Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/8726
Title: Intelligent transformation and customer concentration
Authors: Mao, Jinzhou 
Zhao, Yueyang 
Yang, Siying 
Dr. LI Yi Man, Rita 
Abbas, Jawad 
Issue Date: 2023
Source: Journal of Organizational and End User Computing, 2023, Vol. 35(2).
Journal: Journal of Organizational and End User Computing 
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. © 2023 IGI Global. All rights reserved.
Type: Peer Reviewed Journal Article
URI: http://hdl.handle.net/20.500.11861/8726
ISSN: 15462234
DOI: 10.4018/JOEUC.333470
Appears in Collections:Economics and Finance - Publication

Show full item record

Page view(s)

13
checked on Jan 3, 2024

Google ScholarTM

Impact Indices

Altmetric

PlumX

Metrics


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.