet Allocation (LDA) topic modelling, correspondence analysis, and non-parametric statistical testing. The sentiment analysis indicates a predominantly positive lexical orientation, although validation results suggest that individual-level sentiment classifications should be interpreted cautiously. LDA topic modelling, conducted on 1792 posts retained after vocabulary filtering, identifies three principal thematic domains interpreted as textual proxies for cognitive framing: Sustainable Development and ESG Transition (29.97%), Climate, Energy and Net-Zero Transition (44.64%), and Circular Economy and Sustainable Business Practices (25.39%). Emotion profiles differ significantly across thematic domains, while cross-platform analysis reveals systematic variation in sentiment, emotional expression, and thematic composition. Correspondence analysis further indicates platform-specific associations between social media environments and thematic domains. Overall, the findings demonstrate systematic associations between thematic framing and affective expression in green growth-related online discourse, while avoiding causal interpretation of these relationships. The study contributes to sustainability communication research by integrating cognitive and affective dimensions within a multi-platform analytical framework and provides practical insights for designing context-sensitive green communication strategies.
This article bridges the gap between the necessary technical knowledge, experience, and equipment for reverse engineering, and the ability to conveniently reconstruct and 3D print parts needed for everyday life repairs with no prior CAD knowledge. This overview analyzes all quintessential steps of this process, including taking a broken or non-broken reference component, capturing and digitizing its respective dimensions, processing the captured information, producing and printing a corresponding 3D model. Within this multi-stage pipeline, we have identified three crucial challenges, specifically: (1) Consistently capturing complete closed point-cloud models with one continuous 3D scan; (2) Receiving mesh models as outputs for further CAD reconstruction; (3) Implementing automated modeling for reconstruction purposes within existing CAD workflows. By doing so, this paper has identified the need to rethink digitization methods, highlighting the necessity to transition from digitization methods that produce mesh models to parametric models – objects that enable streamlined integration within existing CAD software. This reduces the overall project pipeline complexity and increases automation through integration of CAD APIs, making 3D-printed parts more accessible to everyone. The aforementioned generates tangible contributions towards a more sustainable future, promoting the circular economy by extending product life cycles, reducing shipping-associated emissions, and preventing industry overproduction, all enabled through no-effort home repairs with 3D printing.
