ompany is planning to launch a new pr It currently has four possible new products under consideration to invest in but it must select one. It has estimated the following data: Product Expected annual demand Unit cost of production Unit selling price Fixed cost incurred before production Expected product life in years A 500 £700 £900 £150,000 2 years B 700 £900 £1300 £350,000 2.5 years C 850 £1000 £1400 £450,000 3 years D 1000 £1200 £1500 £550,000 3.25 years On the basis that the main selection criterion is the product that offers the largest safety margin between break even quantity and expected product life select the safest product to invest in.
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- A. A company wants to produce a souvenir with a marketing life of six months. Uncertainty surrounds the likely sales volume as well as the fixed costs of the venture as shown below: Sales units Probability Contrn. /unit Probability Fixed cost K7 K5 100 000 0.3 80 000 0.6 60 000 0.1 1.0 0.5 0.5 1.0 Determine the expected value of the contribution K400 000 K450 000 K500 000 Probability 0.2 0.5 0.3 1.0(b) Demand history of five different products of a company is shown below. Products 2012 2013 2014 2015 2016 2017 2018 2019 2020 A 37 40 41 45 49 26 34 30 26 23 33 28 32 C 58 55 32 38 45 56 62 70 77 86 95 83 88 81 92 85 i. Name the methods that is suitable to forecast the demand of the above five products? ii. Forecast demand of the product B or D with error for the year 2021. If you need a value of a then consider it 0.7.A company wants to produce a souvenir with a marketing life of sixmonths. Uncertainty surrounds the likely sales volume as well as thefixed costs of the venture as shown below:Sales units Probability Contrn. /unit Probability Fixed cost Probability100 000 0.3 K 7 0.5 K400 000 0.2 Page 5 of 80 000 0.6 K 5 0.5 K450 000 0.560 000 0.1 K500 000 0.31.0 1.0 1.0 Determine the expected value of the contribution
- The following table shows the three-period moving average and five-period moving average for monthly sales of Budget Furniture's during 2019. Moving averages of Budget Furniture's Time period Months Sales Three-period moving average (rounded off to Five-period moving average four decimals) R'millions 1 Jan 7 5.0000 6.2 February 5.6667 6.6 March 5 7.0000 B 4 April 8.3333 8.2 May 7 9.3333 8.4 June 8.3333 9.6 7 July 12 8.6667 9.6 August 4 A 9.2 September 10 10.6667 10 October 13 10.6667 11 November 9 12 December 10 The seasonal index for the month of February in 2019 is: LOQ2: An economist who estimated the Keynesian money demand function in logarithmic form using data from Sri Lankan economy, obtained the graph on the left by using predicted and actual money demand. While the model was very successful in predicting money demand until 2010 (small forecast errors), it predicts a consistently higher money demand than actually occurred since then (growing forecast errors each period). 48 Ln(M) 4.75 4.7 4.65 4.6 4.55 Actual 4.5 Predicted ...... 4.45 Help this economist who has trouble explaining this situation, even if you do not know anything about the economy in question. Can you answer this question with details please? 6toz StorDemand for stereo headphones and MP3 players for joggers has caused Nina Industries to grow almost 50 percent over the past year. The number of joggers continues to expand, so Nina expects demand for headsets to also expand, because, as yet, no safety laws have been passed to prevent joggers from wearing them. Demand for the players for last year was as follows: a. Using linear regression analysis, what would you estimate demand to be for each month next year? (Do not round intermediate calculations. Round your answers to 2 decimal places.) b. To be reasonably confident of meeting demand, Nina decides to use 2 standard errors of estimate for safety. How many additional units should be held to meet this level of confidence? (Do not round intermediate calculations. Round your answer to the nearest whole number.)
- Year Quarter Sales Isolated trend 2016 1 18 2016 2 28 2016 12 2016 4 8 2017 1 16 2017 2 38 2017 3 24 2017 4 17 2018 1 34 A 2018 2 40 2018 29 2018 4 26 2019 1 42 2019 2 52 2019 40 2019 4 34 43.75 2020 1 46 2020 2 58 The table contains decomposition figures of the quarterly sales in millions of Rands for a large store. The value of A is3. The manager for a manufacturing company must recommend whether to construct a large plant, construct a small plant or do nothing. He estimates the long-run profits in $ as follows: State of Nature Alternative Good Average Poor Market($) Market ($) Market ($) Construct a 100,000 35,000 -60,000 large plant Construct a 75,000 25,000 -40,000 small plant Do nothing -5,000 0 0 Probability 25% 50% 25% Solve using: A. Expected Opportunity Loss B. Expected Value of Perfect InformationSales of a particular product (in the thousands of dollars) for the year of 2015 through 2018 have been $48,000, $64,000, $67,000 and $83,000 respectively. (a) What sales would you predict for 2019, using a simple four year moving average? (b) What sales would you predict for 2019, using a weighted moving average with weights of 0.50 for the immediate preceding year 0.3, 0.15, and 0.05 for the three years before that?
- Consider the table below which represents the number of active credit card accounts issued by a small credit union in a particular customer segment from 1994 to 2017 and a relevant forecast method. Time Credit cards A B abs sq abs% err 1994 13260 13260 60 1995 13310 13319 60 10 10 97 0.0007 1996 13383 13379 60 13379 4 4 20 0.0003 1997 13427 13438 59 13439 12 12 149 0.0009 1998 13455 13493 58 13497 42 42 1743 0.0031 1999 13520 13548 57 13551 31 31 962 0.0023 2000 13663 13611 59 13605 -58 58 3360 0.0042 2001 13717 13675 60 13670 47 47 2220 0.0034 2002 13753 13737 61 13735 -17 17 296 0.0013 2003 13792 13798 61 13798 6 6 37 0.0004 2004 13858 13858 61 13858 1 1 0.0000 2005 13915 13919 61 13919 4 4 13 0.0003 2006 13966 13978 60 13979 13 13 177 0.0010 2007 14017 14036 60 14038 21 21 450 0.0015 2008 13945 14081 55 14096 151 151 22852 0.0108 2009 14008 14123 51 14136 128 128 16382 0.0091 2010 14076 14164 48 14174 98 98 9658 0.0070 2011 14122 14204 46 14213 90 90 8128 0.0064 2012 14164 14241 43…New Accounts New Accounts Period 200 232 11 214 248 12 211 250 13 228 253 14 5 235 10 267 15 Using linear regression, what is your forecast for period 16? Less than 300 Between 301 and 308 Between 309 and 350 Period 1 2 3 4 O Higher than 350 Period 6 7 8 9 New Accounts 281 275 280 288 310The Gorman Manufacturing Company must decide whether to manufacture a component part at its Milan, Michigan, plant or purchase the component part from a supplier. The resulting profit is dependent upon the demand for the product. The following payoff table shows the projected profit (in thousands of dollars): Decision State of Nature Alternative Low Demand (S1) Medium Demand (S2) High Demand )S3) Manufacture, d(1) -20 40 100 Purchase, d(2) 10 45 70 The state-of-nature probabilities are P s1= 0.35, P s2= 0.35, and P s3= 0.30 Use expected value to recommend a decision.