Accept Me as I Am or See Me Go: A Qualitative Analysis of User Acceptance of Self-Sovereign Identity Applications

Self-sovereign identity represents a novel phenomenon aiming to innovate how entities interact with, manage, and prove identity-related information. As with any emerging phenomenon, user acceptance represents a major challenge for the adoption of Self-sovereign identity. Since previous initiatives for digital identity management solutions have not been successfully adopted while at the same time their benefits are largely driven by network effects, user acceptance research is of particular importance for Self-sovereign identity. Therefore, we investigate the user acceptance of Self-sovereign identity by conducting a qualitative interview study. We contribute novel variables to existing theory and offer guidelines for building Self-sovereign identity systems

Enabling end-to-end digital carbon emission tracing with shielded NFTs

In the energy transition, there is an urgent need for decreasing overall carbon emissions. Against this background, the purposeful and verifiable tracing of emissions in the energy system is a crucial key element for promoting the deep decarbonization towards a net zero emission economy with a market-based approach. Such an effective tracing system requires end-to-end information flows that link carbon sources and sinks while keeping end consumers’ and businesses’ sensitive data confidential. In this paper, we illustrate how non-fungible tokens with fractional ownership can help to enable such a system, and how zero-knowledge proofs can address the related privacy issues associated with the fine-granular recording of stakeholders’ emission data. Thus, we contribute to designing a carbon emission tracing system that satisfies verifiability, distinguishability, fractional ownership, and privacy requirements. We implement a proof-of-concept for our approach and discuss its advantages compared to alternative centralized or decentralized architectures that have been proposed in the past. Based on a technical, data privacy, and economic analysis, we conclude that our approach is a more suitable technical backbone for end-to-end digital carbon emission tracing than previously suggested solutions