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The Applied Business Analytics Casebook: Applications in Supply Chain Management, Operations Management and Operations Research

The Applied Business Analytics Casebook: Applications in Supply Chain Management, Operations Management and Operations Research

ISBN 9780133407365
Edition 1
Publication Date
Purchase Type Buy New
Publisher Pearson Professional
Author(s)
Overview

A unique casebook in analytics for supply chain management places the reader in the simulated role of decision-maker, exposes them to the entire decision-making process, and provides opportunities to perform analyses, interpret output, and recommend an optimal course of action.

 

Contributed by many of today’s leading experts in “big data” for supply chain, operations research, and operation management, this reference’s cases are short, concise, and to the point. Coverage includes: 

Forecasting and statistical analysis: time series forecasting models, regression models, data visualization, and hypothesis testing
Optimization and simulation: linear, integer, and nonlinear programming; Monte Carlo simulation and risk analysis; and stochastic optimization
Decision analysis: decision making under uncertainty; expected value of perfect information; decision trees; game theory models; AHP; and multi-criteria decision making
Advanced business analytics: data warehousing/mining; text mining; neural networks; financial analytics; CRM analytics; and revenue management models
Overview

A unique casebook in analytics for supply chain management places the reader in the simulated role of decision-maker, exposes them to the entire decision-making process, and provides opportunities to perform analyses, interpret output, and recommend an optimal course of action.

 

Contributed by many of today’s leading experts in “big data” for supply chain, operations research, and operation management, this reference’s cases are short, concise, and to the point. Coverage includes: 

Forecasting and statistical analysis: time series forecasting models, regression models, data visualization, and hypothesis testing
Optimization and simulation: linear, integer, and nonlinear programming; Monte Carlo simulation and risk analysis; and stochastic optimization
Decision analysis: decision making under uncertainty; expected value of perfect information; decision trees; game theory models; AHP; and multi-criteria decision making
Advanced business analytics: data warehousing/mining; text mining; neural networks; financial analytics; CRM analytics; and revenue management models
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