Nan Yang , Shanmin Li , Zhihong Huang , Caiping Wang
{"title":"The role of digital transformation in mergers and acquisitions","authors":"Nan Yang , Shanmin Li , Zhihong Huang , Caiping Wang","doi":"10.1016/j.najef.2024.102306","DOIUrl":null,"url":null,"abstract":"<div><div>How digital transformation influences mergers and acquisitions (M&A) in firms is a significant yet seldom-explored inquiry. We argue that, differing from the “winner-take-all” logic observed in M&A undertaken by born-digital enterprises, digital transformation initiatives pursued by traditional firms can enhance long-term M&A performance by mitigating internal control costs in terms of organizational inertia. The findings from an analysis of M&A activities conducted by publicly listed Chinese firms demonstrate that the digital transformation efforts of traditional enterprises possess the potential to substantially augment long-term M&A performance. Nevertheless, this facilitative impact may encounter limitations due to structural inertia, strategic persistence and external pressure. Moreover, when compared to “technology-based” digital transformation, “application-based” digital transformation exhibits a superior capacity to facilitate long-term M&A performance by alleviating routine rigidity. This study extends the application of organizational inertia theory to the digital economy era and provides practical insights for enterprises that are implementing digital-transformation strategies.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102306"},"PeriodicalIF":3.8000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"North American Journal of Economics and Finance","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1062940824002316","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
How digital transformation influences mergers and acquisitions (M&A) in firms is a significant yet seldom-explored inquiry. We argue that, differing from the “winner-take-all” logic observed in M&A undertaken by born-digital enterprises, digital transformation initiatives pursued by traditional firms can enhance long-term M&A performance by mitigating internal control costs in terms of organizational inertia. The findings from an analysis of M&A activities conducted by publicly listed Chinese firms demonstrate that the digital transformation efforts of traditional enterprises possess the potential to substantially augment long-term M&A performance. Nevertheless, this facilitative impact may encounter limitations due to structural inertia, strategic persistence and external pressure. Moreover, when compared to “technology-based” digital transformation, “application-based” digital transformation exhibits a superior capacity to facilitate long-term M&A performance by alleviating routine rigidity. This study extends the application of organizational inertia theory to the digital economy era and provides practical insights for enterprises that are implementing digital-transformation strategies.
期刊介绍:
The focus of the North-American Journal of Economics and Finance is on the economics of integration of goods, services, financial markets, at both regional and global levels with the role of economic policy in that process playing an important role. Both theoretical and empirical papers are welcome. Empirical and policy-related papers that rely on data and the experiences of countries outside North America are also welcome. Papers should offer concrete lessons about the ongoing process of globalization, or policy implications about how governments, domestic or international institutions, can improve the coordination of their activities. Empirical analysis should be capable of replication. Authors of accepted papers will be encouraged to supply data and computer programs.