Global business analytics models : concepts and applications in predictive, healthcare, supply chain, and finance analytics

171 Pages·2016·7.09 MB·English

by  Min

About This eBook
EPUB is an open, industry-standard format for e-books. However, support for
EPUB and its many features varies across reading devices and applications. Use
your device or app settings to customize the presentation to your liking. Settings
that you can customize often include font, font size, single or double column,
landscape or portrait mode, and figures that you can click or tap to enlarge. For
additional information about the settings and features on your reading device or
app, visit the device manufacturer’s Web site.
Many titles include programming code or configuration examples. To
optimize the presentation of these elements, view the e-book in single-column,
landscape mode and adjust the font size to the smallest setting. In addition to
presenting code and configurations in the reflowable text format, we have
included images of the code that mimic the presentation found in the print book;
therefore, where the reflowable format may compromise the presentation of the
code listing, you will see a “Click here to view code image” link. Click the link
to view the print-fidelity code image. To return to the previous page viewed,
click the Back button on your device or app.
Global Business
Analytics Models
Concepts and Applications in Predictive, Healthcare,
Supply Chain,
and Finance Analytics
Hokey Min
James R. Good, Chair in Global Supply Chain Strategy at
Bowling Green State University
Publisher: Paul Boger
Editor-in-Chief: Amy Neidlinger
Executive Editor: Jeanne Glasser Levine
Cover Designer: Alan Clements
Managing Editor: Kristy Hart
Senior Project Editor: Andy Beaster
Copy Editor: Cheri Clark
Proofreader: Anne Goebel
Indexer: Johnna Dinse
Compositor: Gloria Schurick
Manufacturing Buyer: Dan Uhrig
© 2016 by Hokey Min
For information about buying this title in bulk quantities, or for special sales
opportunities (which may include electronic versions; custom cover designs; and
content particular to your business, training goals, marketing focus, or branding
interests), please contact our corporate sales department at
[email protected] or [phone].
For government sales inquiries, please contact
[email protected].
For questions about sales outside the U.S., please contact
[email protected].
Company and product names mentioned herein are the trademarks or registered
trademarks of their respective owners.
All rights reserved. No part of this book may be reproduced, in any form or by
any means, without permission in writing from the publisher.
Printed in the United States of America
First Printing March 2016
ISBN-10: 0-13-405760-0
ISBN-13: 978-0-13-405760-6
Pearson Education LTD.
Pearson Education Australia PTY, Limited
Pearson Education Singapore, Pte. Ltd.
Pearson Education Asia, Ltd.
Pearson Education Canada, Ltd.
Pearson Educación de Mexico, S.A. de C.V.
Pearson Educación de Mexico, S.A. de C.V.
Pearson Education—Japan
Pearson Education Malaysia, Pte. Ltd.
Library of Congress Control Number: 2015959815
This book is dedicated to my late father,
B.J. Min; my mother, H.W. Seo;
my wife, Christine; and my son, Alexander Snow.
Contents
Chapter 1 Introduction to Business Analytics
1.1 The Origin and Evolution of Business Analytics
1.2 Developing Analytical Thinking
1.3 Operationalizing Big Data from Global Perspectives
1.4 Extracting Useful Information from Big Data
1.5 Unique Challenges for Business Analytics
1.6 Capitalizing on Business Analytics for Building a Winning Global
Strategy
Chapter 2 Collecting, Sorting, Prioritizing, and Storing Big Data
2.1 Finding and Capturing the Right Data
2.2 Data Sampling
2.3 Data Preparation
2.4 Data Segmentation
2.5 Data Filtering
2.6 Data Warehousing
2.7 Data Security
2.8 Fitting Analytics Models to Data
Chapter 3 Business Analytics Models
3.1 Quantitative Tools for Business Analytics
3.2 Basic Statistical Techniques
3.3 R Programming
3.4 Hypothesis Testing
3.4.1 t-Test
3.4.2 ANOVA Test
3.4.3 Nonparametric Test
3.5 Power Analysis
3.6 Data Mining
3.6.1 Decision Trees
3.6.2 Neural Networks
3.6.3 Text Mining
3.6.4 Image Mining
Chapter 4 Predictive Analytics
4.1 Predicting International Customer Behavior
4.2 Demand Forecasting in Unfamiliar Foreign Markets
4.2.1 Moving Average
4.2.2 Exponential Smoothing
4.2.3 Trend Analysis
4.2.4 Focus Forecasting
4.2.5 Agent-Based Forecasting
4.3 Global Market Basket Analysis
4.4 Risk Analytics
4.5 Digital Analytics
4.6 Social Sensing
4.7 Mobile Analytics
Chapter 5 Essentials for the Successful Implementation of Business
Analytics
5.1 Understanding the Voice of Overseas Customers
5.2 Collaborating with Foreign Business Partners for Sharing Big Data
5.2.1 Building Trust
5.2.2 Establishing an Information Exchange Mechanism
5.2.3 Ensuring Secure Data Transmission
5.3 Analytics Execution and Implementation
5.4 Performance Measurement and Metrics
5.5 Outcome Analysis
5.6 Corrective Actions
5.7 Emulating Best-in-Class Practices
Chapter 6 Global Finance Analytics
6.1 Foreign Market Scenario Planning
6.2 Financing Global Business Operations through Capital
Management
6.3 Global Financial Risk Assessment
6.3.1 Foreign Direct Investment Risk Analysis
6.3.2 Loan and Credit Risk Assessment
6.3.3 Liquidity Risk Assessment
6.3.4 Foreign Currency Exchange Risk Assessment
6.3.5 Value at Risk (VaR) as the Financial Risk Measure
6.4 Foreign Investment Portfolio Analysis
6.5 Product/Service Pricing Using Analytics
6.6 Multinational Profit Planning and Budgeting Using Analytics
Chapter 7 Global Supply Chain Analytics
7.1 Turning Integrated Big Data into Supply Chain Intelligence
7.2 Global Sales and Promotion Analytics
7.3 Global Sourcing Analytics
7.4 Contract Manufacturing Analytics
7.5 Distribution Analytics
7.6 Transportation Analytics
7.7 Integrating Functional Analytics into Global Supply Chain
Management
Chapter 8 Healthcare Analytics
8.1 Healthcare Analytics as an Emerging Discipline
8.2 Big Data in Healthcare
8.3 Analyzing Clinical and Pharmaceutical Data
8.4 Analyzing the Voice of the Patient
8.5 Healthcare Quality Function Deployment via Analytics
8.6 Healthcare Outcome Analysis
Chapter 9 Future of Business Analytics
9.1 Innovating Analytics
9.2 Embedding Business Analytics into Enterprise-wide Information
Systems
9.3 Future Roles of Business Analytics in Global Business Intelligence
9.4 Epilogue
Index