The Quality of Revenue Disclosures regarding IFRS15
The Quality of Revenue Disclosures regarding IFRS15; What are the influences of audit committee, board structure and the size of the firm?
For parts in research methodology sections
Data ; The industries in with the companies operate are; construction, technology, telecommunications.
2 excel sheets;
One with company characteristics from company annual reports from 2018 and 2019. Looked up by students via the internet
The other with a disclosure index from the same company annual reports from 2018 and 2019. This disclosure index was made by the lecturer, and the questions were answered by the students. And they gave by answering the questions points to the specific companies.
A few companies are removed from the disclosure index because of several reasons.
-ifrs 15 not yet implemented in annual report.
-ifrs 15 explanation not applicable for company’s activities. Revenue is disclosed with point-in-time accountability.
-no annual report available
Characteristics disclosure index; 25 questions about quality of IFRS15 reporting.
It is based on IFRS 115.110 and further.
Scores to be given are ; 0,1,2. Score of 0 data missing/ 1 minimum info / 2 good and clear information
Assumption; the higher the score/the better a firm complies to the checklist/25 questions ; the better the quality.
The disclosure index is made up from information that several student looked up. The research population is a mixture of companies that operate in; construction, technology, telecommunications. On basis of STOXX600 list. These are relevant sectors because of the complex, long lasting contracts. And IFRS15 is focusing on these revenues on how to disclose this.
This list was provided by us by the lecturer.
Also a definition of quality of reporting from ifrs15 about mandatory and voluntary disclosures
Short explanation of how to measure the quality; thus by disclosure index
Furthermore ; method of measurement of the research model ; thus by analysis of the hypotheses through spss and regression analysis. See also attached files about the analysis.
Beware of nested data. Especially with statistic analysis.
Analyses of the years of 2018 and 2019 needs to be done separately.
OLS analysis not useful for nested data
Population 2018; 62 annual reports
Population 2019; 67 annual reports
Both for the disclosure index as well as the determinants
For determinants in research model ; further data analysis needs to be done so hypotheses are tested.
Below are some tables as an example , these are used in an other research which used a survey. So do not use these tables in this research paper
Table 1: Variables, Proxy, and Measurement
|Rank in the survey per case question|
Table 2: Descriptive
Table 3: Correlations
|Model||Unstandardized Coefficients||Standardized Coefficients||t||Sig.|
Table 4: Regression
|Model||Sum of Squares||df||Mean Square||F||Sig.|
Table 5: Coefficients
|Model/Variables||Unstandardized Coefficients||Standardized Coefficients||t||Sig.|
Table 6: Regression Analysis
|Model||R||R Square||Adjusted R Square||Std. Error of the Estimate|
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