在物流公司数字会计系统中实施云计算

IF 0.8 Q4 ENGINEERING, INDUSTRIAL
Mohammad Ahmad Alnaimat, Oleg Kharit, Iryna Mykhailenko, Ihor Palchyk, S. Purhani
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引用次数: 0

摘要

本文旨在确定云服务在满足物流公司供应链管理和数字会计需求方面的能力。本研究综述了当前的学术出版物、对云服务提供商公司官方文件的分析以及研究作者的专家意见。研究基于企业用于进行数学计算的 5 种最常用云服务的相关信息。亚马逊网络服务注重可靠性和可扩展性,提供广泛的数据存储和处理服务,以及执行无服务器数学计算。Microsoft Azure 因其集成解决方案以及数据管理和分析服务而脱颖而出。谷歌云提供广泛的开发和分析工具,包括数据可视化和数据共享。甲骨文云提供全面的财务和数据库管理解决方案。SAP 云平台专门提供财务管理和分析解决方案。研究结果为研究不同平台上的服务整合问题以及找到物流公司现有数学计算系统与所提供的云服务相结合的最佳解决方案开辟了前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of cloud computing in the digital accounting system of logistics companies
The aim of the article is to determine the capabilities of cloud services for meeting the needs of logistics companies in the management of supply chains and digital accounting. The study provides a review of current academic publications, analysis of official documentation of cloud service provider companies, and expert opinion of the authors of the study. The study was based on information about the 5 most popular cloud services used by companies to perform mathematical calculations. Amazon Web Services focus on reliability and scalability, providing a wide range of data storage and processing services, as well as performing serverless mathematical calculations. Microsoft Azure stands out for its integrated solutions, as well as data management and analytics services. Google Cloud offers a wide range of development and analytics tools, including data visualization and data sharing. Oracle Cloud provides comprehensive financial and database management solutions. SAP Cloud Platform specializes in financial management and analytics solutions. The results of the research open up prospects for studying the problems of integrating services built on different platforms and finding optimal solutions for combining the existing system of mathematical calculations in a logistics company with the offered cloud-based services.
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来源期刊
Acta Logistica
Acta Logistica Engineering-Industrial and Manufacturing Engineering
CiteScore
1.80
自引率
28.60%
发文量
36
审稿时长
4 weeks
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