Tobias Mettler , Gianluca Miscione , Claus D. Jacobs , Ali A. Guenduez
{"title":"Same same but different: How policies frame societal-level digital transformation","authors":"Tobias Mettler , Gianluca Miscione , Claus D. Jacobs , Ali A. Guenduez","doi":"10.1016/j.giq.2024.101932","DOIUrl":null,"url":null,"abstract":"<div><p>The digital transformation (DT) is not only forcing companies to rethink their business models but is also challenging governments to address the question of how information technology will change society today and in the future. By setting the legal boundaries and acting as an investor and promoter of the domestic digital economy, governments actively influence in which ways this transformational process takes place. The vision and objectives how DT should be realized on state level is portrayed in well-crafted DT policies. Yet, little is known how governments, as strategic actors, see their role in the DT and how they frame these documents. In this paper, we argue that policymaking about DT is isomorphic in the global context, rather than a differentiator for countries to gain a competitive edge. Using machine learning to analyze a vast text corpus of policy documents, we identify the common repertoire of narratives used by governments from all around the globe to picture their vision of the DT and show that DT policies appear to be almost context-free due to their high similarity.</p></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"41 2","pages":"Article 101932"},"PeriodicalIF":7.8000,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0740624X24000248/pdfft?md5=bb4d30b1977970f03bf33c91dbf70f8c&pid=1-s2.0-S0740624X24000248-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Government Information Quarterly","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0740624X24000248","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The digital transformation (DT) is not only forcing companies to rethink their business models but is also challenging governments to address the question of how information technology will change society today and in the future. By setting the legal boundaries and acting as an investor and promoter of the domestic digital economy, governments actively influence in which ways this transformational process takes place. The vision and objectives how DT should be realized on state level is portrayed in well-crafted DT policies. Yet, little is known how governments, as strategic actors, see their role in the DT and how they frame these documents. In this paper, we argue that policymaking about DT is isomorphic in the global context, rather than a differentiator for countries to gain a competitive edge. Using machine learning to analyze a vast text corpus of policy documents, we identify the common repertoire of narratives used by governments from all around the globe to picture their vision of the DT and show that DT policies appear to be almost context-free due to their high similarity.
期刊介绍:
Government Information Quarterly (GIQ) delves into the convergence of policy, information technology, government, and the public. It explores the impact of policies on government information flows, the role of technology in innovative government services, and the dynamic between citizens and governing bodies in the digital age. GIQ serves as a premier journal, disseminating high-quality research and insights that bridge the realms of policy, information technology, government, and public engagement.