{"title":"Internal Information Quality and Corporate Employment Decisions","authors":"Ahrum Choi, Woo-Jong Lee, Yong Gyu Lee, Gaoguang Zhou","doi":"10.1111/auar.12406","DOIUrl":null,"url":null,"abstract":"<p>Prior studies argue that high-quality internal information improves forecasting and reduces internal information asymmetry, and hence facilitates firms’ decision-making. Consistent with this argument, we find that internal information quality (IIQ) is positively associated with employment efficiency. Furthermore, we find that better IIQ leads to an improvement in employment efficiency primarily by improving demand forecasts. The baseline finding is robust to using a setting that exploits time-series shocks to IIQ (i.e., the adoption of SFAS 158) and other sensitivity analyses. Our findings add to prior studies on the role of IIQ in decision-making.</p>","PeriodicalId":51552,"journal":{"name":"Australian Accounting Review","volume":"33 3","pages":"262-283"},"PeriodicalIF":3.1000,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/auar.12406","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Australian Accounting Review","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/auar.12406","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 1
Abstract
Prior studies argue that high-quality internal information improves forecasting and reduces internal information asymmetry, and hence facilitates firms’ decision-making. Consistent with this argument, we find that internal information quality (IIQ) is positively associated with employment efficiency. Furthermore, we find that better IIQ leads to an improvement in employment efficiency primarily by improving demand forecasts. The baseline finding is robust to using a setting that exploits time-series shocks to IIQ (i.e., the adoption of SFAS 158) and other sensitivity analyses. Our findings add to prior studies on the role of IIQ in decision-making.