The Quality of Revenue Disclosures regarding IFRS15 Assignment

The Quality of Revenue Disclosures regarding IFRS15

Paper instructions

The Quality of Revenue Disclosures regarding IFRS15; What are the influences of audit committee, board structure and the size of the firm?

To be included in the research methodology; all the purple sections

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.

List of company characteristics is compiled by students by searching on the internet.

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

Add the definitive list of the companies which are used(so not the excel documents, but just a list)  in the thesis as a appendix

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
AC1 AC2 AC3 AC4 AC5 AC6
3 1 2 1 2 4
2 3 1 2 4 1
4 4 4 4 1 3
1 2 3 3 3 2

Table 2: Descriptive

Variables Frequency Mean Standard Deviation Variance
AC1 199 3.294 .6995 .489
AC2 165 2.706 1.0960 1.201
AC3 64 3.341 .9436 .890
AC4 91 1.458 .7083 .502
AC5 76 1.654 .6435 .414
AC6 230 1.526 .7477 .559

Table 3: Correlations

Coefficients
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Variables) -.543 .522   -1.040 .299
ENF .018 .064 .010 .275 .783
CLA .029 .078 .020 .378 .706
ROL -.053 .068 -.035 -.781 .435
ACH .083 .056 .058 1.502 .134
COM -.058 .070 -.034 -.823 .411
TRA .197 .058 .146 3.404 .001
DIS .073 .057 .048 1.293 .197
ACC -.078 .069 -.044 -1.141 .255
BEL -.010 .057 -.008 -.179 .858
DIA .127 .049 .116 2.612 .009
Constant: INT

Table 4: Regression

Model Sum of Squares df Mean Square F Sig.
1 Regression 1832105.166 18 101783.620 8.855 .000b
Residual 4701421.834 409 11494.919    
Total 6533527.000 427      

Table 5: Coefficients

Model/Variables Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 Variables 102.266 115.232   .887 .375
ENF 5.939 8.229 .034 .722 .471
CLA -21.721 5.368 -.192 -4.046 .000
ROL -2.624 8.617 -.020 -.305 .761
ACH -21.905 7.917 -.125 -2.767 .006
COM 24.812 9.805 .129 2.531 .012
TRA -3.620 9.464 -.022 -.383 .702

Table 6: Regression Analysis

Model R R Square Adjusted R Square Std. Error of the Estimate
1 .562 .342 .356 104.735

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