Geographical influences, media attention and enterprise digital transformation

Teng Wang, Xiaoyang Zhao and Xiaotong Li

Technological Forecasting and Social Change, 2025, vol. 210, issue C

Abstract: We investigate how geographic factors influence enterprise digital transformation (EDT) by applying resource dependence theory and the attention-based view. Analyzing spatial and attribute data from Chinese firms between 2011 and 2020, our study reveals three key findings: (1) proximity to major cities positively affects EDT; (2) local enterprise digitalization density (LEDD) mediates the relationship between city proximity and EDT; and (3) media attention has an inverted U-shaped moderating effect on both the relationship between LEDD and EDT, and on LEDD’s mediation effect. Our heterogeneity analysis shows that compared to non-provincial dual-core cities, proximity to major cities has stronger influence on enterprise digital transformation in provincial capitals and first-tier cities. Additionally, the impact of proximity to major cities on EDT is significantly stronger for non-state-owned enterprises and technology-intensive enterprises. Our research broadens the understanding of the spatial dimensions of digital transformation, offering a nuanced theoretical framework that highlights the interplays between geographic and cognitive factors in shaping corporate digital strategy. These insights have valuable implications for policymakers and business leaders seeking to promote enterprise digital transformation.

Keywords: Enterprise digital transformation; Geographical location; Proximity to major cities; Local density; Media attention (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162524006516
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:210:y:2025:i:c:s0040162524006516

DOI: 10.1016/j.techfore.2024.123853

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().