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  • 标题:Underlying Variables Concerning Statutory Auditors’ Independent Engagement: A Regression Analysis
  • 本地全文:下载
  • 作者:Siddhartha Sankar Saha ; Mitrendu Narayan Roy
  • 期刊名称:European Journal of Business and Management
  • 印刷版ISSN:2222-2839
  • 电子版ISSN:2222-2839
  • 出版年度:2015
  • 卷号:7
  • 期号:13
  • 页码:249-258
  • 语种:English
  • 出版社:The International Institute for Science, Technology and Education (IISTE)
  • 摘要:This study identifies few issues that positively or negatively influence statutory auditors’ independent engagement. A primary survey is conducted to gather opinion of knowledgeable and experienced respondents on these issues. Score of 1 to 5 was allotted to 5 levels of agreement of each respondent. Mean score of the sample identifies overall opinion of the sample on statutory auditors’ independent engagement and variables governing the same. In order to examine impact of select issues on statutory auditors’ independent engagement, Multiple Regression Analysis is conducted. From the estimated values of standardised regression coefficients, it is observed that a few variables like appointment procedure, relationship with management, provision of non-audit services negatively influence statutory auditors’ engagement. On the other hand, other variables like appointment by independent regulatory authority, mandatory rotation, maximum limit on total remuneration and complete prohibition of non-audit services has positive influence on it. Result of t test for individual parameter estimates suggests that maximum limit on total remuneration and complete prohibition of non-audit services significantly influence statutory auditors’ independent engagement. Adjusted Coefficient of Multiple Determinations (R²) measures a weak association between statutory auditors’ independent engagement and its governing issues, while result of F Test indicates that R 2 is significant. Hence, the model perfectly fits the data.
  • 关键词:Statutory Auditor; Statutory Auditors’ Independent Engagement; Mean Score; Multiple Linear Regression Analysis; Regression Estimates; t test; Coefficient of Multiple Determinations; F test
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