MGT723 Research Project Oz Assignments Solution

MGT723 Research Project Oz Assignments Solution

MGT723 Research Project Oz Assignments Solution

Introduction

In this section, the relationship between provision of incentives by management and reduction of carbon emissions will be checked for both the Forest and Paper Industry and also for the Air Freight Transportation Industry. Chi- square analysis tests will be used in both cases to check for the association between the independent and dependent variables. A chi- square test is used to check whether there is a significant connection amid two variables (Rana & Singhal, 2015).

Previous research studies have revealed that provision of incentives motivates employees to adopt new proposed policies (Lazaroiu, 2015). Therefore in this case, provision of incentives as a bid to push employee benefits to accept climate change policies aimed at reducing carbon emissions might work. To confirm this however, statistical tests will be conducted as shown in the sections below.

Forest and Paper Products Industry: Relationship between Provision of Incentives and Reduction of Carbon Emissions

The table below shows results from achi- squaretest between the aforementioned study variables.

Table 1: Chi-Square Tests on Forest and Paper Products Industry

 

Value

df

Asymp. Sig. (2-sided)

    

Pearson Chi-Square

28.718a

29

.480

Likelihood Ratio

28.112

29

.512

Linear-by-Linear Association

3.489

1

.062

N of Valid Cases

32

  
    

a. 60 cells (100.0%) have expected count less than 5. The minimum expected count is .19.

The results are given under the Pearson chi- square test statistics. From the results, it is evident that there was no significant connection between provision of incentives by the management of companies and reduction in the rate of carbon emission in the Forest and Paper Products Industry (χ2 = 28.718, p = 0.480). The obtained p- value is greater than the 0.05 level of significance, thus showing that there is no relationship between the independent and dependent variables. In this case therefore, the null hypothesis that states there is no relationship between provision of incentives and reduction of carbon emissions will be accepted. This provides a possibility of type 2 error, which is an error of accepting a null hypothesis that is wrong (Hopkins, 2017). However, this error is small in this case, since the sample size used is large enough to detect any relationships between provision of incentives and reduction of carbon emissions.

Air Freight Industry: Relationship between Provision of Incentives and Reduction of Carbon Emissions

The table below shows results from achi- squaretest between the aforementioned study variables.

Table 2: Chi-Square Tests on Air Freight Industry

 

 

Value

df

Asymp. Sig. (2-sided)

    

Pearson Chi-Square

32.000a

30

.368

Likelihood Ratio

27.738

30

.584

Linear-by-Linear Association

.102

1

.749

N of Valid Cases

32

  
    

a. 62 cells (100.0%) have expected count less than 5. The minimum expected count is .16.

The results are given under the Pearson chi- square test statistics. From the results, it is evident that there was no significant connection between provision of incentives by the management of companies and reduction in the rate of carbon emission in the Air Freight Industry (χ2 = 32.000, p = 0.368). The obtained p- value is greater than the 0.05 level of significance, thus showing that there is no relationship between the independent and dependent variables. The null hypothesis that states no relationship exists between provision pf incentives and reduction of carbon emissions is accepted. This, just like in the section above, creates a chance of committing a type 2 error. But as stated before, the utilized sample size is big enough to detect any significant connection between the independent variable and the dependent variable.

Hypothesis Testing

Results in the section above are useful in answering the hypothesis. The hypotheses of the study are as given below:

H1:There is no effect on carbon emission reduction when the management gives incentives to the employees for climate change

H2:There is an effect on carbon emission reduction when the management provides incentives to the employees for climate change

Data analysis was performed for both the Forest and Paper Products Industry and the Air Freight industries. Results from the Chi- square test revealed that there was no connection between provision of incentives and reduction of carbon emission for the Forest and Paper Products industry, and also for the Air Freight industries. Therefore, there is sufficient evidence to accept the null hypothesis that states: there is no effect on carbon emission reduction when the management gives incentives to the employees for climate change.

Discussions

The research study aimed at finding out whether there was a significant association between provision of incentives and reduction of carbon emission. Findings from the analysis confirmed the null hypotheses that there is no effect on carbon emission reduction when the management gives incentives to the employees for climate change. These results were similar for the two types of industries that were considered. That is, the Forest and Paper Products industry and the Air Freight industry.

Therefore, it is evident that there was no significant dissimilarity in the discharge of carbon between companies receiving incentives from their managers and companies that never receive incentives.

Even though previous studies have shown that there is a connection between provision of incentives and acceptance of new policies by employees (Lazaroiu, 2015), insuffient research has been carried out to determine the factors that could significantly reduce carbon emissions. This therefore calls for further research to check what factors would assist in curbing the emissions.

A research by Liesen et al., (2015) revealed that one of the ways in which carbon is released into the air is through burning gasoline. Therefore, strategies should be developed in line with reducing the rate of burning gasoline. Given that gasoline is still extensively used in the automobile sector and also in manufacturing sectors, it is important that more studies are funded in line with developing stronger proposals to totally stop the burning of gasoline.

There have been several proposals to this effect of reducing emissions, such as encouraging more use of non- organic fuel such as electricity or solar energy (Armaroli & Balzani, 2016). However, this proposal has not been fully accepted in many countries’ companies. Since this research methodology has proven that providing incentives is not a significant ways of reducing carbon emissions in industries, it is important that strategists develop better ways to motivate the employees to curb emissions.

Carbon emissions are a global concern. Various research studies have proposed additional ways of curbing emissions. This is through reducing the amount of carbon emissions in households. This includes buying vehicles that either, do not consume gasoline or consume low levels of it. Secondly, reduction in emissions can be reduced through recycling clothes and furnishings (Huisingh et al., 2015). Strategists should follow this example and develop more achievable strategies towards curbing carbon emissions.

Limitations of the Research

The sample size used in this research is small compared to the purpose. The sample should be considerably larger in order to have more reliable results.

The study only considered incentives as a possible factor of reducing carbon emission. However, the research should also consider other factors that might considerable reduce carbon emission.

Data collected for this study captures a small amount of the industries in connection with carbon emission. Therefore, more industries should be targeted for more generalizable results.

However, the assumptions of the study that were previously set were not breached, and therefore the conclusion of the study are reliable.

Further Research

For further research, another study should be carried out while using a larger sample than the one used in this research. An increase in sample size increases the validity of results. This is true because using a greater sample produces results that are easily generalizable to the target population (Kaplan et al., 2014).

In addition, more industries apart from Forest and Paper industry and Air Freight industry should be considered while collecting the data for future research. In this way, the recommendations developed will cover all industries with a potential of carbon emissions.

Moreover, for further research more factors that might have an impact on the reduction of carbon emission apart from provision of incentives should be considered, to determine which factors significantly reduce carbon emissions (Feng et al., 2015).

Additionally while carrying out further research, other avenues which contribute to carbon emissions should be considered in order to develop more comprehensive recommendations. Such sectors include the household sector. In this way, governance of emissions will be done holistically by covering all possible channels.

References

1. Armaroli, N. and Balzani, V., 2016. Solar electricity and solar fuels: status and perspectives in the context of the energy transition. Chemistry–A European Journal22(1), pp.32-57. London: John Wiley & Sons.
2. Feng, K., Davis, S.J., Sun, L. and Hubacek, K., (2015). Drivers of the US CO2 emissions 1997–2013. Nature communications6, p.7714. New York: Elsevier.
3. Hopkins, W.G., 2017. Estimating Sample Size for Magnitude-Based Inferences. Sportscience21. New York: Elsevier.
4. Huisingh, D., Zhang, Z., Moore, J.C., Qiao, Q. and Li, Q., 2015. Recent advances in carbon emissions reduction: policies, technologies, monitoring, assessment and modeling. Journal of Cleaner Production103, pp.1-12. New York: Elsevier.
5. Kaplan, R.M., Chambers, D.A. and Glasgow, R.E., 2014. Big data and large sample size: a cautionary note on the potential for bias. Clinical and translational science7(4), pp.342-346. London: Routledge.
6. Lazaroiu, G., 2015. Employee motivation and job performance. Linguistic and Philosophical Investigations14, p.97. Seoul: ASIA Publishers.
7. Liesen, A., Hoepner, A.G., Patten, D.M. and Figge, F., 2015. Does stakeholder pressure influence corporate GHG emissions reporting? Empirical evidence from Europe. Accounting,Auditing & AccountabilityJournal28(7), pp.1047-1074. London: Routledge.
8. Rana, R. and Singhal, R., 2015. Chi-square test and its application in hypothesis testing. Journal of the Practice of Cardiovascular Sciences1(1), p.69. India: Sage Publications.