MGT723 Research Project: Inferential Analysis & Hypothesis Test

This report presents an inferential data analysis using chi-square tests to explore relationships between various factors like country, industry type, climate change integration in business strategy, emission reduction targets, and carbon emission changes. The analysis reveals significant relationships between countries and industry types, climate change integration, and emission reduction strategies. However, it also indicates no significant relationship between integrating climate change in business strategy and carbon emission reduction, nor between carbon emission targets and percentage change in carbon emission. The report discusses the implications of these findings, highlighting the importance of implementing climate change strategies effectively and the potential role of management incentives. It also acknowledges the limitations of the study and suggests areas for further research to enhance the understanding and effectiveness of carbon emission reduction strategies.

Data analysis –inferential
In this section, we are going to focus on inferential data analysis. Statistical test we are going to use here
is chi-square. We are going to obtain the cross-tabulation table their respective chi-square test.
1. Country versus Industry type
From the chi-square test table below gives the relationship between country and the type of
industry emitting the carbon, we find that Pearson Chi-Square has value of 459.396a with degree
of freedom 168 and p-value of 0.0001. Likelihood Ratio test has a value of 342.170 with degree of
freedom of 168 and p-value of 0.0001. Since the p-value 0.0001<0.05 at 95% confidence level,
we can say that there is significant relationship between the countries and the industry type.
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 459.396a 168 .000
Likelihood Ratio 342.170 168 .000
N of Valid Cases 781
a. 164 cells (76.3%) have expected count less than 5. The minimum expected count is .01.
2.
3. Country versus climate integrated into business strategy
The table below shows the cross tabulation between different countries and how they have
integrated into their business strategy climate change. Out of possible 781 observations from five
countries 702 has adopted the integration of business idea into their business strategy.
Crosstab
Count
CC2.2 - Is climate change integrated into your
business strategy?
TotalYes No
country Canada 85 14 99
China 3 5 8
Germany 57 9 66
United Kingdom 205 14 219
USA 352 37 389
Total 702 79 781
From the chi-square test table below, we find that Pearson Chi-Square has value of 30.304 with
degree of freedom 4 and p-value of 0.001. Likelihood Ratio test has a value of 19.326 with
degree of freedom of 4 and p-value of 0.001. Since the p-value 0.0001<0.05 at 95% confidence

level, we can say that there is significant relationship between the countries and the integration of
climate change in the business strategy.
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 30.304a 4 .000
Likelihood Ratio 19.326 4 .001
N of Valid Cases 781
a. 1 cells (10.0%) have expected count less than 5. The minimum expected count is .81.
4. Country versus emission reduction target
The table below shows the cross tabulation between the country and carbon emission target. Out
of the 781 observations, 576 said they had the emission reduction or renewable energy
consumption or production target that was active.
Crosstab
Count
CC3.1. Did you have an emissions reduction or
renewable energy consumption or production target
that was active (ongoing or reached completion) in
the reporting year?
TotalYes No
country Canada 55 44 99
China 6 2 8
Germany 48 18 66
United Kingdom 180 39 219
USA 287 102 389
Total 576 205 781
From the chi-square test table below, we find that Pearson Chi-Square has value of 25.033a with
degree of freedom 4 and p-value of 0.001. Likelihood Ratio test has a value of 23.968with degree

of freedom of 4 and p-value of 0.001. Since the p-value 0.0001<0.05 at 95% confidence level,
we can say that there is significant relationship between the countries and emission reduction
strategy
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 25.033a 4 .000
Likelihood Ratio 23.968 4 .000
N of Valid Cases 781
a. 1 cells (10.0%) have expected count less than 5. The minimum expected count is 2.10.
5. Country versus carbon emission reduction
From the chi-square test table below gives the relationship between country and percentage
change in carbon emission, we find that Pearson Chi-Square has value of 1682.168a with degree of
freedom 1536 and p-value of 0.005. Likelihood Ratio test has a value of 1041.061with degree of
freedom of 1536 and p-value of 1.000. Since the p-value 0.0001<0.05 at 95% confidence level,
we can say that there is significant relationship between the countries and percentage change in
carbon emission.
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 1682.168a 1536 .005
Likelihood Ratio 1041.061 1536 1.000
N of Valid Cases 781
a. 1917 cells (99.6%) have expected count less than 5. The minimum expected count is .01.

6. Integrating climate change versus percentage change in metric tons of carbon
emission.
From the chi-square test table below gives the relationship between integrating climate change in
business strategy and percentage change in carbon emission, we find that Pearson Chi-Square
has value of 302.560a with degree of freedom 384 and p-value of 0.999. Likelihood Ratio test has a
value of 238.929with degree of freedom of 384 and p-value of 1.000. Linear-by-Linear Association
has a value of 157 with a degree of freedom of 1 and p-value of 0.692. Since the p-value
0.999>0.05 at 95% confidence level, we can say that there is no significant relationship
integrating into business strategy the climate change and percentage change in carbon emission.
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 302.560a 384 .999
Likelihood Ratio 238.929 384 1.000
Linear-by-Linear Association .157 1 .692
N of Valid Cases 781
a. 753 cells (97.8%) have expected count less than 5. The minimum expected count is .10.
The table below gives the additional information on the relationship between integrating into
business strategy the climate change and percentage change in the emission of carbon. It gives
the Pearson’s correlation coefficient and Spearman correlation coefficient. The Pearson
correlation coefficient has value of -0.014 and asymptotic standardized error of 0.019. The
Spearman correlation coefficient has value of 0.044 and asymptotic standardized error of 0.036
Symmetric Measures
Value
Asymptotic
Standardized
Errora Approximate Tb
Approximate
Significance
Interval by Interval Pearson's R -.014 .019 -.396 .692c
Ordinal by Ordinal Spearman Correlation .044 .036 1.227 .220c
N of Valid Cases 781
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.

7. Emission reduction target versus percentages change of carbon emissions
From the chi-square test table below gives the relationship between emission reduction target
and percentage change in carbon emission, we find that Pearson Chi-Square has value of 420.388a
with degree of freedom 384 and p-value of 0.097. Likelihood Ratio test has a value of 493.288with
degree of freedom of 384 and p-value of 0.0001. Linear-by-Linear Association has a value of 0.0
with a degree of freedom of 1 and p-value of 0.988. Since the p-value 0.097>0.05 at 95%
confidence level, we can say that there is no significant relationship between carbon emission
target and percentage change in carbon emission.
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 420.388a 384 .097
Likelihood Ratio 493.288 384 .000
Linear-by-Linear Association .000 1 .988
N of Valid Cases 781
a. 758 cells (98.4%) have expected count less than 5. The minimum expected count is .26.
The table below gives the additional information on the relationship between emission reduction
target and percentage change in the emission of carbon. It gives the Pearson’s correlation
coefficient and Spearman correlation coefficient. The Pearson correlation coefficient has value of
0.001 and asymptotic standardized error of 0.046. The Spearman correlation coefficient has
value of 0.163 and asymptotic standardized error of 0.036
Symmetric Measures
Value
Asymptotic
Standardized
Errora Approximate Tb
Approximate
Significance
Interval by Interval Pearson's R .001 .046 .015 .988c
Ordinal by Ordinal Spearman Correlation .163 .036 4.599 .000c
N of Valid Cases 781
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.

8. Industry type versus the percentage change of carbon emission
From the chi-square test table below gives the relationship between country and percentage
change in carbon emission, we find that Pearson Chi-Square has value of 16209.768a with degree
of freedom 16128 and p-value of 0.323. Likelihood Ratio test has a value of 3527.574 with degree
of freedom of 16128 and p-value of 1.000. Since the p-value 0.323<0.05 at 95% confidence level,
we can say that there is significant relationship between the industry types and percentage
change in carbon emission.
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 16209.768a 16128 .323
Likelihood Ratio 3527.574 16128 1.000
N of Valid Cases 781
a. 16548 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Hypothesis testing
H0: Integration of climate change in business strategy has no significant relationship with carbon
emission reduction.
H1: Integration of climate change in business strategy has significant relationship with carbon
emission reduction.
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 302.560a 384 .999
Likelihood Ratio 238.929 384 1.000
Linear-by-Linear Association .157 1 .692
N of Valid Cases 781
a. 753 cells (97.8%) have expected count less than 5. The minimum expected count is .10.
The above table shows the chi-square test between integrating climate change into business
strategy. The p-value from the table of the Pearson Chi-Square is 0.999. At 95% confidence level,
0.999>0.05. We therefore fail to reject the null hypothesis and conclude that integration of climate
change into business strategy has no significant relationship with carbon emission reduction.

Discussion
The main objective of the study was to identify if there could be statistical significance
relationship between the integrating climate change business strategies and carbon emission
reduction. Carbon dioxide is one of the greenhouse gasses which contribute to global warming and
eventually causing the climate change. The only way to prevent the effects of climate change is to
reduce as much as possible the emission of carbon into the atmosphere. Much of the carbon
released in the atmosphere is emitted as a result of majorly the human activities, especially the big
manufacturing firms hence our study. To reduce the carbon emission, it is solely in the hand of
both the regulators and the firm’s management to ensure that carbon emitted is reduced. One of
the ways the firms can do this, from the findings is to integrate climate change into the business
strategy and bringing into play the management incentives.
By business integrating climate change as their business strategy, the main objective of that
particular business is to ensure their objectives are achieved including the one for climate change.
A strategy is something which the life of a business depend on, without it they cannot succeed.
Therefore this calls for not just integrating it just as a strategy but also implementing those
strategies. Some strategies have worked while some haven’t worked. Studying the different types
of strategies which other firms has put in place across the world can help in spreading the idea and
help the firms which have not implemented them to do so. There is the need for both the
governments of specific countries and the international organizations to come out and put
awareness concerning climate change to the firms which have not implemented those strategies.
The government also has the power to enforce some strategies to different firms. Putting it a must
that for a firm to operate they must integrate and implement climate change in their business
strategy this will help great time.
One of the study variable was management incentives on employees. This has quite work well in
some countries. By offering benefits to employees so that they can help the firm to achieve its
objectives can be very effective. Though this comes in handy with integrating into the business
strategy the issue of climate change, management incentive can help in the general
implementation. Firms should be encouraged to adopt this for the people who have not adopted
sine it can help to achieve carbon emission free.
On studying on how integrating climate change business strategy, our main expectation was to
find how this has contributed majorly, but our hypothesis is saying there is no significant
relationship between integrating climate change in business strategy and carbon emission
reduction. This might be as a result of putting everything in place but not implementing the idea
into real action. Some of the countries has no proper strategies to ensure that climatic change
strategies are enforced into action. Some firms might also lack the good will for the reduction of
carbon emissions. With reduced carbon emitted less global warming, hence no climate change.
Limitations to the study
There are some limitations faced during the study.

Poor implementation. There are many firms according to the study who have integrated climate
change in their business strategy, but we still find that this do not have greater effect on the carbon
emission has it should be. From individual countries it has worked therefore it can work anywhere.
Irrelevant strategies. There are some strategies put in place by some firms across the world which
are related to climate change, but doesn’t necessarily address the climate change. This may lead to
many people saying that they have integrate strategies to curb carbon emission, but in real sense
they don’t work.
Inadequate government intervention on the implementation of the climatic change strategies. The
government may be reluctant on their side in ensuring that these strategies are put in place for
effective carbon emission. This can lead to many firms saying they have integrated the strategies
but still no effect on the reduction of carbon emission.
Further research
The further research should be conducted on how different firms are implementing the strategies
they have put in place to reduce the carbon emission. This will help in sharing ideas across the
world on how proper implementation can be done.
Another research can look into the different strategies different firms are adopting to ensure
reduction of carbon emission. This will also help to share the ideas to curb carbon emission.
Finally research on how the different governments are ensuring that carbon emission reduction
policies are followed and met by different operating firms.