MGMT20005 Business Decision Analysis - Lecture 2: Decision Making under Risk

Vocabulary flashcards focusing on key terms, definitions, formulas, and case example figures from MGMT20005 Lecture 2 on Decision Making under Risk.

Decision Node

A node in a decision tree, represented by a square shape, from which branches emanate representing the decision alternatives available to the decision maker.

Chance Node

A node in a decision tree, represented by a circle shape, from which branches emanate representing the possible states of nature for a chance event.

Decision Tree

A visual decision analysis tool that provides a structured, visual representation of all possible decision paths, decision alternatives, states of nature, probabilities, and payoffs in chronological order from left to right.

Mutually Exclusive States of Nature

A property of states of nature in a decision tree meaning that only one state of nature outcome can occur for a given chance event.

Collectively Exhaustive States of Nature

A property of states of nature in a decision tree meaning that the defined set of outcomes includes all possible states of nature, and no other outcomes exist.

Expected Value (EV) Approach

A decision-making criterion under risk where the expected value of a decision alternative $d_i$ is calculated as the weighted average payoff using the formula $EV(d_i) = \sum_{j=1}^{N} P(s_j) V_{ij}$.

Folding Back Approach

A method used to solve decision tree models by starting at the endpoints on the far right-hand side and moving left: calculating expected values at chance nodes and choosing the alternative with the maximum expected value at decision nodes.

Risk Analysis

An analysis that helps the decision maker understand the difference between the expected value of a decision and the actual payoff that may occur by computing the probability distribution of payoffs.

Decision Alternatives ($d_i$)

The specific options or courses of action directly available for choice by the decision maker in a decision problem.

States of Nature ($s_j$)

The possible outcomes or future events associated with a chance event that are beyond the direct control of the decision maker.

Consequence ($V_{ij}$)

The payoff or profit/loss value associated with choosing a specific decision alternative $d_i$ when a specific state of nature $s_j$ occurs.

PDC Example Expected Values

In the PDC decision problem with $P(s_1) = 0.8$ and $P(s_2) = 0.2$, the calculated expected values are $EV(d_1) = 7.8\text{ million}$, $EV(d_2) = 12.2\text{ million}$, and $EV(d_3) = 14.2\text{ million}$, making large complex ($d_3$) the optimal decision.

Flop (Movie Production Exercise)

A TV series project outcome where audience reaction is not very positive, resulting in a loss of around $k\$500$ for the cost of producing the pilot, occurring with a probability of $85\%$.

Hit (Movie Production Exercise)

A TV series project outcome where audience reaction to the pilot is sufficiently positive, yielding a profit of about $m\$4.5$, occurring with a probability of $12\%$.

Monster (Movie Production Exercise)

A TV series project outcome consisting of hits that are exceptionally well received by the TV audience, yielding a profit of $m\$25$, occurring with a probability of $3\%$.