Empirical Analysis of Enterprise Digital Transformation Degree on Listed Manufacturing Companies' Performance from the Digital Economy Perspective.
As a cornerstone of China's economy, the manufacturing sector's digital transformation is crucial for corporate sustainability and vital to the structural optimization of the national economy. Using panel data from China's manufacturing A-share listed firms (2014–2023), this paper empirically analyz...
| Publicado en: | SHS Web of Conferences Vol. 218; pp. 1 - 9 |
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| Autor principal: | |
| Formato: | Artículo |
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EDP Sciences
7/3/2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=186412676&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 186412676 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 24165182 FT5R jtl: SHS Web of Conferences issn: 24165182 maglogo: N pubinfo: dt: 7/3/2025 vid: 218 pid: 76090 pub: EDP Sciences artinfo: ui: 186412676 10.1051/shsconf/202521801017 ppf: 1 ppct: 8 formats: tig: atl: Empirical Analysis of Enterprise Digital Transformation Degree on Listed Manufacturing Companies' Performance from the Digital Economy Perspective. aug: au: Lu, Kehan affil: School of Economics, Guangdong University of Technology, Guangzhou, 510006, China sug: ab: As a cornerstone of China's economy, the manufacturing sector's digital transformation is crucial for corporate sustainability and vital to the structural optimization of the national economy. Using panel data from China's manufacturing A-share listed firms (2014–2023), this paper empirically analyzes the impact of corporate digital transformation on business performance using text mining and econometric methods. It is found that the coefficient of digital transformation is 0.0063, which significantly enhances the financial performance of enterprises. The regression analysis yields a parameter estimate of 0.0086 for private sector entities, which contrasts with the negative coefficient for state-owned entities (-0.0031), suggesting differences in the strength of the ownership structure among them. This paper reveals the mechanism by which digital transformation promotes performance improvement by optimizing resource allocation and operational efficiency through fixed effects model and group regression analysis. At the same time, this study establishes a theoretical foundation for manufacturing firms' digital transformation and proposes differentiated policy measures: strengthen the precise policy inclination for non-state-owned enterprises (NSOEs); establish a system to assess the success of digital transformation in state-owned enterprises (SOEs); promote the construction of a cross-enterprise data-sharing platform; and foster collaborative progress in digital transformation throughout the industry. pubtype: Conference Proceedings doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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