弹性供应链利用区块链技术提高全球金融机构会计数据的完整性

IF 0.5 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING International Journal of Data Warehousing and Mining Pub Date : 2023-03-24 DOI:10.4018/ijdwm.320648
Yu Yang, Zecheng Yin
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引用次数: 4

摘要

会计信息系统(AIS)收集、存储和分析数据,为企业领导人提供信息。信息技术资源和以计算机为基础的会计系统经常被用来监控会计信息系统中的会计活动。供应链管理战略、计划和实施越来越依赖于全球化会计师的专业知识。会计的工作是协助供应链设计、开发和实施小组。最高管理者的承诺、所使用的会计信息系统的类型以及输入控制都是影响会计信息系统数据质量的因素。他们可以使用区块链(BC)追踪任何形式的盗窃或挪用,区块链负责维护资产转移。为了避免欺诈,满载经济和金融原则的协议可能被用来管理公司运营。利用物联网(IoT)数据,银行可以更好地了解客户的业务需求和价值链。
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Resilient Supply Chains to Improve the Integrity of Accounting Data in Financial Institutions Worldwide Using Blockchain Technology
Accounting information systems (AIS) gather, store, and analyze data in providing information to business leaders. Information technology resources and a computer-based accounting system are often used to monitor accounting activities in an accounting information system. Supply chain management strategies, planning, and implementation are increasingly dependent on the expertise of accountants with globalization. The accountant's job is to assist the supply chain design, development, and implementation group. Top management commitment, the kind of accounting information systems used, and input controls are all factors that affect accounting information systems' data quality. They can trace any form of theft or misappropriation using the blockchain (BC), which maintains asset transfers. In hopes of avoiding fraud, agreements loaded with economics and finance principles might be used to govern corporate operations. Using internet of things (IoT) data, banks can better understand their customers' business demands and value chain.
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来源期刊
International Journal of Data Warehousing and Mining
International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.40
自引率
0.00%
发文量
20
审稿时长
>12 weeks
期刊介绍: The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving
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