Case 2 - Motomart

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Case 2: Motomart

INTRODUCTION

The Motomart case is designed to supplement your managerial/ cost accounting textbook coverage of cost behavior and variable costing using real-world cost data and an auto-industry- accepted cost driver. Unlike textbook problems, this data is real. It won’t necessarily produce a clear solution when you attempt to analyze cost behavior and apply scatter-plot, high-low, and regression methods to separate mixed costs into their fixed and variable components. This case also illustrates that financial accounting decisions and methods can have an influence on cost accounting and managerial applications and decisions.

OBJECTIVES

When you complete this case, you’ll be able to

• Explain the importance of accrual accounting and proper application of the matching principle for the computation of contribution margins and break-even points

• Apply knowledge of generally accepted accounting principles (GAAP) to a specific real-world example

• Integrate statistical analyses and scatter plots, line graphs, and regression to determine the reliability of financial information prepared for external use

• Use analytical review procedures to examine a firm’s financial statements

• Apply critical-thinking skills to real-world business circumstances

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CASE BACKGROUND

This case is based on real financial data provided by a retail automobile dealership (Motomart) seeking to relocate closer to an existing retail dealership. You’ll examine the mixed cost data from Motomart and apply both high-low and regression to attempt to separate mixed costs into their fixed and variable components for break-even and contribution margin compu- tations. You’ll find that the data is flawed because Motomart was a single observation in a larger database. Don’t attempt to correct the data (e.g., remove outliers or influential outliers). You’ll be producing a scatterplot and apply high-low and regression methods to the extent practicable and writing a summary report of the findings.

Motomart operates a retail automobile dealership. The manufacturer of Motomart products, like all automobile manufacturers, produces forecasts. It has long been an industry practice to use variable costing-based/break-even analyses as the foundation for these forecasts, to examine their cost behavior as it relates to the new retail vehicles sold (NRVS) cost driver. In preparing this financial information, a common financial statement format and accounting proce- dures manual is provided to each retail auto dealership. The dealership is required to produce monthly financial statements using the guidelines provided by this common accounting procedures manual, and then furnish these financial statements to the manufacturer. General Motors, Ford, Nissan, and all other automobile manufacturers employ similar procedures manuals.

The use of a common format facilitates the development of composite financial statements that can be used to estimate costs and produce financial forecasts for future or proposed retail dealership sites (Cataldo and Kruck 1998). Zimmerman (2003) suggests that as many as 77 percent of manufacturers divide costs into variable and fixed components, and that managers arrive at these estimates by classifying individual accounts as being primarily fixed or primarily variable (67).

For this case, you’ll examine mixed costs as defined by the manufacturer. Using the scatterplot, high-low, and regression methods, separate these mixed costs into their fixed and

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variable components. The data is problematic, and a clear solution won’t exist. Don’t attempt to correct the data by removing outliers, but make observations based on any pat- terns you observe. The case will expose you to actual data and require you to summarize your findings, including any conclusions you’re able to reach and why the financial data makes it impossible to separate the mixed costs into their fixed and variable components.

Motomart: A Litigation Support Engagement

The Motomart case evolved from a litigation support engage- ment. The lead author of this case was hired to analyze the data and provide expert testimony. His report and testimony was made available to the public (for a fee to cover reproduc- tion costs). A broad description of the relevant points for the Motomart case follows.

Motomart wanted to move their retail automobile dealership, blaming their location for declining profits and increasing losses. They provided financial projections, using variable costing, to show that after relocation both Motomart and the existing dealership would be profitable. They created these financial projections using a database provided by the manu- facturer, which included all North American retail automobile dealerships. Motomart was one of the observations or retail automobile dealerships included in the database used to create these financial projections. You’ll be examining portions of Motomart’s historical financial data.

The relocation site was quite close to the existing dealership (which we’ll refer to as Existing Dealer), and Existing Dealer felt that, if the relocation was permitted, one or both of the dealerships would fail to break even and eventually go bank- rupt, leading to poor service, or what the industry refers to as “orphaned” owners of these automobiles.

Antitrust laws provided Existing Dealer with the means to block the relocation requested by Motomart, but only if it could prove that the relocation wasn’t in the best interest of the consuming public. Generally, the only way to prove this

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is to prove that there’s simply not enough business for both retail automobile dealerships to break even (or generate a reasonable return on investment, given the risks associated with the industry). Again, the manufacturer, in support of the proposed Motomart relocation, supplied financial projections showing that both retail automobile dealerships would be profitable after the relocation.

The expert witness hired to investigate the merits of the relocation was given the Motomart data, but not the entire database that included the Motomart data. The Motomart data was in such poor form that it wasn’t possible to produce a financial forecast. An alternative forecast, not included in this case, was produced. This alternative forecast did not support the relocation of Motomart to a site closer to Existing Dealer. The alternative forecast showed that the market simply couldn’t support two retail automobile dealerships. The impli- cation was that, as the weaker of the two dealerships, Motomart was losing business to Existing Dealer. In conclusion, the relocation request by Motomart was denied.

Income and Expense Data

The following tables give you information such as income statements, semi-fixed expenses, and salaries for Motomart. Look for unusual entries or discrepancies in their records and, where you can, note the cause of the problems.

Table 3 summarizes financial and cost driver information produced by Motomart, where new retail vehicles sold (NRVS) is the cost driver. The account classification method has resulted in three cost behavior classifications: variable, semi-fixed, and fixed costs. Semi-fixed is the automobile industry-specific term used for mixed costs. We’ll assume that Motomart’s classifications of variable costs (VCs) and fixed costs (FCs) are correct, and focus our analysis on Motomart’s semi-fixed or mixed costs.

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Table 4 provides five years of monthly data (N=60) for NRVS and the related semi-fixed or mixed cost measures. Semi- fixed costs were significant. Recall that they ranged from nearly $1.2 million for calendar and fiscal year (FY) 1984 to almost $2.2 million for FY 1988 (see Table 3).

Recall the cost function applying to the high-low and regression methods, which are provided in a variety of forms, depending on the texts you used in your previous math, economics, or accounting courses. Figure 3 is a brief outline of the high-low and regression methods.

Table 3

SELECTED HISTORICAL INCOME STATEMENT AND RELATED MEASURES

1984 1985 1986 1987 1988

Net Variable Revenues* 2,885,969 3,828,255 4,086,667 3,940,799 4,298,748

Semi-Fixed (S-F) Expenses:

Salaries 613,006 968,789 1,211,464 1,289,758 1,360,489

Vacation 600 26,705 19,468 19,059 18,268

Advertising & Training 210,226 288,347 281,219 309,608 371,314

Supplies/Tools/Laundry 31,473 46,141 75,468 65,935 81,252

Freight 5,719 5,987 6,528 5,731 4,663

Vehicle 22,913 23,718 23,664 20,370 19,483

Demonstrators 10,465 4,969 –1,513 4,192 707

Floor-Planning 278,531 301,113 276,201 156,129 305,044

Total S-F Expenses 1,172,933 1,665,769 1,892,499 1,870,782 2,161,220

Fixed Expenses:

Total Fixed Expenses 1,449,208 2,050,172 2,290,867 2,164,362 2,653,620

Operating Profit/(Loss)** 263,828 112,314 -96,699 -94,345 -516,092

New Retail Vehicles Sold 1,798 1,977 1,674 1,450 1,897

Notes:

* Revenues less variable costs equal Net Variable Revenues (or Contribution Margin, in aggregate).

** Net Variable Revenue less Total S-F Expenses less Total Fixed Expenses equals Operating Profit/(Loss).

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Mo NRVS Salary Vacation Adv/Trng SplyTls/Lndry Freight Vehicles Demo's Floor-Plan Total 1 197 $ 52,951 $ - $ 22,561 $ 1,118 $ 382 $ 2,052 $ 1,881 $ (78,173) $ 2,772 2 133 $ 47,054 $ - $ 19,040 $ 3,573 $ 409 $ 1,405 $ 695 $ 28,456 $100,632 3 132 $ 55,372 $ - $ 14,373 $ 1,388 $ 742 $ 1,380 $ 469 $ 34,423 $108,147 4 141 $ 46,114 $ - $ 15,022 $ 2,894 $ 675 $ 2,057 $ 125 $ 5,697 $ 72,584 5 182 $ 48,309 $ - $ 19,966 $ 1,896 $ 572 $ 1,603 $ 131 $ 34,599 $107,076 6 156 $ 49,643 $ - $ 12,019 $ 1,188 $ 407 $ 2,524 $ 1,229 $ 53,737 $120,747 7 196 $ 55,784 $ 300 $ 13,217 $ 3,912 $ 643 $ 2,348 $ 1,206 $ 5,507 $ 82,917 8 178 $ 47,957 $ - $ 17,303 $ 2,012 $ 605 $ 1,208 $ 436 $ 32,436 $101,957 9 159 $ 53,743 $ - $ 16,535 $ 2,717 $ 209 $ 2,400 $ 1,476 $ 28,950 $106,030

10 141 $ 53,109 $ - $ 23,821 $ 1,102 $ 184 $ 2,076 $ 1,168 $ 20,876 $102,336 11 152 $ 45,491 $ 300 $ 14,146 $ 2,630 $ 331 $ 1,677 $ 635 $ 45,278 $110,488 12 31 $ 57,479 $ - $ 22,223 $ 7,043 $ 560 $ 2,183 $ 1,014 $ 66,745 $157,247 13 280 $ 49,049 $ - $ 19,992 $ 1,999 $ 582 $ 1,927 $ (477) $ (30,104) $ 42,968 14 136 $ 46,698 $ 300 $ 20,251 $ 1,192 $ 603 $ 1,156 $ 1,839 $ 50,583 $122,622 15 174 $ 59,790 $ 200 $ 20,082 $ 1,336 $ 492 $ 1,898 $ 1,260 $ 18,803 $103,861 16 171 $ 80,773 $ 600 $ 26,716 $ 3,873 $ 559 $ 1,808 $ 510 $ 23,080 $137,919 17 167 $ 71,130 $ 9,212 $ 25,223 $ 5,560 $ 356 $ 1,816 $ 2,350 $ 18,774 $134,421 18 161 $ 82,490 $ 6,007 $ 21,106 $ 1,737 $ 439 $ 1,384 $ (288) $ 23,802 $136,677 19 173 $ 98,172 $ 500 $ 17,799 $ 1,847 $1,628 $ 1,962 $ 1,591 $ 33,848 $157,347 20 161 $ 90,685 $ 2,690 $ 28,038 $ 4,415 $ (12) $ 2,446 $ (3,308) $ 13,480 $138,434 21 167 $ 97,771 $ 600 $ 37,284 $ 2,827 $ 480 $ 2,296 $ 1,709 $ 22,965 $165,932 22 153 $ 87,129 $ 1,740 $ 24,236 $ 5,836 $ 79 $ 3,175 $ 798 $ 18,898 $141,891 23 201 $ 95,910 $ 2,074 $ 27,244 $ 3,387 $ 188 $ 1,287 $ (2,025) $ 38,699 $166,764 24 33 $109,192 $ 2,782 $ 20,376 $ 12,132 $ 593 $ 2,563 $ 1,010 $ 68,285 $216,933 25 227 $ 89,041 $ 1,880 $ 26,719 $ 4,383 $ 769 $ 2,205 $ 2,493 $ (44,140) $ 83,350 26 150 $ 92,165 $ 3,602 $ 14,727 $ 10,231 $ 593 $ 2,289 $ (2,051) $ 36,311 $157,867 27 142 $ 88,981 $ 744 $ 27,880 $ 7,734 $ 414 $ 1,891 $ 386 $ 19,865 $147,895 28 104 $ 95,898 $ 960 $ 21,872 $ (684) $ 425 $ 2,288 $ 178 $ 19,013 $139,950 29 121 $ 96,245 $ - $ 18,705 $ 8,329 $ 483 $ 2,223 $ (262) $ 16,228 $141,951 30 99 $106,364 $ - $ 23,835 $ 2,540 $ 417 $ 1,683 $ (1,356) $ 37,637 $171,120 31 150 $ 90,564 $ 1,950 $ 25,605 $ 5,862 $ 222 $ 1,586 $ 486 $ (1,121) $125,154 32 144 $ 98,418 $ 1,540 $ 17,763 $ 6,998 $ 49 $ 1,751 $ (1,924) $ 34,757 $159,352 33 154 $110,436 $ 2,693 $ 32,379 $ 8,131 $ 818 $ 2,082 $ 1,547 $ 26,419 $184,505 34 130 $102,042 $ 1,060 $ 19,324 $ 6,026 $1,015 $ 1,714 $ 132 $ 21,134 $152,447 35 202 $124,413 $ 3,519 $ 22,412 $ 9,120 $1,255 $ 2,173 $ (2,337) $ 18,578 $179,133 36 51 $116,897 $ 1,520 $ 29,998 $ 6,798 $ 68 $ 1,779 $ 1,195 $ 91,520 $249,775 37 148 $ 97,083 $ 1,080 $ 9,112 $ 6,627 $ 565 $ 1,324 $ 1,164 $ (73,753) $ 43,202 38 153 $104,727 $ 3,230 $ 38,616 $ 5,892 $ 369 $ 1,523 $ (1,839) $ 30,443 $182,961 39 83 $ 95,622 $ 953 $ 22,690 $ 3,450 $ (182) $ 2,087 $ 454 $ 17,725 $142,799 40 101 $ 96,438 $ 1,244 $ 14,703 $ 5,259 $ 709 $ 2,095 $ 868 $ 26,402 $147,718 41 140 $114,995 $ - $ 28,764 $ 2,294 $1,006 $ 1,304 $ (1,990) $ (3,789) $142,584 42 132 $105,337 $ 160 $ 27,253 $ 8,155 $ 521 $ 1,667 $ 1,869 $ 15,090 $160,052 43 112 $ 98,989 $ 2,480 $ 24,419 $ 1,621 $ 514 $ 1,040 $ 329 $ (945) $128,447 44 127 $124,352 $ 1,800 $ 26,011 $ 902 $ 917 $ 2,880 $ (1,897) $ 30,405 $185,370 45 139 $115,875 $ 1,417 $ 24,492 $ 5,158 $ (77) $ 1,281 $ 2,959 $ 14,781 $165,886 46 156 $113,035 $ 1,820 $ 31,158 $ 2,901 $ 450 $ 2,259 $ 417 $ 15,613 $167,653 47 126 $119,106 $ 3,338 $ 32,213 $ 14,426 $ 120 $ 1,394 $ (2,659) $ 40,968 $208,906 48 33 $104,199 $ 1,537 $ 30,177 $ 9,250 $ 819 $ 1,516 $ 4,517 $ 43,189 $195,204 49 209 $ 98,938 $ 1,866 $ 26,737 $ 1,694 $ 853 $ 1,657 $ 601 $ (20,127) $112,219 50 124 $108,606 $ 3,676 $ 31,084 $ 9,040 $ 498 $ 2,266 $ (284) $ 18,236 $173,122 51 131 $106,396 $ 1,197 $ 33,278 $ 2,099 $ 605 $ 1,952 $ 668 $ 15,176 $161,371 52 144 $106,778 $ 241 $ 32,657 $ 9,328 $ 483 $ 1,852 $ 1,409 $ 25,245 $177,993 53 93 $124,805 $ 500 $ 29,794 $ 4,268 $ 788 $ 1,704 $ (1,771) $ 6,493 $166,581 54 199 $110,153 $ 1,910 $ 38,431 $ 5,407 $ 529 $ 1,882 $ 453 $ 21,851 $180,616 55 170 $117,276 $ 800 $ 27,640 $ 9,305 $ (180) $ 977 $ 1,310 $ 7 $157,135 56 186 $112,055 $ 980 $ 28,657 $ 1,803 $ (242) $ 846 $ (2,844) $ 17,192 $158,447 57 200 $114,765 $ 1,695 $ 36,425 $ 8,839 $ 859 $ 2,856 $ 1,532 $ 14,864 $181,835 58 146 $128,007 $ 1,560 $ 27,720 $ 10,944 $ (492) $ 1,864 $ 1,400 $ 10,121 $181,124 59 222 $116,811 $ 2,249 $ 27,941 $ 5,775 $ 245 $ 1,141 $ (3,513) $ 7,946 $158,595 60 73 $115,899 $ 1,594 $ 30,950 $ 12,750 $ 717 $ 486 $ 1,746 $ 188,040 $352,182

Table 4

SEMI-FIXED (MIXED) EXPENSES FOR THE 60-MONTH PERIOD (FY 1984 THROUGH 1988)

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Preparing Graphs

The single cost driver and nonfinancial measure in Table 4 is new retail vehicles sold (NRVS or X in the above cost function). There are eight financial measures (salary; vacation; advertising and training; supplies, tools, and laundry; freight; vehicles; demonstrators; and floor-planning [also known in the auto- mobile retail industry as interest expense relating to new car inventory]), as well as a total (aggregate measure) provided for all eight financial measures (or the Y in the above cost function).

FIGURE 3—For the high-low method to work, the $H and #H and the $L and #L measures must be from the same accounting period.

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Using NRVS, the only available cost-driver, use Excel to prepare nine separate scatter plots and cost function-based trend lines and nine separate line graphs for each of the financial measures provided in Table 4. See Figure 4 and Figure 5 for a examples of completed graphs for salaries.

Now examine, on a preliminary basis, the pattern or trend (or lack thereof) for each of the “X” (NRVS) and “Y” (financial measure) data pairs and consider the following questions:

• You’re observing these data pairs for a 60-month period (i.e., five years); are any annual or other seasonal patterns or trends immediately apparent?

• Do the slopes of the trend lines (i.e., variable costs) make sense?

FIGURE 4—A Scatterplot Graph for Motomart Salaries

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In the case of salaries (see Figures 4 and 5), there’s no appar- ent trend or pattern. It’s odd that salaries decrease as NRVS increases—in fact, this doesn’t make any sense. However, it’s consistent with the high-low results, which also didn’t make sense. But remember, since this data came from Motomart, the firm attempting to relocate, it’s real and from an actual litigation support engagement (not a textbook problem), so it won’t necessarily work out perfectly.

The cost equation in Table 5 shows fixed costs (FC) at $106,866.00 and variable costs to be used to “reduce” total costs (TC) by $110.10 per NRVS. Compare the salary figures and coefficients (in bold type) to Figure 4. Notice that if you extended the trend line in Figure 4, it would hit the y-axis intercept at $106,866.00 (the fixed cost). Also notice that the R-squared (R-sq) measure in Table 5 equals 4.1 percent.

FIGURE 5—A Line Graph for Motomart Salaries

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Your math and statistics courses probably reviewed the use of the t-statistic, overall F-statistic, and related p-values, as well as some of the other measures presented here. Our application is a very simple one, so we’ll focus on only the R-squared measure. The other measures are provided in this example only for completeness.

Because the high-low technique didn’t work, it makes sense that the regression technique wouldn’t work well, either. Therefore, the results for high-low and regression are consis- tent. The advantage of the regression technique is that it mathematically quantifies the level of the problem or diffi- culty with the data. In this case, one of simple regression, the R-squared measure tells the story. Still focusing on the salaries example in Figure 5, the R-squared measure tells us that only 4.1 percent of the total or mixed or semi-fixed cost is explained by NRVS. This means that that cost equation developed from this historical data isn’t helpful in predicting future costs, as nearly 96 percent of the cost behavior, through use of this equation, remains unexplained.

Table 5

SALARY = $106,866.00 – $110.10 NRVS

Predictor Coefficient Std Deviation t-statistic p-value

Constant 106,866.00 10,793.00 9.90 0.000

NRVS 110.10 70.17 –1.57 0.122

s = 25300 R-sq = 4.1%

Analysis of Variance

SOURCE DF SS MS F-statistic p-value

Regression 1 261,795 261,795 0.10 0.754

Error 58 152,801,120 2,634,502

Total 59 153,062,912

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REQUIREMENTS

Operating Profits and Semi-Fixed Expenses

Step 1

First, using Tables 3–5, note the pattern of operating profits (or losses) over the five-year period. Then focus only on the semi-fixed expenses contained in Table 3. Do any amounts appear to be odd? Next, briefly comment on the five-year pattern or trend for operating profit/loss measures. You should be able to respond to this step in a few well- written sentences.

Step 2

Focus only on the detailed semi-fixed expense contained in Table 4. Are there any unusual or odd patterns you might note in this detailed financial data? There are eight expense items. About five of the eight should immediately catch your attention. You should be able to respond to this requirement in a few well-written sentences. Briefly comment on only the most obvious or apparent measures or patterns, by expense item.

Step 3

Identify the high and low measures in each column, just as you would in preparation for application of the high-low method or technique. For example, in Table 4 the high measure for the cost driver (NRVS) is 280 NRVS in month 13 and the low measure is 31 NRVS in month 12. Repeat this process for each of the eight separate semi-fixed expense columns and also for the total expense column. (You could transfer the figures to Excel to use the maximum and minimum functions to assist you in identifying the high and low measures [N=60] for each of the ten columns.)

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After the high and low measures have been identified in each column, try to match each expense column’s high and low measure, separately, to the highs and lows identified in the NRVS column. They won’t match. Don’t try to correct the data, but comment on the potential for application of the high-low technique. What happens when the high and low activity level doesn’t match the high and low expense measure? Does this prevent you from correctly applying the high-low technique?

Don’t overanalyze this data, because there’s a problem with it and you don’t have sufficient information to correct it. Merely summarize your observations and unsuccessful attempts to match the high and low NRVS months (identified above), separately, with each of the high and low expense measure months. You should be able to do this in a very few well- written sentences.

Finally, summarize your findings with respect to the applica- tion of the high-low method to separate mixed costs into their fixed and variable components or the development of a cost equation.

Step 4

Use Table 6 to compute the cost equations and R-squared measures for each of the remaining eight expenses and total expenses. Notice that there’s a computed total requirement in the table. This just means that you must total these two columns and compare the computed totals to the Excel- generated measures in the row below. In effect, you’re being asked to comment on whether the separate cost formulas are “additive.”

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Complete the cost equations for the table. Use the R-squared as the single measure of “goodness of fit.” Don’t attempt to improve your results with the elimination of “outliers” or “influential outliers.” As you complete Table 6, answer the following questions:

1. What problems did you encounter?

2. Are the R-squared measures high or low?

3. Are the slopes negative or positive?

4. Are your conclusions consistent with those from the high-low effort?

Step 5

Summarize your findings on a single page (250 words or less, double-spaced). Can the Motomart data be used to prepare a reliable financial forecast? Why or why not? If Motomart is included in the very large database used to prepare the financial forecast that supports the relocation of Motomart closer to Existing Dealer, what concerns might present them- selves with respect to the remainder of the database used for this forecast? Would you rely on this forecast?

Table 6

Column Expense FC VC R-sq

1 Salaries $106,866 –$110 4.10%

2 Vacation

3 Advertising and training

4 Supplies/tools/laundry

5 Freight

6 Vehicles

7 Demonstrators

8 Floor planning

Computed total

9 Total

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It’s common for businesses to keep poor financial records most of the year, because many are trying to reduce the cost of financial record keeping (e.g., the salary of a CPA is higher than that of a bookkeeper). Then, at the year’s end, these businesses employ a CPA or accounting firm to make adjust- ing journal entries to correct data for the twelfth months of the year, only to reverse the adjusting journal entries immediately after the annual financials are prepared.

Examine your graphics to identify any seasonal (12-month) patterns. Do any exist? Is there evidence to suggest that the process described above was being employed by Motomart?

Writing Guidelines Refer to the “Submitting Your Work” section at the end of this book for details on submission requirements for the Motomart Case assignment.

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SUBMITTING YOUR WORK

Writing Guidelines 1. Type your submission, double-spaced, in a standard

print font, size 12. Use a standard document format with 1-inch margins. (Do not use any fancy or cursive fonts.)

2. Include the following information at the top of your paper:

a. Name and complete mailing address

b. Student number

c. Course title and number (Senior Capstone: Business, BUS 450)

d. Project number (see Format instructions)

e. Project title (Professional Development Activity, Case 1, etc.)

3. Read the assignments carefully and complete each one in the order given.

4. Be specific. Limit your submission to the questions asked and issues mentioned.

5. If you include quotes or ideas from textbooks or other sources, provide a reference page in either APA or MLA style. On this page, list books, Web sites, journals, or any other references used in preparing the paper.

6. Proofread your work carefully. Check for correct spelling, grammar, punctuation, and capitalization.

Grading Criteria Your assignments will be evaluated according to the following criteria:

Content 80 percent

Written communication 10 percent

Format 10 percent

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Here’s a brief explanation of each of these points.

Content

The student

• Fulfills each assignment completely, answering all questions and fully addressing the topics and issues presented

• Writes answers in complete sentences and well-developed paragraphs

• Supports his or her judgment by citing specific informa- tion from coursework, textbooks, or other appropriate references, using correct APA or MLA guidelines for citations and references

• Stays focused on the assigned issues

• Writes in his or her own words and uses quotation marks to indicate direct quotations

Written Communication

The student

• Addresses each section in complete paragraphs that include an introduction, a complete answer or explanation for each issue, and a conclusion.

• Uses correct grammar, spelling, punctuation, and sentence structure

• Provides clear organization (for example, uses words like first, however, on the other hand, and so on, consequently, since, next, and when)

• Makes sure the paper contains no typographical errors

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Format

The paper is double-spaced and typed in font size 12. It includes the student’s

• Name and complete mailing address

• Student number

• Course title and number (Senior Capstone: Business, BUS 450

• Correct research project number for each submission:

Professional Development Seminar 50089400 Case 1: Purchase Point Media Corporation 50089500 Case 2: Motomart 50089600

SUBMITTING YOUR ASSIGNMENT

You can submit your research assignment online, following this procedure:

1. On your computer, save a revised and corrected version of your project.

2. Go to http://www.takeexamsonline.com and log in.

3. Go to My Courses.

4. Click on Take Exam next to the lesson you’re working on.

5. Enter your e-mail address in the box provided. (Note: This information is required for online submission.)

6. Attach your file or files as follows:

a. Click on the Browse box.

b. Locate the file you wish to attach.

c. Double-click on the file.

d. Click on Upload File.

e. If you have more than one file to attach, repeat steps a–d.

7. Click on Submit Files.