Drivande faktorer för individuell användning av big data system inom revisionsbolag
(2022) FEKH39 20222Department of Business Administration
- Abstract (Swedish)
- Title: Drivande faktorer för individuell användning av big data system inom revisionsbolag
Seminar date: 11/1-2023
Course: FEKH39, Degree Project, Business Administration, Undergraduate level, 15 University Credit
Points ECTS
Authors: Christoffer Yngwe, Jacob Svensson & Rasmus Thunberg
Advisor: Magnus Johansson
Keywords: Audit, big data systems, UTAUT-model, big data usage, general ledger systems.
Research questions: Which factors affect individual usage of big data systems for employees within
the audit industry?
Purpose: Explaining and mapping driving factors for individual usage of big data systems for auditors.
Methodology: The study applies the UTAUT-model and performs a regression analysis in order to map
the driving... (More) - Title: Drivande faktorer för individuell användning av big data system inom revisionsbolag
Seminar date: 11/1-2023
Course: FEKH39, Degree Project, Business Administration, Undergraduate level, 15 University Credit
Points ECTS
Authors: Christoffer Yngwe, Jacob Svensson & Rasmus Thunberg
Advisor: Magnus Johansson
Keywords: Audit, big data systems, UTAUT-model, big data usage, general ledger systems.
Research questions: Which factors affect individual usage of big data systems for employees within
the audit industry?
Purpose: Explaining and mapping driving factors for individual usage of big data systems for auditors.
Methodology: The study applies the UTAUT-model and performs a regression analysis in order to map
the driving factors for individual usage of big data systems for auditors. Data is collected through a survey
which was sent out to employees at four big auditing firms in Sweden. By using bootstrapping the study
estimates the significance levels and coefficients for the factors affecting individual usage of big data
systems.
Theoretical perspectives: The paper’s theoretical framework is based on the UTAUT-model, which is
adjusted accordingly to recent theories regarding big data usage and decision-making.
Results: The study identified social influences, facilitating conditions and expected performance as the
driving factors for individual usage of big data systems within the auditing industry. All of the variables
had a positive statistically significant relationship with the dependent variable, actual usage.
Conclusions: Social influences, facilitating conditions and expected performance had a significant
positive relationship with actual usage of big data systems for auditors. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9110624
- author
- Thunberg, Rasmus LU ; Svensson, Jacob LU and Yngwe, Christoffer LU
- supervisor
- organization
- course
- FEKH39 20222
- year
- 2022
- type
- M2 - Bachelor Degree
- subject
- keywords
- Revision, big data system, UTAUT-modellen, big data användning, huvudboksanalyseringssystem, Audit, big data systems, UTAUT-model, big data usage, general ledger systems.
- language
- Swedish
- id
- 9110624
- date added to LUP
- 2023-02-27 10:35:01
- date last changed
- 2023-02-27 10:35:01
@misc{9110624, abstract = {{Title: Drivande faktorer för individuell användning av big data system inom revisionsbolag Seminar date: 11/1-2023 Course: FEKH39, Degree Project, Business Administration, Undergraduate level, 15 University Credit Points ECTS Authors: Christoffer Yngwe, Jacob Svensson & Rasmus Thunberg Advisor: Magnus Johansson Keywords: Audit, big data systems, UTAUT-model, big data usage, general ledger systems. Research questions: Which factors affect individual usage of big data systems for employees within the audit industry? Purpose: Explaining and mapping driving factors for individual usage of big data systems for auditors. Methodology: The study applies the UTAUT-model and performs a regression analysis in order to map the driving factors for individual usage of big data systems for auditors. Data is collected through a survey which was sent out to employees at four big auditing firms in Sweden. By using bootstrapping the study estimates the significance levels and coefficients for the factors affecting individual usage of big data systems. Theoretical perspectives: The paper’s theoretical framework is based on the UTAUT-model, which is adjusted accordingly to recent theories regarding big data usage and decision-making. Results: The study identified social influences, facilitating conditions and expected performance as the driving factors for individual usage of big data systems within the auditing industry. All of the variables had a positive statistically significant relationship with the dependent variable, actual usage. Conclusions: Social influences, facilitating conditions and expected performance had a significant positive relationship with actual usage of big data systems for auditors.}}, author = {{Thunberg, Rasmus and Svensson, Jacob and Yngwe, Christoffer}}, language = {{swe}}, note = {{Student Paper}}, title = {{Drivande faktorer för individuell användning av big data system inom revisionsbolag}}, year = {{2022}}, }