Lecture 5
Individual Demand
Price changes, income changes
Normal, inferior goods; Engel curves
Income and Substitution Effect
Revealed Preference
If the consumer purchases bundle A when B is
inside the budget set, A is preferred to B.
Budget line 1
Budge
Lecture 8
Introduction to uncertainty and consumer behavior
Measuring risk
Risk preferences
Risk aversion
Risk premium
Uncertainty and Consumer Behavior
What is risk?
How can we model consumers risk preferences?
What is the value of reducing risk? What
Lecture 2: Consumer Behavior (1)
Market bundles
Indifference curves
Marginal rate of substitution
Utility functions
Consumer theory: strategy
Start with choice of a single consumer
The consumer buys a bundle of goods
Individual demand depends on:
Avai
Leadership / Opportunities in
Global Sustainability
LOGS
University of California, Irvine
Paul Merage School of Business
William Hernndez Requejo
Introduction
William Hernndez Requejo, JD
Center for Global Leadership
UCI Anteater
BA Political Science
A project is a temporary
sequence of unique,
complex, and
connected
activities having one
goal
or purpose and that
must
be completed by a
specific time, within
budget, and according
to
Temporary
Does not necessarily mean short
duration
Have a definite beg
IT Functional Organization Chart
IT Environment: Key Drivers
Improve Customer Service
Relationship Management
Scale & Growth
Baseline Production Support
Training
Enterprise Class Systems
Applications
ERP / SSC
Middleware
Portal
ECM
Catch Up with Bus
D-4165-1
1
The Beginning of System Dynamics
by
Jay W. Forrester
Germeshausen Professor Emeritus
Sloan School of Management
Massachusetts Institute of Technology
Cambridge, Massachusetts, U.S.A.
Banquet Talk
at the international meeting of the
System Dynam
Sustainability Leadership
Wendell Brase
Vice Chancellor for Administrative & Business Services
Co-Chair UC President Janet Napolitanos Global Climate Leadership Council
Chair, UC Energy Services Governing Board
Leadership and Opportunities in Global Susta
MGMT #178
Management of IT
Winter, 2017
Week #1 Readings
The Dynamics of CIO Derailment: How
CIOs Come Undone and How to Avoid IT
Beyond Agile: Reorganizing IT for Faster
Software Delivery (McKinsey)
What Digital Really Means (McKinsey)
Week #1 Readings
T
MGMT #178
Management of IT
Investment and Risk Management
Ed Trainor
Outline of Week #2
Investment and Risk Management discussion
Readings review for key points
CDVS Case Study
Individual Research Presentations
Short video: The Expert
Discuss Week #
What Got You Here Won't Get You There
Strategic Planning Assumption
By 2020 the strongest companies
will be those with most industry
digital platform control.
2013 Gartner, Inc. and/or its affiliates. All rights reserved.
We Have Entered a Third Era of
E
Week #3 MGMT #178
Management of IT
Enterprise Architecture Strategy
Ed Trainor
Reading Assignments
Ten Practical Ideas for Organizing and Managing
Your Enterprise Architecture (McKinsey)
Architect Your Business Not Just IT (MIT/CISR)
Managing Total Dig
Enterprise Architecture Practice
Today and Tomorrow
Trivia Question
What was the schools (at that time known as Graduate
School of Management) first multi-user computer system?
a)
b)
c)
d)
Sun Microsystem
HP3000 minicomputer
Novell NetWare
IBM AS/400
Addi
Management 1
Introduction to Business
Fall 2016
Course Code
Days
Time
Location
38003
Tu/Th
9:30-10:50
SB1 1200
Instructor :
Dr. Grace McLaughlin
SB1 4309
949.824.4945 (It is better to email me)
[email protected]
Tuesday 1-4 pm
Office:
Phone:
Email:
Office
Markov Chain Problems
1. There are two types of beers in the market: Beer A and Beer B. If a customer consumes Beer A there is an
80% probability he will buy beer A in his next purchase (and 20% chance of switching to Beer B). A
customer who consumes Beer
DR
AF
MGMT 190 / 290
LEADERSHIP OPPORTUNITIES IN GLOBAL SUSTAINABILITY
WINTER 2017
WEDNESDAYS, 8-9:20AM, SB1 2200
William Hernandez Requejo
Center for Global Leadership
Contact Information
William Hernandez Requejo
Faculty Assistant: Gail Ho
Office: Cente
Queueing Formulas (Poisson Arrival)
Summary of Symbols
N
e
P0
Pw
Lq
L
Wq
W
Arrival rate per time unit.
Service rate (1/service time).
Finite capacity of the system.
N +1
=
N
Effective . e =
1 ; for = : e = N +1 .
Standard deviation of service time.
Prob
Forecasting Solution
Data for t and Xt are given. The rest should be calculated by using = 0.4, = 0.2 and
seasonality of 4. Note: for calculating Ft and Tt use the adjusted result and not the original
Xt .
t
1
2
3
4
5
6
7
8
Xt
23
45
30
52
32
54
43
60
M.A.
Forecasting (Seasonality)
Regression with dummy variables
Suppose a seasonality of period P exists in the data. We fit the data by multiple linear regression with P
independent variables. One independent variable is the month. The remaining P-1 variables
Mgmt 1 Winter 2017
Introduction to Business
Schedule of readings, assignments, exams
Quizzes are taken before we discuss the material. This is to encourage you to read the book!
HW assignments are to be completed after we have discussed the associated m
Fall, 2010
Management 101 First Exam
Name:
Question 1:
The following is a summary of historical data. There were 26 presidential elections in which the
incumbent ran for re-election. In 16 elections the incumbent won, and in 10 he lost. 14 out of these
16
Question 1:
Customers arrive to the bank according to a Poisson process at a rate of 14 per hour. Service
time takes about 4 minutes.
a. What is the average length of the line if service is exoponential and one teller is open?
b. What is the average lengt
Consider the following PERT problem:
Act.
Pred.
a
m
b
A
C
12
15
18
B
5
8
17
C
E,G
14
16
18
D
A,H
7
10
13
E
4
7
10
F
C,E
14
14
20
G
6
7
8
H
B,C,G
7
10
19
I
A,H
3
5
7
J
A,D
23
26
29
T
ES
EF
LS
LF
Slack
2
a. Find the expected duration of the project.
b. What
Inventory Formulas
Basic E.O.Q. (Economic Oreder Quantity)
D
ch
co
Q
Q
TC
Annual demand.
Annual holding cost.
Ordering cost.
Order quantity.
Optimal order quantity
Total annual inventory cost.
T C = ch Q2 + co D
Q;
Q =
q
2Dco
ch ;
Ordering
D
Q
times a yea
Queueing Formulas (Poisson Arrival)
Summary of Symbols
N
e
P0
Pw
Lq
L
Wq
W
Arrival rate per time unit.
Service rate (1/service time).
Finite capacity of the system.
N +1
=
N
Effective . e =
1 ; for = : e = N +1 .
Standard deviation of service time.
Prob
Queueing Formulas (Poisson Arrival)
Summary of symbols
P0
Pw
Lq
L
Wq
W
Arrival rate per time unit.
Service rate (1/service time).
Standard deviation of service time.
Probability of no customers in system.
Probability of waiting for service.
Average number