{"title":"Digital transformation and enterprise mergers and acquisitions: Mechanism tests and empirical evidence","authors":"Mengyu Shi , Qiong Xu , Yu Shi , Jiamin Yan","doi":"10.1016/j.econmod.2026.107528","DOIUrl":null,"url":null,"abstract":"<div><div>Digital transformation acts as a driver for high-quality enterprise development. Focusing on Chinese A-share listed firms, this study uses machine learning methods to empirically investigate the impact of digital transformation on enterprise mergers and acquisitions (M&A). Results indicate that digital transformation can significantly promote enterprise M&A. This conclusion remains valid after overcoming endogeneity and executing various robustness checks. Notably, the influence of digital transformation on M&A varies significantly, with stronger effects observed in non-state-owned enterprises, those in competitive markets, and firms in a better financial environment. Mechanistic analysis reveals that enhanced financing and information channels are key pathways through which digital transformation facilitates M&A. This study offers empirical insights into the microeconomic impacts of digital transformation, emphasizing its role in enterprise M&A strategies.</div></div>","PeriodicalId":48419,"journal":{"name":"Economic Modelling","volume":"158 ","pages":"Article 107528"},"PeriodicalIF":4.7000,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Modelling","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S026499932600057X","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/2/5 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Digital transformation acts as a driver for high-quality enterprise development. Focusing on Chinese A-share listed firms, this study uses machine learning methods to empirically investigate the impact of digital transformation on enterprise mergers and acquisitions (M&A). Results indicate that digital transformation can significantly promote enterprise M&A. This conclusion remains valid after overcoming endogeneity and executing various robustness checks. Notably, the influence of digital transformation on M&A varies significantly, with stronger effects observed in non-state-owned enterprises, those in competitive markets, and firms in a better financial environment. Mechanistic analysis reveals that enhanced financing and information channels are key pathways through which digital transformation facilitates M&A. This study offers empirical insights into the microeconomic impacts of digital transformation, emphasizing its role in enterprise M&A strategies.
期刊介绍:
Economic Modelling fills a major gap in the economics literature, providing a single source of both theoretical and applied papers on economic modelling. The journal prime objective is to provide an international review of the state-of-the-art in economic modelling. Economic Modelling publishes the complete versions of many large-scale models of industrially advanced economies which have been developed for policy analysis. Examples are the Bank of England Model and the US Federal Reserve Board Model which had hitherto been unpublished. As individual models are revised and updated, the journal publishes subsequent papers dealing with these revisions, so keeping its readers as up to date as possible.