scholarly journals Big Data, Blockchain, and Artificial Intelligence in Cloud-based Accounting Information Systems

2019 ◽  
Vol 18 (0) ◽  
pp. 44 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Information Systems ◽  
Accounting Information ◽  
Accounting Information Systems

An Accounting Information Systems Perspective on Data Analytics and Big Data

2017 ◽  
Vol 31 (3) ◽  
pp. 101-114 ◽  
Author(s):  
Esperanza Huerta ◽  
Scott Jensen
Keyword(s):  
Big Data ◽  
Information Systems ◽  
Data Analytics ◽  
Accounting Information ◽  
Security Requirements ◽  
Future Research ◽  
Accounting Information Systems ◽  
Systems Perspective ◽  
Analytic Skills

ABSTRACT Forty-six academics and practitioners participated in the second Journal of Information Systems Conference to discuss data analytics and Big Data from an accounting information systems perspective. The panels discussed the evolving role of technology in accounting, privacy within the domain of Big Data, and people and Big Data. Throughout all three panels, several topics emerged that impact all areas of accounting—developing enhanced analytical and data handling skills; evaluating privacy, security requirements, and risks; thinking creatively; and assessing the threat of automation to the accounting profession. Other topics were specific to a segment of the profession, such as the growing demand for privacy compliance audits and the curriculum adjustments necessary to develop data analytic skills. This commentary synthesizes and expands the discussions of the conference panels and suggests potential areas for future research.

scholarly journals The impact of artificial intelligence on corporate control

2020 ◽  
Vol 17 (3) ◽  
pp. 171-178 ◽  
Author(s):  
Reem Solaimani ◽  
Fatima Rashed ◽  
Shahad Mohammed ◽  
Walaa Wahid ElKelish
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Qualitative Content Analysis ◽  
Emerging Market ◽  
Corporate Control ◽  
Accounting Information ◽  
Firm Productivity ◽  
Accounting Information Systems ◽  
Research Questions ◽  
The Impact

This paper investigates the relationship between artificial intelligence (AI) and corporate control in the United Arab Emirates (UAE) emerging market. An exploratory study was conducted to derive the research questions. The nonprobability purposive sampling technique was implemented to select 10 highly experienced interviewees. In-depth primary data was collected through semi-structured interviews during 2019. Qualitative content analysis was used to answer the research questions. The results show a positive impact of AI on firm productivity and the auditing process, but uncertain influence on accounting information systems. More specifically, AI intervention increases firm productivity, creates new jobs and speeds up work processes. However, current AI technology is less likely to redefine auditing roles and still insufficient for developing accounting information systems. Human integration with AI systems will lead to more efficient results. This paper increases our understanding of how AI techniques can improve corporate control practices and the importance of selecting appropriate accounting professionals to decrease AI operation risks.

An REA Ontology-Based Model for Mapping Big Data to Accounting Information Systems Elements

2017 ◽  
Vol 31 (3) ◽  
pp. 45-61 ◽  
Author(s):  
Uday S. Murthy ◽  
Guido L. Geerts
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Information Systems ◽  
Accounting Information ◽  
Data Sources ◽  
Complex Data ◽  
Accounting Information Systems ◽  
Business Transaction ◽  
Business Transactions ◽  
Data Elements

ABSTRACT The term “Big Data” refers to massive volumes of data that grow at an increasing rate and encompass complex data types such as audio and video. While the applications of Big Data and analytic techniques for business purposes have received considerable attention, it is less clear how external sources of Big Data relate to the transaction processing-oriented world of accounting information systems. This paper uses the Resource-Event-Agent Enterprise Ontology (REA) (McCarthy 1982; International Standards Organization [ISO] 2007) to model the implications of external Big Data sources on business transactions. The five-phase REA-based specification of a business transaction as defined in ISO (2007) is used to formally define associations between specific Big Data elements and business transactions. Using Big Data technologies such as Apache Hadoop and MapReduce, a number of information extraction patterns are specified for extracting business transaction-related information from Big Data. We also present a number of analytics patterns to demonstrate how decision making in accounting can benefit from integrating specific external Big Data sources and conventional transactional data. The model and techniques presented in this paper can be used by organizations to formalize the associations between external Big Data elements in their environment and their accounting information artifacts, to build architectures that extract information from external Big Data sources for use in an accounting context, and to leverage the power of analytics for more effective decision making.

scholarly journals An Accounting Information Systems Perspective On Data Analytics And Big Data During 2015-2020

2021 ◽  
Vol 12 (5) ◽  
pp. 509-514
Author(s):  
Jesús Vargas Villa, Mohammad Haroun Sharairi, Alberto Clavería Navarrete, Gerber F. Incacari Sancho
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Information Systems ◽  
Data Analytics ◽  
Accounting Information ◽  
Raw Material ◽  
Accounting Information Systems ◽  
Systems Perspective ◽  
Productivity And Competitiveness

Accounting information systems are responsible for providing information that constitutes raw material for decision making in terms of investment, payments to suppliers, payroll, income, among others. The analysis of such information becomes a cornerstone in the positioning strategies through productivity and competitiveness of any organization. When this analysis is applied to large volumes of information, there are Big Data tools that facilitate the grouping of data according to its source or nature. This paper will describe the most influential accounting information systems in the analysis of large volumes of data that affect the decision making of companies in different sectors of the economy during the period between 2015 and 2020.

scholarly journals The Effect of Artificial Intelligence (AI) on the Quality and Interpretation of Financial Statements in the Hotels Classified in the AQABA Special Economic Zone (ASEZA)

2021 ◽  
Author(s):  
Nawaf Hamadneh ◽  
Mousa Saleh ◽  
Omar Jawabreh ◽  
Muhammad Tahir ◽  
Rania Al Omari ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Standard Deviation ◽  
Accounting Information ◽  
Financial Statements ◽  
Arithmetic Mean ◽  
T Test ◽  
Accounting Information Systems ◽  
Limit Value ◽  
The Impact

The study aims to examine the effects of artificial intelligence (AI) on the consistency and analysis of financial statements in hotels in ASEZA, Jordan. This research is an exploratory, empirical study, which uses the methodology of data collection and interpretation to draw conclusions. The researchers used the arithmetic mean, standard deviation, T-test and ANOVA test to calculate the degree of significance of the study questions. The findings of a basic linear regression study of the impact of AI implemented in Jordanian hotels on the integration of accounting information systems and the association between AI and the integration of accounting information systems (R = 59.6%) also indicate that the fixed limit value amounted to (2.060) and the value of (Beta) for T-test

scholarly journals Using Deming's Cycle for Improvement in a Course

2020 ◽  
Vol 15 (3) ◽  
pp. 31-45
Author(s):  
Anil K. Aggarwal
Keyword(s):  
Big Data ◽  
Information Systems ◽  
Data Analytics ◽  
Business Models ◽  
Accounting Information ◽  
Professional Organizations ◽  
Longitudinal Assessment ◽  
Accounting Information Systems ◽  
Pdca Cycle ◽  
Future Challenges

The boundaries between accounting and technology is becoming fuzzier as accounting companies are becoming consulting companies. Digital economies are changing business models and companies that do not adept can become obsolete very fast. Even professional organizations are recommending using technology to modernize, automate and expedite accounting discipline. Therefore, it is necessary to train personnel to become competent in both technology and accounting. Universities are fulfilling this requirement by offering courses such as Accounting Information Systems, data analytics, big data, etc. This article uses Deming's PlanDoCheckAct (PDCA) cycle for longitudinal assessment and improvement of the AIS course. Instead of re-inventing the wheel, instructors can learn from our experience. This article would be useful for instructors trying different and emerging approaches. In addition, this article would be useful for instructors trying to engage students and to train them for future challenges.

IMPACT OF AIS AND STRESSED OUT AN EMPLOYEES TO THEIR PERFORMANCE AT PT EFRATA RETAILINDO

2019 ◽  
Vol 5 (1) ◽  
pp. 22-30
Author(s):  
Wiwit Ayu Retno Sari ◽  
Suhendro Suhendro ◽  
R. Riana Dewi
Keyword(s):  
Information Systems ◽  
Work Stress ◽  
Quantitative Research ◽  
Linear Regression Analysis ◽  
Accounting Information ◽  
Multiple Linear Regression Analysis ◽  
Primary Data ◽  
Coefficient Of Determination ◽  
Accounting Information System ◽  
Accounting Information Systems

This research aims to test the influence of accounting information system and work stress on performance of employees of PT Efrata Retailindo. The type of research used in this research is quantitative research. The source of the data in the research is primary data. The population in this study are all employees of PT Efrata Retailindo totalling 47 people. Sampling techniques in the study using a purposive sample. While the data collection method used is to use the questionnaire to all employees of PT Efrata Retailindo. Data analysis techniques using multiple linear regression analysis. Based on the results of the study it can be concluded that work stress had no effect on performance of employees of PT Efrata Retailindo, while information systems accounting effect on the performance of the employees of PT Efrata Retailindo. The value of the coefficient of determination (R2) amounting to 0.106. This indicates that variansi on a variable performance practice undertaken by the company PT Efrata Retailindo of 10.6% can be explained by work stress variables and accounting information systems, while the remaining 89.4% explained by other factors outside the researched.

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