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MGT723 Research Project-Socio Political Theory

What is your research problem Provide your summary (maximum 1 page) of the theoretical argument leading to the conceptual model with theoretical constructs clearly identified.Provide a diagram to show the relationships between the key theoretical constructs.Indicate your hypotheses – they will be assessed in your Assessment Task 1 for ACC620.Complete the spreadsheet and submit it separately.Provide a descriptive analysis of the relevant data from the CDP dataset provided. Maximum of five pages.Describe the inferential statistics that you plan to use to test your hypotheses.

Answer:

There have been many studies which tried to study the relationship between the disclosure of the carbon emission and the performance of the firms. However there is no unique conclusion about the relationship. So the main aim of this study is to examine the relationship between the carbon disclosure score and the organisation influencing public policy related to climate change.  To examine the relationship both the descriptive and the inferential analysis will be conducted on the collected data.

There are many theories which have been previously used to examine the relation between carbon emission and the performance of the firms.  According to the stakeholder theory firms are operating in such a way that the expectations of the particular stakeholders are met, as the stakeholders are the key factors who can have significant impact on the firm’s performance. The stakeholder


theory is considered to be the socio-political theory. The socio-political theory assumes the disclosure behaviour as the function of political and social pressure by different stakeholders. So stakeholder theory further argues that the decision related to the organisation’s management should be taken only after consulting the major stakeholders(Najah & Cotter 2013).

In terms of relationship previous studies some scholars have found positive relationship between environmental and financial performance of the firms. Study by (Clarkson et al. 2010) found positive relationship between the two. On the other hand study of (Cormier et al. 2011) shows negative relationship and author argues that the inferior firms’ disclosure about the environment is higher than the superior firms. Since the relationship is not clear from the previous studies so this study will examine how the firms can influence the public policy related to disclosure of the carbon emission. This will give a new dimension to the existing literature. 

This study will test the following hypothesis:

There is positive and significant relationship between the organization influencing public policy and carbon disclosure score.For the current study data was collected among 188 firms in different countries and from different sectors. Data related to the carbon disclosure score was collected from secondary sources whereas the data for the various methods used by companies to influence the public policy related to the climate change was collected from primary sources. While collecting the data from the primary source the close ended questionnaire was used.In this section the results from the descriptive analysis has been discussed.  As mentioned in the previous section carbon disclosure and the method used by firms on influencing the public policy are the main variables of interest for this research. The descriptive analysis of the carbon disclosure score is shown below:

Statistics

score  

N

Valid

188

Missing

0

Mean

81.8138

Median

96.0000

Std. Deviation

30.25122

Variance

915.136

Skewness

-1.994

Std. Error of Skewness

.177

Kurtosis

2.652

Std. Error of Kurtosis

.353

Minimum

.00

Maximum

100.00

Percentiles

25

81.2500

50

96.0000

75

99.0000

Results show that the mean score is 81.81 whereas the median score is 96. This shows that there is high variation in the data set as the mean value is affected by the extreme values.  The standard deviation is also quite high. The high variation in the score can also be seen from the minimum and maximum score. On one hand the minimum score is as low as 0 whereas the maximum score is as high as 100. Results also show that most of the firms who have score of 100 belongs to information technology industry. Similarly the results from percentile show that 75 % of the firms have score of 99 of lower as the value for 75th percentile is 99.

Industry

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Energy

9

4.8

4.8

4.8

Financials

31

16.5

16.5

21.3

Health Care

31

16.5

16.5

37.8

Information Technology

96

51.1

51.1

88.8

Telecommunication Services

21

11.2

11.2

100.0

Total

188

100.0

100.0

 

Similarly the descriptive statistics for industry shows that more than 50 % of the firms in the data set belongs to information technology sector followed by Financials and Healthcare. The number of firms in the energy sector is only 4.8 % of the total data set.  

disclousure

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

No

18

9.6

9.6

9.6

Yes

170

90.4

90.4

100.0

In terms of disclosure more than 90 % of the firms disclose their carbon emission and only 9.6 % firms (in the data set) do not disclose. This is may be due to different rules and regulations in every country, or in some cases the firms are not willing to disclose the data as it might affect their performance.

Results for countries shows that most of the firms are from United States followed by United Kingdom and Japan. This indicates that most of the firms in the data set are from the developed world where the advancement in technology has helped them to reduce the carbon emission as compared to the developing countries.

As already discussed around 10 % of the total firms in the data set do not disclose their carbon emission data where rest of the 90 % firms disclose their data.

While collecting the primary data the respondents were asked whether their firm influence on public policy related to climate change and four different options were also given to know how the firms influence. The four different options were direct engagement with policy makers, trade associations, funding research organisation and others.

Results from the influence data shows that around 55 % of the firms influence on public policy through direct engagement with the policy makers.Similarly around 15 % firms use the method of trade associated to influence the public policy as shown.

Finally 30 % of the firms said they use the method of funding research organisation as a process of influencing the public policy. This can be called as the indirect influencing as the firms are not directly involving in the process. However one should note that there are many firms which follow two or more than two methods for influencin

Correlations

 

DE

TA

FR

score

Pearson Correlation

.224**

.118

.142

Sig. (2-tailed)

.002

.108

.052

N

188

188

188

DE

Pearson Correlation

1

-.544**

.393**

Sig. (2-tailed)

 

.000

.000

N

188

188

188

TA

Pearson Correlation

-.544**

1

-.107

Sig. (2-tailed)

.000

 

.142

N

188

188

188

FR

Pearson Correlation

.393**

-.107

1

Sig. (2-tailed)

.000

.142

 

N

188

188

188

**. Correlation is significant at the 0.01 level (2-tailed).

For the inferential analysis the correlation analysis has been conducted and the results are shown in the table above.  Correlation analysis is used to examine the relationship between the two variables and the results from the correlation help to find the how strongly are the variable related and also the direction of relationship.

In this case, the main aim is to see the relationship between score and the different influencing method used by the firms. So the results show that direct engagement with the policy makers and carbon disclosure score are positively correlated. Also the sig (2-tailed) is less than 0.05 which ensure that the correlation coefficient is significant. However for the other two influencing method the correlation is positive with score but the correlation is not significant at 5 %. So on the basis of these results it can be said that our hypothesis is partially true.

Since correlation does not give proper conclusion about the relationship, so in the next inferential analysis the regression model will be used. The regression is used to see the change in the dependent variable which is explained by the independent variables. So regression analysis will give clearer picture about the proposed hypothesis.

 References

Clarkson, P. et al., 2010. The relevance of environmental disclosures for investors and other stakeholder groups: which audience are firms speaking to?, Queensland.

Cormier, D., Ledoux, M. & Magnan, M., 2011. The informational contribution of social and environmental disclosures for investors. Management Decision, 49(8), pp.1276–1304.

Najah, M.M. & Cotter, J., 2013. Are climate change disclosures an indicator of superior climate change risk management?, Queensland.

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