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Brett Saraniti
Brett Saraniti

MANAGERIAL ECONOMICS & DECISION SCIENCES
Visiting Professor of Managerial Economics & Decision Sciences

Print Overview
Brett Saraniti received his PhD in Managerial Economics and Decision Sciences from the Kellogg School of Management at Northwestern University in 1997. His dissertation chair was Roger Myerson, Nobel Laureate 2007. Brett has been a visiting professor at Kellogg for the past 12 summers, and he is currently a Professor of Economics and Quantitative Methods at Hawaii Pacific University where he has taught since 1997.

In addition to teaching at HPU and Kellogg, Brett has been a visiting professor at INSEAD; the Sasin Graduate Institute in Bangkok, Thailand; the Brisbane Graduate School of Business in Queensland, Australia; the Thunderbird School of Global Management; and the Helsinki School of Economics and Business Administration in Finland. He is also scheduled to teach at IESE during 2009.

Professor Saraniti is the author of two textbooks: Managerial Statistics: A Case Based Approach, with Peter Klibanoff, Boaz Moselle, and Alvaro Sandroni, and (forthcoming) Vital Statistics: Statistics for Business and Economics with William Sandholm.

He has also worked for and/or consulted for McKinsey & Company, Xerox Corporation, Chevron Oil Field Research, Cantor Fitzgerald/ Hollywood Stock Exchange, Unext.com, MRJ Technologies, Chipin.com, Carddomains.com, Lee Ceramics, and Surflight Hawaii.

Brett spends most of the year in Waialua, Hawaii with his wife Samantha and their children: Francesca, Carlo, and Enzo.
Print Vita
 
Print Research
Books
Klibanoff, Peter, Boaz Moselle, Brett Saraniti and Alvaro Sandroni. 2006. Managerial Statistics: A Case-Based Approach. Mason, OH: Cengage Learning (formerly Thomson South-Western).
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Cases
Saraniti, Brett. 2008. The Hawaiian Airline Industry, 2001–2008. Case 5-108-005 (KEL351).
Abstract

 
Print Teaching
Full-Time / Part-Time MBA
Decision Making Under Uncertainty (DECS-433-0)

This course counts toward the following majors: Decision Sciences.

Provides frameworks for reasoning about decisions in uncertain environments. Case studies and experiments are used to motivate the importance of probabilistic reasoning to avoid the systematic biases that cloud managers' decision making. Formal probabilistic tools are introduced and their relevance to modern business issues is conveyed via cases, exercises, and class experiments. Some of the applications include: inventory management with uncertain demand, principal-agent models, herd behavior, selection bias, rare events, real options and risk. The course is self-contained, and should be of value to all students, including those with prior exposure to formal probability models.

Statistical Methods For Management Decisions (DECS-434-0)

This course counts toward the following majors: Decision Sciences.

This sequel to DECS-433 extends the statistical techniques learned in that course to allow for the exploration of relationships between variables. Topics include one- and two-population hypothesis testing, correlation, simple and multiple regression analysis, and qualitative variables. The course also covers applications of the material and a number of case studies. Extensive use of spreadsheet statistical analysis software is required.

Managerial Decision Analysis (DECS-438-A)
This course presents the standard approach taken in all Kellogg courses in dealing with risk and uncertainty. The principal focus is on the language of probability, random variables, decision trees and commonly encountered probability distributions. A number of applications are explored, with most analysis performed using spreadsheets.

Statistical Decision Analysis (DECS-439-B)
The study of statistics at Kellogg has two complementary goals: The first is to master the two languages of statistics: How to measure how much an estimate can be trusted and how to measure the weight of evidence with respect to a claim that has been made. The objective is to become knowledgeable consumers of statistical reports, effective managers of those doing the statistical "dirty work" and confident critics of statistics done badly. The other goal is to become facile at performing regression analysis, a tool for understanding the types of relationships all managers must deal with. A spreadsheet-based statistical analysis package is provided to all students.

Competitive Strategy and Industrial Structure (MECN-441-0)

This course counts toward the following majors: Management & Strategy, Managerial Analytics, Managerial Economics.

The course studies the determinants nature of competitive strategy in a variety of industry structures. The course considers how the structure of a firm's industry affects its strategic choices and performance. Topics include the dynamic aspects of pricing, entry and predation in concentrated industries, and product differentiation, product proliferation and innovation as competitive strategies.