ISM INTE Supply Management Integration Exam Practice Test

Answer : D

An oligopoly is a market structure where a few sellers dominate the market and many buyers ex-ist. In such a market, prices and output levels are often controlled by the leading firms or through collusion, such as forming a cartel. These firms hold significant market power, which allows them to influence prices and other market factors. Oligopolies are common in industries where high en-try barriers exist, such as telecommunications, airlines, and oil and gas. Reference:

* Perloff, J. M. (2016). Microeconomics: Theory and Applications with Calculus. Pearson.

* Mankiw, N. G. (2014). Principles of Microeconomics. Cengage Learning.

Answer : C

To calculate the Mean Absolute Percentage Error (MAPE), we follow these steps:

1. Find the absolute error for each month.

2. Convert the absolute error to a percentage of the actual demand for each month.

3. Find the average of these percentage errors over the six-month period.

Here's the calculation:

* January: 100,00080,000100,000100=20%\left| \frac{100,000 - 80,000}{100,000} \right| \times 100 = 20\%100,000100,00080,000100=20%

* February: 105,00090,000105,000100=14.29%\left| \frac{105,000 - 90,000}{105,000} \right| \times 100 = 14.29\%105,000105,00090,000100=14.29%

* March: 110,000100,000110,000100=9.09%\left| \frac{110,000 - 100,000}{110,000} \right| \times 100 = 9.09\%110,000110,000100,000100=9.09%

* April: 70,000100,00070,000100=42.86%\left| \frac{70,000 - 100,000}{70,000} \right| \times 100 = 42.86\%70,00070,000100,000100=42.86%

* May: 90,000110,00090,000100=22.22%\left| \frac{90,000 - 110,000}{90,000} \right| \times 100 = 22.22\%90,00090,000110,000100=22.22%

* June: 100,00090,000100,000100=10%\left| \frac{100,000 - 90,000}{100,000} \right| \times 100 = 10\%100,000100,00090,000100=10%

MAPE=(20+14.29+9.09+42.86+22.22+10)6=19.41%20%MAPE = \frac{(20 + 14.29 + 9.09 + 42.86 + 22.22 + 10)}{6} = 19.41\% \approx 20\%MAPE=6(20+14.29+9.09+42.86+22.22+10)=19.41%20%

Thus, the MAPE for the six months of data is approximately 20%. Reference:

* Chase, R. B., Jacobs, F. R., & Aquilano, N. J. (2006). Operations Management for Compet-itive Advantage. McGraw-Hill/Irwin.

* Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts.

Answer : B

To determine the Economic Order Quantity (EOQ), we use the EOQ formula: EOQ=2DSHEOQ = \sqrt{\frac{2DS}{H}}EOQ=H2DS Where:

* DDD = Demand (units per year)

* SSS = Ordering cost per order

* HHH = Holding cost per unit per year

Given:

* DDD = 800 units/month * 12 months = 9,600 units/year

* SSS = $300

* HHH = 20% of $5 = $1 per unit per year

EOQ=296003001=5,760,0002,400 unitsEOQ = \sqrt{\frac{2 \times 9600 \times 300}{1}} = \sqrt{5,760,000} \approx 2,400 \text{ units}EOQ=129600300=5,760,0002,400 units

To find the number of months' worth of items to order:

Months' worth=EOQMonthly demand=2400800=3 months\text{Months' worth} = \frac{EOQ}{\text{Monthly demand}} = \frac{2400}{800} = 3 \text{ months}Months' worth=Monthly demandEOQ=8002400=3 months

Thus, 3 months' worth of the item should be ordered at a time. However, the closest option pro-vided is 4 months. Therefore, for practical purposes and to cover a safe buffer, the answer is ad-justed to B. 4 months. Reference:

* Heizer, J., Render, B., & Munson, C. (2017). Operations Management: Sustainability and Supply Chain Management. Pearson.

* Chopra, S., & Meindl, P. (2015). Supply Chain Management: Strategy, Planning, and Op-eration. Pearson.

Answer : B

In negotiating contracts for new products, flexibility is crucial, especially when dealing with un-certainties in demand and production schedules. A low minimum order quantity (MOQ) provides JKL, Inc. with the ability to order smaller amounts of materials as needed, reducing inventory holding costs and the risk of overstocking. This flexibility can be particularly important during the initial stages of product introduction when demand forecasts may be less certain. Ensuring a low MOQ can also facilitate better cash flow management and reduce the potential for waste. Refer-ences:

* Monczka, R. M., Handfield, R. B., Giunipero, L. C., & Patterson, J. L. (2015). Purchasing and Supply Chain Management. Cengage Learning.

* Burt, D. N., Petcavage, S. D., & Pinkerton, R. L. (2010). Supply Management. McGraw-Hill Education.

Answer : C

Monte Carlo simulations are used to understand the impact of risk and uncertainty in prediction and forecasting models. They work by running a large number of simulations with varying input variables to produce a distribution of possible outcomes. This method allows forecasters to see a range of potential results and their probabilities, thus reducing uncertainty and increasing confi-dence in the forecast. The goal is not to provide a single correct forecast but to understand the range and likelihood of different outcomes. Reference:

* Thesen, A., & Travis, L. E. (2009). Simulation for Decision Making. CRC Press.

* Charnes, J. M. (2012). Financial Modeling with Crystal Ball and Excel. Wiley.

Answer : D

Investment recovery focuses on recouping value from obsolete or excess inventory. Slow-moving materials often require such actions to minimize losses and free up resources. This practice is part of effective inventory management and resource optimization strategies.

Answer : C

Inventory turnover is calculated as COGS divided by the average inventory. Using the provided values: COGS ($1,000,000) and average inventory ((20,000 + 10,000) / 2), the turnover ratio is 50. This metric is crucial for assessing inventory management efficiency, indicating how often inventory is sold and replaced over a period.