【影响因子】10.884
【主题类别】
区块链治理-市场治理-元宇宙
【Abstract】The aim of this paper is to identify the characteristics of advertising in the metaverse and its implications for brands and society. A group of 35 experts representing advertising agencies and brands from Central and Eastern Europe were interviewed. The findings are presented in the form of a conceptual model that provides a cartography for the landscape of metaverse advertising. Our results demonstrate that metaverse advertising uses existing formats (e.g. billboards, product placement), while also developing new ones (e.g. automated avatars, virtual products, and branded spaces). In addition, metaverse advertising is more focused on brand building than on direct, measurable impact. Advertising in the metaverse is not as precisely targeted as it is on the internet. Given their high up-front costs, these activities are currently more suitable for multinationals and well-known global brands. Metaverse advertising is not perceived to be associated with elevated brand risk. However it is burdened with myopia, understood as a lack of long-term perspective. Our findings reveal three stakeholder personas representing different approaches to metaverse advertising; including Cautious Pioneers, Empathic Pragmatists, and Blockchain Enthusiasts. We conclude by documenting the social consequences, capturing shifts towards automated communication, digital ownership, and the metaverse's potential to replace social media.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Metaverse; Advertising; Virtual worlds; Brands; Society
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 实证数据
【Author】 Bojkovic, Zoran S. Bakmaz, Bojan M.
【影响因子】9.030
【主题类别】
区块链应用-实体经济-社交媒体
【Abstract】
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 编辑社论
【影响因子】7.307
【主题类别】
区块链应用-实体经济-车辆领域
【Abstract】The rapid evolution of vehicular communication technologies in recent times necessitates robust security measures and enhanced road safety protocols. Integrity of data shared between vehicles, their Digital Twins (DT) and road side units is at stake. Intrusion in these data can potentially lead to misinformation in Advanced Driving Assistance Systems (ADAS) causing serious consequences upon road safety. These include improper detection of drunk driving behaviors. In this domain, Web 3.0 emerges as the overarching approach that can transform security of vehicles and ensure road safety. This paper explores the potential of Web 3.0 and its key enabling technologies to establish a VEhicular meTAVERSE (Vetaverse) utilizing edge-based DTs of the vehicles to process their dynamics shared in real-time, and based on its deep learning models, predict whether the driving behavior is drunk or sober. This Deep Neural Network (DNN) performs these predictions with 96% accuracy. It secures all Vehicle-to-Digital Twin (V2DT) communications via Multichain- a horizontally scaled parallel blockchains platform that tamper proofs each bit of sensor data, and optimizes transaction validation time to leverage vetaverse security. Results reveal that this framework is accurate and computationally lightweight in comparison to existing state-of-the-art, and brings Web 3.0 to the crucial road safety use-case.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Web 3.0; Metaverse; Digital Twin; Artificial intelligence; Augmented reality
【发表时间】2025
【收录时间】2024-11-12
【文献类型】 理论模型
【Author】 Yu, Qi Zhang, Min Mujumdar, Arun S.
【影响因子】6.757
【主题类别】
区块链应用-实体经济-食品供应链
【Abstract】It is challenging to gather and track information in a timely and reliable manner since there are numerous phases involved in the manufacture, transportation, and distribution of fresh food products. Currently, the implementation of food supply chain traceability is largely affected by factors such as opaque supply chains, opaque data storage, low third-party trust, difficulties in sharing resource information and incorrect data and information transmission. Blockchain technology provides an immutable and transparent ledger that holds advantages in fresh food quality traceability and dynamic monitoring. This review describes the relationship between blockchain and food quality traceability and dynamic monitoring, and points out current new technologies for food traceability and dynamic monitoring that can provide practical data for blockchain. The current application of blockchain-based fresh food quality tracking is promising as it can help address many of the current issues in the food supply chain, including fresh food safety, dynamic monitoring of the transportation environment, and traceability of fresh food. It could also provide consumers with more detailed and accurate information about the food they consume, which could help them make more informed decisions about what they eat. Overall, the research progress and application prospects for blockchain-based fresh food quality traceability are positive, indicating a bright future for this emerging technology.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Fresh food; Blockchain; Intelligent technology; Traceability; Dynamic monitoring
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 综述
【Author】 Hina, Maryam Islam, Najmul Dhir, Amandeep
【影响因子】6.353
【主题类别】
区块链治理-市场治理-技术采用
【Abstract】Purpose - There is little empirical evidence on how blockchain affordances may encourage consumers to make sustainable choices. Thus, this paper examines how blockchain affordances affect consumers' sustainable consumption. Design/methodology/approach - We focus on three blockchain affordances: transparency, traceability, and immutability in this paper. By integrating the affordance lens and theory of consumption values (TCV), we develop a research model wherein we posit that blockchain affordances influence several consumption values, which then affect consumers' intention to purchase sustainable products. In the study, we designed a scenario and user interface for a novel blockchain-based app for sustainable consumption in the context of the fashion industry and surveyed 295 European consumers to examine the study's research model. We then analyzed the collected data using the partial least squares technique.
Findings - The results show that blockchain affordances positively affect consumption values, including efficiency, social impression, trust, and sustainability information clarity. In turn, these values influence the consumers' purchase intention of sustainable products. Additionally, our post hoc analysis shows that these consumption values fully mediate the effect of blockchain affordances on consumers' purchase intention, where trust and sustainability information clarity is found to have a higher impact.
Originality/value - Empirical research studies focusing on understanding blockchain's effect on sustainable consumption values have been limited in prior literature. This study, drawing on the affordance lens, proposes distinct blockchain affordances and empirically validates their impact on consumers' sustainable purchase intention. By integrating TCV, it highlights the mediating mechanism that drives blockchain's impact on consumers' purchase intention. We empirically identify the values that mediate the effects of blockchain affordances on consumers' purchase intention; further, we discuss implications for research and practice based on the study findings.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Affordance; Consumption values; Transparency; Traceability; Immutability; Sustainability
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 实证数据
【Author】 Alsharif, Mohammed H. Kannadasan, Raju Wei, Wei Nisar, Kottakkaran Sooppy Abdel-Aty, Abdel-Haleem
【影响因子】5.711
【主题类别】
区块链技术-协同技术-联邦学习
【Abstract】The Internet of Things (IoT) has embedded itself in our daily lives, offering smart services and AIdriven applications. However, traditional AI methods face challenges due to centralized data management in vast IoT networks and privacy concerns. Federated Learning (FL) solves this by training AI directly on distributed IoT devices, avoiding extensive data sharing. This article provides interested researchers of FL with an in-depth and up-to-date exploration of the multifaceted of FL in a privacy-centric era. This study is structured with three principal objectives. Firstly, within the realm of taxonomies for FL, the study aims to identify and categorize the existing frameworks utilized in FL research. Furthermore, it seeks to provide a thorough overview of how FL is delineated and conceptualized in current literature. Secondly, the study endeavors to explore the applications of FL by scrutinizing and classifying various use cases across diverse domains and industries. This objective aims to illuminate the applications and industries benefitting from FL implementations. Thirdly, the study addresses the inherent challenges in FL by examining the associated limitations. The study strives to offer insights into the technical and practical obstacles encountered in FL scenarios, contributing to a comprehensive understanding of the challenges within this dynamic field. This survey serves as a roadmap towards establishing sustainable massive IoT networks. Additionally, it paves the way for interested researchers to pursue and advance the vision of FL's evolving role in IoT.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Machine learning; Federated learning; ML; AI; IoT; 6G; Privacy; Healthcare
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 综述
【Author】 Park, Kisung Park, Youngho
【影响因子】5.711
【主题类别】
区块链应用-实体经济-医疗领域
【Abstract】Medical internet of things (MIoT) environments continue to expand, and numerous MIoT services are available to improve the quality of human life. However, these services, facilitated by a multitude of interconnected IoT devices analyzing the environment, face significant security challenges due to the volume of interconnected devices and the exchange of data through open channels. Moreover, the vulnerability is exacerbated by the centralized infrastructure commonly used by IoT services, where compromising a trusted third party (TTP) or service provider jeopardizes the entire system's security. Existing privacy-preserving schemes for IoT, while aiming for decentralization, often rely on a TTP to sustain the system. In such environments, users typically either entrust their secret keys and parameters to a TTP or store their data in cloud servers. Consequently, as the TTP assumes control over the actual keys and data, a significant challenge arises regarding the assurance of user and data sovereignty. In this paper, we propose a complete decentralized privacy-preserving scheme for MIoT that ensures data self-sovereignty, transparency, and complete decentralization without TTP intervention. In the proposed scheme, users can directly manage their keys with secret parameters. Then, they can upload encrypted data directly to distributed storage and securely share it with other users based on the security levels they have set themselves. We perform informal and formal (mathematical and simulation) security analysis to prove the security of the proposed scheme and conduct comparative analysis to evaluate the security functionalities, communication costs, and computational costs of our scheme compared with those of previous schemes. Further, we implement our scheme in a practical setting through simulations on Ethereum blockchain networks, validating its complete decentralization, security, efficiency, and suitability for MIoT environments. The specificity of our research lies in addressing the critical security concerns inherent in MIoT through a complete decentralized, TTP-independent framework.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Medical internet of things; Access control; Self-sovereignty; Complete decentralization; Blockchain
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 理论模型
【影响因子】5.576
【主题类别】
区块链应用-实体经济-旅游领域
【Abstract】Purpose - This study aims to investigate the perceptions of service providers in the travel and hospitality industry toward the adoption of blockchain technology (BCT), focusing on its impact on consumer experiences and expectations, especially in terms of trustworthiness and the management of privacy and security concerns. Design/methodology/approach - The research used a quantitative methodology, collecting data from 135 industry practitioners across fi ve tourism sectors (lodging, connected industries, entertainment, FandB, transportation) in Europe. This approach aimed to understand the diverse perspectives on the benefits and challenges of implementing BCT in their opera Findings - The results indicate mixed perceptions regarding blockchain adoption. While there are positive views on BCT's potential to enhance customer experience and service quality, there are significant concerns about its impact on trust and security. A consensus exists between customer and provider perspectives on BCT's trustworthiness, but significant differences were observed in views on privacy and security enhancement. Originality/value - This research contributes to the existing literature by providing insights into the service providers' and customers' perspectives on BCT within the travel and hospitality industry. It underscores the complexities of adopting new technologies and calls for more in-depth studies to address the identified concerns, thereby offering a novel viewpoint on the adoption of distributed ledger technologies in enhancing customer experience and service delivery.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Tourism; User perceptions; Trust; Customer experience; Security; Privacy; Service provider; Multi theoretical approach; Distributed ledger technologies
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 实证数据
【Author】 Gomez-Valenzuela, Victor Holl, Adelheid
【影响因子】5.361
【主题类别】
区块链应用-实体经济-社会治理
【Abstract】This paper provides a systematic review of the scientific landscape of the interdisciplinary field of rural depopulation studies, considering the potential contribution of Fourth Industrial Revolution technologies or Industry 4.0 to enhance our contemporary understanding and policy approach to facing the complex challenge of rural transitions. Two levels of intersec search are examined: (a) an aggregated conceptual level of rural population studies and (b) a more policy-based level. Blockchain, the Internet of Things, additive manufacturing, and other 4.0 technologies highlight a scientific panorama in which social and sustainable concerns are integrated with the disruptive potential of these technologies.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Industry 4.0; rural depopulation; socio-technical systems; sustainable transitions; transformative innovation policies
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 综述
【影响因子】4.996
【主题类别】
区块链技术-协同技术-联邦学习
【Abstract】In federated learning, secret sharing is a key technology to maintain the privacy of participants' local models. Moreover, with the rapid development of quantum computers, existing federated learning privacy protection schemes based on secret sharing will no longer be able to guarantee the data security of participants in the post-quantum era. In addition, existing privacy protection methods have the problem of high communication and computational overhead. Although the multi-stage secret sharing scheme proposed by Pilaram et al. is one of the effective solutions to the above problems, existing studies have proven the privacy leakage risk of this scheme. This paper firstly designs a new lattice-based multi-stage secret sharing scheme Improved-Pilaram to solve the security problem, which allows participants to use public vectors to reconstruct different secret values without changing the secret sharing. Based on Improved-Pilaram, this article proposes a post-quantum secure federated learning scheme PQSF. PQSF uses double masking technology to encrypt model parameters and achieves mask reconstruction through secret sharing. Since Improved-Pilaram is multi-stage, participants do not need to update their local secret shares frequently during training. Analysis and experimental results show that the PQSF proposed in this paper reduces the communication complexity between participants and reduces the computational overhead by about 20% compared with existing solutions.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Federated learning; Secure aggregation; Secret sharing; Post quantum security
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 实验仿真
【Author】 Li, Li Tian, Pengbo Dai, Jiapeng Miao, Fengjuan
【影响因子】4.996
【主题类别】
区块链应用-实体经济-农业领域
【Abstract】Ensuring the traceability of agricultural products is essential for quality control and food safety. Recent technological advances have provided new ways to enhance traceability systems. This study aims to use blockchain technology, centralized database and RFID tags to develop a secure agricultural product traceability system, retain the detailed information of agricultural products traceability, ensure that the summary information of agricultural products on the chain cannot be modified, and optimize the SM3 algorithm to effectively summarize the traceability data and improve the efficiency of the system. The aggregated data is time-stamped, recorded on the blockchain, and written into an RFID tag. The optimization of the SM3 algorithm improved the efficiency by 30% and reduced the execution time of 192-byte messages to 210 mu s. The system ensures accurate linking of traceability data through secure data retention and unalterable summaries on the blockchain. The integrated use of blockchain, centralized database and RFID technology, as well as the enhanced SM3 algorithm, allows the system to meet the standards for data accuracy and performance requirements in agricultural traceability applications.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Traceability of agricultural products; RFID; Blockchain; SM3; HSM; Internet of things technology
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 实验仿真
【影响因子】4.803
【主题类别】
区块链应用-实体经济-供应链
【Abstract】Purpose - Blockchain technology is one of the major contributors to supply chain sustainability because of its inherent features. However, its adoption rate is relatively low due to reasons such as the diverse barriers impeding blockchain adoption. The purpose of this study is to identify blockchain adoption barriers in sustainable supply chain and uncovers their interrelationships. Design/methodology/approach - A three-phase framework that combines machine learning (ML) classifiers, BORUTA feature selection algorithm, and Grey-DEMATEL method. From the literature review, 26 potential barriers were identified and evaluated through the performance of ML models with accuracy and f-score. Findings - The findings reveal that feature selection algorithm detected 15 prominent barriers, and random forest (RF) classifier performed with the highest accuracy and f-score. Moreover, the performance of the RF increased by 2.38% accuracy and 2.19% f-score after removing irrelevant barriers, confirming the validity of feature selection algorithm. An RF classifier ranked the prominent barriers and according to ranking, financial constraints, immaturity, security, knowledge and expertise, and cultural differences resided at the top of the list. Furthermore, a Grey-DEMATEL method is employed to expose interrelationships between prominent barriers and to provide an overview of the cause-and-effect group. Practical implications - The outcome of this study can help industry practitioners develop new strategies and plans for blockchain adoption in sustainable supply chains. Originality/value - The research on the adoption of blockchain technology in sustainable supply chains is still evolving. This study contributes to the ongoing debate by exploring how practitioners and decision- makers adopt blockchain technology, developing strategies and plans in the process.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain technology adoption; Sustainable supply chain; Barriers; BORUTA; Machine learning; Grey-DEMATEL
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 综述
CCF-C
【影响因子】4.757
【主题类别】
区块链应用-虚拟经济-加密货币
【Abstract】Leveraging Deep Reinforcement Learning (DRL) for training agents for financial trading has gained significant attention in recent years. However, training these agents in noisy financial environments remains challenging and unstable, significantly impacting their performance as trading agents, as the recent literature has also showcased. This paper introduces a novel distillation method for DRL agents, aiming to improve the training stability of DRL agents. The proposed method transfers knowledge from a teacher ensemble to a student model, incorporating both the action probability distribution knowledge from the output layer, as well as the knowledge from the intermediate layers of the teacher's network. Furthermore, the proposed method also works in an online fashion, allowing for eliminating the separate teacher training process typically involved in many DRL distillation pipelines, simplifying the distillation process. The proposed method is extensively evaluated on a large-scale cryptocurrency trading setup, demonstrating its ability to both lead to significant improvements in trading accuracy and obtained profit, as well as increase the stability of the training process.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Financial Trading; Deep reinforcement learning; Online probabilistic acknowledgment; distillation
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 理论模型
【Author】 Alkhalifa, Amal k. Alanazi, Meshari h. Mahmood, Khalid Almukadi, Wafa sulaiman al Qurashi, Mohammed Alshehri, Asma hassan Alanazi, Fuhid Mohamed, Abdelmoneim ali
【影响因子】4.555
【主题类别】
区块链应用-实体经济-医疗领域
【Abstract】The Internet of Medical Things (IoMT) refers to interconnected medical systems and devices that gather and transfer healthcare information for several medical applications. Smart healthcare leverages IoMT technology to improve patient diagnosis, monitoring, and treatment, providing efficient and personalized healthcare services. Privacy-preserving Federated Learning (PPFL) is a privacy-enhancing method that allows collaborative method training through distributed data sources while ensuring privacy protection and keeping the data decentralized. In the field of smart healthcare, PPFL enables healthcare professionals to train machine learning algorithms jointly on their corresponding datasets without sharing sensitive data, thereby maintaining confidentiality. Within this framework, anomaly detection includes detecting unusual events or patterns in healthcare data like unexpected changes or irregular vital signs in patient behaviors that can represent security breaches or potential health issues in the IoMT system. Smart healthcare systems could enhance patient care while protecting data confidentiality and individual privacy by incorporating PPFL with anomaly detection techniques. Therefore, this study develops a Privacy-preserving Federated Learning with Blockchain-based Smart Healthcare System (PPFL-BCSHS) technique in the IoMT environment. The purpose of the PPFL-BCSHS technique is to secure the IoMT devices via the detection of abnormal activities and FL concepts. Besides, BC technology can be applied for the secure transmission of medical data among the IoMT devices. The PPFL-BCSHS technique employs the FL for training the model for the identification of abnormal patterns. For anomaly detection, the PPFL-BCSHS technique follows three major processes, namely Mountain Gazelle Optimization (MGO)-based feature selection, Bidirectional Gated Recurrent Unit (BiGRU), and Sandcat Swarm Optimization (SCSO)-based hyperparameter tuning. A series of simulations were implemented to examine the performance of the PPFL-BCSHS method. The empirical analysis highlighted that the PPFL-BCSHS method obtains improved security over other approaches under various measures.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Internet of Medical Things; Federated Learning; Blockchain; Sandcat Swarm Optimization; Feature Selection
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 理论模型
【影响因子】3.817
【主题类别】
区块链治理-市场治理-数字货币
【Abstract】Modeling and analyzing interrelationships within the Bitcoin market, as a prominent cryptocurrency, leads to understanding hidden structures, effective management and informed decision-making. Regarding this matter, numerous studies have analyzed the time-varying spillover patterns in this ecosystem. Although spillover network analysis can elucidate the nature and strength of correlations, it may not be adept at handling the conditional interdependencies within intricate non-linear and dynamic essential behaviors of financial time series. This research tries to address the mentioned challenges by presenting a novel analytical model to investigate the dynamic communication patterns among Bitcoin, United States Economic Policy Uncertainty (US EPU) and public sentiments. Following this objective, rather than directly exploring the effect of original data series on each other, the approach decomposes them into sequences of meaningful statistical behaviors, at different lag-lead horizons. Subsequently, considering the significance of conditional dependencies, we extract and analyze the rules and patterns of information flow among the observed behaviors. The findings not only unveil a distinct flow pattern compared to the spillover network, but also offer valuable insights into dynamic interactions and dominant behaviors under various scenarios. One observation suggests that as the historical range of predictors increases in predicting future changes, their effectiveness or reliability decreases, while their number simultaneously increases. Moreover, the trend slope of Bitcoin functions as a notable behavior in propagating information, directly influencing both economic uncertainty and investor sentiment. The proposed model enhances the understanding of interaction between financial time series and provides useful perspectives for analysis and risk management.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Information flow analysis; Conditional inference; Time-varying causality; Bitcoin; Economic policy uncertainty; Sentiment analysis
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 实证数据
【影响因子】2.908
【主题类别】
区块链应用-实体经济-医疗领域
【Abstract】BackgroundDigitalization in long-term care (LTC) is being discussed as a means of easing pressures on care service delivery, optimizing care coordination and planning processes, and improving service quality. With its advanced data protection and process automation features, blockchain technology could help solve data security and privacy issues, especially for the implementation of assistive technologies. Blockchain (BC) is thus a new technology being tapped in LTC. However, little is known about the fields, scope, and experiences of BC applications in this sector.ObjectiveThis systematic review aims to provide an extensive overview of current discussions of BC technology in LTC settings. Particular attention was given to the use cases, the objectives behind applying the new technology, and barriers as well as facilitating factors for the implementation.MethodAccording to the PRISMA methodology, we conducted a systematic literature review of academic articles and conference papers published between 2016 and 2023. The search through the Scopus database yielded 194 results, 29 of which were selected according to our inclusion and exclusion criteria.ResultsResearch on BC technologies has taken off in LTC since 2016. Scientific interest centers around use cases for Ambient Assisted Living (AAL), care service management, and the improved integration of care ecosystems. However, most of the selected studies discuss prototypes that have neither yet been extensively evaluated nor been implemented and tested in real-world scenarios. Among the implementation barriers, technical immaturity, stakeholder cooperation, organizational change management, access to adequate IT infrastructure and end-user acceptance issues were most evident.ConclusionFuture research is needed to gain insights into context-specific implementation efforts, user experiences, benefits, and pitfalls of using BC technologies in LTC settings. While many expectations are tied to BC applications, potential negative effects have received little attention in the literature. Whether BC technology can serve as a mitigator between privacy and security preservation and improved information sharing in LTC settings is an important topic for further research.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Long-term care; Systematic review; AAL; Care service management; Care ecosystems; Privacy; Security; Health data
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 综述
【影响因子】2.853
【主题类别】
区块链治理-市场治理-数字货币
【Abstract】Given the financial markets' growing preference for examining digital platforms, this study explores the dynamic relationship of oil shocks with both conventional and digital currencies. It provides a novel approach for evaluating the relationship between aggregate oil, demand, and supply shocks using three conventional currencies (Japanese Yen, Chinese Yuan, and Euro), cryptocurrencies (Bitcoin, Ethereum, Tether), and DeFi tokens (Maker, Chainlink, and Basic Attention Token). We use wavelet analysis to test the asymmetric association among variables from June 22, 2018, to July 11, 2023. The outcomes of continuous wavelet confirm the volatile behavior of oil shocks and studied currencies. In particular, a nonlinear wavelet coherence is observed between oil shocks and DeFi tokens, cryptocurrencies, and traditional currency in the short, medium, and long term. Moreover, crypto and conventional currencies are found to respond more strongly to external events than DeFi tokens. Given the empirical findings and the rapid transformation of digitalized finance with ongoing currency restructuring, this study plays a critical role by actively influencing the adaptation of regulatory frameworks to align with dynamic changes in associations, serving as a strategic guide for regulatory bodies to navigate the complexities of emerging financial paradigms.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Digital finance; Oil shocks; Exchange rate; Cryptocurrencies; DeFi tokens; Wavelet analysis
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 实证数据
【影响因子】2.032
【主题类别】
区块链应用-实体经济-政务领域
【Abstract】This study empirically investigates the role of blockchain technology awareness in the adoption of electronic government (e-government) services in the northern part of Cyprus. With data collected from a random sample of 374 individuals eligible to use e-government services, a conceptual model that combines the Unified Theory of Acceptance and Use of Technology (UTAUT2) and the e-Government Adoption Model (GAM) was assessed. In addition to finding support for some predictors already used in prior literature, the current study investigated whether awareness of blockchain technology through its role in increasing trust would also enhance users' intention for e-government adoption. Findings have shown that increasing blockchain technology awareness can contribute to building trust and facilitate e-government adoption. Policymakers should consider developing awareness campaigns to enhance trust and get the public to adopt the offered online services.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】e-government; adoption; blockchain technology; UTAUT2; GAM
【发表时间】2024
【收录时间】2024-11-12
【文献类型】 实证数据
【作者】 郎晓夫; 谭敏; 张延强; 李欣; 刘国栋
【作者单位】中国移动通信集团设计院有限公司;国家信息中心;中国移动通信集团有限公司;北京红枣科技有限公司;
【文献来源】电信科学
【复合影响因子】
【综合影响因子】
【主题类别】
区块链应用-实体经济-数据管理
【摘要】大型企业集团作为平台化、多元化发展的复杂联合体组织，具有数据服务快速创新、多业务系统信息协同、数据可信治理和数据资产管理等中台型数据能力需求。对非可信系统环境下的企业数据中台典型架构及问题进行了分析，提出了基于区块链技术的可信数据服务中台技术路径、系统架构和可信度评估指标模型，并针对数据服务多门户、多方系统协同、数据功能模块化、“云网链”基础设施这4项关键机制实现进行了研究，为企业通过数据要素可信技术应用和机制创新、激发业务发展新动能提供了解决思路。进一步结合区块链服务网络在大型集团企业中的案例实践，对所提出架构机制的应用效果进行了阐述。
【关键词】区块链;;数据中台;;数据治理;;可信数据;;企业集团
【文献类型】 理论模型
【发表时间】2024-11-12