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As a particular subfield of futures studies, foresight evaluation has not yet been thoroughly studied. This paper investigates research on foresight evaluation, reviewing authors, articles, journals, topics, evaluative elements, and foresight frames. We analyzed 186 academic papers published over the past 30 years. The analysis shows that foresight evaluation, which originated in Europe and partly diffused to North America and Asia, is still an emerging discipline. Research on the evaluation of foresight has covered four topics: 1) Project for Policy, 2) Future Methodology, 3) Technology, and 4) Future Impact; studies in these areas show that there is currently no active research on topics other than technology. Each of these four topics encompasses traditional evaluative elements, such as impact and quality, but few studies reflect the hopeful element of learning. Also, the results of our analysis show that the predictive and planning frames are in high demand, while less predictable frames are not. This study elucidates the reasons behind the inactive state of foresight evaluation research. This paper argues that both researchers and decision-makers have an important role in overcoming this inertia and finding new paths for continuing the development of foresight evaluation. ● Investigates the research on foresight evaluation over the past 30 years. ● No currently active research on topics other than technology. ● Among the evaluative elements, quality and impact are more prevail than learning. ● Predictive and planning are more active than others among the six foresight frames. ● Suggest a new path for continuing the development of foresight evaluation. [ABSTRACT FROM AUTHOR]

In recent years, the accelerated aging process in China has brought enormous pressure on the traditional aged care system. The private family-based aged care mode cannot resolve the contradiction between the insufficient labor force and a large elderly population. The public community-based aged care mode could effectively integrate various social resources such as housing, healthcare, land, education, etc., which may better meet diverse elderly care demands. The senior residents' evaluation of public aged care services is essential for local pension policy making, determining the local government's investment direction to some extent. Therefore, this research organizes a decision group to conduct the evaluation of alternative aged care service projects with Maslow's hierarchy-based evaluation framework. The decision group consists of senior citizens from the Xiaolingwei community in Nanjing, which is a deeply aging metropolis with the flourishing aged care service market and demand. Considering the aged residents' inherent preference differences rooted in living habits, cultural background, and risk attitude, it is essential to introduce an effective consensus model into the group evaluation to control opinion conflict and reach consensus. The current consensus models still have the following limitations: consensus models depend on the preset empirical consensus threshold, hardly reflecting the spontaneous consensus emergence; the inconsistency of group consensus opinion harms the reliability and effectiveness of group decision; the existing methods generally identify the non-cooperative behavior passively, lacking the adaptive and active management. Therefore, this paper develops the consensus emergence model driven by the social learning mechanism based on the BA scale-free network and the Bayesian learning rule, guiding the self-adaptive opinion evolution and the spontaneous consensus convergence. The novel consensus model includes three crucial parts: the environment network construction, the private cognition formation, and the individual preference modification. The proposed consensus emergence model has outstanding advantages in consensus consistency through spontaneous opinion evolution, the adaptive consensus emergence with greater consensus efficiency, and the consensus robustness under non-cooperators disturbance. [ABSTRACT FROM AUTHOR]

Identity sharing systems, regardless of their architectural models, share common vulnerabilities. These systems compel users to divulge personal information and furnish proof of identity for accessing services, leaving them susceptible to data breaches that can culminate in identity theft and jeopardize online data security. While blockchain technology offers a potential remedy, delivering enhanced security, immutability, and traceability, it simultaneously raises pertinent concerns surrounding privacy and transparency. The integration of zero-knowledge proof (ZKP) technology has emerged as a promising solution, particularly in enhancing privacy within the transparent blockchain ecosystem. Our paper conducts an exhaustive survey of the existing literature, with a particular focus on the assimilation of ZKP technology into blockchain for the secure sharing of user identities. We undertake a critical evaluation of the advancements achieved in this domain, pinpoint the formidable challenges that must be confronted, and uncover nascent opportunities for further exploration. Our contribution transcends the realms of mere summarization and analysis; we go a step further by offering recommendations drawn from real-world case studies and delineating future research directions. [ABSTRACT FROM AUTHOR]