IMPACT OF TECHNOLOGICAL READINESS ON ADOPTING ARTIFICIAL INTELLIGENCE IN ACCOUNTING
Thesis title: | IMPACT OF TECHNOLOGICAL READINESS ON ADOPTING ARTIFICIAL INTELLIGENCE IN ACCOUNTING |
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Author: | Al Bari, Huzaifa Mahmood |
Thesis type: | Diploma thesis |
Supervisor: | Křivanec, Oto |
Opponents: | Kmoch, Štěpán |
Thesis language: | English |
Abstract: | This Master’s Thesis is focused on Artificial Intelligence in Accounting in terms of the changing environment, increasing challenges, automation and the Technological readiness of Accounting Students and Entry-Level Accountants who are the target population of the study. This quantitative correlation study was conducted to find the relationship between the technological readiness and technological adoption of Artificial Intelligence enabled technologies in accounting and auditing which is vital in coping with the challenges posed by changing environment. The study was conducted in regards to the TR and TA perseverance of accounting students and entry-level accountants, of which the respondents were (n=104) which consisted of Bachelor level, Masters and PHD level accounting students from Prague University of Economics and Business and entry level accountants from DXC Technology shared service center in Prague. The participants were presented with a questionnaire survey through google forms online platform. Using the forms of analysis such as bivariate correlation and linear regression it was concluded that TR, PU and PEOU have a positive influence in the TA of A.I. by accounting students and entry-level accountants and that TR positively impacts PU and PEOU. |
Keywords: | Bivariate Correlation; Linear Regression Analysis; Artificial Intelligence, Technological Acceptance; Robotic Process Automation; Pearson’s Correlation, ; Technological Readiness; Perceived Usefulness, Perceived Ease of Use.; Machine Learning, Technological Acceptance |
Thesis title: | IMPACT OF TECHNOLOGICAL READINESS ON ADOPTING ARTIFICIAL INTELLIGENCE IN ACCOUNTING |
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Author: | Al Bari, Huzaifa Mahmood |
Thesis type: | Diplomová práce |
Supervisor: | Křivanec, Oto |
Opponents: | Kmoch, Štěpán |
Thesis language: | English |
Abstract: | This Master’s Thesis is focused on Artificial Intelligence in Accounting in terms of the changing environment, increasing challenges, automation and the Technological readiness of Accounting Students and Entry-Level Accountants who are the target population of the study. This quantitative correlation study was conducted to find the relationship between the technological readiness and technological adoption of Artificial Intelligence enabled technologies in accounting and auditing which is vital in coping with the challenges posed by changing environment. The study was conducted in regards to the TR and TA perseverance of accounting students and entry-level accountants, of which the respondents were (n=104) which consisted of Bachelor level, Masters and PHD level accounting students from Prague University of Economics and Business and entry level accountants from DXC Technology shared service center in Prague. The participants were presented with a questionnaire survey through google forms online platform. Using the forms of analysis such as bivariate correlation and linear regression it was concluded that TR, PU and PEOU have a positive influence in the TA of A.I. by accounting students and entry-level accountants and that TR positively impacts PU and PEOU. |
Keywords: | Linear Regression Analysis, Bivariate Correlation; Technological Readiness, ; Artificial Intelligence, Technological Acceptance; Robotic Process Automation; Machine Learning, ; Pearson’s Correlation, ; Perceived Usefulness, ; Perceived Ease of Use |
Information about study
Study programme: | Finance and Accounting |
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Type of study programme: | Magisterský studijní program |
Assigned degree: | Ing. |
Institutions assigning academic degree: | Vysoká škola ekonomická v Praze |
Faculty: | Faculty of Finance and Accounting |
Department: | Deparment of Finacial Accounting and Auditing |
Information on submission and defense
Date of assignment: | 27. 11. 2020 |
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Date of submission: | 16. 5. 2021 |
Date of defense: | 9. 6. 2021 |
Identifier in the InSIS system: | https://insis.vse.cz/zp/75323/podrobnosti |