MGT723 Research Project: Stakeholder Theory Impact on Carbon Emissions

This research report examines the impact of stakeholder theory on carbon emissions within USA companies, analyzing data from 2012 to 2013. The study investigates whether providing incentives to management for climate change initiatives correlates with changes in carbon emission percentages. Descriptive statistics, including mean, median, mode, variance, and skewness, are used to analyze the trends in carbon emissions for companies that do and do not offer incentives. The report includes trend analysis and descriptive statistics to show the relationship between company incentives and carbon emissions. The findings indicate a complex relationship between stakeholder incentives and carbon emission reduction efforts, highlighting the importance of stakeholder engagement in environmental performance. Desklib provides access to this and other solved assignments for students.

MGT723 Research Project
Semester X 20XX
Assessment Task 3: Report
Student Name: XXXXX
Title: XXXXX
Submission Date: XXXXX
(Note that the submission is due by 5:00pm via SafeAssign)
Acknowledgement:
I certify that I have carefully reviewed the university’s academic misconduct policy. I understand
that the source of ideas must be referenced and that quotation marks and a reference are required
when directly quoting anyone else’s words.

Introduction: (Not assessed)
Carbon emissions are one of the major problems in the environment today globally.
Emissions of carbon have been affecting the industries greatly. In this research, the stakeholder
theory will be discussed with effect to the carbon emissions. There are certain theoretical as well
as practical motivations to this concept of carbon emissions in accordance with the stakeholder
theory. The research is mainly aimed at evaluating the changes in the emissions of carbon by the
companies.
Literature Review: (Not assessed)
In view of dependence on carbon-based utilities, our atmosphere is changing quickly and
it's a remediable issue of the present corporate world. Organizations convey and discharge a huge
measure of carbon in the earth in perspective of their radiation of taking care of plant abuse in
pointless aggregate and a section of the ruinous fabricated blends utilized as a bit of storing up of
the thing. Nowadays the organizations also end up being extremely aware of the need to make a
move on environmental change.
The Stakeholder got a huge influence on the organization. According to Donaldsom and
Preston (1995), “Stakeholder theory has been used to describe (a) the nature of the firm (Brenner
and Cochran, 1991), (b) the way managers think about managing (Brenner and Molander, 1977),
(c) how board members think about the interests of corporate con stridencies (Wang and
Dewhirst, 1992), and (d) how some corporations are actually managed (Clarkson, 1995; Halal,
1990; Kreiner and Bhambri, 1991)”. There is not much disagreement on what kind of entity can
be a stakeholder. Persons, groups, neighborhoods, organizations, institutions, societies, and even
the natural environment are generally thought to qualify as actual or potential stakeholders
(Mitchell and Agle, 1997). One investor's advantage is to expand the benefits and lessen the
useless exercises from the business in here and now, yet the primary focus of association ought
to be to deal with the prerequisites and meet the desires for Stakeholder (George, 2003). The
primary individuals who ring a bell while considering who holds the stakes at an association are
the Shareholder and the government. Other than the undeniable, Stakeholder consolidates each

one of those exercises and responsibilities affects association execution, like laborers, customers,
and business accomplices (Bridoux and Stoelhorst, 2014).
Analyses have also shown that the associations in the USA transmit a massive proportion
of carbon into the air. 23 – 24 % of the carbon Dioxide transmitted by the corporate firms
wherever all through the world start with the USA associations. The USA uses oil-based goods
to make essentialness and subsequently, the surge of carbon in the atmosphere by the USA firms
are high (Jones and Wicks, 1999). This examination paper is thusly away to work up the
capabilities in the rate changes in the arrival of carbon by the relationship in the context of USA
as for the presentation of jolts that a few affiliations accommodate the association and some
others don't. The adjustments in the arrival of carbon dioxidehave been assessed in a rating scale
from the year 2012 to 2013. The choice of the relationship in the spread of carbon dioxide is all
things considered in the context of the impact the accessories play on the affiliations.
Considering the choice of the accessories, the affiliations will pick whether to give influencing
forces to the association or not.
Conceptual Model: (Not Assessed)
IndependentvariableUSAcompaniesprovidingincentivestControlveribleLocationofthecompany(UDependentveriablePercentagechangesincarbon

Hypotheses: (Not assessed)
1) H01: No significant difference exists between the company provide incentive in 2012
with the companies do not provide incentive in 2012 on percentage changes in carbon
emissions.(Null)
H11: There is statistically significant difference that exists between the companies who
provide incentive in 2012 and the companies who do not provide incentive in 2012 on
percentage changes in carbon emissions. (Alternative)
2) H02: No significant difference exists between the company provide incentive in 2013
with the companies do not provide incentive in 2013 on percentage changes in carbon
emissions. (Null)
H12: There is statistically significant difference that exists between the companies who
provide incentive in 2013 and the companies who do not provide incentive in 2013 on
percentage changes in carbon emissions. (Alternative)
3) H03: No significant difference exists between the company provide incentive in 2012
and the companies who provide incentive in 2013 on percentage changes in carbon
emissions. (Null)
H13: There is statistically significant difference that exists between the companies who
provide incentive in 2012 and the companies who provide incentive in 2013 on
percentage changes in carbon emissions. (Alternative)
4) H04: No significant difference exists between the company who do not provide
incentive in 2013 and the companies who do not provide incentive in 2013 on percentage
changes in carbon emissions. (Null)
H14: There is statistically significant difference that exists between the companies who
do not provide incentive in 2013 and the companies who do not provide incentive in 2013
on percentage changes in carbon emissions. (Alternative)

5) H05: No significant difference exists between the company provide incentive in 2012
and the companies who do not provide incentive in 2013 on percentage changes in carbon
emissions. (Null)
H15: There is statistically significant difference that exists between the companies who
provide incentive in 2012 and the companies who do not provide incentive in 2013 on
percentage changes in carbon emissions. (Alternative)
6) H06: No significant difference exists between the company who do not provide
incentive in 2012 and the companies who do not provide incentive in 2013 on percentage
changes in carbon emissions. (Null)
H16: There is statistically significant difference that exists between the companies who
do not provide incentive in 2012 and the companies who do not provide incentive in 2013
on percentage changes in carbon emissions. (Alternative)
Data Analysis – Descriptive (Not assessed)
Trend Analysis
-600
-500
-400
-300
-200
-100
0
100
Company provide incentives for the management
of climate change issue including the attainment,
of targets in and2012 2013.
2012
2013
Figure 1: percentages of carbon emissions changes in the year 2012 and 2013 when the USA
Company provides incentives to the management.

The trend in 2012 and 2013 can be seen to be almost similar to one of the companies had an
impressive change in the percentages of carbon emissions of -489.04 and which is considered as
outliers.
-100
-80
-60
-40
-20
0
20
40
Company does not provide incentives for the
management of climate change issue including,
the attainment of targets in and2012 2013.
2012 2013
Figure 2 percentages of carbon emissions changes in the year 2012 and 2013 when the USA
Company does not provides incentives to the management.
Similarly, the trend for 2012 and 2013 are almost similar though there are marginal differences
which means if the company doesn’t provide any incentive to the management than the company
shows a very less effort in carbon emissions reduction.
The company provides incentives for the management
Table 1: Descriptive statistics of 2012 and 2013 when company provides incentives to
management.
2012 2013
Mean -10.03 -25.41
Median -8.50 -8.50
Mode -14 -1
Range 67.80 488.33
Variance 164.47 7731.80

Standard deviation 12.82 87.93
Interquartile range 9.75 10.48
quartile deviation 4.88 5.24
Skewness -2.01 -5.41
Kurtosis 6.72 29.45
From table 1 above, it is evident that the mean of carbon emissions when the company
provides incentives for the management is -10.03 ± 12.82 in 2012 and -25.41 ± 87.93 in 2013.
Thus, the mean of the level of carbon emissions is higher in 2012 compared to 2013 when the
company provides incentives to the management. However, the median of the level of carbon
emissions for both years is the same (both at -8.50). Since the median is greater than the mean,
we conclude that the distribution is negatively skewed (Skewness of the level of carbon
emissions is -2.01 and -5.41 in 2012 and 2013 respectively). Conversely, the mode the two
distribution varies with -14 in 2012 and -1 in 2013. Thus, -14 level of percentages changes in
carbon emissions occurs more in 2012 while -1 occurs more in 2013. The range of the level of
carbon emissions in 2012 is 67.80 while in 2013 is 488.33. From this, it can be seen that in 2013,
the level of dispersion of 488.33 is greater than the 2012 level of dispersion of 67.80. Factoring
in the interquartile range, it can be seen that the level of dispersion in 2013 (10.48) is greater than
the level of dispersion in 2012 (9.75). Since the interquartile range is not affected by outliers, it is
evident that the interquartile range is a better measure of spread through the results remain the
same. The quartile deviation in 2012 and 2013 are lower compared to the interquartile range.
This is expected since the quartile deviation is robust than the interquartile range since it
considers every variable in the dataset. Consequently, the quartile deviation is higher in 2013
(5.24) compared to 2012 (4.88). Thus, there is more spread in 2013 compared to 2012.
Consequently, the variance of the level of carbon emissions in 2013 (7731.80) is greater than
2012(164.47). Hence, the level of carbon emissions is more volatile in 2013 compared to the
level of carbon emissions in 2012.

The kurtosis on the level of carbon emissions distribution is 6.72 in 2012 and 29.45 in 2013.
Since the kurtosis is greater than 3, it is evident that the two datasets have heavier tails than a
normal distribution.
The company does not provide incentives for the management
Table 2: Descriptive statistics of 2012 and 2013, when a company does not provide incentives to
the management.
2012 2013
Mean -6.88 -14.23
Median -8.11 -10.46
Mode -13 -20
Range 70.00 77.50
Variance 147.55 234.06
Standard deviation 12.15 15.30
Interquartile range 11.73 12.16
quartile deviation 5.87 6.08
Skewness -0.78 -2.78
Kurtosis 4.09 9.99
From table 2, it is evident that the mean of carbon emissions when the company does not
provide incentives for the management is -6.88 ± 12.15 in 2012 and -14.23 ± 15.30 in 2013.
Hence, the mean of the level of carbon emissions is higher in 2012 compared to 2013. In this
scenario, the company does not provide incentives to the management.
On the other hand, the median of the level of carbon emissions for both years is -8.11 and -10.46
in 2012 and 2013 respectively. The median is greater than the mean in 2013 while it is less in
2012. From this, it can be deduced that the distribution in 2013 is negatively skewed while the
distribution in 2012 is positively skewed. However, the negativity if the skewness is proved in
2013 (-2.78) unlike in 2012 where the skewness was found to be negative (-0.78).
The mode of the two distribution varies from -13 in 2012 and -20 in 2013. Thus, -13 level of
percentages changes in carbon emissions occurs more in 2012 unlike in 2013 where -20 occurs

more. The range of the level of carbon emissions in 2012 is 70 while in 2013 is77.5. From this, it
can be seen that in 2013, the level of dispersion of 77.5 is greater than the 2012 level of
dispersion of 70. Factoring in the interquartile range, it can be seen that the level of dispersion in
2013 (12.16) is greater than the level of dispersion in 2012 (11.73). As expected, the quartile
deviation in 2012 and 2013 are lower compared to the interquartile range. Consequently, the
quartile deviation is higher in 2013 (6.08) compared to 2012 (5.87). Thus, there is more spread in
2013 compared to 2012.
Consequently, the variance of the level of carbon emissions in 2013 (234.06) is greater than
2012(147.55). Hence, the level of carbon emissions is more volatile in 2013 compared to the
level of carbon emissions in 2012.
The kurtosis on the level of carbon emissions distribution is 4.09 in 2012 and 9.99 in 2013. Since
the kurtosis is greater than 3, it is evident that the two datasets have heavier tails than a normal
distribution.
Based on the descriptive analysis, it can be seen that carbon emissions have decreased in
2013 compared to 2012 regardless of whether there are incentives for the management or not.
However, when there are incentives for the management, carbon emissions are less. It can be
also seen from the above descriptive analysis, when the company provide incentive to the
management the standard deviation in 2013 is much bigger compared to 2012 and that means the
company take some efforts to reduce the carbon emissions where the standard deviation is almost
similar in both 2012 and 2013 when the company does not receive any type of incentive. It goes
same with the range as well where the range is almost same in both years when the company
does not receive any incentive but it shows a big deviation when the company receives some
incentives(67 in 2012 and 488 in 2013). The stakeholders’ theory claim that an organization
must make a profit to benefit all the stakeholders. Thus, when a company is forced to reach its
targets, corporate responsibilities are bound to be overlooked. Thus, more carbon emissions will
be seen by the company in the USA.

Data Analysis – Inferential (ASSESSED)(20%)
The results of the descriptive statistical analysis only provides an exploratory idea about
the impact of incentives being included into the company business strategy and offered to the
management to influence the company to reduce its carbon emissions. Although the descriptive
analysis reveals a general decrease in carbon emissions from 2012 to 2013 among the sample,
regardless of the fact that a company has such an incentive plan in place or not, it cannot be
asserted to be true for the population of companies that exist or not. The statistical validity of the
conjecture that inclusion of such incentives to influence a core stakeholder group, that is the
management, could go on to significantly impact and hence reduce the emission levels is hence
still not established on the sole of the descriptive measures. In order to come to an evidence
based conclusion regarding the impact of incentives, inferential analysis is then employed to
approach the problem.
Inferential statistics is a tool that allows for the researcher to arrive at conclusions about
the whole population on the basis of the given representative sample, with some degree of
controlled error. The two errors associated with the methodology are type I error or the
probability that the true null hypothesis is rejected. This is also equivalent to the level of
significance of the test. Type II error or the probability that the false alternative will be accepted.
Then naturally, decreasing one error would imply the increase in the other. The following
methodology set the type I error as 0.05 and the type II error was minimized to arrive at the
conclusion. This means that the null is rejected whenever the p-value is found to be less than
0.05, at 5% level of significance. The difference in the percentage change of the companies who
give incentives between 2012 and 2013 was then tested for using the paired t-tests. The
difference between the two groups of companies, namely, those who give incentives and those
who do not, in terms of percentage emission in 2012 and in 2013 was tested for using two
independent sample t-tests. The same was employed for the difference between the companies
who offered incentives in 2012 and those which did not offer incentives in 2013 and those which
did not offer incentives in 2012 and those which did offer incentives in 2013.
The first assumption for both paired t-tests and independent sample t-tests is that the data
is free from outliers. This is primarily due to the fact that the test statistics are based on the mean

which is highly susceptible to presence of outliers. Thus presence of extreme values in the data
could potentially lead to erroneous results.The two sets of data to be compared for the paired t-
tests must be on the same attribute but dependent on each other, such that they may be from the
same individual or object in different time or scenarios, that is, should be observations on the
same variable at different scenarios but related to the same unit. The assumption for independent
t-tests however is that the data samples are on the same variable but drawn independently from
each other. Again, another assumption is that the data samples are underlined by some normal
distribution.
The data is therefore first explored for the presence of outliers. The following boxplots
show the presence of values that lie beyond the Interquartile range and those that may be
regarded as extremes. The observations numbered, 7, 11, 14 and 25 were identified as outliers
and hence removed from the dataset before commencing with the tests for the six specified
hypothesis.

Boxplot of the Percentage change in Carbon emissions for companies who give incentives in
2012