Increasing the utility of performance audit reports: Using textual analytics tools to improve government reporting

Q1 Economics, Econometrics and Finance Intelligent Systems in Accounting, Finance and Management Pub Date : 2022-12-07 DOI:10.1002/isaf.1526
Huijue Kelly Duan, Hanxin Hu, Yangin (Ben) Yoon, Miklos Vasarhelyi
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Abstract

This study conducts a pilot test analyzing reports from New York, New Jersey, and California and uses textual analytics to reengineer government performance audit reporting. It advocates a performance audit database that can facilitate easier access and extract relevant information from lengthy reports in a timely manner. The study presents a framework to identify the commonalities and differences in terminologies used by sampled states, evaluates and extracts relevant content from the reports according to Generally Accepted Government Auditing Standards requirements, and constructs a taxonomy specific to government performance audits. Furthermore, this study investigates the disclosure quality by examining linguistic and similarity features, such as report length, specificity, readability, comprehensibility, and content similarity. This paper raises attention to a key legislative task that requires reporting reforms.

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提高绩效审计报告的效用:使用文本分析工具改进政府报告
本研究对来自纽约、新泽西和加利福尼亚的报告进行了试点测试,并使用文本分析来重新设计政府绩效审计报告。它提倡建立一个绩效审计数据库,以便于更容易地访问和及时从冗长的报告中提取相关信息。该研究提出了一个框架,以识别抽样国家使用的术语的共性和差异,根据公认的政府审计标准要求评估和提取报告中的相关内容,并构建了一个针对政府绩效审计的分类。此外,本研究通过考察语言和相似性特征,如报告长度、特异性、可读性、可理解性和内容相似性来调查披露质量。本文引起了对一项需要报告改革的关键立法任务的关注。
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来源期刊
Intelligent Systems in Accounting, Finance and Management
Intelligent Systems in Accounting, Finance and Management Economics, Econometrics and Finance-Finance
CiteScore
6.00
自引率
0.00%
发文量
0
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.
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