Lean Six Sigma: Impacts on Audit Quality Indicators

<p>There are many concerns about the sustainability of the accounting profession and the ability of the profession to maintain a satisfactory level of quality personnel. The profession would benefit from a more appealing and transparent environment that could attract and retain personnel and alleviate some of the adverse effects being experienced. Therefore, this study is designed to examine the potential benefits of a management and quality improvement program, specifically Lean Six Sigma (LSS), regarding audit quality. Surveys were administered to the employees of public accounting firms that have implemented LSS and those of firms that have not implemented LSS. Regression analysis and partial least squares structural equation modeling were used to determine whether LSS can serve as an intervention strategy that can decrease employee turnover and improve audit quality. While there was no difference found in the overall audit quality of firms that have implemented LSS and firms that have not, significant differences were found between LSS and non-LSS firms in the impact that employee resilience and turnover intentions have on audit quality. The results of this study show that non-LSS firms have similar audit quality outcomes as LSS firms, however, the implementation of LSS offers additional benefits that can help to improve audit quality due to its apparent enhancement of the positive impact of resilient employees and its reduction of the negative impact from employee turnover. </p>

Name thesis:degree_name

Accounting

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Business Administration

Year dc:date.available

2023

Author dc:creator

• DeRoy, Tiffany

Contributors dc:contributor

• Velina Popova
• Dana Hermanson

• audit quality
• Lean Six Sigma(LSS)
• burnout
• turnover
• resilience
• environment
• Accounting

Repository record dc:identifier

https://digitalcommons.kennesaw.edu/phdba_etd/30

OAI identifier oai:identifier

oai:digitalcommons.kennesaw.edu:phdba_etd-1030