Charles P. Cullinan, Richard Holowczak, David Louton, Hakan Saraoglu
{"title":"与退出或处置活动相关的成本:对信息披露和市场反应的专题建模调查","authors":"Charles P. Cullinan, Richard Holowczak, David Louton, Hakan Saraoglu","doi":"10.1002/isaf.1545","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The Securities and Exchange Commission (SEC) mandates disclosure of exit or disposal activity events in 8-K filings. We use Latent Dirichlet Allocation (LDA), a topic modeling method from computational linguistics, to investigate the possibility that substantively different event types may be subsumed under Item 2.05, the SEC category for costs associated with exit or disposal activities. Our analysis reveals that four distinct topics are reported under the Item 2.05 umbrella category: (1) restructuring, (2) disposal of a line of business, (3) plant closings, and (4) layoffs/workforce reductions. We then investigate various aspects of these 8-K filings. We find that the market reacts most negatively to workforce reductions that are reported in the absence of a broader strategic initiative. Subsequent amendments to the Item 2.05 8-K filings are significantly more likely for restructuring initiatives, and significantly less likely for layoffs. Asset impairment charges most frequently accompany line-of-business disposals and plant closings. Our results demonstrate that there are meaningful differences between the event types reported within Item 2.05 filings and that LDA provides a useful means of differentiating among these event types.</p>\n </div>","PeriodicalId":53473,"journal":{"name":"Intelligent Systems in Accounting, Finance and Management","volume":"30 4","pages":"173-191"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Costs associated with exit or disposal activities: A topic modeling investigation of disclosure and market reaction\",\"authors\":\"Charles P. Cullinan, Richard Holowczak, David Louton, Hakan Saraoglu\",\"doi\":\"10.1002/isaf.1545\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>The Securities and Exchange Commission (SEC) mandates disclosure of exit or disposal activity events in 8-K filings. We use Latent Dirichlet Allocation (LDA), a topic modeling method from computational linguistics, to investigate the possibility that substantively different event types may be subsumed under Item 2.05, the SEC category for costs associated with exit or disposal activities. Our analysis reveals that four distinct topics are reported under the Item 2.05 umbrella category: (1) restructuring, (2) disposal of a line of business, (3) plant closings, and (4) layoffs/workforce reductions. We then investigate various aspects of these 8-K filings. We find that the market reacts most negatively to workforce reductions that are reported in the absence of a broader strategic initiative. Subsequent amendments to the Item 2.05 8-K filings are significantly more likely for restructuring initiatives, and significantly less likely for layoffs. Asset impairment charges most frequently accompany line-of-business disposals and plant closings. Our results demonstrate that there are meaningful differences between the event types reported within Item 2.05 filings and that LDA provides a useful means of differentiating among these event types.</p>\\n </div>\",\"PeriodicalId\":53473,\"journal\":{\"name\":\"Intelligent Systems in Accounting, Finance and Management\",\"volume\":\"30 4\",\"pages\":\"173-191\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligent Systems in Accounting, Finance and Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/isaf.1545\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Systems in Accounting, Finance and Management","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/isaf.1545","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
Costs associated with exit or disposal activities: A topic modeling investigation of disclosure and market reaction
The Securities and Exchange Commission (SEC) mandates disclosure of exit or disposal activity events in 8-K filings. We use Latent Dirichlet Allocation (LDA), a topic modeling method from computational linguistics, to investigate the possibility that substantively different event types may be subsumed under Item 2.05, the SEC category for costs associated with exit or disposal activities. Our analysis reveals that four distinct topics are reported under the Item 2.05 umbrella category: (1) restructuring, (2) disposal of a line of business, (3) plant closings, and (4) layoffs/workforce reductions. We then investigate various aspects of these 8-K filings. We find that the market reacts most negatively to workforce reductions that are reported in the absence of a broader strategic initiative. Subsequent amendments to the Item 2.05 8-K filings are significantly more likely for restructuring initiatives, and significantly less likely for layoffs. Asset impairment charges most frequently accompany line-of-business disposals and plant closings. Our results demonstrate that there are meaningful differences between the event types reported within Item 2.05 filings and that LDA provides a useful means of differentiating among these event types.
期刊介绍:
Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.