2. The following shows the information of a government bond traded in the secondary market.

Type of Bond Government bond

Issue Date May 16, 2006

Maturity Date May 16, 2016

Face Value $100

Redemption Value $108

Coupon Rate 5% payable semiannually

Yield Rate 8% convertible semiannually

Construct the bond amortization schedule for year 5 and year 6 (i.e., for the 9th coupon through the 12th coupon).

The Railway Service in Andaleland

The Railway service industry in Andaleland is categorised into groups according to the areas of operation and revenue. International rail services are offered by firms who own large and luxurious trains that travel to just about anywhere in the continent. Companies in this segment typically have revenues in excess of $1 billion. National trains have revenues between $100 million and $1 billion and travel domestically only. Regional rail companies have smaller trains with revenues below $100 million. Cargo trains do not carry commercial passengers. They specialise in the transportation of goods.

The suppliers to the railway industry are caterers, railway stations, train manufacturers and security firms which are oligopolies, meaning that the railway companies are in a less advantageous position. Key suppliers include manufacturers of trains Zanzi and Taraget who dominate the market and are able to garner significant profits at the railway companies’ expense by virtue of their specialised position. Another key supply for the industry is fuel, the price of which is currently proving a very problematic issue for companies.

The top three competitors are Virgin, Bota and Dannes railway companies. Other competitors include TubaTran, Canker Rail, Andale West, Continental Rails, Jama Rail, Atlantic Rail Northwest Rail, Southwest Rail and Una Railways. Most rail companies make extremely low returns; indeed many are currently losing as the industry is characterised by many price wars. Most railway companies also compete with non-price competitive tactics such as frequent traveller programs.

The customers of the industry can be categorised into three groups; business travellers, leisure travellers and buyers of large blocks of seats known as consolidators, who buy excess seat inventory at large discounts. Switching costs are very low and buyers are price sensitive.

Communication technology has proven to be a viable substitute for some form of business travel. Also, alternatives such as auto travel and bus transportation exist for leisure travellers who frequent regional and national train travel.

The capital intensity of the railway industry would appear to pose a formidable entry barrier. However, Atlantic Rail, TubeTran and other entrants have proven that financing is available when there is a convincing business plan and when economic conditions are conducive to the business. Brand name and frequent traveller plans would also seem to be deterrents to entry however, Atlantic Rail’s success demonstrates that customers are willing to switch to other railway companies if the price is right.

(Source: Adapted from Carpenter et al, (2011) Strategic Management, A Dynamic Perspective, New Jersey, Pearson Prentice Hall)

a. Identify four strategic groups in the railway service industry and explain why they do not compete directly against each other in the industry

b. Examine two barriers in the case that could act as obstruction to keep away new entrants from entering and reducing the profits of the established firms.

c. Explain two reasons why these barriers have or have not been effective in preventing new entrants from entering the industry

d. Identify two supplier groups in the industry and explain why they have high bargaining power over the rail companies.

e. Explain how two substitute services would pose a threat to the profitability of the companies in the industry?

Balance sheet

December 31

Assets 2007 2006

Cash $25,000 $40,000

Short term investments 15,000 60,000

Accounts receivable 50,000 30,000

Inventory 50,000 70,000

Property, plant and equipment (net) 160,000 200,000

Total assets $300,000 $400,000

Liabilities and stockholders equity

Accounts payable $20,000 $30,000

Short term notes payable 40,000 90,000

Bonds payable 80,000 160,000

Common stock 60,000 45,000

Retained earnings 100,000 75,000

Total liabilities and stockholders equity $300,000 $400,000

Income statement (for the year ended December 31, 2007)

Net sales $360,000

Cost of goods sold 184,000

Gross profit 176,000

Expenses

Selling expenses 30,000

Administrative expenses 59,000

Total expenses 89,000

Income before interest expense and taxes 87,000

Interest expense 12,000

Income before income taxes 75,000

Income tax expense 30,000

Net income $45,000

Additional information

1. 120,000 shares were outstanding in 2007:90,000 shares were outstanding in 2006
2. Market value of common stock on December 31, 2007 was $12 per share.

1. Working capital
2. Current Ratio
3. Quick ratio
4. Cash ratio

4. There is data for you in the tab called EComSales. It comes from the Federal Reserve and represents quarterly e-commerce sales data in the U.S. for Quarter 4, 1999 to Quarter 4, 2019. Month 1=Q1, Month 4=Q2, Month 7=Q3, Month 10 = Q4. Run a regression forecasting sales for all 4 quarters in 2020. Print your regression results in a new tab. Rename that tab Answer Q4. In that cells below your regression results, forecast sales for Q1:2020, Q2:2020, Q3:2020, and Q4:2020. Round all answers to the nearest dollar in Excel and put a comma in so I can read it easier (do not round by hand or put the comma in by hand– set up excel to do the rounding and the comma for you).

IT IS NOT LETTING ME POST CORRECTLY, THE COLUMN OF 5553 IS FOR Q1, THE 6059 FOR Q2, THE 6892 FOR Q3 AND THE 5241 FOR Q4

PLEASE EXPLAIN STEP BY STEP AND PUT EXCEL FORMULAS! THANK YOU

1. The process for buying a car in the U.S. seems to usually exhibit the following characteristics (it may differ from these, but I’m not an expert in the auto industry so just take these as given for the sake of argument):
   1. A car dealership purchases cars from a manufacturer at a specific wholesale price, set by the manufacturer.
   2. The car dealership puts a sticker in the car window which includes the MSRP, or manufacturer suggested retail price.
   3. The car dealership negotiates the actual selling (retail) price with individual customers, such that the same car may sell for different retail prices for different customers.

For the three prices mentioned above (wholesale price, MSRP, and retail/selling price) describe how much market power an individual car dealership would have in setting each price. In terms of just the retail/selling price, how might an individual car dealership’s potential market power be affected by the presence of other car dealerships in town? (E.g., a small town that has one dealership vs. a larger city where several car dealerships usually cluster in a certain area).

Given that car dealerships always ensure that the retail/selling price exceeds the wholesale price, such that customers pay more for the car than the dealership itself does, why do customers continue using car dealerships instead of purchasing the car directly from the manufacturer at its factory?

A paper describes a study in which researchers observed wait times in coffee shops in Boston. Both wait time and gender of the customer were observed. The mean wait time for a sample of 145 male customers was 85.6 seconds. The mean wait time for a sample of 141 female customers was 113.6 seconds. The sample standard deviations (estimated from graphs that appeared in the paper) were 50 seconds for the sample of males and 75 seconds for the sample of females. For purposes of this exercise, suppose that these two samples are representative of the populations of wait times for female coffee shop customers and for male coffee shop customers. Is there convincing evidence that the mean wait time differs for males and females? Test the relevant hypotheses using a significance level of 0.05. (Use a statistical computer package to calculate the P-value. Use μ_males − μ_females. Round your test statistic to two decimal places, your df down to the nearest whole number, and your P-value to three decimal places.)

State your conclusion.

Reject H₀. There is convincing evidence that the mean wait time differs for males and females.

Reject H₀. There is not convincing evidence that the mean wait time differs for males and females.   

Fail to reject H₀. There is not convincing evidence that the mean wait time differs for males and females.

Fail to reject H₀. There is convincing evidence that the mean wait time differs for males and females.

1. The process for buying a car in the U.S. seems to usually exhibit the following characteristics (it may differ from these, but I’m not an expert in the auto industry so just take these as given for the sake of argument):
   1. A car dealership purchases cars from a manufacturer at a specific wholesale price, set by the manufacturer.
   2. The car dealership puts a sticker in the car window which includes the MSRP, or manufacturer suggested retail price.
   3. The car dealership negotiates the actual selling (retail) price with individual customers, such that the same car may sell for different retail prices for different customers.

For the three prices mentioned above (wholesale price, MSRP, and retail/selling price) describe how much market power an individual car dealership would have in setting each price. In terms of just the retail/selling price, how might an individual car dealership’s potential market power be affected by the presence of other car dealerships in town? (E.g., a small town that has one dealership vs. a larger city where several car dealerships usually cluster in a certain area).

Given that car dealerships always ensure that the retail/selling price exceeds the wholesale price, such that customers pay more for the car than the dealership itself does, why do customers continue using car dealerships instead of purchasing the car directly from the manufacturer at its factory?

Divisional Income Statements and Return on Investment Analysis

E.F. Lynch Company is a diversified investment company with three operating divisions organized as investment centers. Condensed data taken from the records of the three divisions for the year ended June 30, 20Y8, are as follows:

The management of E.F. Lynch Company is evaluating each division as a basis for planning a future expansion of operations.

Required:

1. Prepare condensed divisional income statements for the three divisions, assuming that there were no support department allocations.

2. Using the DuPont formula for return on investment, compute the profit margin,investment turnover, and return on investment for each division. Round your answers to one decimal place.

The following scenarios are drawn from real research articles. Imagine you were the one conducting these studies – tell me which type of statistical test would you in the following situations and why?

1. In a study from 2009, researchers set out to examine whether call light use rate and the average call light response time contribute to patients’ fall and the injurious fall rates in acute care settings. As part of this study they compared the average call light response time between patients in medical, surgical, combined medical-surgical, and other settings.  

1. What test would the authors have run to determine whether there was a difference in call light response times between these groups? Why?

2. While effective communication is critical during the handover of patients between hospital shifts, to date (at least in 2013 when this study was conducted) there is no standard handover protocol. In one study of 56 ICU nurses in a large-scale Iranian teaching hospital, nurses were trained to use a standard protocol tool. Their adherence to/deviation from standards and protocols deemed vital to patient outcomes were assessed with a 20-point scale called the Nurses’ Safe Practice Evaluation Checklist (NSPEC) before and after the nurses were trained to utilize the standard protocol tool for handing over patients between shifts.  

1. What test would the authors run to determine whether nurses’ mean score on the NSPEC increased significantly after training with the standard protocol tool? Why?