Data analytics strategy and internal information quality

IF 3.2 3区 管理学 Q1 BUSINESS, FINANCE Contemporary Accounting Research Pub Date : 2024-03-04 DOI:10.1111/1911-3846.12942
Katie W. Lem
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Abstract

I examine whether a strategic focus on data analytics is associated with improvements in firms' internal information quality. Using textual analysis of firm disclosures to identify a data analytics strategy, I first document that firm, leadership, and operating environment characteristics are all important determinants of the decision to adopt a data analytics strategy. I next use operating and financial reporting outcomes to infer whether a data analytics strategy improves internal information quality. I find that a data analytics strategy is associated with enhanced operating efficiency, as adopting firms invest and utilize existing resources more efficiently. I also find that a data analytics strategy is associated with more accurate management forecasts. These results, collectively, are consistent with a data analytics strategy improving firms' internal information quality. Lastly, I corroborate and extend my findings with job postings data, and the results suggest that firm leadership signals their support for data analytics initiatives through disclosure.

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数据分析战略和内部信息质量
我研究了数据分析的战略重点是否与公司内部信息质量的改善相关。通过对公司披露信息的文本分析来确定数据分析战略,我首先记录了公司、领导力和运营环境特征都是决定采用数据分析战略的重要因素。接下来,我利用运营和财务报告结果来推断数据分析战略是否能提高内部信息质量。我发现,数据分析战略与运营效率的提高有关,因为采用数据分析战略的公司会更有效地投资和利用现有资源。我还发现,数据分析战略与更准确的管理预测有关。这些结果共同表明,数据分析战略能提高企业的内部信息质量。最后,我用招聘信息数据证实并扩展了我的研究结果,结果表明,公司领导层通过信息披露发出了支持数据分析计划的信号。本文受版权保护。
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来源期刊
CiteScore
6.20
自引率
11.10%
发文量
97
期刊介绍: Contemporary Accounting Research (CAR) is the premiere research journal of the Canadian Academic Accounting Association, which publishes leading- edge research that contributes to our understanding of all aspects of accounting"s role within organizations, markets or society. Canadian based, increasingly global in scope, CAR seeks to reflect the geographical and intellectual diversity in accounting research. To accomplish this, CAR will continue to publish in its traditional areas of excellence, while seeking to more fully represent other research streams in its pages, so as to continue and expand its tradition of excellence.
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