Effective Management Decision Making Language ... - Tutorsindia

Effective Management Decision MakingChapter 3The part of the new tree (nodes 10,11 and 5) – have been resolved earlier in the discussion. Nodes 6,7,8 and 9 are resolvedby considering THE LOGICAL ORDER of the decisions. We know for example that P(S1 |D1) represents the first probabilityon Node 6, followed by P(S2 |D1) and P(S3 |D1). The second event outcomes are similarly, P(S1 |D2), P(S2 |D2) and P(S3|D2). We have already determined however the following probabilities of: P(CP|s 1) =0.30, P(CP|s 2) =0.2 P(CP|s 3) =0.05, wheres i(i=1..3) or in terms of the nomenclature of figure 2, and Node 4, P(Very Busy Clearing | S1), P(Very Busy Clearing | S2),P(Very Busy Clearing | S3). In other words, we need to revise the prior probabilities in light of this new conditional information.This can be achieved using a BAYESIAN revision (discussed later). Consider first the BUSY CLEARING PERIOD.State of Nature (after Clearing) Prior Conditional Joint PosteriorS1 (Small Market) 0.4 0.3 0.12 0.36 P(S1 |D1)S2(Medium Market) 0.3 0.2 0.06 0.18 P(S2 |D1)S3(Large Market) 0.3 0.5 0.15 0.45 P(S3 |D1)0.33 (SUM)And hence for Node 8 and Node 9: where Node 9 EMV (with leasing) and Node 8 EMV(without leasing):EMV(9) = (0.36)(1) +(0.18 ) (0.75)+(0.45) (-0.5)EMV(8) = (0.36)(1.5))+(0.18)(0.5)+(0.45)(-2)Please click the advert120Download free ebooks at bookboon.com