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7 pages/≈1925 words
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4 Sources
Level:
APA
Topic:
Literature & Language
Type:
Term Paper
Language:
English (U.S.)
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Topic:

Transportation: Aviation, Road, Ship And Rail Transport (Term Paper Sample)

Instructions:

Select a topic of interest
Identify an industry that you have covered in your MG 615 (Managing in the Global Environment). An industry could be one of the following (these are just examples):
a) Pet Industry
b) Transportation Industry
c) Pharmaceutical Industry
d) Merchandizing Industry
Here, the industry annual sales will be designated as the dependent variable.
Next, we need to identify theoretically all those factors that may explain the variations of the dependent variable. Some explanations are:
a) Average annual income that can be measured by US GDP. In theory, it is argued that as the average annual income increases, consumers will be inclined to make more purchases. So, the relationship between pet sales and average income is expected to be positive.
b) After we have defined the theoretical relationship between the dependent and independent variable, we proceed to collect data on the variables for the purpose of testing. Does the data provide evidence of the theoretical relationship between Sales (Y) and income( X). Details on the expected relationship will be covered in chapter 13 in the course.
In other words, establish whether a causal relationship exists between industry sales and the explanatory variable; is the relationship positive or negative? Once you have identified the theoretical relationship, collect your data and then test your hypothesis. This is the first stage of the DCOVA; defining your goal or objective of your study or to define your variable of interest: STATE YOUR HYPOTHESIS.
Once you have defined the dependent and independent variables, provide a brief explanation as to how the explanatory variable influences the industry sales. Choose 2 variables to observe: 1) Industry sales and 2) Only one explanatory variable.
For each variable, collect data points for the past 25 years. How do you plan to collect the data: This is the second stage of data collection? Use Secondary data. A questionnaire is not needed for this project.
Required: The remaining three stages of Organize, Visualize and Analyze are listed below
1. Construct a frequency distribution or histogram for your variable
2. Graphically depict your data using two other methods studied (scatter plot/trend line/ histogram/pie chart).
3. Establish your hypothesis; that is the expected sign(s) between the dependent and independent variables. After you have established the various hypotheses, narrow down your research to only one hypothesis.
4. Run an OLS regression to test the significance of the theoretical signs expected
- What is the Y-intercept
- Compute the slope
- R square
- Is the explanatory variable significant at the 5% level? that is what is the “t” value?
- Estimate the regression equation and graphically show the regression line
- Compute the p-value
5. Comments on your results – this is important so think carefully and write.
Format:
1. Introduction
- Background material to your topic (the industry)
- The scope of your research ( what aspect of the industry are you focusing on)
- State the overall purpose of your research ( to evaluate, to examine whether a relationship exists)
- Your main findings (offer an analysis); make recommendations, etc.
2. Body
3. Summary
4. Conclusion (main findings)
5. References
6. APA:
a) Double lines
b) APA style
c) Times Numeral Font
d) Errors free

source..
Content:



Transportation Industry
Student’s Name
Institutional Affiliation
Transportation Industry
Introduction
Transportation is a competitive industry featuring various forms of transport including aviation, road, ship and rail transport. The industry sector is made of logistic services, Air and express delivery services (EDS), freight rail, trucking and maritime transport. According to report file by Plunkett Research LTD, Transport Industry recorded an aggregate global revenue of $ 4.7 Trillion as at 2016. This amount translates to 6% of the world’s gross domestic product (GDP) (International Transport Forum, 2009). Locally, the U. S transport industry generated an average revenue of $1.48 trillion in 2015 and $ 1.65 trillion in 2016 and the latter represented 8% of the US GDP. The 2016 revenue statistics indicates that there was huge investments in the sector especially in the trucking transport, which generated up to $ 787 billion globally and 211 billion in the US only (Plunkett, 2009). From the growth, both the international and domestic companies in the industry benefited from the availability of affordable and skilled workforce. However, the revenue generation largely depends on the consumers’ Disposable Personal Income (DPI) position. DPI refers to the available amount of money for an individual to spend after savings and paying for taxes. The amount of disposable income available affects a consumers’ spending habits, and this is always a major concern for companies (Flatters, Paul, & Willmott, 2009). In a global perspective, consumer’s disposable income are negatively affected by factors such global financial crisis, negative taxation policies, high interest rates and consumer confidence respective to their level of income and wealth. Theoretically, it is argued that an increase in the average annual income will encourage consumers to increase their expenditure on goods and services. Therefore, the paper seeks to validate the relationship the annual sales in the transport industry (dependent variable) and consumer average annual income (independent variable) through regression analysis.
To demonstrate the nature if transportation industry, the papers uses United Service Parcel (UPS), company as the case study, UPS sales data is compared against the global per capita annual income in the last 10 years. UPS provides a good representation and insight of the industry because it is a U.S. based multinational company with the biggest market share of 36.48 % in the industry beating other big players such as FedEx, DHL and USPS (Plunkett, 2009).
UPS Revenue Data and Global Global Average Income between Fiscal Year 2006 and 2016 (Plunkett, 2009)
Year/Revenue Revenue in Millions Dollars Global Average Income per Annum200711,90638,571200812,67540 026200910,93839 573201011,72840 320201112,58241 885201213,136 43 553201313,43443 368
201413,77945 184201513,97746 509201614,41847 231
Hypothesis
H0: There is no close relationship between annual sales and the global average disposable personal Income per annum.
H1: There is a strong relationship between annual sales and the global average disposable income per annum.
A Histogram Showing A Relationship Between UPS Annual Sales And Average Disposable Personal Income in the Last 10 Years.

Based on the histogram, H1 is true as any significant increase in household income translated to an increase the UPS annual sale. This indicates that when the customers’ purchasing power is high, they tend to spend more as they have enough money after saving and paying taxes. Same results is evident in the transport customers will book flights to travel f...

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