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 Prof. 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 |
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