Answer:
a. $5,850
Explanation:
Under the LIFO Method, the cost of good sold equals to
= January 28 units × cost per unit + Remaining units × cost per unit
= 100 units × $24 + 150 units × $23
= $2,400 + $3,450
= $5,850
Since the firm has sold 250 units, so out of which 100 units sold at a price of $24 and the remaining 150 units sold at a price of $23
The cost of the inventory at January 31, year 2, under the LIFO method is not provided in the answer choices.
The LIFO (Last In First Out) method assumes that the most recently purchased inventory is sold first. In this case, the cost of the 250 units purchased on January 18, 23, and 24 will be used to calculate the cost of the inventory at January 31st.
Let's calculate the cost of the inventory:
The total cost of the inventory at January 31st, year 2, under the LIFO method is $9,350. Therefore, the correct option is none of the above.
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Answer:
POAR= 170% of the direct material cost.
Explanation:
Explanation:
The predetermined overhead absorption rate (POAR: The overhead absorption is a rate which is used to charge overheads to production units. Note that this rate is computed using estimated figures
The rate is computed as follows:
Predetermined overhead absorption rate
POAR
= (Budgeted overhead for the period/Budgeted direct material cost)× 100
= $680,000/400,00 × 100
= 170% of the direct material cost.
Upon assessing the costs of adding new suppliers and potential losses from a super-event, Phillip Witt of Witt Input Devices should manage three suppliers. Each supplier acts as an insurance against the super-event, with the cost to manage a new supplier being less than the potential loss from a super-event.
In this scenario, the president of Witt Input Devices, Phillip Witt, should consider the cost of adding a supplier against the potential risk of having them all shut down, causing a significant loss. The disadvantage of getting a new supplier is the marginal cost, which is $14,800. On the other hand, the potential loss that the firm could suffer in the event of a super-event is $480,000.
To solve this scenario, you need to consider each supplier as a form of insurance against the super-event. By looking at the probability of the super-event, we can obtain the expected loss per year which is 3% of $480,000 (0.03 * 480000 = $14,400).
Considering all factors, it appears that it would be economically feasible for Phillip Witt to manage three suppliers because the expected potential loss is less than the expense of adding a new supplier. Therefore, his best strategy is to maintain all three suppliers to minimize the overall risk.
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To minimize costs, Witt Input Devices should consider the likelihood of a total shutdown and the cost of managing additional suppliers. By calculating the expected cost for different numbers of suppliers, we can determine the optimal number that minimizes costs. This decision depends on the specific probabilities and costs involved.
To determine the number of suppliers that Witt Input Devices should use, we need to consider the likelihood of a total shutdown due to a 'super-event' and the cost of managing additional suppliers. According to the given information, there is a 3% probability in any year of a 'super-event' shutting down all suppliers for at least 2 weeks, resulting in a cost of $480,000. The 'unique-event' risk for any individual supplier is 5%. To minimize the overall costs, we should calculate the optimal number of suppliers by comparing the cost of managing additional suppliers to the potential losses from a shutdown.
The marginal cost of managing an additional supplier is $14,800 per year. Let's assume that Witt Input Devices can choose up to three nearly identical local suppliers, and we need to find the ideal number of suppliers for minimizing costs. We can start with one supplier and calculate the expected cost. If there is a 'super-event,' the cost will be $480,000. If there is no 'super-event,' the cost will be the annual cost of managing one supplier, which is $14,800.
Next, we can calculate the expected cost for two suppliers. The probability of both suppliers being shut down due to a 'super-event' is the square of the individual risk, which is (0.03)^2 = 0.0009. The cost would then be $480,000. The probability of only one supplier being shut down is calculated as the sum of the probability of exactly one supplier being shut down multiplied by the probability of the other supplier not being shut down. This comes out to be 2 * (0.03) * (0.97) = 0.0582. In this case, the cost would be 2 * $14,800 = $29,600. Finally, the probability of both suppliers being operational is (0.97)^2 = 0.9409, resulting in a cost of 2 * $14,800 = $29,600. Therefore, the expected cost with two suppliers is 0.0009 * $480,000 + 0.0582 * $29,600 + 0.9409 * $29,600.
We can extend this calculation to find the expected cost for three suppliers. The probabilities of all three suppliers being shut down, two suppliers being shut down and one supplier being operational, and one supplier being shut down and two suppliers being operational can be calculated using the same approach. The expected cost in this case will be 0.0009 * $480,000 + 0.0582 * $29,600 + 0.0582 * $29,600 + 0.9409 * $29,600.
By comparing the expected costs for each number of suppliers, we can determine the optimal number of suppliers that minimizes costs. The answer will be the number of suppliers with the lowest expected cost. The result will depend on the specific values of the probabilities and costs involved.
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O Tooling
O Money
O Buildings
O Employees
Answer: employees
Explanation:
Answer: See explanation
Explanation:
Based on the scenario in the question, the amount that the restaurant charge for the lunch excluding any tax will be calculated as:
= $15.40 × 100/(100 + 8)
= $15.40 × 100/108
= $1540/108
= $14.26
Sales tax will be:
= $15.40 × 8%
= $15.40 × 8/100
= $15.40 × 0.08
= $1.23
Answer:
SecuriCorp
The First level Allocations will be:
Of a total cost of $2,540,000
Travel allocated costs is $915,000
Pick Up and Delivery is $451,000
Customer Service is $690,000
Others is $484,000
Explanation:
the next level of allocation will be to determine the cost rate based on the Activity Measures, however these were not provided in the question
Activity Based Costing is a costing technique that allocates costs based on the activity level of certain pre-determined cost drivers.
Instead of taking the pool of costs and dividing it by Volume to arrive at an Average Costs, Activity Based Costing believes all components leading to the cost generated should bear the burden of the cost by determining the Driver rate per activity.
If from the example we have worked above, we are told the number of miles covered is 20,000 miles and the actual Cost we worked out for Travels was $960,000. This implies we have an activity rate of $48 Per mile covered as travels costs.
The same would apply to Customer Services if for example 3,000 customers were attended to in the period, the Rate Per Customer will become $690,000 divided by 3,000 = $230 Per Customer
With these indices, it is easy to then allocate costs on the basis of miles traveled + Customers Attended to etc
To allocate costs to the activity cost pools, multiply the total costs by the resource consumption percentages provided for each activity.
In order to allocate costs to the activity cost pools, we need to use the distribution of resource consumption percentages provided. Let's calculate the cost allocation for each activity cost pool:
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Answer:
jury of executive opinion.
Explanation:
The forecasting technique that pools the opinions of a group of experts or managers is known as jury of executive opinion.
For example, when XYZ manufacturing company decides to conduct a series of strategic meetings for its forecasting by involving its key employees such as directors, analysts, managers etc to discuss (gathering opinions, ideas, perspectives and views) before reaching a forecasting consensus. This is simply a jury of executive opinion.
The forecasting technique that combines the opinions of a group of experts or managers is known as the 'jury of executive opinion'. It leverages collective expertise for prediction in complex decision-making situations or when there's a lack of sufficient hard data.
The forecasting technique that gathers and combines the views and opinions of a group of experts or managers is called the Jury of executive opinion. This technique relies on the collective knowledge, experience, and intuition of a group of high-level managers to predict future events or outcomes. It's often used in situations where decision-making is complex, or when there aren't enough hard data available. For instance, a group of corporate executives could use their combined expertise to make forecasts about trends in their industry, the potential impact of significant new legislation, or the likely behavior of their competitors.
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