Analysis on the Allocation of Control Right of Intergenerational Inheritance of Family Enterprises in the New Era

IF 0.5 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

International Journal of Data Warehousing and Mining Pub Date : 2023-03-22 DOI:10.4018/ijdwm.319966

Zhanzhong Wang, Jiajun Li

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引用次数: 0

Abstract

Artificial intelligence (AI) is the primary tool used by businesses to enhance economic advantages. Family company management is undergoing information and the digital industrial revolution because of artificial intelligence. With the fast development of new technologies, the family company management style has a significant effect and previously unimaginable impact. For most enterprises, intergenerational succession is either taking place or will occur shortly. Here intergenerational inheritance significance for family-owned businesses (IISF-OB) has been proposed to solve family company performance and the internal action mechanisms. Intergenerational succession pathways deserve consideration, and research for the family businesses must utilize artificial intelligence technology to enhance related work. The proposed method investigates how family company management modes can be innovated to fulfill societal development requirements methods in artificial intelligence. It will use case studies, comparative analyses, and develop a new solution.

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新时期家族企业代际传承控制权配置分析

人工智能(AI)是企业增强经济优势的主要工具。由于人工智能，家族企业管理正在经历信息和数字产业革命。随着新技术的快速发展，家族企业的管理方式产生了巨大的影响和以前难以想象的影响。对于大多数企业来说，代际继承要么正在发生，要么即将发生。本文提出了家族企业代际传承意义(IISF-OB)，以解决家族企业绩效及其内部作用机制。代际传承路径值得考虑，对家族企业的研究必须利用人工智能技术来加强相关工作。本文提出的方法探讨了家族企业管理模式如何创新以满足社会发展需求的人工智能方法。它将使用案例研究，比较分析，并开发一个新的解决方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.40

自引率

0.00%

发文量

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