Climate Change Integration into Business Strategy for Carbon Emission Reduction

The research proposes climate change integration into business strategy and state whether it helps in carbon emission reduction. The study uses survey technique and descriptive analysis along with combination of inferential statistical tools to measure the independent variable affecting the dependent variable.

MGT723 Research Project
Semester 2 2018
Assessment Task 2: progress report
Student Name: Ashish Subedi
Draft Research Question: why some firms have achieved greater carbon reduction than others.
Submission Date: 14 september2018
Student ID: 1101763
Location: South bank Campus

Introduction
The research proposes climate change integration into business strategy and state whether it
helps in carbon emission reduction. The research method of the study relates to the disclosures
retrieved with the use of survey technique which is available in the website of the CDP. The
study also states the purpose of considering sample of companies to participate in the survey.
The main idea of the study is explained with the response of the descriptive design. The study
will use the disclosure percentages as per the climate change which needs to be integrated into
the perception of the pressure taken from the consumers which may have a considerable amount
of impact on the performance of market. This analysis will consist of the descriptive analysis
along with combination of inferential statistical tools. The objectives pertaining to the analysis
will be measurable as per the independent variable affecting the dependent variable. As the
companies has self-reported the statistics, this is speculated in terms of the performance of the
company and various other factors which may be measured as political influences and social
influences. In case survey of the study is larger than the size then the disclosure of the carbon
emissions will be able to show whether a company will be able to actively take part in the
strategy for showing the main agents which are responsible for the emissions. Theoretical
Construct has been taken from the Climate change integrated into business strategy which has
shown climate change integration with the topic of carbon emission will depend on the strategies
integrated by the business. Carbon emission reduction has been depicted with the dependent
variable which is included under the scope of the study of carbon emissions. Motivation
construct are considered to be important as the companies may decide to be benefitted financially
relating to these incentives (Moriarty, 2014).

Literature Review
Stakeholder theory as suggested by Dr Edward Freeman, the brain behind the idea, argues that
shareholders are among the many shareholders in accompanied. In this theory the stakeholder
ecosystem is made up of any individual who has in any way invested in or has taken part in a
firm. The stakeholders of a firm include company’s plants, environmentalists, government
agencies and its employees among other stakeholders (McNabb 2015).
According to Freeman, the actual success of a firm to a great extent depends on meeting the
needs and demands of the various stakeholders. This is in contravention ion of just meeting the
needs of only those people who may reap from the stock issued (McNabb 2015). In his work, the
philosopher suggests that the stakeholders of a firm are defined by the group of people on which
their support forms the basis of continuous existence of the company.
Favourable environmental policies and regulations, promotion of environmental conservation as
well as incorporation of the need to conserve the environment as part of the missions of a
company can be attributed to be some of the underlying reasons for some firms having greater
carbon reduction than others.
Conceptual Model
Normative and managerial motivations both have an influence on the process of decision making
in offering suggestions on the various strategies to the stakeholder theory. Such motivations are
important in the analysis of the interaction between the company and the stakeholder (McNabb
2015).
Following the broad question posed:
“Why have some firms achieved greater carbon reductions that others”
A metaphoric approach to stakeholder theory is thus adopted in which identification of the
motivations have been done through the various theories to be underlying factors in the process
of decision making by the management and the stakeholders (Hitt & Duane Ireland 2017). The
empirical parts of this research aim at the identification and determination whether such
motivations that have been identified by the theory have a role to play when it comes to the
process of decision making by the management of the various firms. Below is a conceptual

model for this project that illustrates the dependent variable, the independent variable and the
presence of the moderating variable.
Independent variable – Physical Climate Change
Dependent Variable – Reduction in Carbon
Moderating Variable – Provision of the incentive by the management
Suggestions are made that the analysis would be carried out at the interaction between the firm
and the stakeholder in a framework of the motivations that is achieved from the various theories
of stakeholder and acknowledge being having an impact on the decision making in real practice
(Sharp, Peters & Howard 2017). By achieving that, the study offers an approach that is usable in
the operationalization of the stakeholder theory by taking into account the already identified
motivations by every individual different theory on the interaction between the firm and the
stakeholders who are assumed to be formed a fundamental part and parcel of the decision on
making reports to the shareholders.
The stakeholder is thus the common link between the two cases in which it is to the
responsibility of the various perspectives of management to establish the actual response to the
Physical Climate Change
(Independent Variable)
Provision of the incentive
(Controlling/Moderating
Variable)
Reduction in Carbon
(Dependent Variable)

anticipated stakeholders. On the other hand, the normative perspective provides suggestion that
the firm has a role to play in attaining the intrinsic rights of the various stakeholders through the
provision of environmental information (El-Nasr, Drachen & Canossa 2016).
 The dependent variable in the study is reduction in carbon
 The year in which the study was conducted is the moderating or control variable (Ahuja
2017)
 The physical climate change of the various countries form the independent variable
Hypotheses
The null and alternative hypotheses to be tested for this study can be formulated as follows;
Ho: Favourable climatic regulations and policies enhance higher carbon reduction in firms
H1: Favourable climatic regulations and policies do not enhance higher carbon reduction in firms
Research Method
This research adopted survey for gathering of data for analysis and achievement of the objectives
of the study which were the reasons behind some firms having greater carbon reductions than
others (Saghafian, Austin & Traub 2015). Approximately 550 firms were sampled in the study to
offer a wide range of the independent variable. The survey was found to be simple, convenient,
precise in its results and low cost as some of its main strengths. Rigidity of the technique besides
as well as the possibility of deliberately providing false or inaccurate information was the main
drawbacks of surveys as the technique.
Data collection
Data was obtained from a CPD database that contain all the carbon emissions data for all the
countries around the globe. The dataset are categorized for the different industries in different
countries working on different sectors of economy. We considered the 2012 data set for three
countries; Australia, Belgium and Brazil which have achieved greater carbon reduction. There
were a total of 218 observations (industries) considered for this study with 80 companies from
Australia, 11 companies from Belgium and 127 companies from Brazil. A separate excel file is
submitted together with this report. This paper applied both descriptive and inferential statistics

to investigate the relationship between the dependent variables and the independent variable with
reference to the moderating variable.
Data Analysis
Descriptive Statistics
The table below presents the descriptive statistics for the numerical data that was collected. The
two variables are the carbon intensity and percentage change in carbon emissions in 2012.
Results shows that the average carbon emissions for 2012 for the selected companies was 321.51
with the highest recorded emission amount for that year being 13093.78. The lowest emission
amount recorded was 0.00 with the standard deviation being 1755.65. In regard to the percentage
change the average percentage change was found to be -2.16% with the highest change recorded
being 305.33% and the lowest change recorded being -78%. The standard deviation for the
percentage change was 29.34.
The results for the skewness and kurtosis for both the intensity and percentage change indicated
that the variables are heavily skewed. The fact that the skewness values are greater than positive
3 implies that the variables (intensity and percentage change in intensity) are positively skewed
and that they seem to have a number of outliers.
a. Independent Variable: Physical Climate Change
Intensity % change
N 142.00 222.00
Range 13093.78 383.33
Minimum 0.00 -78.00
Maximum 13093.78 305.33
Mean 321.51 -2.16
Std. Deviation 1755.65 29.34
Variance 3082289.75 860.88
Skewness 6.37 6.21
0.20 0.16
Kurtosis 40.62 60.49
0.40 0.33
Table 1: Descriptive statistics for the independent variable

b. Dependent Variable: Reduction in Carbon emission
Intensity % change
N 142.00 222.00
Range 15893.78 377.39
Minimum 0.00 -91.20
Maximum 13093.78 415.33
Mean 321.51 -2.16
Std. Deviation 1855.65 29.34
Variance 2982289.75 960.78
Table 2: Descriptive statistics for the dependent variable
Frequency distributions
Countries
As can be seen, most the companies included in the study were from Brazil (58.3%, n = 127)
followed by companies from Australia (36.7%, n = 80) and the least were from Belgium (5.0%, n
= 11).

Table 2: Distribution of companies based on countries
Frequency Percent Valid Percent Cumulative
Percent
Valid
Australia 80 36.7 36.7 36.7
Belgium 11 5.0 5.0 41.7
Brazil 127 58.3 58.3 100.0
Total 218 100.0 100.0
Respondents were asked to where the highest level of direct responsibility for climate change is
within their organization. Results showed that the highest level of direct responsibility lies on the
board for most of the companies (72%, n = 157) followed by the senior manage (24.3%, n = 53)
and lastly form other manager (3.7%, n = 8). The table 3 below shows the statistics for the
independent variable
Table 3: Highest responsibility level
Frequenc
y
Percent Valid
Percent
Cumulative
Percent
Valid Other manager 8 3.7 3.7 3.7

Senior
manager
53 24.3 24.3 28.0
Board 157 72.0 72.0 100.0
Total 218 100.0 100.0
In regard to whether the Company provides incentives for the management of climate change
issues, including the attainment of targets. Slightly more than half of the companies (50.9%, n =
111) said to offer incentives while 49.1% (n = 107) did not offer incentives for the management
of climate change issues (moderating variable).
Provision of incentives
Frequency Percent Valid
Percent
Cumulative
Percent
Valid
Yes 111 50.9 50.9 50.9
No 107 49.1 49.1 100.0
Total 218 100.0 100.0
Lastly, the survey sought to understand whether the companies have climate change integrated
into their business strategy. 70.4% (n = 152) had the climate change integrated into their business
strategy while the rest 29.6% (n = 64) did not have.
Is climate change integrated into your business strategy?
Frequency Percent Valid Percent Cumulative Percent
Valid
Yes 152 69.7 70.4 70.4
No 64 29.4 29.6 100.0
Total 216 99.1 100.0
Missing 999 2 .9
Total 218 100.0

Inferential Statistics
For the inferential statistics, correlation analysis, regression analysis and hypothesis testing was
conducted to determine “Why have some firms achieved greater carbon reductions that others”
and the relationship that exist between the dependent and independent variables.
Correlation analysis: Correlation analysis is conducted to examine the relationship between the
two variables. The value of the correlation is between -1 and +1. Higher correlation coefficient
indicates strong relation whereas the small correlation coefficient indicates weak relationship
between the variables. From correlation analysis, there exist no relation between the dependent
and dependent variable since the coefficient is negative. The result is as shown in table below;
Coefficients
Model Unstandardized
Coefficients
Standardize
d
Coefficients
t Sig. 95.0% Confidence Interval
for B
B Std. Error Beta Lower
Bound
Upper
Bound
1
(Constant
) 19.502 76.536 -.255 .823 -309.807 348.811
Carbon
reduction .435 1.299 .230 -.334 .770 -5.156 6.025
a. Dependent Variable: reduction in carbon
Regression analysis: The regression analysis is conducted to examine the impact of the set of
independent variables on the dependent variable. In the current research the regression analysis
can be conducted to examine the factors affecting the emission of carbon emission. In this case
the carbon emission will be taken as the dependent variable (Lanfranchi, Viola and Nascimento,
2010; Armstrong, 2012). The result indicates no association exist between carbon emission and
climate change. The table below shows the result out
ANOVA

Model Sum of
Squares
df Mean Square F Sig.
1
Regression 458.658 1 458.658 -.112 .770b
Residual 8202.092 2 4101.046
Total 8660.750 3
a. Dependent Variable: reduction in carbon
b. Predictors: (Constant), Physical Climate Change.
The coefficient = -.112 which is negative thus implies no association between the variables.
Inferential statistics was used to test the hypothesis.
Hypothesis testing
The first hypothesis we sought to test is;
H0: There is no significant difference in the amount of carbon emission for the companies in the
three countries.
HA: There is significant difference in the amount of carbon emission for the companies in the
three countries.
To test this, a one-way Analysis of Variance (ANOVA) was used and tested at 5% level of
significance.
The one-way Analysis of Variance was applied in order to test whether there is differences in
means of the carbon emission for the companies in the three countries
In order to carry out this test, the assumption of normality must be checked and for this case,
normality test of carbon emission using Shapiro test was done. Table and Q-Q plot above shows
the distribution of carbon reduction.
Test of Normality between carbon reductions.
ANOVA
Intensity
Sum of Squares df Mean Square F Sig.
Between Groups 2458070.402 2 1229035.201 .376 .687
Within Groups 431383697.384 132 3268058.314

Total 433841767.785 134
The p-value is given as 0.687 (a value greater than α = 0.05), this means that the null hypothesis
is not rejected. By failing to reject the null hypothesis we conclude that there is no significant
difference in the amount of carbon intensity for the companies in the three countries. That is,
none of the three countries can be thought to produce more carbon emissions than the other in
2012.
The second hypothesis we sought to test is;
H0: There is no significant difference in the percentage change in carbon emissions for the
companies in the three countries.
HA: There is significant difference in the percentage change in carbon emissions for the
companies in the three countries.
To test this, a one-way Analysis of Variance (ANOVA) was used and tested at 5% level of
significance. Results are given below;
ANOVA
% change
Sum of Squares df Mean Square F Sig.
Between Groups 538.960 2 269.480 .302 .740
Within Groups 185687.185 208 892.727
Total 186226.145 210
Again, the p-value is given as 0.740 (a value greater than α = 0.05), this means that the null
hypothesis is not rejected. By failing to reject the null hypothesis we conclude that there is no
significant difference in the percentage change in carbon emissions for the companies in the
three countries. That is, none of the three countries can be thought to have had a significant
change in carbon emissions than the other in 2012.
The third hypothesis we sought to test is;
H0: There is no significant difference in the amount of carbon intensity for the companies based
on highest level of responsibility for climate change within the organization.

HA: There is significant difference in the amount of carbon intensity for the companies based on
highest level of responsibility for climate change within the organization.
To test this, a one-way Analysis of Variance (ANOVA) was used and tested at 5% level of
significance. Results are given below;
ANOVA
Intensity
Sum of Squares df Mean Square F Sig.
Between Groups 3512416.492 2 1756208.246 .539 .585
Within Groups 430329351.293 132 3260070.843
Total 433841767.785 134
The p-value is given as 0.585 (a value greater than α = 0.05), this means that the null hypothesis
is not rejected. By failing to reject the null hypothesis we conclude that there is no significant
difference in the amount of carbon intensity for the companies based on highest level of
responsibility for climate change within the organization. That is, the individual responsibility
level does not affect the company’s carbon emission intensity.
We also sought to test how highest level of responsibility for climate change within the
organization affects the percentage change in the carbon emissions for the companies in 2012.
The following hypothesis was tested;
H0: There is no significant difference in the percentage change of the carbon emissions for the
companies based on highest level of responsibility for climate change within the organization.
HA: There is significant difference in the percentage change of the carbon emissions for the
companies based on highest level of responsibility for climate change within the organization.
To test this, a one-way Analysis of Variance (ANOVA) was used and tested at 5% level of
significance. Results are given below;
ANOVA
% change
Sum of Squares df Mean Square F Sig.
Between Groups 221.881 2 110.940 .124 .883

Within Groups 186004.264 208 894.251
Total 186226.145 210
The p-value is given as 0.883 (a value greater than α = 0.05), this means that the null hypothesis
is not rejected. By failing to reject the null hypothesis we conclude that there is no significant
difference in the percentage change of the carbon emissions for the companies based on highest
level of responsibility for climate change within the organization. That is, the individual
responsibility level does not affect the company’s percentage change in carbon emissions.
Another hypothesis tested was whether there is significant difference in the carbon emission
intensity between the companies that provide incentives for the management of climate change
issues and those that do not provide. The following hypothesis was tested at 5% level
significance using an independent samples t-test.
H0: There is no significant difference in the carbon intensity emissions for the companies that
provide incentives for the management of climate change issues and those that do not provide.
HA: There is significant difference in the carbon intensity emissions for the companies that
provide incentives for the management of climate change issues and those that do not provide.
The results are presented in the table below;
Group Statistics
Provision of incentives N Mean Std. Deviation Std. Error Mean
Intensity Yes 81 323.4760 1749.18341 194.35371
No 54 360.2330 1888.52836 256.99616
Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means

F Sig. t df Sig.
(2-
tailed)
Mean
Differ
ence
Std.
Error
Differ
ence
95%
Confidence
Interval of the
Difference
Lower Upper
Intensi
ty
Equal
variances
assumed
.084 .772 -.11
6
133 .908 -36.76 317 -664 591
Equal
variances not
assumed
-.11
4
107.63
5
.909 -36.76 322 -675 602
We performed an independent t-test in order to compare the average means of carbon intensity
emissions for the companies that provide incentives for the management of climate change issues
and those that do not provide. Results showed that the average carbon intensity emissions for the
companies that provide incentives for the management of climate change issues and those that do
not provide (Mean = 323.48, Standard Deviation = 1749.18, N = 81) was not significantly with
the average carbon intensity emissions for the companies that did not provide incentives for the
management of climate change issues (Mean = 360.23, Standard Deviation = 1888.53, N = 54), t
(133) = -0.116, p > .05, two-tailed test.
Discussion
Based on the different analyses conducted in the above sections, some tests confirmed
significant relationship and association between the dependent variables and the independent
variable for this study. For instance, the hypothesis test about amount of intensity for companies
based on the highest level of responsibilities for climate change in organization, showed no
positive significant results and thus suggest that highest level of responsibilities for climate
change within a firm does nor influence level of carbon emission reduction from a firms. When
the hypothesis about difference in the percentage change of the carbon emissions for the firms
regarding highest level of board management, there was also no significant difference in the

level of the carbon reduction for the companies based on highest level of management for the
climate change within a given firm. This implies that the higher the influence of responsibility
for climate in an organization, there is no influence the reduction in carbon emission from the
firm.
Also, while the previous researches have demonstrated that reduction of carbon emissions
and exhibiting good board management environmental performance is very vital for the
companies, none of the study has ever examined the mechanisms of how the environmental goals
are achieved at smaller levels within the firm. We therefore can argue that adoption of the
incentive schemes for the employees should exist in any company that emits carbon as this will
tend to reduce the level and percentage of carbon into the atmosphere McNabb 2015). Out
finding have important implications for the public and government suggesting that non-
mandatory guidance or the consideration of a likely introduction of a requirement may result to
higher level of carbon emission and subsequent sustainable actions. The measurement and the
subsequent disclosure of emissions is a tool that can make management be aware of the need to
improve on the terms of the sustainable developments against climate change.
The analysis of variance (ANOVA) indicates that none of the three countries that can be
thought to have had a significant change in carbon emissions than the other in the year 2012.
Also, from the ANOVA test, the p-value is given as 0.673 (a value greater than α = 0.05), this
means that the null hypothesis is not rejected. By failing to reject the null hypothesis we
conclude that there is significant difference in the level of the carbon emissions for the
companies based on highest level of responsibilities for climate change within any given
company. That is, the board responsibility has great influence in either increasing or reducing
carbon emission within an organization. In addition, with reference to the moderating variable,
there was a positive significant value which implies that provision of the incentives to the
employees also contributes positively to lower levels of carbon emission within the firms.
When an independent sample t-test was performed in order to compare the average
means of carbon emissions for the companies with higher level of responsibility for the climate
change in an organization, the results showed that the average carbon emissions for the
companies that have better and good level of management tend to have low emission of carbon
from the firms. Moreover, based on the moderating variable, the management incentives for the

employees of climate change issues and those that do not provide, there was significant
difference with the average carbon emissions for the companies that did not provide incentives
for the management of climate change issues based on the two tail test. The findings therefore
suggests that provision of incentives and policies enhances climate change mitigation in many
countries across the world by reducing carbon emissions. Therefore, in this research paper, it can
be asserted that the higher the influence of board responsibility for the climate change in an
organization, the higher will be carbon emission reduction.
Limitations of the study
In relation to this research, a many caveats were recognized as well. First, our sample is
comprised of only big predominantly multinational organizations from three countries Australia,
Belgium and Brazil which can be considered to have achieved greater carbon reduction leaving
out smaller and average firms which have not or are in the process of reducing carbon emission.
It is thus possible that consequences dominated here do not claim for the smaller firms that are
competing locally.
Another limitation to this study is that only four countries data have been examined and
also the data examined is limited to a period of one year (2012 to 2013). It could be well and
reasonable if the data is analysed over a more than five countries through a longer time frame.
This may result to somewhat different and better findings and outcomes for the future study. All
these will as well form the fruitful areas of the future work.
Lastly, the study was only limited to among 550 firms which have achieved greater
carbon reduction and thus may not give overall inference about whole carbon reduction among
firms in different settings. Lastly, in relation to the analysis conducted based on the dependent
and the independent variable, the dataset used for the analysis had few outliers which were
removed. This may have compromised the nature of the results in general as the data collected
was not much accurate for the other advanced analysis.
Future Researches
For the future studies, a relatively bigger sample size of the companies should be considered for
the analysis as this would result to more concrete and reliable findings for better references. The
outcomes in this paper cannot be fully relied upon for future references since only three world

countries and sample of 550 firms from them were selected for the study and analysis. Moreover,
future work should not only aim at bigger predominantly multinomial organizations which have
achieved or have well integrated board management and business strategy in reducing carbon
emission but also, focus on small organizations which have no or little strategies on carbon
reduction. This will compromise the nature of the results and can lead to poor references about
the existing variable and predictors hence bad results.

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