Top managers with information technology backgrounds and digital transformation: Evidence from small and medium companies
Kaixia Zhang and
Caiqi Bu
Economic Modelling, 2024, vol. 132, issue C
Abstract:
Small and medium-sized enterprises (SMEs) often struggle to successfully realize digital transformation (DT) due to constraints of size, technology, capital, and the ability and willingness to transform. This study first investigates the effect of top managers with information technology (IT) backgrounds on SMEs' DT from the perspective of within the business organization by using Chinese-listed company data from 2005 to 2020. The results show that IT top managers significantly facilitate SMEs' DT, especially for non-state-owned companies and those located in highly market-oriented regions. Mechanism analysis reveals that IT top managers promote SMEs' DT by increasing IT investment, reducing information asymmetry, and lowering financing constraints. Our findings provide new insights into solving SMEs' DT dilemma and improving the endogenous dynamics of digitalization among SMEs from a top-down perspective within the company.
Keywords: Top manager; Information technology; Digital transformation; Small and medium-sized companies (search for similar items in EconPapers)
JEL-codes: G30 G33 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0264999323004418
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:ecmode:v:132:y:2024:i:c:s0264999323004418
DOI: 10.1016/j.econmod.2023.106629
Access Statistics for this article
Economic Modelling is currently edited by S. Hall and P. Pauly
More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().