智能转型与客户集中

IF 3.6 3区 管理学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of Organizational and End User Computing Pub Date : 2023-11-09 DOI:10.4018/joeuc.333470
Jinzhou Mao, Yueyang Zhao, Siying Yang, Rita Yi Man Li, Jawad Abbas
{"title":"智能转型与客户集中","authors":"Jinzhou Mao, Yueyang Zhao, Siying Yang, Rita Yi Man Li, Jawad Abbas","doi":"10.4018/joeuc.333470","DOIUrl":null,"url":null,"abstract":"With the gradual integration of artificial intelligence and production processes, will the traditional business model of enterprises change? Based on the data of China's manufacturing companies listed in Shanghai and Shenzhen A-shares from 2008 to 2021, we study the impact of enterprise intelligent transformation on customer concentration. Using text mining and machine learning tools, this study measures the degree of enterprise intelligent transformation and constructs an index based on the relevant words in annual reports. A multiphase DID model results show that enterprise intelligent transformation reduces customer concentration. A series of robustness tests and endogeneity tests validate this finding. This study shows that enterprise intelligent transformation improves information disclosure quality, strengthens innovation ability, and expands business boundaries, thus reducing customer concentration. Our findings provide empirical evidence to strengthen enterprise intelligent transformation further and maintain robust supply chain relationships.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":" 25","pages":"0"},"PeriodicalIF":3.6000,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intelligent Transformation and Customer Concentration\",\"authors\":\"Jinzhou Mao, Yueyang Zhao, Siying Yang, Rita Yi Man Li, Jawad Abbas\",\"doi\":\"10.4018/joeuc.333470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the gradual integration of artificial intelligence and production processes, will the traditional business model of enterprises change? Based on the data of China's manufacturing companies listed in Shanghai and Shenzhen A-shares from 2008 to 2021, we study the impact of enterprise intelligent transformation on customer concentration. Using text mining and machine learning tools, this study measures the degree of enterprise intelligent transformation and constructs an index based on the relevant words in annual reports. A multiphase DID model results show that enterprise intelligent transformation reduces customer concentration. A series of robustness tests and endogeneity tests validate this finding. This study shows that enterprise intelligent transformation improves information disclosure quality, strengthens innovation ability, and expands business boundaries, thus reducing customer concentration. Our findings provide empirical evidence to strengthen enterprise intelligent transformation further and maintain robust supply chain relationships.\",\"PeriodicalId\":49029,\"journal\":{\"name\":\"Journal of Organizational and End User Computing\",\"volume\":\" 25\",\"pages\":\"0\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2023-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Organizational and End User Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/joeuc.333470\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Organizational and End User Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/joeuc.333470","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

随着人工智能与生产流程的逐步融合,企业的传统商业模式是否会发生变化?基于2008 - 2021年在沪深a股上市的中国制造业公司数据,研究企业智能化转型对客户集中度的影响。本研究利用文本挖掘和机器学习工具,对企业智能化转型程度进行测度,并基于年报中的相关词汇构建指标。多阶段DID模型结果表明,企业智能化转型降低了客户集中度。一系列稳健性检验和内生性检验验证了这一发现。研究表明,企业智能化转型提高了信息披露质量,增强了创新能力,拓展了业务边界,从而降低了客户集中度。我们的研究结果为进一步加强企业的智能化转型和维持健全的供应链关系提供了实证证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Intelligent Transformation and Customer Concentration
With the gradual integration of artificial intelligence and production processes, will the traditional business model of enterprises change? Based on the data of China's manufacturing companies listed in Shanghai and Shenzhen A-shares from 2008 to 2021, we study the impact of enterprise intelligent transformation on customer concentration. Using text mining and machine learning tools, this study measures the degree of enterprise intelligent transformation and constructs an index based on the relevant words in annual reports. A multiphase DID model results show that enterprise intelligent transformation reduces customer concentration. A series of robustness tests and endogeneity tests validate this finding. This study shows that enterprise intelligent transformation improves information disclosure quality, strengthens innovation ability, and expands business boundaries, thus reducing customer concentration. Our findings provide empirical evidence to strengthen enterprise intelligent transformation further and maintain robust supply chain relationships.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Organizational and End User Computing
Journal of Organizational and End User Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
6.00
自引率
9.20%
发文量
77
期刊介绍: The Journal of Organizational and End User Computing (JOEUC) provides a forum to information technology educators, researchers, and practitioners to advance the practice and understanding of organizational and end user computing. The journal features a major emphasis on how to increase organizational and end user productivity and performance, and how to achieve organizational strategic and competitive advantage. JOEUC publishes full-length research manuscripts, insightful research and practice notes, and case studies from all areas of organizational and end user computing that are selected after a rigorous blind review by experts in the field.
期刊最新文献
Cross-Checking-Based Trademark Image Retrieval for Hot Company Detection E-Commerce Review Sentiment Analysis and Purchase Intention Prediction Based on Deep Learning Technology Financial Cycle With Text Information Embedding Based on LDA Measurement and Nowcasting Enhancing Innovation Management and Venture Capital Evaluation via Advanced Deep Learning Techniques Going Global in the Digital Era
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1