Answer:
$1,050,000
Explanation:
The computation of the net income is shown below:
Net income = Sales revenue × profit margin percentage
= $17,500,000 × 6%
= $1,050,000
To determine the net income we multiplied the sales revenues by its profit margin percentage so that the correct value could be arrived.
The first law of demand states that as price increases, less quantity is demanded. This is why the demand curve slopes down to the right. Because price and quantity move in opposite directions on the demand curve, the price elasticity of demand is always negative.
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Answer:
The president of Riggs has missed something.
She should make the Sail instead of buying because its cheaper to manufacture than purchasing it outside.
Explanation:
<u>Cost of Manufacturing the Sails:</u>
Direct materials $93
Direct Labor $83
Total $173
The president of Riggs has included the $90 overhead based on $78,000 of annual fixed overhead that is allocated using normal capacity in the cost of manufacturing the sail which is incorrect.
Riggs Company is operating at 80 % of full capacity, hence utelizing the 20% excess capacity would not expand its fixed costs.
Thus said the current fixed cost are irrelevent for this decison and would be incurred whether or not Riggs Company utilizes the excess capacity
<u>Conclusion:</u>
The cost of making the sail is $173 which is lower than the cost of buying them at $ 258.
I would advise The president of Riggs to make the sail by utilizing the excess capacity since its cheaper than purchasing it outside.
Answer:
Assume the weight to be invested in Bay Corp is x. That means (1 - x) will be the weight for City Inc. The expression for the expected return will be;
(x * 11.2%) + ( (1 - x) * 14.8%) = 12.4%
0.112x + 0.148 - 0.148x = 0.124
-0.036x = -0.024
x = 0.67
Portfolio beta is;
= 0.67 * 1.2 + ( 1 - 0.67) * 1.8
= 1.398 so beta condition is satisfied.
Amount in Bay Corp.;
= 0.67 * 50,000
= $33,500
Amount in City Inc.;
= 50,000 - 33,500
= $16,500
Answer:
They should operate Mine 1 for 1 hour and Mine 2 for 3 hours to meet the contractual obligations and minimize cost.
Explanation:
The formulation of the linear programming is:
Objective function:
Restrictions:
- High-grade ore: 
- Medium-grade ore: 
- Low-grade ore: 
- No negative hours: 
We start graphing the restrictions in a M1-M2 plane.
In the figure attached, we have the feasible region, where all the restrictions are validated, and the four points of intersection of 2 restrictions.
In one of this four points lies the minimum cost.
Graphically, we can graph the cost function over this feasible region, with different cost levels. When the line cost intersects one of the four points with the lowest level of cost, this is the optimum combination.
(NOTE: it is best to start with a low guessing of the cost and going up until it reaches one point in the feasible region).
The solution is for the point (M1=1, M2=3), with a cost of C=$680.
The cost function graph is attached.
