{"title":"New intelligent empowerment for digital transformation","authors":"Peng Yifeng, Gao Chen","doi":"arxiv-2406.18440","DOIUrl":null,"url":null,"abstract":"This study proposes an innovative evaluation method based on large language\nmodels (LLMs) specifically designed to measure the digital transformation (DT)\nprocess of enterprises. By analyzing the annual reports of 4407 companies\nlisted on the New York Stock Exchange and Nasdaq from 2005 to 2022, a\ncomprehensive set of DT indicators was constructed. The findings revealed that\nDT significantly improves a company's financial performance, however, different\ndigital technologies exhibit varying effects on financial performance.\nSpecifically, blockchain technology has a relatively limited positive impact on\nfinancial performance. In addition, this study further discovered that DT can\npromote the growth of financial performance by enhancing operational efficiency\nand reducing costs. This study provides a novel DT evaluation tool for the\nacademic community, while also expanding the application scope of generative\nartificial intelligence technology in economic research.","PeriodicalId":501294,"journal":{"name":"arXiv - QuantFin - Computational Finance","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Computational Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2406.18440","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study proposes an innovative evaluation method based on large language
models (LLMs) specifically designed to measure the digital transformation (DT)
process of enterprises. By analyzing the annual reports of 4407 companies
listed on the New York Stock Exchange and Nasdaq from 2005 to 2022, a
comprehensive set of DT indicators was constructed. The findings revealed that
DT significantly improves a company's financial performance, however, different
digital technologies exhibit varying effects on financial performance.
Specifically, blockchain technology has a relatively limited positive impact on
financial performance. In addition, this study further discovered that DT can
promote the growth of financial performance by enhancing operational efficiency
and reducing costs. This study provides a novel DT evaluation tool for the
academic community, while also expanding the application scope of generative
artificial intelligence technology in economic research.