IMPACT OF TECHNOLOGICAL READINESS ON ADOPTING ARTIFICIAL INTELLIGENCE IN ACCOUNTING

Thesis title: IMPACT OF TECHNOLOGICAL READINESS ON ADOPTING ARTIFICIAL INTELLIGENCE IN ACCOUNTING
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
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
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
Date of submission: 16. 5. 2021
Date of defense: 9. 6. 2021
Identifier in the InSIS system: https://insis.vse.cz/zp/75323/podrobnosti

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