Answer: facility location
Explanation:
Based on the information given, it can be infered that Reliable Industries is in the process of facility location.
Facility Location simply refers to the selection of the rightt location for the manufacturing facility. The location selected should be easily accessible for the customers and transportation.
Selecting a suitable facility location is essential for an effective operation.
Answer:
a) $337,615.38
b-1) $360,910.85
b-2) $415,266.92
c-1) $362,637.36
c-2) $438,461.54
Explanation:
a) To find the current value of the company, we have:
=
= $337,615.38
b-1) If the company takes on debt equal to 30 percent of its unlevered value.
337,615.38 + (0.23 * 337,615.38 * 0.30)
= $360,910.85
b-2) When the company can borrow at 10 percent. The value of the firm if the company takes on debt equal to 100 percent of its unlevered value will be:
337,615.38 + (0.23 * 337,615.38 * 1)
= $415,266.92
c-1) The value of the firm if the company takes on debt equal to 30 percent of its levered value:
= $362,637.36
c-2) The value of the firm if the company takes on debt equal to 100 percent of its levered value:
= $438,461.54
Answer:
800,000/600,000=1.33
Profit percentage = 1.33-1=0.33=33%
0.02*800,000=16,000 worth of goods returned
Profit= 0.33*16,000=5280
COGS= 16,000-5280=10,720
Adjusting Entry
Debit Credit
Goods returned 10,720
Profit 5,280
Cash 16,000
Explanation:
Answer:
coefficient = 0
Explanation:
We have the formula to calculate the price elasticity of demand as following:
<em>Elasticity coefficient = % Change in quantity/ % Change in price</em>
As given:
+) The percentage change in price is: (120-150)/150= - 20%
+) The quantity bought remains unchanged - which means the percentage change in quantity demanded is 0%
=> <em>Elasticity coefficient = % Change in quantity/ % Change in price</em>
<em>= 0/-20 = 0</em>
<em />
<em>So the coefficient of price elasticity of demand in this example would be 0</em>
Answer:
Budgeting, forecasting and planning
Explanation:
Service industries uses budgeting, which includes expected sales and operational cost, to forecast, plan and predict revenue. With regards to forecasting; historical or past company data are used to make sound prediction.