Unit: Quantitative Analysis
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Login to Access| Economic conditions | |||
| Project | Favourable | Moderate | Unfavourable |
| A | 7,300 | 5,600 | 4,100 |
| B | 15,100 | 6,700 | 0 |
| C | 9,500 | 6,000 | 2,500 |
| Probability | 0.20 | 0.30 | 0.50 |
| Option 1: | Launch immediately:
|
| Option 2: | Conduct market research at a cost of Sh.50,000
|
| Market condition (Demand in Units) | |||
| Selling price | Good | Moderate | Bad |
| Sh.50 | 20,000 | 18,000 | 14,000 |
| Sh.55 | 18,000 | 16,500 | 12,000 |
| Sh.60 | 16,000 | 14,000 | 8,500 |
| States of nature | ||||
| Weak | Mixed | Strong | ||
| Nairobi | 85 | 30 | 75 | |
| Strategies | Nakuru | 45 | 45 | 110 |
| Nanyuki | 60 | 95 | 85 | |
| State of nature | ||||
| Product | \(S_1\) | \(S_2\) | \(S_3\) | \(S_4\) |
| \(P_1\) | 5,000 | 9,000 | 7,000 | 8,000 |
| \(P_2\) | 7,000 | 4,000 | 6,000 | 12,000 |
| \(P_3\) | 10,000 | 8,000 | 9,000 | 7,000 |
| \(P_4\) | 14,000 | 5,000 | 7,000 | 6,000 |
(i) Decision alternative.
(ii) State of nature.
(iii) Conditional payoff.
(iv) Opportunity cost
| Probability of | No testing | Market testing |
| High success | 0.20 | 0.40 |
| Moderate success | 0.35 | 0.40 |
| Low success | 0.45 | 0.20 |
| High success | Sh.900 million |
| Moderate success | Sh.450 million |
| Low success | Sh.225 million |
(i) Venn diagram.
(ii) Complement of a set.
(iii) Union of a set.
| Type of demand | |||
| Product | Good | Moderate | Poor |
| Silk | 70,000 | 55,000 | -10,000 |
| Matt | 100,000 | 40,000 | -6,000 |
| Gloss | 120,000 | 50,000 | -40,000 |
| Payoff matrix | |||
| Demand | |||
| Product | Low | Moderate | High |
| \(S_1\) | 15 | 22 | 29 |
| \(S_2\) | 22 | 24 | 28 |
| \(S_3\) | 32 | 23 | 34 |
| \(S_4\) | 35 | 22 | 33 |
(ii) Highlight four assumptions of Markov analysis.
1. A diversified portfolio promising Sh.15 million with a probability of 0.7 and Sh.8 million with a
probability of 0.3.
2. A risky investment consisting of two contracts with independent outcomes one promising Sh.7 million with a probability of 0.7 and the other Sh.3.5 million with a probability of 0.3.
Required:
(i) Construct a decision tree depicting the above information using the expected monetary value (EMV) criterion.
(ii) Advise on the best decision using the EMV criterion.
| Activity | Preceding Activity | Expected estimated time (in weeks) |
| A | - | 5 |
| B | - | 7 |
| C | - | 3 |
| D | A | 7 |
| E | A | 6 |
| F | B | 8 |
| G | C | 10 |
| H | E,F | 3 |
| I | E,F | 4 |
| J | D,I | 2 |
| K | G,H,J | 4 |
| L | D,I | 7 |
| Number of units of product "Ndovu" | Probability demanded |
| 10 | 0.36 |
| 20 | 0.42 |
| 30 | 0.22 |
| State of the economy | |||
| Company | Weak | Moderate | Strong |
| A | -4.0 | 3.5 | 6.0 |
| B | -2.0 | 2.5 | 4.5 |
| C | -2.4 | 2.8 | 3.5 |
| Player B strategy | ||||||
| I | II | III | IV | V | ||
| I | -2 | 0 | 0 | 5 | 3 | |
| Player A strategy | II | 4 | 2 | 1 | 3 | 2 |
| III | -4 | -3 | 0 | -2 | 6 | |
| IV | 5 | 3 | -4 | 2 | -6 | |
| Number of weeks | ||
| Number of cakes | Cakes Produced | Cakes Sold |
| 150 | 20 | 35 |
| 250 | 50 | 50 |
| 350 | 80 | 80 |
| 450 | 80 | 65 |
| 500 | 20 | 20 |
| Cakes produced | 33 | 86 | 50 | 41 | 31 | 78 | 30 | 22 | 26 | 88 |
| Cakes sold | 79 | 03 | 40 | 13 | 58 | 61 | 72 | 49 | 82 | 86 |
| Activity | Preceding | Duration in days | Total cost | Number of | |
| activity | Normal | Crash time | normal Sh. | persons per day | |
| A | - | 7 | 5 | 7,500 | 5 |
| B | - | 6 | 3 | 6,000 | 4 |
| C | - | 2 | 2 | 2,500 | 6 |
| D | A | 5 | 4 | 6,000 | 5 |
| E | B | 5 | 4 | 7,000 | 5 |
| F | E | 6 | 2 | 8,000 | 6 |
| G | E | 7 | 6 | 6,000 | 4 |
| H | C | 6 | 5 | 7,200 | 6 |
| I | H | 8 | 5 | 9,800 | 9 |
| J | D | 4 | 4 | 3,500 | 3 |
| K | J | 6 | 5 | 3,600 | 2 |
| L | F | 3 | 2 | 7,000 | 12 |
| M | G,I | 8 | 4 | 9,200 | 6 |
| N | K,L,M | 4 | 2 | 7,700 | 15 |
A more efficient machine for use by the therapist is available for purchase. If the machine is purchased by the therapist, it would increase the average service rate at the parlour to 12 customers per hour. The cost of each hour lost due to a customer waiting for service is Sh.875.
Required:
(i) The average waiting cost per day.
(ii) Evaluate the effect of purchasing the more efficient machine on the average daily waiting cost.
| Selling price (Sh) 600 700 800 Variable cost (Sh.) 300 400 500 Sales volume (units) 40,000 50,000 60,000 | Probability 0.30 0.50 0.20 Probability 0.40 0.50 0.10 Probability 0.30 0.50 0.20 |

| Pay off conditional on events | |||||
| Alternative | E1 | E2 | E3 | E4 | E5 |
| A | 6 | 2 | -2 | -12 | 4 |
| B | -6 | -3 | 10 | 16 | 0 |
| C | 12 | 8 | 4 | 0 | 6 |
| Annual profit (Sh."000") | ||||
| State of demand | Probability | P1 | P2 | P3 |
| High | 0.35 | 15,000 | 34,000 | 22,000 |
| Moderate | 0.40 | 25,000 | 30,000 | 15,000 |
| Low | 0.25 | (5,000) | (3,000) | 8,000 |
| Company A | Company B | ||
| Newspaper | Radio | Television | |
| Newspaper | 40 | 50 | -17 |
| Radio | 10 | 25 | -10 |
| Television | 100 | 30 | 60 |
| Time estimates (days) | |||
| Activity | Optimistic time | Most likely time | Pessimistic time |
| A | 7 | 17 | 27 |
| B | 5 | 11 | 23 |
| C | 3 | 8 | 19 |
| D | 23 | 31 | 45 |
| E | 9 | 21 | 39 |
| F | 9 | 11 | 25 |
| G | 2 | 5 | 14 |
| H | 9 | 10 | 17 |
| Activity | Earliest start time (days) | Latest start time (days) | Earliest finish time (days) | Latest finish time (days) |
| A | 0 | 0 | 17 | 17 |
| B | 17 | 17 | 29 | 29 |
| C | 19 | 43 | 38 | 52 |
| D | 19 | 29 | 61 | 61 |
| E | 38 | 52 | 60 | 74 |
| F | 61 | 61 | 74 | 74 |
| G | 61 | 79 | 67 | 85 |
| H | 74 | 74 | 85 | 85 |
| Activity | Immediate predecessor (s) | Duration (weeks) | Probability |
| A | - | 3 4 5 | 0.25 0.50 0.25 |
| B | - | 4 5 6 7 8 | 0.15 0.30 0.20 0.20 0.15 |
| C | A | 1 3 5 | 0.20 0.65 0.15 |
| D | B,C | 4 5 | 0.80 0.20 |
| E | D | 3 4 5 6 | 0.15 0.25 0.25 0.35 |
| F | D | 5 7 | 0.20 0.80 |
| G | E,F | 2 3 | 0.50 0.50 |
| Type of pen | Fixed cost (Sh.) | Variable cost (Sh.) |
| P1 | 2,000,000 | 100 |
| P2 | 3,200,000 | 80 |
| P3 | 6,000,000 | 60 |
| State of demand | Number of pens |
| Low | 250,000 |
| Moderate | 1000,000 |
| High | 1,500,000 |
| Activity | Preceding activity | Time estimates (weeks) | ||
| Most optimistic | Most likely | Most pessimistic | ||
| A | - | 2 | 4 | 12 |
| B | - | 10 | 12 | 26 |
| C | A | 8 | 9 | 10 |
| D | A | 10 | 15 | 20 |
| E | A | 7 | 7.5 | 11 |
| F | B,C | 9 | 9 | 9 |
| G | D | 3 | 3.5 | 7 |
| H | E,F,G | 5 | 5 | 5 |
| Airline Q | ||||
| Q1 | Q2 | Q3 | ||
| K1 | -30 | 0 | -90 | |
| Airline K | K2 | -40 | -15 | -20 |
| K3 | 80 | 20 | -50 | |
| Unit selling Price(sh.) | Probability | Variable cost (Sh.) | Probability | Sales yolume (units) | Probability |
| 60 | 0.25 | 20 | 0.25 | 40,000 | 0.30 |
| 80 | 0.45 | 40 | 0.55 | 60,000 | 0.35 |
| 100 | 0.30 | 60 | 0.20 | 100,000 | 0.35 |
| Activity | Normal duration (Days) | Crash duration (Days) | Normal cost (Sh.) | Crash cost (Sh.) |
| 1 - 2 | 6 | 4 | 2,800,000 | 3,800,000 |
| 1 - 3 | 8 | 5 | 4,000,000 | 5,600,000 |
| 2 - 3 | 4 | 2 | 2,200,000 | 3,000,000 |
| 2 - 4 | 3 | 2 | 1,600,000 | 2,800,000 |
| 3 - 4 | Dummy | - | - | - |
| 3 - 5 | 6 | 3 | 1,800,000 | 3,200,000 |
| 4 - 6 | 10 | 6 | 5,000,000 | 7,000,000 |
| 5 - 6 | 3 | 2 | 1,000,000 | 1,600,000 |
| Company B's strategies | ||||
| \(B_1\) | \(B_2\) | \(B_3\) | ||
| Company A's strategies | \(A_1\) | 7 | 4 | 1 |
| \(A_2\) | 4 | 2 | 0 | |
| \(A_3\) | 3 | -1 | -2 | |
| \(A_4\) | 2 | 5 | -3 | |
| Small scale production | Large scale production | ||||
| Profit (Sh. million) | Probability | Profit (Sh. million) | Probability | ||
| Demand | Low | 40 | 0.25 | 5 | 0.25 |
| Medium | 140 | 0.45 | 90 | 0.45 | |
| High | 180 | 0.30 | 280 | 0.30 | |
| Selling price per tonne (Sh."000") | Probability | Yield per acre (tonne) | Probability | Cost per acre (Sh."000") | Probability |
| 240 | 0.18 | 70 | 0.09 | 12,000 | 0.14 |
| 250 | 0.29 | 75 | 0.16 | 14,000 | 0.22 |
| 260 | 0.31 | 80 | 0.24 | 16,000 | 0.36 |
| 270 | 0.14 | 85 | 0.38 | 18,000 | 0.26 |
| 280 | 0.08 | 90 | 0.13 | 20,000 | 0.02 |
| Activity | Preceding activity | Duration (months) | Total Cost (Sh.million) |
| A | - | 8 | 100 |
| B | - | 2 | 75 |
| C | A | 3 | 135 |
| D | A | 7 | 70 |
| E | B | 5 | 160 |
| F | C,D | 9 | 255 |
| G | D | 2 | 30 |
| H | D,E | 4 | 90 |
| I | G,H | 3 | 55 |
| Activity | Duration (months) | Total cost (Sh.million) |
| A | 6 | 125 |
| B | 1 | 90 |
| C | 5 | 85 |
| D | 3 | 200 |
| E | 7 | 275 |
| F | 2 | 95 |
| Time (weeks) | ||||
| Activity | Preceding activity | Optimistic | Most probable | Pessimistic |
| A | - | 1.5 | 2.0 | 2.5 |
| B | A | 2.0 | 2.5 | 6.0 |
| C | - | 1.0 | 2.0 | 3.0 |
| D | C | 1.5 | 2.0 | 2.5 |
| E | B,D | 0.5 | 1.0 | 1.5 |
| F | E | 1.0 | 2.0 | 3.0 |
| G | B,D | 3.0 | 3.5 | 7.0 |
| H | G | 3.0 | 4.0 | 5.0 |
| I | F,H | 1.5 | 2.0 | 2.5 |
|
Activity
A B C D E F G H |
Duration (weeks) 5 2 4 2 5 7 6 3 |
Preceding activity
- - - B B, C C A, D G, D, E, F |
|
Packaging system
A B C |
Purchase cost
Sh. "000" 100 200 400 |
Variable cost per
unit of product Sh. "000" 1.50 1.00 0.50 |
Scrap value
Sh. "000" 10 20 40 |
|
Demand (units)
100 200 400 |
Probability
0.3 0.6 0.1 |
|
Number of house sold Number of months |
0 1 |
1 2 |
2 1 |
3 2 |
4 1 |
5 3 |
6 2 |
|
Model
I II |
Additional cost per day (Sh.)
370 390 |
Increase in typist's efficiency (%)
50 75 |
| Market survey | Actual state of nature | ||
| Result G P | H 0.7 0.3 | M 0.6 0.4 | L 0.2 0.8 |
| Activity A B C D E F G H I J K L M | Predecessory activity - - A A A A,B C C,D E G,H H H,I H,I,F | Time(Days) 10 12 10 9 13 17 12 14 13 12 10 14 13 |