Question: Fashion Bling operates a chain of 10
Fashion Bling operates a chain of 10 retail department stores. Each department store makes its own purchasing decisions. Barry Lee, assistant to the president of Fashion Bling, is interested in better understanding the drivers of purchasing department costs. For many years, Fashion Bling has allocated purchasing department costs to products on the basis of the dollar value of merchandise purchased. A $100 item is allocated 10 times as many overhead costs associated with the purchasing department as a $10 item.
Lee recently attended a seminar titled “Cost Drivers in the Retail Industry.†In a presentation at the seminar, Couture Fabrics, a leading competitor that has implemented activity-based costing, reported number of purchase orders and number of suppliers to be the two most important cost drivers of purchasing department costs. The dollar value of merchandise purchased in each purchase order was not found to be a significant Cost Driver. Lee interviewed several members of the purchasing department at the Fashion Bling store in Miami. They believed that Couture Fabrics’ conclusions also applied to their purchasing department.
Lee collects the following data for the most recent year for Fashion Bling’s 10 retail department stores:
Lee decides to use simple regression analysis to examine whether one or more of three variables (the last three columns in the table) are cost drivers of purchasing department costs. Summary results for these regressions are as follows:
Required:
1. Compare and evaluate the three simple regression models estimated by Lee. Graph each one. Also, use the format employed in to evaluate the information.
2. Do the regression results support the Couture Fabrics’ presentation about the purchasing department’s cost drivers? Which of these cost drivers would you recommend in designing an ABC system?
3. How might Lee gain additional evidence on drivers of purchasing department costs at each of Fashion Bling’s stores?
Transcribed Image Text:
Home Insert Page Layout Formulas Data Review View A C Purchasing Department Dollar Value of Number of Merchandise Purchased Purchase Number of Costs Orders Department Store (No. of POs) Suppliers (No. of Ss) (MP$) $ 68,307,000 1 (PDC) $1,522,000 1,095,000 Baltimore 4,345 125 3 Chicago 33,463,000 2,548 230 Los Angeles 542,000 121,800,000 119,450,000 4 1,420 8 Miami 2,053,000 5,935 188 New York 1,068,000 33,575,000 2,786 21 7 Phoenix 517,000 29,836,000 1,334 29 Seattle 1,544,000 1,761,000 102,840,000 38,725,000 8 7,581 101 9 St. Louis 3,623 127 Toronto 1,605,000 202 139,300,000 130,110,000 1,712 4,736 10 11 Vancouver 1,263,000 196 Regression 1: PDC = a + (b × MP$) Variable Coefficient Standard Error t-Value 3.00 Constant $1,041,421 $346,709 Independent variable 1: MP$ p? = 0.08; Durbin-Watson statistic = 2.41 0.0031 0.0038 0.83 Regression 2: PDC = a (b × No. of POs) t-Value 2.72 Variable Coefficient Standard Error Constant Independent variable 1: No. of POs 12 = 0.43; Durbin-Watson statistic = 1.97 $722,538 $ 159.48 $265,835 $ 64.84 2.46 Regression 3: PDC = a + (b × No. of Ss) Variable Coefficient Standard Error t-Value Constant $828,814 $ 3,816 $246,570 $ 1,698 3.36 Independent variable 1: No. of Ss 2.25 p? = 0.39; Durbin-Watson statistic = 2.01
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