【Author】 Adaryani, Rasool Lavaei Palouj, Mojtaba Karbasioun, Mostafa Asadi, Ali Gholami, Hesamedin Kianirad, Ali Damirchi, Milad Joodi
【影响因子】10.884
【主题类别】
区块链应用-实体经济-供应链
【Abstract】Currently, blockchain adoption as an emerging technology is in its infancy in most developing countries such as Iran. However, there is a current paucity of empirical research focusing specifically on the antecedents of blockchain adoption in the context of these countries. This study aims to investigate the behavioral intention (BI) to use blockchain by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) model, incorporating subjective and objective knowledge, trust in technology, and information literacy. The proposed structural model was assessed by partial least squares structural equation modeling (PLS-SEM) using the data from 275 senior managers of Iranian poultry supply chains. The results showed that effort expectancy and performance expectancy were the most influential variables in predicting the BI to use blockchain technology, respectively. Furthermore, objective knowledge had an impact on the intention to use blockchain. However, subjective knowledge was not found to have any effect. The proposed model including the moderating effects of trust in technology and information literacy showed a higher predictive power. Trust in technology moderated the relationship between performance expectancy and behavioral intention, and information literacy moderated the relationship between technical infrastructure, as one of the facilitating conditions, and behavioral intention. The theoretical and practical implications are discussed in the paper.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain adoption; UTAUT; Subjective and objective knowledge; Trust in technology; Information literacy
【发表时间】2024
【收录时间】2024-08-19
【文献类型】 实证数据
【Author】 Garcia-Buendia, Noelia Nunez-Merino, Miguel Moyano-Fuentes, Jose Maqueira-Marin, Juan Manuel
【影响因子】10.801
【主题类别】
区块链应用-实体经济-供应链
【Abstract】Circular supply chain management (CSCM) is the revolutionary integration of circular principles into supply chain management and the supply chain environment to achieve zero waste and outperform traditional supply chain sustainability models in advancing supply chain circularity. This study examines CSCM and the corresponding literature to highlight key research themes and trends. An advanced iteration of the Systematic Science Mapping analysis methodology has been designed and implemented with a Named Entity Recognition approach to extract relevant information from scientific articles. Key themes are revealed such as essential capabilities for circularity in the supply chain, circular business models, sustainable supplier selection and blockchain technology's role. The article gives insights into current research and identifies emerging trends in CSCM. This exploration aims to provide a nuanced understanding of CSCM's transformative power and shed light on its practical implications.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】bibliometrics; circular; circular economy; closed-loop; supply chain management; systematic science mapping
【发表时间】2024
【收录时间】2024-08-19
【文献类型】 综述
【DOI】 10.1002/bse.3932
CCF-C
【影响因子】7.574
【主题类别】
区块链技术-核心技术-智能合约
【Abstract】Smart contracts are self-executing digital agreements that automatically enforce the terms between parties, playing a crucial role in blockchain systems. However, due to the potential losses of digital assets caused by vulnerabilities, the security issues of Ethereum smart contracts have garnered widespread attention. To address this, researchers have developed various techniques to detect vulnerabilities in smart contracts, with fuzzing techniques achieving promising results. Nonetheless, current fuzzers are unable to effectively exercise suspicious targets because they overlook two key factors: comprehensively exploring all paths to the targets and providing high-quality directed seed inputs. This paper presents a Directed vulnerability veriFier (DFier), which elaborates effective transaction sequences with directed inputs for the fuzzer. This focuses on exploring target paths and automatically validating whether the specified locations are vulnerable. Specifically, DFier employs static analysis to help locate target paths, facilitating their comprehensive exploration. Additionally, we devise three heuristic strategies to enable our fuzzing technique to generate directed inputs that effectively validate the targets. Extensive experiments demonstrate that DFier is effective in verifying contract security, compared with three existing contract fuzzers (i.e., contractFuzzer, sFuzz, and conFuzzius), while the performance losses are in an acceptable range.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Smart contract; Vulnerability detection; Fuzzing
【发表时间】2024
【收录时间】2024-08-19
【文献类型】 实验仿真
【Author】 Deng, Yinjuan Wang, Shangping Zhang, Qian
【影响因子】4.960
【主题类别】
区块链应用-实体经济-物联网
【Abstract】In Internet of Things (IoT) system, the data acquisition devices collect substantial volumes of diverse categories data, such as temperature, frequency and quantity data, etc., which is subsequently transmitted to the data center for analysis. To ensure precise outcomes, it is crucial to authenticate the data and their categories against any possible tampering, destruction or forgery throughout its transmission process. Traditional aggregate signature schemes are not capable of performing authentication on data as while as its category, which can lead to inefficiencies and security risks in data processing and management. On the other hand, authentication schemes relying on a central platform are susceptible to single point of failure and corruption issues at the center. To address these challenges, a novel data authentication protocol, named Classified Certificateless Aggregate Signature (CCAS), is proposed in this paper to perform aggregate authentication on data with specified categories, and is implemented in collaboration with Hyperledger Fabric. Elaborate design making the authentication is efficient and eliminating the need to manage the certificates. And an abnormal data isolation algorithm is proposed when an aggregate authentication fails, which can quickly identify abnormal data and preserves normal data. A rigorous proof on the unforgeability of the CCAS protocol is given, and multiple experiments are conducted to evaluate the scheme. The experimental results demonstrate the high efficiencies of CCAS, smart contracts on Fabric and our solution, indicating that proposed scheme is suitable for the classified authentication of IoT collection data in decentralized form.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Internet of Things; Blockchain; Signature; Data authentication; Security
【发表时间】2024
【收录时间】2024-08-19
【文献类型】 实验仿真
【影响因子】2.559
【主题类别】
区块链技术-核心技术-密码学
【Abstract】A distributed ledger is a shared and synchronized database across multiple designated nodes, often referred to as miners, validators, or peers. These nodes record, distribute, and access data to ensure security and transparency. However, these nodes can be compromised and manipulated by selectively choosing which user transactions to include, exclude, or reorder, thereby gaining an unfair advantage. This is known as a miner/maximal extractable value (MEV) attack. Existing solutions can be classified into various categories, such as MEV auction platforms and time-based ordering properties, which rely on private transaction Mempools. In this paper, we first identify some architectural weaknesses inherent in the latest proposals that divide the block creation and execution roles into separate functions: block builders and block executors. The existing schemes mainly suffer from the verifiability of the decryption process, where a corrupted builder or executor can simply deny the inclusion of specific targeted transactions by exploiting the fact that all transactions are in plain format. To address this, we propose an enhanced version that incorporates a verifiable decryption process. On a very high level, within our proposal, whenever an Executor or a Builder performs a decryption, the decrypted values must be broadcasted. This enables any entity in the network to publicly verify whether the decryption was executed correctly, thus preventing malicious behavior by either party from going undetected. We also define a new adversary model for MEV and conduct a comprehensive security analysis of our protocol against all kinds of potential adversaries related to MEV. Finally, we present the performance analysis of the proposed solution.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Miner/maximal extractable value (MEV); Cryptographic; Frontrunning; Backrunning
【发表时间】2024
【收录时间】2024-08-19
【文献类型】 实验仿真
【影响因子】1.916
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】This study investigates whether representative sectoral stock indices, gold, oil, Bitcoin, and wheat can mitigate risk and improve portfolio performance during normal times versus crises. The cutting-edge Quantile Vector Autoregressive model and the Generalized Dynamic Conditional Correlations (Generalized-DCC) framework are adopted covering from 9 January 2017 until 30 August 2022. Econometric findings by the Q-VAR reveal that oil presents the strongest connection with commodities and stock indices and that Bitcoin and wheat despite their significant linkages with financial markets fail to act as safe havens. Moreover, GDCC-GARCH indicates that the returns of sectoral indices are weakly related but display powerful volatility co-movements. Gold serves efficiently as a hedger and oil follows and both act as better shelters during crises. Nevertheless, Bitcoin partly abides by conventional markets in stressed periods. Notably, wheat reliably works as a hedger overall but does not become a safe haven during crises.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Stocks; commodities; cryptocurrencies; crises; dynamic connectedness; F30; G11; G12; G15
【发表时间】2024
【收录时间】2024-08-19
【文献类型】 实证数据
【影响因子】1.815
【主题类别】
区块链应用-实体经济-贸易领域
【Abstract】In 2001, China's accession to the World Trade Organization and the attainment of permanent Most Favored Nation (MFN) status from the USA significantly reduced external trade policy uncertainties for the country. Utilizing comprehensive data from 1998 to 2006, this paper employs a Difference-in-Differences (DID) regression approach to dissect the intricate relationship between trade policy uncertainties, financing constraints, and enterprise innovations. Our findings reveal that a notable decrease in trade policy uncertainties has considerably spurred innovation among Chinese enterprises, particularly for high-productivity firms and regions with advanced marketization. However, this effect is mitigated by financing constraints. The uniqueness of this paper lies in its detailed exploration of how trade policy uncertainties influence enterprise innovation through financing constraints. Specifically, the reduction in uncertainties boosts corporate profitability, fosters the growth of cluster commercial credit, and enhances credit resource allocation efficiency. Consequently, it alleviates financial pressures on enterprises, thereby facilitating innovation. While our data covers the period from 1998 to 2006, the insights remain relevant in the current global trade environment characterized by heightened uncertainties. Future research could validate these findings using updated data or investigate how emerging technologies like fintech and blockchain finance can alleviate financing constraints, thus aiding businesses in navigating trade policy uncertainties.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Trade policy uncertainty; Financing constraints; Enterprise innovation; DID
【发表时间】2024
【收录时间】2024-08-19
【文献类型】 实证数据
【Author】 Soltani, Hayet Abbes, Mouna Boujelbene
【影响因子】1.815
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】The purpose of this paper is to empirically investigate the volatility spillover between financial stress, the Gulf Cooperation Council (GCC) stock markets, and oil and gold markets in the presence of state (regime) dynamics. We first use the Dynamic Conditional Correlation (DCC)-GARCH model in order to study the correlation between variables. Second, the authors use a continuous wavelet decomposition technique so as to examine the interactions between financial stress, oil and GCC stock, and gold markets. Finally, the authors examine the spillover effects by estimating the Baba-Engle-Kraft-Kroner (BEKK)-GARCH model. The findings indicate various patterns of spillover between GCC financial stress index and oil, gold, and GCC stock market returns in high- and low-volatility regimes, especially during the COVID-19 pandemic. The wavelet coherency results indicate a substantial co-movement between oil and GCC financial stress and between GCC financial stress and GCC stock markets in the periods of high volatility. BEKK-GARCH model outcomes confirm this relation and report the noteworthy bi-directional transmission of volatility between GCC financial stress and oil market for some countries (see Oman, Saudi Arabia, and UAE in the bearish state and Bahrain and Saudi Arabia under bullish state) and between oil market shocks and the GCC stock market returns, chiefly in the turmoil period. Thus, these results are important for investors aiming at managing and reducing portfolio risk. These empirical findings are of significant importance in the development of effective allocation strategies to mitigate financial stress (FSIs) prevalent in the Gulf Cooperation Council (GCC) region. Moreover, they hold crucial implications for portfolio diversification, risk management, and policy formulation by shedding light on the interdependencies among various asset classes and financial markets across different market conditions.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】GCC financial stress; GCC stock markets; Wavelet coherence analysis; BEKK-GARCH
【发表时间】2024
【收录时间】2024-08-19
【文献类型】 实证数据