1. ShopSmart’s International Growth Strategy

ShopSmart, founded by in 1919 by Nick Smart, is a British multinational grocery and merchandise retailer. It is the largest grocery retailer in the United Kingdom, with a 28% share of the local market and the second largest after Walmart measured in revenue. In 2017, ShopSmart had sales of more than £62 billion ($70 billion US dollars), more than 480,000 employees and 6,553 stores in 13 countries.

In its home market of the United Kingdom, the company’s strengths are reputed to come from strong competencies in marketing and store site selection, logistics and inventory management and its own label product offerings. By the early 1990s, these competencies had already given the company a leading position in the United Kingdom. ShopSmart was generating strong cash flows and senior managers had to decide how to use that cash. One strategy they settled n was international expansion.

As managers looked at international markets, they soon concluded that the best opportunities were not in established markets in North America and Western Europe where strong competitors already existed but in emerging markets of Eastern Europe and Asia, where there were strong underlying growth trends. ShopSmart’s first international foray was into Hungary in 1995 where it acquired Globals Stores, a state-owned grocery chain. By 2017, ShopSmart was the market leader in Hungary accounting for 1% of the whole economy of Hungary.

Next, ShopSmart acquired 31 stores in Poland from Stavia Limited. The following year, in 1996, ShopSmart added 13 stores that it purchased from Kmart in the Czech Republic and Slovakia. The next year, ShopSmart moved to purchase stores in the Republic of Ireland.

ShopSmart’s Asian expansion begun in 1998 when it moved into Thailand. In 1999, the company entered South Korea when it partnered with Samsung to develop a chain of hypermarkets. This was followed by entry into Taiwan in 2000, Malaysia in 2002, Japan in 2003 and China in 2004.

The move into China came after three years of careful research and discussions with potential partners. Like many other western companies, ShopSmart was attracted to the Chinese market by its large size and rapid growth. In the end, ShopSmart settled on a 50-50 joint venture with Hymall, a hypermarket chain that is controlled by Ting Hsin, which has been operating in China for six years. In 2014, ShopSmaart combined its 131 stores in China in a joint venture with the state-run China Resources Enterprise and its nearly 3,000 stores. ShopSmart owned 20% of the joint venture. As a result of these moves, by 2017, ShopSmart generated sales of about $21 billion outside the United Kingdom. The addition of international stores has helped make ShopSmart the second largest company in the global grocery market behind only Walmart. By 2017, all its foreign ventures were making money.  

(Source: Adapted from Hill, C.W.L. & Hult, G.T.M., (2019), International Business: Competing in the Global Marketplace, 12th Edition, McGraw Hill Education)

1. Examine two reasons why ShopSmart’s initial international expansion focused on emerging markets rather than competing with established companies in the more advanced markets of North America and Western Europe.

2. Discuss two disadvantages that ShopSmart encountered as a first mover into these emerging markets.

3. ShopSmart’s entry strategy into the Eastern European countries was through acquisition. Discuss three disadvantages that the company is likely to encounter as a result of this entry strategy

4. Identify ShopSmart’s strategic entry into the Asian market and discuss two benefits that the company sought to achieve with this strategy

with python
Fatima wants to purchase a new dining table at an affordable price, so she collected the models name, description and prices of different dining tables from IKEA website and stored them in the file DiningTables.txt.

The file contains records with the following format:

model_name(string)\ndescription\nprice (int)\n

Help Fatima get some statistics about the dining table records by performing the following tasks:

• Read the file DiningTables.txt and print the number of records in the file.
• Create a function called tables_statistics(file_name) that prints the records of the dining tables with the following criteria:
  • The most expensive dining table model name, description and price.
  • The cheapest dining table model name, description and price.
  • The average price of all dining tables in the file.

Here is a sample run for your reference:

—————-

TÄRENDÖ / GUNDE

Table and 4 chairs110 cm

231

TÄRENDÖ / ADDE

Table and 4 chairs110 cm

255

MELLTORP / ADDE

Table and 4 chairs125 cm

275

JOKKMOKK

Table and 4 chairs

595

LANEBERG / EKEDALEN

Table and 4 chairs130/190x80 cm

1375

LANEBERG / KARLJAN

Table and 4 chairs130/190x80 cm

1175

EKEDALEN

Table with 2 chairs and bench120/180 cm

1530

NORDVIKEN / LEIFARNE

Table and 4 chairs152/223x95 cm

1995

LERHAMN

Table and 2 chairs74x74 cm

495

EKEDALEN

Table and 4 chairs120/180 cm

1575

MÖRBYLÅNGA / LEIFARNE

Table and 6 chairs220x100 cm

3545

EKEDALEN

Table and 6 chairs180/240 cm

2165

IKEA PS 2012 / TEODORES

Table and 2 chairs

823

SKOGSTA / NORRARYD

Table and 6 chairs235x100 cm

3645

MELLTORP / TEODORES

Table and 4 chairs125 cm

491

MELLTORP / JANINGE

Table and 4 chairs125 cm

715

MELLTORP / TEODORES

Table and 2 chairs75x75 cm

273

MELLTORP / ADDE

Table and 2 chairs75 cm

165

INGATORP / INGOLF

Table and 4 chairs155/215 cm

1895

INGATORP / INGOLF

Table and 6 chairs155/215 cm

2685

INGATORP / INGOLF

Table and 6 chairs155/215x87 cm

3185

LANEBERG / SVENBERTIL

Table and 4 chairs130/190x80 cm

1295

NORDVIKEN / LEIFARNE

Table and 6 chairs210/289x105 cm

2745

NORDVIKEN

Table and 6 chairs210/289x105 cm

2865

NORDVIKEN

Table and 4 chairs152/223x95 cm

2075

MELLTORP / NILSOVE

Table and 2 chairs75x75 cm

785

MELLTORP / NISSE

Table and 2 folding chairs75 cm

265

MÖRBYLÅNGA / LEIFARNE

Table and 4 chairs140x85 cm

2995

VOXLÖV / ODGER

Table and 4 chairs180x90 cm

2175

EKEDALEN / ODGER

Table and 4 chairs120/180 cm

1975

MÖRBYLÅNGA / TOSSBERG

Table and 4 chairs145 cm

4275

GAMLARED / STEFAN

Table and 2 chairs85 cm

535

TINGBY / NILSOVE

Table and 4 chairs180x90 cm

2075

YPPERLIG / NILSOVE

Table and 4 chairs200x90 cm

2275

TINGBY / LEIFARNE

Table and 6 chairs180x90 cm

1745

MÖCKELBY / NORRARYD

Table and 6 chairs235x100 cm

4445

MÖCKELBY / ODGER

Table and 6 chairs235x100 cm

4265

VANGSTA / TEODORES

Table and 4 chairs120/180 cm

701

MÖRBYLÅNGA / BALTSAR

Table and 4 chairs140x85 cm

4475

MÖRBYLÅNGA / TOSSBERG

Table and 6 armchairs220x100 cm

5465

LISABO / SVENBERTIL

Table and 4 chairs140x78 cm

1295

MÖRBYLÅNGA / BALTSAR

Table and 6 chairs220x100 cm

5765

Is Your Car “Made in the U.S.A.”? The phrase “made in the U.S.A.” has become a familiar battle cry as U.S. workers try to protect their jobs from overseas competition. For the past few decades, a ma- jor trade imbalance in the United States has been caused by a flood of imported goods that enter the country and are sold at lower cost than comparable American-made goods. One prime concern is the automotive industry, in which the number of imported cars steadily increased during the 1970s and 1980s. The U.S. automobile industry has been besieged with complaints about product quality, worker layoffs, and high prices, and has spent billions in advertising and research to produce an American-made car that will satisfy consumer demands. Have they been successful in stopping the flood of imported cars purchased by American consumers? The data in the table represent the numbers of imported cars y sold in the United States (in millions) for the years 1969–2009. To simplify the analysis, we have coded the year using the coded variable x = Year - 1969.

Year	x, (Year - 1969)	y, Number of Imported Cars
1969	0	1.1
1970	1	1.3
1971	2	1.6
1972	3	1.6
1973	4	1.8
1974	5	1.4
1975	6	1.6
1976	7	1.5
1977	8	2.1
1978	9	2.0
1979	10	2.3
1980	11	2.4
1981	12	2.3
1982	13	2.2
1983	14	2.4
1984	15	2.4
1985	16	2.8
1986	17	3.2
1987	18	3.1
1988	19	3.1
1989	20	2.8
1990	21	2.5
1991	22	2.1
1992	23	2.0
1993	24	1.8
1994	25	1.8
1995	26	1.6
1996	27	1.4
1997	28	1.4
1998	29	1.4
1999	30	1.8
2000	31	2.1
2001	32	2.2
2002	33	2.3
2003	34	2.2
2004	35	2.2
2005	36	2.3
2006	37	2.3
2007	38	2.4
2008	39	2.3
2009	40	1.8

1. Using a scatterplot, plot the data for the years 1969–1988. Does there appear to be a linear relationship between the number of imported cars and the year?

2. Use a computer software package to find the least-squares line for predicting the number of imported cars as a function of year for the years 1969–1988.

3. Is there a significant linear relationship between the number of imported cars and the year?

4. Use the computer program to predict the number of cars that will be imported us- ing 95% prediction intervals for each of the years 2007, 2008, and 2009.

5. Now look at the actual data points for the years 2007–2009. Do the predictions obtained in step 4 provide accurate estimates of the actual values observed in these years? Explain.

6. Add the data for 1989–2009 to your database, and recalculate the regression line. What effect have the new data points had on the slope? What is the effect on SSE?

7. Given the form of the scatterplot for the years 1969–2009, does it appear that a straight line provides an accurate model for the data? What other type of model might be more appropriate? (Use residual plots to help answer this question.)

1. List the owner's name of all male customers in the bank who have a ’Checking’ account.
2. Find all accounts associated with ’Alexander Felix’.
3. For each account of the previous question, compute the Balance, and return a table that shows the account number, type, and balance for each account (hint: use UNION).
4. The list of customer names that have transactions greater than or equal to one thousand dollars.

Bank.sql is under this statement.

DROP DATABASE IF EXISTS Bank;
CREATE DATABASE Bank;
USE Bank;

DROP TABLE IF EXISTS transaction;
DROP TABLE IF EXISTS customer;
DROP TABLE IF EXISTS account;

CREATE TABLE customer (
name VARCHAR(20),
sex CHAR(1),
ssn CHAR(9) NOT NULL,
phone CHAR(15),
dob DATE,
address VARCHAR(50),
PRIMARY KEY(ssn)

);
  
CREATE TABLE account (
number CHAR(16) UNIQUE NOT NULL,
open_date DATE,
type CHAR(20),
owner_ssn CHAR(9) NOT NULL,
PRIMARY KEY(number)
);
  
CREATE TABLE transaction (
id INT(20) UNIQUE NOT NULL,
amount DECIMAL(9,2),
tdate DATE,
type CHAR(10),
account_num CHAR(16),
PRIMARY KEY(id)
);

INSERT INTO customer VALUE ('John Adam', 'M', '512432341', '(438) 321-2553', '1987-11-15',NULL);
INSERT INTO customer VALUE ('Alexander Felix', 'M', '724432341', '(541) 321-8553', '1991-05-22', NULL);
INSERT INTO customer VALUE ('Andrew William', 'M', '861894272', '(308) 692-1110', '1995-01-04', NULL);
INSERT INTO customer VALUE ('Ana Bert', 'F', '844192241', '(203) 932-7000', '1982-12-07', '23 Boston Post Rd, West Haven, CT 06516');

INSERT INTO account VALUE ('1111222233331441', '2018-12-03', 'Checking', '861894272');
INSERT INTO account VALUE ('2111222233332442', '2019-01-06', 'Saving', '512432341');
INSERT INTO account VALUE ('3111222233333443', '2017-09-22', 'Checking', '844192241');
INSERT INTO account VALUE ('4111222233335444', '2016-04-11', 'Checking', '724432341');
INSERT INTO account VALUE ('5111222233339445', '2018-11-05', 'Saving', '724432341');
INSERT INTO transaction VALUE (1001, 202.50, '2019-08-15', 'Deposit', '5111222233339445');
INSERT INTO transaction VALUE (1002, 100.00, '2019-09-21', 'Deposit','2111222233332442');
INSERT INTO transaction VALUE (1003, 200.00, '2019-09-29', 'Deposit', '2111222233332442');
INSERT INTO transaction VALUE (1004, 50.00, '2019-09-29', 'Deposit', '2111222233332442');
INSERT INTO transaction VALUE (1005, 1000.00, '2019-09-29', 'Deposit','3111222233333443');
INSERT INTO transaction VALUE (1006, -202.50, '2019-08-29', 'Withdraw', '5111222233339445');
INSERT INTO transaction VALUE (1007, 50.00, '2019-09-29', 'Deposit', '2111222233332442');
INSERT INTO transaction VALUE (1008, 50.00, '2019-09-29', 'Deposit', '2111222233332442');
INSERT INTO transaction VALUE (1009, -10.00, '2019-09-26', 'Withdraw', '2111222233332442');
INSERT INTO transaction VALUE (1010, 50.00, '2019-09-29', 'Deposit', '4111222233335444');
INSERT INTO transaction VALUE (1011, 320.00, '2019-09-29', 'Deposit', '5111222233339445');
INSERT INTO transaction VALUE (1012, 50.00, '2019-09-18', 'Deposit', '4111222233335444');
INSERT INTO transaction VALUE (1013, 5000.00, '2019-06-21', 'Deposit', '1111222233331441');
INSERT INTO transaction VALUE (1014, -100.00, '2019-09-02', 'Withdraw', '1111222233331441');
INSERT INTO transaction VALUE (1015, -200.00, '2019-09-08', 'Withdraw', '1111222233331441');

Alice J. and Bruce M. Smith are married taxpayers who file a joint return. Their social security numbers are 123-45-6789 and 111-11-1111, respectively. Alice’s birthday is September 21, 1966, and Bruce’s is June 27, 1965. They live at 473 Revere Avenue, Lowell, MA 01850. Alice is the office manager for Lowell Dental Clinic. Bruce is the self-employed physical therapist.

The following information is shown on Alice’s Wage and Tax Statement (Form W-2) for 2017.

Line	Description	Alice
1.	Wage, tips, other compensation	$58,000
2.	Federal income tax withheld	6,960
4.	Social security tax withheld	3,596
6.	Medicare tax withheld	841
17.	State income tax withheld	2,610

During 2017, Bruce recorded the following items of his business:

Revenue from patient visits	$270,000
Property tax on the office	4,500
Mortgage interest on the office	12,000
Depreciation on the office	5,500
Malpractice insurance	37,500
Utilities paid for the office	13,750
Office staff salaries	51,000
Rent payments on equipment	15,000
health insurance premium paid for himself	2,500
health insurance premium paid for his employees	5,000

Bruce made the quarterly federal tax payments totaled $40,000  (same as tax withheld and should be reported on line 64)

The Smiths provide over half of the support of their two children, Cynthia (born January 25, 1989, Social security number 123-45-6788) and John (born February 7, 1995, Social Security number 123-45-6786). Both children are full-time students and live with the Smiths except when they are away at college. Cynthia earned $4,200 from a summer internship in 2017, and John earned $3,800 from a part-time job.

During 2017, The Smiths furnished 60% of the total support of Bruce’s widower father, Sam Smith (born March 6, 1937, social security number 123-45-6777). Sam died in November, and Bruce, the beneficiary of a policy on Sam’s life, received life insurance proceeds of $800, 000 on December 28.

The Smiths also made some investment activities during 2017. The following information is shown their investment income / (loss) for 2017.

Dividend income (qualified dividend) from investing in Apple Inc.	$200
A gain from selling Netflix stock (hold for 7 months)	5,000
A loss from selling Bank of America stock (hold for 15 months)	(1,500)
An non-business bad debt  (hint: tax treatment as short-term capital loss)	(2,000)

The Smiths had the following expenses relating to their personal residence during 2017

Property Taxes	$5,000
Qualified interest on home mortgage	$8,800
Medical expense for 2017:          Medical insurance premium paid for two children          Doctor bill for Sam          Operation for Sam          Hospital expense for Sam	$4,500   7,600   8,500   3,500
Utilities	4,100
Union dues paid by Alice	600
Alice’s work uniform expenses	450

Prepare the Federal income tax return of 2017 for the Smiths. You will include Form 1040, Schedule C, Schedule SE (use the first page of SE to calculate), and Schedule A.

1. Find the total amount of ’Deposit’ transactions at the bank
2. Find the list of transactions (statement) of September 2019 (09/01/2019 to 09/30/2019) for account ’1111222233331441’ (note: look at the date format).
3. Find the balance of ’1111222233331441’ before 09/01/2019 ((not including 09/01/2019).
4. Find the name of the customer that deposited the highest amount with one transaction (include the transaction amount).

The SQL code to solve these problems is below:

DROP DATABASE IF EXISTS Bank;
CREATE DATABASE Bank;
USE Bank;

DROP TABLE IF EXISTS transaction;
DROP TABLE IF EXISTS customer;
DROP TABLE IF EXISTS account;

CREATE TABLE customer (
name VARCHAR(20),
sex CHAR(1),
ssn CHAR(9) NOT NULL,
phone CHAR(15),
dob DATE,
address VARCHAR(50),
PRIMARY KEY(ssn)

);
  
CREATE TABLE account (
number CHAR(16) UNIQUE NOT NULL,
open_date DATE,
type CHAR(20),
owner_ssn CHAR(9) NOT NULL,
PRIMARY KEY(number)
);
  
CREATE TABLE transaction (
id INT(20) UNIQUE NOT NULL,
amount DECIMAL(9,2),
tdate DATE,
type CHAR(10),
account_num CHAR(16),
PRIMARY KEY(id)
);

INSERT INTO customer VALUE ('John Adam', 'M', '512432341', '(438) 321-2553', '1987-11-15',NULL);
INSERT INTO customer VALUE ('Alexander Felix', 'M', '724432341', '(541) 321-8553', '1991-05-22', NULL);
INSERT INTO customer VALUE ('Andrew William', 'M', '861894272', '(308) 692-1110', '1995-01-04', NULL);
INSERT INTO customer VALUE ('Ana Bert', 'F', '844192241', '(203) 932-7000', '1982-12-07', '23 Boston Post Rd, West Haven, CT 06516');

INSERT INTO account VALUE ('1111222233331441', '2018-12-03', 'Checking', '861894272');
INSERT INTO account VALUE ('2111222233332442', '2019-01-06', 'Saving', '512432341');
INSERT INTO account VALUE ('3111222233333443', '2017-09-22', 'Checking', '844192241');
INSERT INTO account VALUE ('4111222233335444', '2016-04-11', 'Checking', '724432341');
INSERT INTO account VALUE ('5111222233339445', '2018-11-05', 'Saving', '724432341');
INSERT INTO transaction VALUE (1001, 202.50, '2019-08-15', 'Deposit', '5111222233339445');
INSERT INTO transaction VALUE (1002, 100.00, '2019-09-21', 'Deposit','2111222233332442');
INSERT INTO transaction VALUE (1003, 200.00, '2019-09-29', 'Deposit', '2111222233332442');
INSERT INTO transaction VALUE (1004, 50.00, '2019-09-29', 'Deposit', '2111222233332442');
INSERT INTO transaction VALUE (1005, 1000.00, '2019-09-29', 'Deposit','3111222233333443');
INSERT INTO transaction VALUE (1006, -202.50, '2019-08-29', 'Withdraw', '5111222233339445');
INSERT INTO transaction VALUE (1007, 50.00, '2019-09-29', 'Deposit', '2111222233332442');
INSERT INTO transaction VALUE (1008, 50.00, '2019-09-29', 'Deposit', '2111222233332442');
INSERT INTO transaction VALUE (1009, -10.00, '2019-09-26', 'Withdraw', '2111222233332442');
INSERT INTO transaction VALUE (1010, 50.00, '2019-09-29', 'Deposit', '4111222233335444');
INSERT INTO transaction VALUE (1011, 320.00, '2019-09-29', 'Deposit', '5111222233339445');
INSERT INTO transaction VALUE (1012, 50.00, '2019-09-18', 'Deposit', '4111222233335444');
INSERT INTO transaction VALUE (1013, 5000.00, '2019-06-21', 'Deposit', '1111222233331441');
INSERT INTO transaction VALUE (1014, -100.00, '2019-09-02', 'Withdraw', '1111222233331441');
INSERT INTO transaction VALUE (1015, -200.00, '2019-09-08', 'Withdraw', '1111222233331441');

The table to the right lists the average number of hours worked in a week and the average weekly earnings for U.S. production workers from 1967 to 1996. (The World Almanac 1998)

1) Construct a scatter diagram and comment on the relationship, if any, between the variables Weekly Hours and Weekly Earnings.

2) Determine and interpret the correlation for hours worked and earnings. Based upon the value of the correlation, is your answer to the previous question reasonable?

3) Based upon the data given, estimate the average weekly earnings for a workweek of 33.8 hours. How confident are you in your estimate? You should use a linear regression model to make your prediction. To create the linear regression model in Excel, right-click on a data point and click Add Trendline... In the options that display on the right, click Display Equation on chart.

4) Increase/decrease in weekly hours: a) For a production worker who wishes to increase weekly earnings, would you recommend a decrease in hours worked per week? Why or why not? b) Does a decrease in hours worked cause an increase in weekly pay? c) What other variables could contribute to an increase in weekly pay?

Part 2 1) Construct a scatter diagram and comment on the relationship, if any, between the variables Year and Hours Worked.

2) Determine and interpret the correlation for the year and hours worked. Based upon the value of the correlation, is your answer to the previous question reasonable?

3) Based upon the data given, estimate the average weekly hours worked this year. How confident are you in your estimate? You should use a linear regression model to make your prediction.

4) Assuming a linear correlation between these two variables, what will happen to the average weekly hours worked in the future? Is it possible for this pattern to continue indefinitely? Explain.

part 3

1) Construct a scatter diagram and comment on the relationship, if any, between the variables Year and Weekly Earnings.

2) Determine and interpret the correlation for the year and weekly earnings. Based upon the value of the correlation, is your answer to the previous question reasonable?

3) Based upon the data given, estimate the average weekly earnings this year. How confident are you in your estimate? You should use a linear regression model to make your prediction.

4) Assuming a linear correlation between these two variables, what will happen to the average weekly earnings in the future? Is it possible for this pattern to continue indefinitely? Explain.

data:

Year	Weekly Hours	Weekly Earnings
1967	38.0	$101.84
1968	37.8	$107.73
1969	37.7	$114.61
1970	37.1	$119.83
1971	36.9	$127.31
1972	37.0	$136.90
1973	36.9	$145.39
1974	36.5	$154.76
1975	36.1	$163.53
1976	36.1	$174.45
1977	36.0	$189.00
1978	35.8	$203.70
1979	35.7	$219.91
1980	35.3	$235.10
1981	35.2	$255.20
1982	34.8	$267.26
1983	35.0	$280.70
1984	35.2	$292.86
1985	34.9	$299.09
1986	34.8	$304.85
1987	34.8	$312.50
1988	34.7	$322.02
1989	34.6	$334.24
1990	34.5	$345.35
1991	34.3	$353.98
1992	34.4	$363.61
1993	34.5	$373.64
1994	34.7	$385.86
1995	34.5	$394.34
1996	34.4	$406.26

Part 2: Schedule M1 (CT1) and M2 (CT2) For Rocky Mountain Equipment Corporation Form 1120-F

The Rocky Mountain Equipment Corporation, a Colorado Corporation, was formed by two Colorado State University business school graduates. The Rocky Mountain Equipment Corporation incorporated on October 20, 1974. The main line of business is selling recreational equipment to outdoor enthusiasts. Starting in their parents’ garage, they have grown the corporation to a multimillion dollar business.

To comply with accounting requirements, the company uses an accrual method of accounting. Its accumulated earnings and profits as of December 31, 2016, were $1,200. It made cash distributions during its 2016 calendar tax year of $140,089. This consisted of $85,089 to preferred shareholders and $55,000 to common shareholders. The entire distribution to preferred shareholders is a taxable dividend. The $27,500 distribution on March 15, 2016, to common shareholders is a taxable dividend to extent of $27,318 (99.33%), and the $27,500 distribution on September 15, 2016, to common shareholders is a taxable dividend to the extent of $26,118 (94.97%).

The following profit and loss account appeared in the books of the Rocky Mountain Equipment Corporation for calendar year 2016. It is required to file Form 1120 and completes Form 1120-F (M-1 and M-2).

Account				Debit	Credit
Gross sales					$1,840,000
Sales returns and allowances				$20,000
Cost of goods sold				1,520,000
Interest income from:
Banks	$10,000
Tax-exempt state bonds	5,000				15,000
Proceeds from life insurance (death of corporate officer)					6,000
Bad debt recoveries (no tax deduction claimed)					3,500
Insurance premiums on lives of corporate officers (corporation is beneficiary of policies)				9,500
Compensation of officers				40,000
Salaries and wages				28,000
Repairs				800
Taxes				10,000
Contributions:
Deductible	$23,000
Other	500			23,500
Interest paid (loan to purchase tax-exempt bonds)				850
Depreciation				5,200
Loss on securities				3,600
Net income per books after federal income tax				140,825
Federal income tax accrued for 2016				62,225
Total				$1,864,500	$1,864,500

The corporation analyzed the retained earnings and the following items appeared in this account on its books.
Item		Debit			Credit
Balance, January 1					$225,000
Net profit (before federal income tax)					203,050
Reserve for contingencies		$10,000
Income tax accrued for the year		62,225
Dividends paid during the year		140,089
Refund of 1995 income tax					18,000
Balance, December 31		233,736
Total		$446,050			$446,050
The following items appear on page 1 of Form 1120.
Gross sales ($1,840,000 less returns and allowances of $20,000)					$1,820,000
Cost of goods sold					1,520,000
Gross profit from sales					$300,000
Interest income					10,000
Total income					$310,000
Deductions:
Compensation of officers			$40,000
Salaries and wages			28,000
Repairs			800
Taxes			10,000
Contributions (maximum allowable)			22,500
Depreciation			6,200
Total deductions					107,500
Taxable income					$202,500

Please prepare Schedule M-1 for Rocky Mountain Equipment Corporation using the financial information and the Form 1120 line items provided above.

Please prepare Schedule M-2 for Rocky Mountain Equipment Corporation using the retained earning information provided. To accurately calculate and support the ending balance, please complete a Retained Earnings Reconciliation Table.

Background: The Clearfield Cheese Company was established by two brothers, Terry and Ted Edwards, in 1931, in Clearfield, Pennsylvania. This section of Central Pennsylvania's economy was based largely upon coal and agriculture at this point in time. The U.S. economy was in the throes of what is usually referred to as the Great Depression, and coal production and agriculture were both experiencing the effects of the slumping economy. The farms in the area were mostly small- to medium-size dairy operations. The farmers were under financial duress because they could not sell their milk in the local area for a price to cover their cost of production. There were better market opportunities in Pittsburgh and Harrisburg, Pennsylvania, but their transportation costs put their "landed cost" at a disadvantage with dairy farmers in Erie, Pennsylvania, and Eastern Ohio. The Edwards brothers were not farmers but rather entrepreneurs and owned several tanker trucks, which could be used for hauling milk. They decided that instead of using their equipment to haul milk to potential markets for very meager profits they would start a cheese processing operation in Clearfield. They had some savings and were able to borrow money from The First National Bank of Clearfield, which was still solvent. Their grandfather who had emigrated from Switzerland was knowledgeable about cheese production and processing and helped them get started. They purchased milk from local farmers with lenient payment terms and started a successful venture. World War II presented some challenges in terms of labor supply and fuel rationing, but they survived and prospered by hiring more women and utilizing more rail service. The next major hurdle was the government-subsidized cheese producers in Canada selling into the Pennsylvania market in the 1980s. Tom Powers, CEO of the Clearfield Cheese Company, with the assistance of two of his key executives, Andy Reisinger (CIO) and Sandy Knight (CSCO), developed a plan, which included improving their supply chain operation efficiency by lowering inventory levels with better forecasting and procurement practices. They expanded their product offerings by adding cottage cheese, sour cream, and yogurt. They also purchased a Canadian company in 1995 because their Canadian sales were growing. This lowered their costs to serve the growing Canadian market and made them much more competitive in Canada. This was an important step to make them a global company.

Current Situation Their board of directors in 2017 was delighted with their cash flow and profits. However, they were concerned about future growth because of the changing diets of many consumers who had become more concerned about consuming milk-based products. The company had already added low-fat versions of the major products, but the board members were concerned that this would not be sufficient to sustain their growth and profits. Some possibilities that were suggested for consideration included (1) setting up a new company to produce non-dairy-based products such as almond milk and other alternatives to cow milk. All the new products would have a healthy "spin" such as the White Wave company; (2) market expansion of their existing product lines into Mexico and Central America; (3) expanding their current product offerings by adding ice cream, high-end cheeses made from goat and sheep milk, and high-end milk-based candy; and (4) a combination of one or more of these alternatives.

Note: Read the case study and answer the following question. The answer should be a minimum of 20 lines. No Plagiarism.

1. Evaluate all three alternatives offering pros and cons of each.

2. What would you recommend? Why?

WG is one of the world’s leading makers of mobile phones, with market share of approximately 20%.Unlike any of its major competitors, it is based in Narnia, a high-cost, developed country. Narnia has very limited natural resources, but has developed significant expertise over the decades in high-end precision engineering and efficient use of materials. WG is quoted on the Narnian stock exchange, where it is the largest company by market capitalisation. It has a wide shareholder base including most Narnian institutional investors and private individuals. Its largest three shareholders are institutions who each own around 2% of the company.WG was founded in the 1960s to make telephone equipment and in the 1990s managers made a strategic decision to focus on the then-tiny mobile phone market. This was partly attributable to the Narnian government being among the first to fully deregulate their telecoms market, which lead to lower call costs. Narnia and its neighbouring countries are also fairly rural, and its populations were enthusiastic early adopters of mobile phones. WG was given a particular boost in 1995 when the transmission standard they had pioneered was adopted as the basis for calls by the government in Narnia and many other governments around the world. Serving a rapidly growing market, WG quickly gained economies of scale that allowed cheaper production than competitors emerging later. WG then exploited these to open up export markets all over the world,enhancing their advantage further. Unlike many of its competitors, who subcontract their manufacturing to others, WG assembles most of its own handsets. Its factories are mostly in Narnia, where it benefits from the highly educated population and the presence of high-quality local suppliers to carry out increasingly high-tech manufacturing processes. Narnia has very good communication links, which helps suppliers to deliver rapidly. Technology is advancing all the time and WG regularly launches new, more sophisticated devices, most recently a suite of smartphones. However, the fastest-growing demand is for cheaper, basic models which just carry out voice calls and text messaging. This demand is driven by users in developing countries, who are concerned to keep costs down, but also want the status of using a well-known brand such as WG. WG has invested significant resources in building up a local sales presence in these markets, which allows it to spot trends and produce phones tailored to local tastes and languages. Competition in the industry is intense, and has become more so due to a recent global economic downturn. The Narnian government has also announced new anti-pollution measures that will result in large-scale manufacturers having to pay more than previously to dispose of their waste products. Shortly afterwards, WG announced that they will increase the proportion of handsets manufactured in lower-cost countries from 15% to 40% over the next three years. Component manufacturers announced plans to follow them to the new locations. This will involve cutting over 1,000 jobs in Narnia. A spokesman for the Narnian government called the decision “disappointing”. A trade union official said, “WG has increasingly been putting pressure on its suppliers to lower costs and respond more quickly to market fluctuations. This has made it unprofitable for them to operate in Narnia and lead to decisions like this”. Required:

(a) Analyse WG’s environment using two appropriate models

(b) Discuss the main stakeholders in WG and how management could try to retain their support as it seeks to reduce costs.