We present a novel hands-on approach for teaching students the concepts and business processes of transaction cycles. Specifically, the hands-on activities focus on sales and procurement cycles. Upon completion of the hands-on activities, students will a) develop a better understanding of the business processes and business forms for sales and procurement cycles and b) build relevant critical thinking skills. We evaluate students’ learning by providing a comparison between students who learned the concepts of transaction cycles and business processes and performed the transaction cycle hands-on activity in class versus those students who only learned the concepts of transaction cycles and business processes in class. Although the hands-on activities were used in an accounting information systems class, they can also be applied to other business disciplines, such as engineering and project management classes.
{"title":"Teaching Business Transaction Cycles Using a Hands-on Activities Approach","authors":"T. Wang, Victoria Chiu, Yunsen Wang, Tiffany Chiu","doi":"10.2308/jeta-2020-066","DOIUrl":"https://doi.org/10.2308/jeta-2020-066","url":null,"abstract":"We present a novel hands-on approach for teaching students the concepts and business processes of transaction cycles. Specifically, the hands-on activities focus on sales and procurement cycles. Upon completion of the hands-on activities, students will a) develop a better understanding of the business processes and business forms for sales and procurement cycles and b) build relevant critical thinking skills. We evaluate students’ learning by providing a comparison between students who learned the concepts of transaction cycles and business processes and performed the transaction cycle hands-on activity in class versus those students who only learned the concepts of transaction cycles and business processes in class. Although the hands-on activities were used in an accounting information systems class, they can also be applied to other business disciplines, such as engineering and project management classes.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48480991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Bora, H. Duan, M. Vasarhelyi, C. Zhang, Jun Dai
This paper advocates for a drastic transformation of government accountability and reporting. With the availability of Big Data and the advancement of technologies, the existing government reporting schema fails to meet the public's increasing demand for accountability. We discuss the need for the government to reform its reporting schema and prescribe potential paths toward a data-driven, analytics-based, real-time, and proactive reporting paradigm. We conceptualize an app-based continuous monitoring and reporting environment that is real-time, structured, future-oriented, and that incorporates non-financial information like ESG and infrastructure. This reformed reporting paradigm highlights the expected role of government reporting: to provide accountability to the public.
{"title":"The Transformation of Government Accountability and Reporting","authors":"I. Bora, H. Duan, M. Vasarhelyi, C. Zhang, Jun Dai","doi":"10.2308/jeta-10780","DOIUrl":"https://doi.org/10.2308/jeta-10780","url":null,"abstract":"\u0000 This paper advocates for a drastic transformation of government accountability and reporting. With the availability of Big Data and the advancement of technologies, the existing government reporting schema fails to meet the public's increasing demand for accountability. We discuss the need for the government to reform its reporting schema and prescribe potential paths toward a data-driven, analytics-based, real-time, and proactive reporting paradigm. We conceptualize an app-based continuous monitoring and reporting environment that is real-time, structured, future-oriented, and that incorporates non-financial information like ESG and infrastructure. This reformed reporting paradigm highlights the expected role of government reporting: to provide accountability to the public.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45379449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is based on an interview on January 9, 2020, with Robert H. (Bob) Herz, the former two-term chairman of the Financial Accounting Standards Board, on how the environment for business reporting has evolved and how it may continue to evolve. Bob Herz has also held decision-making positions as a part-time member of the IASB and on the board of the SASB. In this interview, we discuss a pragmatic reporting model suited to the era of Big Data and technology. We also explain the different interests of the reporting process, including the standard-setters, preparers, auditors, and users. The main idea of this paper focuses on how to incorporate Big Data and technology into reporting models working within the current framework and needs of the stakeholders. We then outline several use cases that illustrate a refined reporting model using Big Data and technology.
{"title":"Advancing Financial Reporting in the Age of Technology: An Interview with Robert H. Herz","authors":"Robert H. Herz, D. Pei","doi":"10.2308/jeta-2021-028","DOIUrl":"https://doi.org/10.2308/jeta-2021-028","url":null,"abstract":"This paper is based on an interview on January 9, 2020, with Robert H. (Bob) Herz, the former two-term chairman of the Financial Accounting Standards Board, on how the environment for business reporting has evolved and how it may continue to evolve. Bob Herz has also held decision-making positions as a part-time member of the IASB and on the board of the SASB. In this interview, we discuss a pragmatic reporting model suited to the era of Big Data and technology. We also explain the different interests of the reporting process, including the standard-setters, preparers, auditors, and users. The main idea of this paper focuses on how to incorporate Big Data and technology into reporting models working within the current framework and needs of the stakeholders. We then outline several use cases that illustrate a refined reporting model using Big Data and technology.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43352883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates some essential questions that might interest auditors regarding the impact of artificial intelligence (AI) applications on the auditing profession by reviewing a selective bibliography of papers published mainly between 2016 and 2020. It discusses the major AI applications in the auditing field and explores the associated benefits in increasing auditing work’s effectiveness, efficiency, and quality. It further illustrates the major internal critical considerations that should be taken into account before AI application adoption in auditing practices, from initial decision-making to the use of proper countermeasures, to ensure the successful and effective implementation of AI applications. The extent to which AI applications in the accounting and auditing field might affect current hiring practices and threaten an auditor’s job, as performed today, is discussed and various debates and contradictory opinions are presented. The major AI applications adopted by the Big Four accounting firms are also discussed.
{"title":"Artificial Intelligence Applications in the Auditing Profession: A Literature Review","authors":"Ghayah Almufadda, N. Almezeini","doi":"10.2308/jeta-2020-083","DOIUrl":"https://doi.org/10.2308/jeta-2020-083","url":null,"abstract":"This paper investigates some essential questions that might interest auditors regarding the impact of artificial intelligence (AI) applications on the auditing profession by reviewing a selective bibliography of papers published mainly between 2016 and 2020. It discusses the major AI applications in the auditing field and explores the associated benefits in increasing auditing work’s effectiveness, efficiency, and quality. It further illustrates the major internal critical considerations that should be taken into account before AI application adoption in auditing practices, from initial decision-making to the use of proper countermeasures, to ensure the successful and effective implementation of AI applications. The extent to which AI applications in the accounting and auditing field might affect current hiring practices and threaten an auditor’s job, as performed today, is discussed and various debates and contradictory opinions are presented. The major AI applications adopted by the Big Four accounting firms are also discussed.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":"1 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41441250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Data analytics problems, methods and software are changing rapidly. Learning how to learn new technologies might be the most important skill for students to develop in an analytics course. We present a pedagogical framework that promotes self-regulated learning and metacognition and three student-driven assignments that can be used in accounting analytics and other courses that incorporate technology. The assignment can be used by faculty who do not have training in analytics. The assignments adopt a learn-through-teaching approach that helps students: 1) define a conceptual or technical knowledge gap; 2) identify resources available for filling that gap; 3) work independently to acquire the desired knowledge; 4) break knowledge into components and arrange in a logical sequence; and 5) reinforce knowledge by presenting to others in an accessible manner. These assignments equip students with confidence and capabilities that will enable them to keep up with advances in technology.
{"title":"Learning Analytics and Technology Through Teaching","authors":"Matthew Kaufman, Kristi Yuthas","doi":"10.2308/jeta-2020-056","DOIUrl":"https://doi.org/10.2308/jeta-2020-056","url":null,"abstract":"Data analytics problems, methods and software are changing rapidly. Learning how to learn new technologies might be the most important skill for students to develop in an analytics course. We present a pedagogical framework that promotes self-regulated learning and metacognition and three student-driven assignments that can be used in accounting analytics and other courses that incorporate technology. The assignment can be used by faculty who do not have training in analytics. The assignments adopt a learn-through-teaching approach that helps students: 1) define a conceptual or technical knowledge gap; 2) identify resources available for filling that gap; 3) work independently to acquire the desired knowledge; 4) break knowledge into components and arrange in a logical sequence; and 5) reinforce knowledge by presenting to others in an accessible manner. These assignments equip students with confidence and capabilities that will enable them to keep up with advances in technology.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44685582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study explores the cybersecurity risk disclosure differences between foreign firms listed in the US and US firms. We first extract cybersecurity risks disclosures text with a Python program based on a list of cybersecurity key words. We then perform textual analysis of the cybersecurity risk disclosures in foreign firms’ 20-F filings and US firms’ 10-K filings. During our study period, we observe that foreign firms disclose more about their cybersecurity risks and their disclosures are more readable than US firms. Foreign firms also use more numbers, fewer uncertainty words and fewer litigious language than their US counterparts. In general, our study suggests that cybersecurity risk disclosures made by foreign firms are clearer and more specific than those made by US firms. This finding could have implications for disclosure regulation and home bias research.
{"title":"Comparing the Cybersecurity Risk Disclosures of US and Foreign Firms","authors":"Thomas G. Calderon, Lei Gao","doi":"10.2308/JETA-2020-008","DOIUrl":"https://doi.org/10.2308/JETA-2020-008","url":null,"abstract":"This study explores the cybersecurity risk disclosure differences between foreign firms listed in the US and US firms. We first extract cybersecurity risks disclosures text with a Python program based on a list of cybersecurity key words. We then perform textual analysis of the cybersecurity risk disclosures in foreign firms’ 20-F filings and US firms’ 10-K filings. During our study period, we observe that foreign firms disclose more about their cybersecurity risks and their disclosures are more readable than US firms. Foreign firms also use more numbers, fewer uncertainty words and fewer litigious language than their US counterparts. In general, our study suggests that cybersecurity risk disclosures made by foreign firms are clearer and more specific than those made by US firms. This finding could have implications for disclosure regulation and home bias research.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47946411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study has two objectives. The first, to develop an earnings movement prediction model to help investors in their decision process, the second, to explore the potential of Recurrent Neural Networks (RNN) in financial statement analysis and present a detailed model for its application. RNNs' two major advantages are: they do not make assumptions regarding the data and allow users to search whatever functional form best describes the underlying relationship between financial data and changes in earnings; they dynamically account for time – series behavior, earnings of a certain time period are not independent of earnings in previous time period s. The paper utilizes the newly mandated XBRL data, whose benefits are that it is freely available, easily accessible and is more timely than traditional data bases. The results of the study validate the use of RNNs by providing a higher accuracy prediction than neural networks and logistic regression.
{"title":"Predicting Earnings Directional Movement Utilizing Recurrent Neural Networks (RNN)","authors":"Amos Baranes, Rimona Palas, A. Yosef","doi":"10.2308/jeta-2021-001","DOIUrl":"https://doi.org/10.2308/jeta-2021-001","url":null,"abstract":"The study has two objectives. The first, to develop an earnings movement prediction model to help investors in their decision process, the second, to explore the potential of Recurrent Neural Networks (RNN) in financial statement analysis and present a detailed model for its application. RNNs' two major advantages are: they do not make assumptions regarding the data and allow users to search whatever functional form best describes the underlying relationship between financial data and changes in earnings; they dynamically account for time – series behavior, earnings of a certain time period are not independent of earnings in previous time period s. The paper utilizes the newly mandated XBRL data, whose benefits are that it is freely available, easily accessible and is more timely than traditional data bases. The results of the study validate the use of RNNs by providing a higher accuracy prediction than neural networks and logistic regression.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43013360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexander Pelaez, Deb Sledgianowski, S. Petra, Jianbing Zhu, Nooshin Nejati
This paper proposes and tests a methodology for the development of a simulation for individual tax returns in the United States, enabling students of taxation and interested parties to examine changes to the tax code, examine the effects of tax planning alternatives, and conduct repeated experimental testing on the tax return data. The simulation produced data for 147,000 tax returns, representing approximately 1% of the population of filed tax returns as noted by the IRS/SOI. We present the methodology on how we created the simulation and compare the tax returns of the simulation to the measures provided by the IRS. Our simulated return data very closely matched the number and combined dollar value of the IRS/SOI summary data at the adjusted gross income (AGI), state, and filing status levels.
{"title":"US Individual Income Tax Return Simulated Data: A Methodology","authors":"Alexander Pelaez, Deb Sledgianowski, S. Petra, Jianbing Zhu, Nooshin Nejati","doi":"10.2308/jeta-2020-055","DOIUrl":"https://doi.org/10.2308/jeta-2020-055","url":null,"abstract":"This paper proposes and tests a methodology for the development of a simulation for individual tax returns in the United States, enabling students of taxation and interested parties to examine changes to the tax code, examine the effects of tax planning alternatives, and conduct repeated experimental testing on the tax return data. The simulation produced data for 147,000 tax returns, representing approximately 1% of the population of filed tax returns as noted by the IRS/SOI. We present the methodology on how we created the simulation and compare the tax returns of the simulation to the measures provided by the IRS. Our simulated return data very closely matched the number and combined dollar value of the IRS/SOI summary data at the adjusted gross income (AGI), state, and filing status levels.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48072641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Students use data analytics to evaluate fictitious online sales data and explore sales tax nexus standards following South Dakota v. Wayfair, Inc. ( Wayfair). This case provides instructors flexibility. Students can use Tableau to create visualizations that identify states with sales satisfying nexus standards, applying the Wayfair or multistate standards. Students can use Robotics Process Automation to evaluate whether the company established nexus in a particular state. Instructors can include no tax research or select from several pertinent tax research questions. This case can be used in undergraduate or graduate tax, audit, or AIS courses, from compliance or tax risk perspectives. The learning objectives are to develop students’: (1) knowledge of data analytics; (2) knowledge of economic nexus and assess the tax law changes impact on business decisions; (3) research skills; (4) skills specific to data analytics and data visualization in accounting; and (5) effective oral and written communication skills.
{"title":"ChicagoLand Popcorn® - Examining Online Retailer Nexus Following Wayfair Using Data Visualization and Robotics Process Automation","authors":"Christine Cheng, J. Eagan, Amy J. N. Yurko","doi":"10.2308/jeta-2020-044","DOIUrl":"https://doi.org/10.2308/jeta-2020-044","url":null,"abstract":"Students use data analytics to evaluate fictitious online sales data and explore sales tax nexus standards following South Dakota v. Wayfair, Inc. ( Wayfair). This case provides instructors flexibility. Students can use Tableau to create visualizations that identify states with sales satisfying nexus standards, applying the Wayfair or multistate standards. Students can use Robotics Process Automation to evaluate whether the company established nexus in a particular state. Instructors can include no tax research or select from several pertinent tax research questions. This case can be used in undergraduate or graduate tax, audit, or AIS courses, from compliance or tax risk perspectives. The learning objectives are to develop students’: (1) knowledge of data analytics; (2) knowledge of economic nexus and assess the tax law changes impact on business decisions; (3) research skills; (4) skills specific to data analytics and data visualization in accounting; and (5) effective oral and written communication skills.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45596875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nuriddin Tojiboyev, Deniz Appelbaum, A. Kogan, M. Vasarhelyi
The purpose of this teaching note is to explain how Structured Query Language (SQL) queries can help auditors to independently retrieve properly formatted data as audit evidence or for further analyses. The note demonstrates data extraction using Microsoft (MS) Access, one of the simplest SQL compliant database software applications. We use a dataset fragment extracted from the publicly available enterprise datasets provided by Walton College (University of Arkansas) to run SQL queries as a part of audit investigations. Data extraction is the first step of Extract, Transform, and Load (ETL) and may be time-consuming. We demonstrate how SQL queries can assist with this task, thereby allowing the auditor to begin analysis sooner. This teaching note can be used to prepare future auditors for the emerging data-rich and technology-driven business environment.
{"title":"Basics of SQL for Audit Data Retrieval and Analysis","authors":"Nuriddin Tojiboyev, Deniz Appelbaum, A. Kogan, M. Vasarhelyi","doi":"10.2308/jeta-2020-021","DOIUrl":"https://doi.org/10.2308/jeta-2020-021","url":null,"abstract":"The purpose of this teaching note is to explain how Structured Query Language (SQL) queries can help auditors to independently retrieve properly formatted data as audit evidence or for further analyses. The note demonstrates data extraction using Microsoft (MS) Access, one of the simplest SQL compliant database software applications. We use a dataset fragment extracted from the publicly available enterprise datasets provided by Walton College (University of Arkansas) to run SQL queries as a part of audit investigations. Data extraction is the first step of Extract, Transform, and Load (ETL) and may be time-consuming. We demonstrate how SQL queries can assist with this task, thereby allowing the auditor to begin analysis sooner. This teaching note can be used to prepare future auditors for the emerging data-rich and technology-driven business environment.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48164088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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