Huijue Kelly Duan, Hanxin Hu, Yangin (Ben) Yoon, Miklos Vasarhelyi
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Increasing the utility of performance audit reports: Using textual analytics tools to improve government reporting
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.
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.