【Author】 Xia, Liangjie Li, Kang Wang, Jun Xia, Yi Qin, Juanjuan
【影响因子】11.251
【主题类别】
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【Abstract】Precision marketing is useful for understanding consumers' low-carbon awareness (CLA). Considering a consignment contract and a reselling contract with a fixed wholesale price, we develop Stackelberg game models between the manufacturer and the platform under different sales contracts. We investigate how precision marketing and contract format impact supply chain members' decision-making and consumer surplus. We find, in any case, the optimal decisions of supply chain members increase with CLA and the manufacturer's emission reduction efficiency. However, the impact of the mean efficiency and accuracy efficiency of precision marketing and the precision marketing efficiency on the companies' decisions depends on the contract format and pro-duction costs. Precision marketing is beneficial for both the platform and consumers under each contract, but it is not always beneficial for the manufacturer. Regardless of whether precision marketing is used, both the platform and the manufacturer prefer the reselling contract if the wholesale price is moderate; otherwise, a transfer payment contract is needed for them to reach an agreement on which contract should be adopted. Precision marketing increases total carbon emissions under the reselling contract, while it decreases total carbon emissions under the consignment contract. Precision marketing increases social welfare under both contracts. With pre-cision marketing, social welfare is greater under the reselling contract than under the consignment contract. This paper is the first to investigate the platform supply chain's decision-making with different sales contracts considering the impact of precision marketing on both the mean value and accuracy improvement of uncertain market demand under low-carbon environment.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Emission reduction; Precision marketing; Platform; Consignment contract; Reselling contract
【发表时间】2024
【收录时间】2024-01-27
【文献类型】
【Author】 Sachan, Swati Liu (Lisa), Xi
CCF-C
【影响因子】7.802
【主题类别】
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【Abstract】Generative AI tools powered by Large Language Models (LLMs) have demonstrated advanced capabilities in understanding and articulating legal facts closer to the level of legal practitioners. However, scholars hold contrasting views on the reliability of the reasoning behind a decision derived from LLMs due to its black-box nature. Law firms are vigilant in recognizing the potential risks of violating confidentiality and inappropriate exposure of sensitive legal data through the prompt sent to Generative AI. This research attempts to find an equilibrium between responsible usage and control of human legal professionals over content produced by Generative AI through regular audits. It investigates the potential of Generative AI in drafting correspondence for pre-litigation decisions derived from an eXplainable AI (XAI) algorithm. This research presents an end-to-end process of designing the architecture and methodology for a blockchain-based auditing system. It detects unauthorized alterations of data repositories containing the decisions by an XAI model and automated textual explanation by Generative AI. The automated auditing by blockchain facilitates responsible usage of AI technologies and reduces discrepancies in tracing the accountability of adversarial decisions. It conceptualizes the two algorithms. First, strategic on-chain (within blockchain) and off-chain (outside blockchain) data storage in compliance with the data protection laws and critical requirements of stakeholders in a legal firm. Second, auditing by comparison of the unique signature as Merkle roots of files stored off-chain with their immutable blockchain counterpart. A case study on liability cases under tort law demonstrates the system implementation results.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Legal; Law; Explainable AI; Blockchain; Generative AI; Responsible AI
【发表时间】2024
【收录时间】2024-01-27
【文献类型】
【Author】 Son, Dong-Hoon Yang, Hai
【影响因子】6.173
【主题类别】
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【Abstract】Reward schemes are common in ride-sourcing markets. Each reward scheme incentivizes users with economic benefits as rewards for rides from the ride-sourcing platform. In practice, reward schemes differ in terms of their operational features. Operational features are the ways in which a ride-sourcing platform manages a reward scheme and users perceive and redeem their rewards. Therefore, different reward schemes involve different decision-making contexts for the platforms. As a result, it poses a challenge to understand the behavior of platforms with different types of reward schemes in the market. To address this challenge, this study analyzes the impacts of point-based and crypto-based fare-reward schemes on a ride-sourcing market. The market is defined as a mathematical model in which a ride-sourcing platform determines trip fares, commission fees, and rewards for passengers and drivers to maximize matching profits. A points-based reward scheme offers loyalty points with fixed redemption values. Issuance of point rewards incurs a liability for the reward scheme to accept users' point redemptions in the future. The crypto-based approach involves the cost of securing cryptocurrencies to reward users. Crypto rewards have various redemption values. Therefore, users perceive the value of crypto rewards based on their beliefs regarding their future value. This study performed an equilibrium analysis to elucidate the relationships between platform decisions and endogenous variables in the market using two fare-reward schemes. Subsequently, the properties of the optimal market solutions are further explored. These properties provide insights into the platform's reward and pricing decisions as follows: First, it is shown that a ride-sourcing platform is likely to adopt a single-sided reward strategy; that is, the platform's reward decisions with reward schemes are made exclusively between passengers and drivers. Second, the heterogeneity of user redemption behavior polarizes the platform's pricing decision on trip fares; that is, a ride-sourcing platform has incentives to set lower and higher trip fares when deciding to reward drivers and passengers, respectively. Third, such distinctive pricing decisions balance passenger demand with driver supply. Therefore, the ride-sourcing market can remain stable and efficient, even in the presence of the platform's reward decisions. A series of numerical experiments were performed to verify the findings of the current study.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Ride -sourcing; Pricing and equilibrium; Reward strategy; Fare -reward scheme; Redemption behavior
【发表时间】2024
【收录时间】2024-01-27
【文献类型】
【Author】 Jackson, Denise Allen, Christina
【影响因子】5.111
【主题类别】
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【Abstract】Although the benefits of technological innovation are widely recognised, the accounting profession continues to undervalue and inadequately leverage technologies such as artificial intelligence, robotic process automation and blockchain. This study builds on earlier work on the antecedents and barriers to technology adoption and considers the role of technological, organisational and environmental factors in the accounting context. The mixed methods design involved surveying 585 accounting managers in Australia and parts of South-East Asia and interviewing 20 Australian accounting managers. Using the Technology-Organisation-Environment model, the study explored differences in the importance of factors by region and organisational type and investigated manager perspectives on strategies to support adoption. Findings indicated that security and privacy concerns are paramount to decision-making, while environment-related factors were of less importance. Prioritised strategies included staying informed of technological innovation, encouraging staff engagement and support, and implementing effective project management. The study illuminates the critical role of professional associations and industry bodies in providing tailored support for members to foster greater technological orientation and advance in the accounting profession, including advocating for high-level, technology-related strategies to drive organisational transformation.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Technology-Organisation-Environment framework; Technology adoption; Barriers; Strategies; Enablers
【发表时间】2024
【收录时间】2024-01-27
【文献类型】
【Author】 Maric, Drazen Vukmirovic, Goran Maric, Radenko Nuseva, Daniela Lekovic, Ksenija Vucenovic, Sonja Testa, Riccardo
【影响因子】3.889
【主题类别】
区块链应用-实体经济-食品供应链
【Abstract】This paper aims to analyze and define incentives for the implementation of modern technology and digitalization of the Food Supply Chain (FSC) in the function of sustainability of the food retail sector of the Western Balkans (WB) region. The survey method was applied to a sample of 255 employees. We tested the importance of certain indicators for the implementation of the digitalization process, such as the application of Blockchain Technology (BT), the use of modern IT solutions for traceability, the implementation of the Internet of Things (IoT), the introduction of Artificial Intelligence (AI), development of a system for electronic food placement, implementation of standards, measures, and procedures for regulating the digitalization process, continuous training of employees and economic and financial measures and incentives. A special segment of research deals with the impact of the implemented digitalization process on the sustainability of food placement. The research was conducted among employees of SMEs, large-scale business entities, and retail chains. The research results showed significant deviations from the mentioned incentives to the digitalization process depending on the size of the FSC participants. The work has practical implications because the obtained results show the FSC management, trade policy makers, and competent institutions (ministries, chambers of commerce, professional associations) what measures to apply in order to improve a more efficient implementation of the digitalization process of food placement and lay the foundation for the sustainability of the FSC. Guidelines for future research are outlined in the paper.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Food Supply Chain (FSC); Internet of Things (IoT); Blockchain Technology (BT); sustainability; digitalization; retail; Western Balkans (WB)
【发表时间】2024
【收录时间】2024-01-27
【文献类型】 实证数据
【DOI】 10.3390/su16010002
【影响因子】3.476
【主题类别】
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【Abstract】Tor (The Onion Routing) network was designed to enable users to browse the Internet anonymously. It is known for its anonymity and privacy security feature against many agents who desire to observe the area of users or chase users' browsing conventions. This anonymity stems from the encryption and decryption of Tor traffic. That is, the client's traffic should be subject to encryption and decryption before the sending and receiving process, which leads to delay and even interruption in data flow. The exchange of cryptographic keys between network devices plays a pivotal and critical role in facilitating secure communication and ensuring the integrity of cryptographic procedures. This essential process is time-consuming, which causes delay and discontinuity of data flow. To overcome delay or interruption problems, we utilized the Software-Defined Network (SDN), Machine Learning (ML), and Blockchain (BC) techniques, which support the Tor network to intelligently speed up exchanging the public key via the proactive processing of the Tor network security management information. Consequently, the combination network (ITor-SDN) keeps data flow continuity to a Tor client. We simulated and emulated the proposed network by using Mininet and Shadow simulations. The findings of the performed analysis illustrate that the proposed network architecture enhances the overall performance metrics, showcasing a remarkable advancement of around 55%. This substantial enhancement is achieved through the seamless execution of the innovative ITor-SDN network combination approach.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Anonymity; blockchain; ML; SDN; Tor networks
【发表时间】2024
【收录时间】2024-01-27
【文献类型】
【Author】 Mohammed, Badiea Abdulkarem Al-Shareeda, Mahmood A. Al-Mekhlafi, Zeyad Ghaleb Alshudukhi, Jalawi Sulaiman Al-Dhlan, Kawther A.
【影响因子】3.476
【主题类别】
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【Abstract】The quick progress of 5G networks has allowed for intelligent driving. The primary environment for intelligent driving is provided by vehicular ad hoc networks (VANETs), which relay real-time data and communications between moving vehicles and fixed infrastructure. Since the communication is open-access, the message exchanged is vulnerable to privacy and security attacks. To address with this challenge, several authentication schemes have proposed. Nevertheless, the complexity of current these schemes means that re-authenticating vehicle identities every time they reach a new area of infrastructure coverage significantly hampers the overall network's efficiency. This paper has proposed a handover authentication, called HAFC scheme based on fog computing to achieve fastly re-authentication of vehicles via secure property transfer among infrastructures (fog servers) for 5G-assisted vehicular blockchain networks. The proposed HAFC scheme consists of both stages namely, initial-authentication stage and handover-authentication stage. In security analysis shows that the proposed HAFC scheme's vehicle to fog server-for both stages is Computational Diffie-Hellma (CDH)-secure. According to the simulation results, the novel handover authentication stage takes only a fraction of the time required for the first one.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Re-authentication scheme; handover authentication; 5G-assisted blockchain; fog computing; vehicular blockchain network
【发表时间】2024
【收录时间】2024-01-27
【文献类型】
CCF-C
【影响因子】2.577
【主题类别】
区块链应用-实体经济-电力领域
【Abstract】A smart grid is a network that utilizes a digital network to monitor the passage of electricity from one node to another within the network. Some of the applications of the smart grid are dynamic control of voltage, substation automation, outage management, and so on. The smart grid become an important topic since the inclusion of digital systems to monitor the electricity flow enhances usage and at the same time, it is affected by malicious attacks. Hence, it is necessary to protect the smart grid from attackers so that the authenticated user gets all the benefits without any scarcity. For this, many approaches have proposed by the researchers and have shortcomings of less accuracy in classifying the normal and abnormal flow, computational complexities, and less throughput. In context with these problems, we proposed a Convolutional Neural Network (CNN) based African Vulture Optimization Algorithm (AVOA) for the enhancement of cybersecurity in the blockchain-based Smart grid. To offer a novel way for improving smart grid security and defect detection in the industry by utilising block chain technology with deep learning architectures. The smart grid network's security performance can be improved by the use of a blockchain-based smart grid node based network module. In addition, the simulation results are carried out utilising a hybrid framework to monitor the attacks in the network. The data from the switches and PMU wascollected in the physical layer of the system. Then a blockchain controller controls the data. This also monitors the transaction details in the smart grids. The data are pre-processed with the aid of a Label encoder, and MIN-MAX scaling approaches. Then the features are extracted by using the CNN and the classification data is also performed by the CNN; however, the conventional CNN lacks scalability, and to enhance the scalability we utilize the AVO algorithm. The AVO algorithm effectively improves the scalability and thus our proposed classifies the normal and abnormal data from the smart grid. For the experimental purpose, we have taken the UNSW_NB15 dataset and compared it with the state of artworks in terms of different parameters. From the analysis, it is observed that the proposed method enhances the cybersecurity level by enhancing the throughput, accuracy (97.40%), F1-score (99.17%), precision (98.25%), recall (98.37%)computational time (1.34 ms) and detection rate (97.3%).
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Attackers; AVOA; Blockchain CNN; Electricity; Detection of abnormalities; Security; And smart grid
【发表时间】2023
【收录时间】2024-01-27
【文献类型】 实证数据
【影响因子】0.000
【主题类别】
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【Abstract】The Trustworthy Healthcare Cloud Storage Auditing Scheme (TCSHAS) represents a progressive solution for resolving trust-related issues linked to third-party auditors (TPAs) within traditional healthcare cloud storage audit systems. As the healthcare industry increasingly relies on cloud storage, concerns surrounding security and privacy have grown, motivating the development of a unique incentive mechanism. This mechanism leverages the non-tamperable and traceable features of blockchain technology to encourage TPAs to uphold honesty and reliability. By organizing TPAs as a group of nodes on the blockchain, a system of mutual surveillance is established, enabling diligent monitoring and penalization of any malicious actions. TCSHAS encompasses a comprehensive system model that incorporates smart contracts to manage transaction-related matters, including dispute resolution. Performance evaluations have confirmed its efficiency and suitability for real-world healthcare applications. Our experiments demonstrate that TCSHAS performs well in terms of gas consumption and exhibits scalability as the number of participant's increases. Compared with other common smart contracts, TCSHAS maintains a balanced level of complexity, incorporates strong security measures, offers comprehensive auditing capabilities, and remains flexible. To further enhance our research, we can explore ways to optimize TCSHAS scalability and performance, such as through shading, as the volume of healthcare data continues to grow. In addition, we can investigate the integration of advanced privacy technologies or AI-based auditing. These advancements will reinforce the role of TCSHAS in establishing trust and security in healthcare cloud storage audits, making it highly relevant in real-world healthcare settings. Ultimately, TCSHAS contributes to improving trust and security in healthcare cloud storage auditing, ensuring responsible management of sensitive healthcare data. TCSHAS improves trust in healthcare cloud storage by using blockchain to ensure honest auditing.Smart contracts and incentives enhance efficiency and accountability in auditing processes.Future research can focus on scalability, privacy, AI-based auditing, and industry integration
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】TCSHAS (trustworthy healthcare cloud storage auditing scheme); Healthcare; Cloud storage; Third-party auditors (TPAs); Auditing scheme; Blockchain technology; Smart contracts; Security and privacy
【发表时间】2023
【收录时间】2024-01-27
【文献类型】
【Author】 Wang, S.
【影响因子】0.000
【主题类别】
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【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】2023
【收录时间】2024-01-27
【文献类型】
【DOI】 10.1155/2023/9862625