MGT723 Research Project: Business Strategy and Carbon Emissions

This report, submitted for MGT723 Research Project, investigates the impact of business strategy and incentives on carbon emissions reduction. The study explores the integration of climate change into business strategies and the role of incentives in promoting climate management, drawing from l...Read More

MGT723 Research Project
Semester 2, 2018
Assessment Task 3: Report
Student Name: Aliza Giri
Title: Impacts of Business Strategy and Incentive on Carbon Emissions Reduction
Submission Date: 21/10/2018
(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.
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Introduction: (Not assessed)
The inclusion of the considerations of climate change into the corporate strategies has begun
giving a new shape to the manner in which enterprises perform the businesses. In their
attempts to handles climate change, companies and firms come across new opportunities,
among them creating new technologies as well as commodities and gaining access to new
markets (Herold, Lee and Gunarathne, 2018). Through gaining higher energy efficiency, the
companies are as well able to make significant savings.
However, companies still face greater and more significant risks when it comes to climate
change among them increasing regulatory and legal pressure, enhanced costs resulting from
internalization of carbon, risks associated with reputation as well as disruptions to the
business activity inducted by changes in the climate (Ben‐Amar and McIlkenny,2017). The
end results is that the balance between the costs and the available opportunities will rely on a
number of factors among them government policies, specificities as well as the ability of the
companies to involve the consumers in handling the challenges of climate change (Andrew
and Cortese, 2011).
This aim of this paper is to establish if business strategy as well as incentives have a
significant role to play when it to comes to checking the level of carbon emissions in a
business organization with more focus being on those activities that are geared towards the
establishment of a low carbon economy. The aim of this paper will be met by drawing mainly
from the works of recent literature, adoption of the recommendations as outlines in the
OEDCD Guidelines for Multinational Enterprises as well as from experimental studies that
will be conducted (Freedman, 2009).
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Literature Review: (Not assesse d)
A continuous audit by McKinsey(2015) on the manner in which associations take into
consideration climate change, where more than 2000 authorities responded, revealed that
60% of chairmen see ecological change as an indispensable idea inside their general system
of the organization, while 70% perceive it as a basic estimation for reputation and check.
Elucidation into the activities of the organization remains at any rate compelled: to the tune
of 4 out of 10 of the CEOs ecological change is certifiably not a basic thing on their
arrangement, 70% uncovered that their association excludes ecological change centers in the
implementation review of authorities as well as including the heads specifying that
supervising characteristic issues was basic, 60% encompassed a niche with firms that had not
portrayed surges diminish targets. In any case, 80% of chairmen foreseen that may be
impacted by some kind of change in the environment in the next half a decade (Sullivan,
2017).
Business state of mind towards environmental change is driven by an assortment of
components, including government approaches also, control and weight from shoppers and
different partners (Ben‐Amar and McIlkenny, 2015). Lately, governments in OECD nations
have actualized residential atmosphere strategy systems, including a blend of approach
instruments went for moderating ozone harming substance (GHG) outflows. These
arrangement blends incorporate market-based instruments, for example, duties and top and-
exchange frameworks, and additionally direction and data battles (Herold, Lee and
Gunarathn, 2018). Residential atmosphere arrangements are advancing, with key points of
reference still to come, for example, the universal post-2012 system that nations are intending
to concur at COP15 in December 2009, in Copenhagen. While organizations are confronting
expanding government measures, a vital part of the business reply to environmental change is
likewise determined by private activities to react to societal desires imparted by different
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channels than law (Bocken et al, 2014 )(e.g., purchaser affiliations, the press, global
associations, and so on.).
The goal of this examination is to decide the connection between carbon emanations decrease
and two different elements business system (as far as environmental change coordination)
and Incentives (as far as motivating force for administration of atmosphere) (Liao, Luo and
Tang, 2015). The examination likewise attempts investigates the response to the two
inquiries; first, why environmental change ought to be coordinated in a business technique
and what influence does it have in decreasing the carbon outflows? Second, does motivating
force for administration of environmental change affect decrease in carbon outflows? The
CDP reactions will help both the organizations and every one of the clients of data, as it gives
chances to the firm to distinguish the methodology for administration and decrease of
emanations and the information ought to likewise profit the financial specialists and different
partners by giving data about organization practices and activities in regards to environmental
change (Andrew and Cortese, 2011).
Research question
What significance does integration of climate change in business strategy have on carbon emission
reduction?
Conceptual Model: (Not Assessed)
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Business Strategy
Independent
Variable
Carbon Emission
Reduction
Dependent Variable
Incentives
Moderating
Variable

Hypotheses: (Not assessed)
Hypothesis 1: Business Strategy with regard to integration of climate change has a significant
impact on the reduction of carbon emissions.
Hypothesis 2: Provision of incentives aimed at climate management has a relatively
significant effect on the reduction of carbon emissions.
Data Analysis – Descriptive (Not assessed)
INDEPENDENT VARIABLE
Statistics
The tables 2, 3 and 4 below are an illustration of the changes in the values for the
independent variable. From the tables it can be observed that the descriptive statistics which
for this case was also the independent variable i.e. the Business Strategy (Integration of
Climate Change), there were 150 observations and not even a single missing observation.
Business Strategy (Climate
Change Integration)
N Valid 150
Missi
ng
0
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Table 1: Descriptive Statistics (Business Strategy)Table 1: Descriptive Statistics
(Business Strategy) above indicates that the data variable had 150 valid observations with no
missing observations.
Table 2: Descriptive Statistics (Business Strategy)
Table 2: Descriptive Statistics (Business Strategy) above indicates the proportions of
the “Yes” and “No” responses to the climate change integration into business strategy. 128
companies have climate change integrated into their business strategy (“Yes” Response). The
percentage equivalence for this is 85.3%. The companies that have not integrated climate
change into their business strategy were 22, the percentage equivalence being 14.7%.
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Figure 1: Pie Chart Business Strategy (Climate Change Integration)
Figure 1 above is the pie chart representation of the independent variable.
DEPENDENT VARIABLE
Table 3: Descriptive Statistics (Carbon Emissions Reduction)
Table 3: Descriptive Statistics (Carbon Emissions Reduction) above shows that the
data variable had 150 observations. The maximum reduction in carbon emissions for the year
2014 was 123.13% while the minimum reduction -72%. The mean for the reduction in carbon
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emissions was -0.6743%. The standard deviation for carbon emissions reduction was
21.98608 (Chu, 2015).
Figure 2: Histogram representation of the dependent variable
The histogram illustrates the frequency the reduction in the emission of carbon for the year
2014 from the 150 valid observations that were made. From the histogram it can be noticed
that the highest reduction was experienced at a frequency of about 50 where the reduction
was at 0.00. Note should take of the nature of the frequency polygon generate from the bars
which demonstrated an exponential increase in the reduction which levels off at 100 (Liesen
et al 2015).
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MODERATING VARIABLE
Table 4: Descriptive Statistics (Incentive Variable)
Table 4: Descriptive Statistics (Incentive Variable) above indicates that the data
variable had 150 valid observations with no missing observations.
Table 5: Descriptive Statistics (Incentive Variable)
Table 5: Descriptive Statistics (Incentive Variable) above indicates the proportions of
the “Yes” and “No” provision of incentive for management of climate. 109 companies have
incentive provided for the management of climate (“Yes” Response). The percentage
equivalence for this is 72.7%. The companies that do not have incentive provided for the
management of climate were 41, the percentage equivalence being 27.3%.
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Figure 3: Bar graph representation of the Incentive variable\
NORMALITY
Statistics
The table 7 below is an illustration of the Normality of Carbon Emissions Reduction.
Information regarding the skewness and kurtosis as well as the accompanying std. errors is
shown. This data shows that the findings of the research illustrated relatively skewed results
or data to a given direction (Chu, 2015)
Carbon Emissions Reduction (%
Reduction in Carbon Emissions for
2014)
N Valid 150
Missing 0
Skewness 1.387
Std. Error of Skewness .198
Kurtosis 6.645
Std. Error of Kurtosis .394
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Range 195.13
Table 6: Normality of Carbon Emissions Reduction
From Table 6: Normality of Carbon Emissions Reduction above, we observe that the
normality statistics for the carbon emissions reduction are: Range = 195.13, Skewness =
1.387, Kurtosis = 6.645. The data on the carbon emissions reduction can therefore be said to
be slightly skewed to the right (Liesen et al, 2015).
Figure 4: Carbon Emissions Reduction in Terms of Business Strategy
Key
“No” Outliers:-3, 2, 13, 7 & 17
“Yes”: -131, 102, 127, 118, 140, 128, 80, 93, 25, 106 & 100
Shown above is the graphical portrayal of the depiction of ward variable (Carbon
Emissions Reduction) as far as the autonomous variable (Business Strategy). Figure 4:
Carbon Emissions Reduction in Terms of Business Strategy appears there are 5 anomalies on
the "No": 3, 2, 13, 7 and 17, while on the "Yes" we have 11 exceptions: 131, 102, 127, 118,
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140, 128, 80, 93, 25, 106 and 100. Of the aggregate 16 exceptions, 2 can be named
extraordinary anomalies: 131 and 100. With the end goal to have proper information for the
investigation, the outrageous exceptions ought to be evacuated (Ioannou, Li and Serafeim,
2015).
Data Analysis – Inferential (ASSESSED)
.
Regression analysis
Regression analysis is a statistical analysis that explains the relationship between variables.
There are two types of variables in regression. The response and the explanatory variables.
The explanatory are independent and are used to predict the response or independent
variables. Linear Regression Analysis would be appropriate for the investigation because of
the nature of variables. The Independent Variable (Business Strategy) is estimated on the
ordinal scale, the Moderating Variable (Incentive) is estimated on the ordinal scale and the
Dependent variable (Carbon Emissions Reduction) is estimated on the Ratio Scale
Regression analysis general equation take the form
yi=β0 +βi xi
The table1 and table 2 below shows the results of linear regression of the dependent variable
(carbon emission reduction) and the independent variable (business strategy on climate
change)
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Table 1: Table of variables
Variables Entered/Removeda
Mod
el
Variables
Entered
Variables
Removed
Method
1 business
strategy,
incentives
. Enter
a. Dependent Variable: carbon emission reduction
b. All requested variables entered.
Table 2 model summary
Model Summary
Mod
el
R R
Square
Adjusted R
Square
Std. Error of
the Estimate
1 .151a .023 .009 84.13181
a. Predictors: (Constant), business strategy, incentives
According to Table 1: Table of variables output the independent variables that were included in
the model were climate change included in the business strategy and whether incentives were
provided for climate management. The dependent variable that was included on the model for
the regression analysis was the reduction in carbon emission
The R square was 0.23 and the adjusted R squared was 0.009. R squared in the model was
very low. According to the R square statistic 0.9% of the independent variable (business
strategy) and control variable (incentives) determined the response variable. (Carbon
emission reduction.)
ANOVA
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ANOVA is a statistical test that is used to determine the significance of a results of the
analysis carried out on the study variable. Table 3 is an output of the analysis of variance
conducted on the study’s regression model.
Table 3 ANOVA table
ANOVAa
Model Sum of
Squares
Df Mean
Square
F Sig.
1 Regression 24229.939 2 12114.970 1.712 .184b
Residual 1040489.796 147 7078.162
Total 1064719.735 149
a. Dependent Variable: carbon emission reduction
b. Predictors: (Constant), business strategy, incentives
Significance level was at 0.184 for the combined independent variables. Significance of a
model indicates whether the prediction made using the model are statistically significant. At
0.05 level of significance the model prediction is insignificant since 0.184 > 0.05. This means
that predictor variables (business strategy and incentives.) were not statistically significant to
predict dependent variable (reduction in carbon emission)
ANOVA univariate test
ANOVA univariate test is used to analyse the significance of each response variable used in
the model at a given level of significance. The table 4 below is the output of the test.
Table 4 Table for the AVNOVA univariate test
Tests of Between-Subjects Effects
Dependent Variable: carbon emission reduction
Source Type III Sum df Mean Square F Sig.
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of Squares
Corrected Model 27160.610a 3 9053.537 1.274 .286
Intercept 5369.498 1 5369.498 .756 .386
Incentives 7568.118 1 7568.118 1.065 .304
Business strategy 3812.449 1 3812.449 .536 .465
incentives, business strategy 2930.670 1 2930.670 .412 .522
Error 1037559.126 146 7106.569
Total 1070093.966 150
Corrected Total 1064719.735 149
a. R Squared = .026 (Adjusted R Squared = .005)
In the F-value for the intercept (point where the response variables were at zero) was 0.386.
The F-value for the independent variables provision of incentives foe climate management
and was climate integrated in business strategy were 0.304 and 0.465 respectively. The F-
value for the model and the combined effect of the independent variables were 0.286 and
0.522 respectively. All the F-value are insignificant at 0.05 level of significance since they
are all greater than the F-value. This means that they are greater than the acceptable level
Levene’s test
The table 5 Levene’s test is used to test whether the control variable and the independent
variable are homoscedastic
Table 5: Levenes test
Levene's Test of Equality of Error
Variancesa
Dependent Variable: carbon emission
reduction
F df1 df2 Sig.
5.812 1 148 .017
Tests the null hypothesis that the error
variance of the dependent variable is equal
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across groups.
a. Design: Intercept + incentives
At the 0.05 level of significance we reject the null hypothesis since 5.82 > 0.05 and conclude
the response and control variable has different variances or are heteroscedastic.
Coefficients
The coefficients offer the required information in the prediction of the reduction in the
emission from business strategy as well as establishing if there is statistical significance to the
model. From the analysis of the regression, the regression equation can be presented as
Reduction in carbon emission=-26.08+25.2 (Business Strategy)
Coefficients Standard
Error
t Stat P-value Lower
95%
Upper
95%
Lower
95.0%
Upper 95.0%
Intercept -26.0889 20.7765221 -1.25569135 0.21120669 -
67.14585
14.9681 -67.14585 14.968054
Business Strategy 25.18945 15.4005828 1.63561664
4
0.10404483 -
5.243989
55.6229 -5.243989 55.622888
Table 12: Coefficients Analysis Table
Hypothesis testing (ASSESSED):
The null and alternative hypotheses for the research were:
H0: Business Strategy with regard to integration of climate change has a significant impact on
the reduction of carbon emissions
H1: Provision of incentives aimed at climate management has a relatively significant effect
on the reduction of carbon emissions.
Decision rule: To assess the truth value of the hypothesis we refer to Table3 (ANOVA table)
and Table 4 (ANOVA univariate table). In Table 3 the F-value of the model is 1.84 > 0.05
thus insignificant at 0.05 level of significance. In Table 4 the F- value for two independent
variables were 0.304 and 0.4645and their combined effect was 0.522 which were again
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insignificant at 0.05 level of significance. The model and the intercept F-values were 0.286
and0.386 respectively and are both insignificant at 0.05 level of significance. We hence reject
the null hypothesis and conclude that provision of incentives aimed at climate management
has a relatively significant effect on the reduction of carbon emissions
Discussion (ASSESSED):
Carbon emission is an ideal case of externality. Most of companies do not realize the cost
incurred by emission of carbon into the environment. However, as indicated in the research,
carbon emission has adverse effect to businesses, community and investors at large
(Fernando and Lawrence, 2014). Business stakeholders include management, shareholders,
customers and government. All the shareholders have part to play in reduction of the
company’s carbon emission levels.
The study was conducted to investigate whether integration of climate change in business
strategy had and provision of incentives to management of climate had had impact on carbon
emission rate. Integration of climate change in the business strategy means that the business
takes active and conscious initiatives to reduce carbon emission into the environment
(Fernando and Lawrence, 2014). Based on the results of the research, business strategy
(independent variable) to did not have a significant effect on reduction in carbon emission on
a significance level of 0.05. Using a higher level of significance 20%, according to table 4,
the independent variable is still insignificant as 0.465 > 0.20.
Incentives to may management of climate is the control variable in the study. Incentives are
meant motivate companies to reduce carbon emission. Incentives come in different forms
form different stakeholders. According to the research result the addition of incentives did not
have a significant effect on the response variable. However, at 20% of significance the
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combined effect business strategy and incentives had significant effect on carbon emission. In
table 3, 0.18 < 0.2.
The implication of research results is that carbon emission can be reduced by integrating
climate change the business strategy. The results of business strategy are mild. However, the
use of incentives yields better results in the effort to reduce carbon emission. Business,
especially those that are emission intensive, should make therefore use incentives boost their
active efforts to curb carbon emission (Dou, Zhu and Sarkis, 2015).
Recommendations
● Governments should give incentives to companies that integrate climate change in
their business strategy. This would serve to motivate companies to actively seek
alternative environment friendly modes of operation (Chun, 2016).
● Business should give incentives to their staff that implement the business strategy in
environment conservation. As indicated in the research incentives go a long way
yielding the business strategy results.
● Governments and business should educated the masses and staff on the cost of carbon
emission. This would create intrinsic motivation to actively make efforts to reduce
carbon emission
Limitations (ASSESSED):
● Inferences were drawn from companies with a small sample size. Only companies and
countries from BRICS namely Brazil, Russia, India, China and South Africa were
sampled thus the results may be not be applicable to other countries with different
economic environments. (Herold, Lee and Gunarathne, 2018),
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● There were numerous null entries in the data, the data may therefore be said to be
incomplete. Null entries were replaced with the mean, this led to more inaccurate
results.
Further Research (ASSESSED):
The purpose of a further research would be to address the limitations of the study. Such a
research would be done on a data set that does not contain missing entries. This would serve
to reduce estimation and increase in data in the research’s accuracy. ( Graceffo, 2011).
The research would be carried out on a broader number of countries. In the research, only
five countries were considered all members of BRICS. This countries formed the union since
they were industrial countries at a certain stage of development (Herold, Lee and Gunarathne,
2018). The results of the study would therefore not suitable for extrapolation to estimate the
carbon emission states in other countries with different economic environments.
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References (ASSESSED):
Andrew, J. and Cortese, C.L (2011). Carbon disclosures: comparability, the carbon disclosure
project and the greenhouse gas protocol. Australasian Accounting, Business and Finance
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Ben‐Amar and McIlkenny, P. (2015). Board effectiveness and the voluntary disclosure of
climate change information. Business Strategy and the Environment, 24(8), pp.704-719
Ben-Amar and McIlkenny, P. (2017). Board gender diversity and corporate response to
sustainability initiatives: Evidence from the carbon disclosure project. Journal of Business
Ethics, 142(2), pp.369-383
Bocken, N.M., Short, S.W., Rana, P. and Evans, S. (2014). A literature and practice review to
develop sustainable business model archetypes. Journal of cleaner production, 65, pp.42-56
Chu, J.M. (2015). The rise of BRICS in Africa: the geopolitics of South-South
relations/Agricultural development and food security in Africa: the impact of Chinese, Indian
and Brazilian investments, 34(7) pp.34-67
Dou, Y., Zhu, Q. and Sarkis, J. (2015). Integrating strategic carbon management into formal
evaluation of environmental supplier development programs. Business Strategy and the
Environment, 24(8), pp.873-891
Fernando, S. and Lawrence, S. (2014). A theoretical framework for CSR practices:
integrating legitimacy theory, stakeholder theory and institutional theory. Journal of
Theoretical Accounting Research, 10(1), pp.149-178
Freedman, D.A. (2009). Statistical models: theory and practice. Cambridge University press
pp. 4-5
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Graceffo, A. (2011). BRIC becomes BRICS: changes on the geopolitical
chessboard. Foreign Policy Journal. Retrieved, 14
Herold, D.M., Lee, K.H. and Gunarathne, N (2018), May. Carbon accounting in the global
logistics industry: Categorising institutional and stakeholder pressures on carbon disclosure
strategies. 22nd EMAN Conference. Social Responsibility and Sustainability Accounting-Key
Corporate Performance Drivers and Measures, 23(6), pp.12.16)
Ioannou, I., Li, S.X. and Serafeim, G( 2015). The effect of target difficulty on target
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1492
Liao, L., Luo, L. and Tang, Q (2015). Gender diversity, board independence, environmental
committee and greenhouse gas disclosure. The British Accounting Review, 47(4), pp.409-424
Liesen, A., Hoepner, A.G., Patten, D.M. and Figge, F (2015). Does stakeholder pressure
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Sullivan, R. (2017). Corporate responses to climate change. Achieving emissions reductions
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