Wordcount: 2000 words

Madrid FC own land in the metropolitan area of Madrid. They would like to build a sports complex which would include state-of the art training facilities for elite athletes. Your consultancy office with the help of architects and sports consultant have drawn up three different projects) (i) 10 hectare site with small capacity for athletes (ii) 20 Ha site and moderate level of capacity; (iii) a high-level complex at 30 Ha.
The success of the project depends upon several factors. Madrid FC want to build make the largest profit. There is uncertainty concerning the demand for the three projects. The decision is to select the optimum project depends on following three decision alternatives:
Decision 1: a small sports complex at 10 Ha Decision 2: a medium complex at 20 Ha Decision 3: a large complex at 30 Ha
Some other information investigated:
Decision 1 would be in the centre of town where property and land are expensive but would have some kudos as it is close to the football ground.
Decision 2 is close to the centre but transport would be needed to get to it. Decision 3 is out of town with lots of opportunity for expansion.
A study was conducted to get some prior knowledge for the probability of each alternative occurring at 2 different demand level. The two directions investigated were high demand and low demand and based on various financial metrics and a probability assigned to these variables (see table 1 below).
Thus, management must first select a decision alternative (complex size), then other states of nature will be investigated e.g. (demand for the sports facility). Given the three decision alternatives and the two states of nature, which sports complex should Madrid FC advance?
To answer this question, Madrid FC will need to know the consequence associated with each decision alternative and each state of nature.
Table 1: Payoff for Madrid FC Sports Complex (payoff in Euros million)

Low Demand

High Demand

Size
Decision
S1 (p=0.4)
S2 (p=0.6)

Small

D1

3000

3200

Medium
D2
2500
2800

Large

D3

2000

2100

Table 2: A survey was completed with 100 people that showed strong interest in signing up to train at the complex. A contingency table of the data is shown below

Trains more than 3 times a week

Trains less than 3 times a month

TOTAL
Football fan
20
40
60
Non-football fan
20
20
40
TOTAL

40
60

100

Questions:

1)  Based on the information in the case, what are Madrid FCs key drivers and objectives in this decision- making process?
2)  Are there any other objectives that you think they should consider?
3)  Identify the basic elements governing Madrid FCs decision-making (values, decisions, uncertain events, consequences, etc) ?
4)  Develop a decision tree for this decision-making process.
5)  What roles do decision trees and influence diagrams play in helping to understand and communicate the structure of your decisions in this project?
6)  Which decision would you recommend based on your investigations. Justify your recommendations?
7)  Given the information in the contingency table, what is the significance of this data and which marketing solutions might be applicable for Madrid FC?
8)  Develop arguments on how decision-making could be improved in a project of this nature?BBA312 Decision Making Final Assignment Brief and Rubrics

Task

• This is an individual task

• Read and study the information below and answer the questions.

• There are 8 questions. Make sure the questions are clearly labelled.

• Document format (upload in pdf format)

Formalities:

• Wordcount: 2000 words

• Cover, Table of Contents, References and Appendix are excluded of the total wordcount.

• Font: Arial 12,5 pts.

• Text alignment: Justified.

• The in-text References and the Bibliography have to be in Harvard’s citation style.

The Project Information

Madrid FC own land in the metropolitan area of Madrid. They would like to build a sports complex which would include state-of the art training facilities for elite
athletes. Your consultancy office with the help of architects and sports consultant have drawn up three different projects) (i) 10 hectare site with small capacity
for athletes (ii) 20 Ha site and moderate level of capacity; (iii) a high-level complex at 30 Ha.

The success of the project depends upon several factors. Madrid FC want to build make the largest profit. There is uncertainty concerning the demand for the three
projects. The decision is to select the optimum project depends on following three decision alternatives:

Decision 1: a small sports complex at 10 Ha

Decision 2: a medium complex at 20 Ha

Decision 3: a large complex at 30 Ha

Some other information investigated:

Decision 1 would be in the centre of town where property and land are expensive but would have some kudos as it is close to the football ground.

United Snus Association2

United Snus Association2

United Snus Association2

Decision 2 is close to the centre but transport would be needed to get to it.

Decision 3 is out of town with lots of opportunity for expansion.

A study was conducted to get some prior knowledge for the probability of each alternative occurring at 2 different demand level. The two directions investigated were
high demand and low demand and based on various financial metrics and a probability assigned to these variables (see table 1 below).

Thus, management must first select a decision alternative (complex size), then other states of nature will be investigated e.g. (demand for the sports facility).

Given the three decision alternatives and the two states of nature, which sports complex should Madrid FC advance?

To answer this question, Madrid FC will need to know the consequence associated with each decision alternative and each state of nature.

Table 1: Payoff for Madrid FC Sports Complex (payoff in Euros million)

Low Demand High Demand

Size Decision S1 (p=0.4) S2 (p=0.6)
Small D1 3000 3200

Medium D2 2500 2800

Large D3 2000 2100

Table 2: A survey was completed with 100 people that showed strong interest in signing up to train at the complex. A contingency table of the data is shown below

Trains more than 3
times a week

Trains less




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