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Drivande faktorer för individuell användning av big data system inom revisionsbolag

Thunberg, Rasmus LU ; Svensson, Jacob LU and Yngwe, Christoffer LU (2022) FEKH39 20222
Department 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:
author
Thunberg, Rasmus LU ; Svensson, Jacob LU and Yngwe, Christoffer LU
supervisor
organization
course
FEKH39 20222
year
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}},
}