García Márquez / Lev Advanced Business Analytics

1. Auflage 2015
ISBN: 978-3-319-11415-6
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 252 Seiten

The book describes advanced business analytics and shows how to apply them to many different professional areas of engineering and management. Each chapter of the book is contributed by a different author and covers a different area of business analytics. The book connects the analytic principles with business practice and provides an interface between the main disciplines of engineering/technology and the organizational, administrative and planning abilities of management. It also refers to other disciplines such as economy, finance, marketing, behavioral economics and risk analysis. This book is of special interest to engineers, economists and researchers who are developing new advances in engineering management but also to practitioners working on this subject.

Dr. Fausto Pedro García Márquez got the European Doctorate on Engineering at University of Castilla-La Mancha (UCLM), 2004. He received his Engineering Degree from University of Murcia, Spain in 1998 and Technical Engineer Degree at UCLM in 1995, and the degree in Business Administration and Management at UCLM 2006. He also holds the titles of Supper Technician in Labor Risks Prevention by UCLM 2000 and Transport Specialist at the Polytechnic University of Madrid, Spain, 2001. He has been Senior Manager in Accenture 2013/2014. He is Senior Lecture (Full professor accredited) at UCLM, and Honorary Senior Research Fellow at Birmingham University UK, Lecturer in Instituto Europeo de Postgrado since 2014 and Director of Ingenium Research Group. He has been principal investigator in 3 European Projects, and 60 national and for company research projects. He has international and national patents, more than 110 international papers, 12 books and 3 International Awards in Engineering Management and Management Science. (www.uclm.es/profesorado/fausto) Dr. Benjamin Lev is Professor and Head of Decision Sciences at LeBow College of Business. He holds a PhD in Operations Research from Case Western Reserve University. Prior to joining Drexel university Dr. Lev held academic and administrative positions at Temple University, University of Michigan-Dearborn and Worcester Polytechnic Institute. He is the Editor-in-Chief of OMEGA-The International journal of Management Science; Co-Editor-in-Chief of International Journal of Management Science and Engineering Management; and serves on several other journal editorial boards. He has published ten books, numerous articles and organized many national and international conferences.  

Autoren/Hrsg.

García Márquez, Fausto Pedro

Lev, Benjamin

Inhaltsverzeichnis

1;Preface;6
2;Contents;10
3;About the Editors;12
4;Decision Making Approach for Optimal Business Investments;14
4.1;1 Introduction;14
4.2;2 DM Process;15
4.2.1;2.1 The Decision Maker;16
4.2.2;2.2 Constraints and Requirements;17
4.2.3;2.3 The Utility Function;17
4.2.4;2.4 Results;17
4.3;3 Logical Decision Trees;18
4.4;4 Binary Decision Diagrams;19
4.4.1;4.1 Ranking of the Basic Causes;19
4.4.1.1;4.1.1 Top-Down-Left-Right (TDLR);20
4.4.1.2;4.1.2 Depth First Search (DFS);20
4.4.1.3;4.1.3 The Breath First Search (BFS);20
4.4.1.4;4.1.4 Level Method;21
4.4.1.5;4.1.5 AND Method;22
4.4.2;4.2 BDD Conversions;22
4.4.3;4.3 Analytical Expression;23
4.5;5 Optimization Approach in DM Process;26
4.6;6 Case Study;28
4.7;7 Conclusions;32
4.8;References;32
5;Integration of a Heuristic Method into an ERP Software: A Successful Experience for a Dynamic Multi-item Lot Sizing Problem;34
5.1;1 Introduction;34
5.2;2 Problem Formulation;36
5.3;3 The Heuristic Approach;38
5.4;4 Development and Implementation Within SAP Business One;40
5.5;5 Visual Example;42
5.5.1;5.1 Demands;42
5.5.2;5.2 Capacity;43
5.5.3;5.3 Setup Costs;43
5.6;6 Conclusions;49
5.7;References;49
6;Economic Viability Analytics for Wind Energy Maintenance Management;51
6.1;1 Introduction;51
6.2;2 Life Cycle Costs;52
6.3;3 Wind Turbines and Wind Turbine Condition Monitoring;52
6.3.1;3.1 Wind Turbines;52
6.3.2;3.2 Condition Monitoring for Wind Turbines;53
6.4;4 State of the Art;55
6.5;5 Case of Study;56
6.6;6 Application of the LCC Model;58
6.6.1;6.1 Model Definition;58
6.6.2;6.2 CMS Investment Costs;59
6.6.3;6.3 CMS Operation Costs;59
6.6.4;6.4 CMS Maintenance Costs;59
6.6.5;6.5 Maintenance Reduction Costs by CMS;59
6.6.6;6.6 Energy Production and Energy Losses by CMS;60
6.6.7;6.7 Net Present Value;60
6.6.8;6.8 Calculation of LCC;61
6.7;7 Conclusions;63
6.8;References;64
7;Introduction to Multi-attribute Decision Making in Business Analytics;67
7.1;1 Introduction;67
7.2;2 Data Envelopment Analysis (DEA);68
7.2.1;2.1 Description and Uses;68
7.2.2;2.2 Methodology;68
7.2.3;2.3 Strengths and Limitations to DEA;69
7.2.4;2.4 Sensitivity Analysis;69
7.2.5;2.5 Illustrative Examples;70
7.3;3 Simple Additive Weighting (SAW) Method;74
7.3.1;3.1 Description and Uses;74
7.3.2;3.2 Methodology;74
7.3.3;3.3 Strengths and Limitations;75
7.3.4;3.4 Sensitivity Analysis;75
7.3.5;3.5 Illustrative Examples;75
7.3.6;3.6 SAW Using Rank Ordering of Data by Criteria;76
7.4;4 Analytical Hierarchy Process (AHP);80
7.4.1;4.1 Description and Uses;80
7.4.2;4.2 Methodology of the Analytic Hierarchy Process;82
7.4.3;4.3 Strengths and Limitations of AHP;83
7.4.4;4.4 Sensitivity Analysis;84
7.4.5;4.5 Illustrative Examples;85
7.5;5 Technique of Order Preference by Similarity to the Ideal Solution (TOPSIS);92
7.5.1;5.1 Description and Uses;92
7.5.2;5.2 Methodology;93
7.5.2.1;5.2.1 Normalization;95
7.5.3;5.3 Strengths and Limitations;96
7.5.4;5.4 Sensitivity Analysis;97
7.5.5;5.5 Illustrative Examples;97
7.6;6 Comparison of Results for the Kite Network;100
7.7;7 Technologies Available;101
7.8;References;102
8;How Business Analytics Should Work;104
8.1;1 A World in Transformation;104
8.1.1;1.1 Some Lasting Stumbling Blocks;105
8.2;2 Data Analysis and Synthesis;106
8.3;3 The Business Analytics Architecture (BAA);107
8.3.1;3.1 Semantic Layer: Business Modelling;109
8.3.2;3.2 Mapping Layer: Conceptual Mapping;112
8.3.3;3.3 Data Layer: Data-Warehouses;113
8.4;4 Analytical Foundations;115
8.5;5 Discussion and Related Work;117
8.6;References;118
9;Vulnerability Analysis of a Signal-Controlled Road Network for Equilibrium Flow;120
9.1;1 Introduction;120
9.2;2 Problem Formulation;125
9.2.1;2.1 Notation;125
9.2.2;2.2 The Expected Performance Measure of a Signal-Controlled Road Network;126
9.2.3;2.3 The Expected Travel Time for Road Users;128
9.2.4;2.4 A Min-Max Mathematical Program;131
9.3;3 Solution Approach;135
9.3.1;3.1 Projection Operator;135
9.3.2;3.2 A Projection Approach;137
9.3.3;3.3 An Efficient Computation Scheme;138
9.4;4 Numerical Computations;140
9.5;5 Conclusion and Discussions;150
9.6;References;151
10;Analytical Model Implementing Objectives in EVM for Advanced Project Control;154
10.1;1 Introduction;154
10.2;2 Enhancing Business Value with Advanced Project Management;155
10.2.1;2.1 Advanced Earned Value Management;155
10.2.2;2.2 Project Driver: Objectives Accomplishment;157
10.3;3 An Analytical Model Implementing Objectives in EVM;159
10.3.1;3.1 Evaluation of Project Objectives Accomplishment;160
10.3.2;3.2 Impact of Initial Phases in the Objectives Accomplishment;160
10.3.3;3.3 Analytical Model Description;161
10.3.4;3.4 Example of Application of the Model;163
10.4;4 Case Study;166
10.5;5 Conclusions;173
10.6;References;173
11;Use of Excellence Models as a Management Maturity Model (3M);175
11.1;1 Introduction;175
11.2;2 Structure of an Excellence Model for EFQM;176
11.2.1;2.1 Principles;177
11.2.2;2.2 Criteria;177
11.2.3;2.3 Assessment Framework;178
11.3;3 Business Process Maturity Models and Excellence Models;179
11.4;4 Measuring Management Maturity: A Real Case Study;180
11.4.1;4.1 Assessment of Management Values: Qualitative Evaluation;181
11.4.2;4.2 Assessment of Management Criteria: Quantitative Evaluation;181
11.5;5 Conclusions;184
11.6;References;189
12;AHP and Intuitionistic Fuzzy TOPSIS Methodology for SCM Selection;190
12.1;1 Introduction;190
12.2;2 Preliminaries;191
12.2.1;2.1 Basic Concept of AHP;191
12.2.2;2.2 FST;192
12.2.3;2.3 Basic Concept of IFS;193
12.3;3 AHP-IFT Hybrid Method;194
12.4;4 Numerical Examples;197
12.5;5 Conclusion;200
12.6;References;201
13;The Assessment and Selection of Hedge Funds;204
13.1;1 Introduction;204
13.2;2 Definitions;207
13.2.1;2.1 What Is a Hedge Fund?;207
13.2.2;2.2 Investment Strategies;207
13.2.3;2.3 Hedge Fund Indexes;208
13.2.4;2.4 Historical Return Analysis;208
13.3;3 Investment Strategies and Indexes;212
13.3.1;3.1 Ratios;213
13.4;4 How to Benchmark Hedge Funds. Should They Be Benchmarkable?;213
13.5;5 Assessment and Selection of Managers;216
13.6;References;218
14;Functional Data Analysis with an Application in the Capital Structure of California Hospitals;220
14.1;1 Introduction;220
14.2;2 Function Representations Using Basis Expansions;222
14.3;3 Recent Applications of FDA in Business Studies;223
14.3.1;3.1 Production and Operations;223
14.3.2;3.2 Marketing and Sales;224
14.4;4 Case Study: Capital Structure of California Hospitals;224
14.4.1;4.1 Data and Preparation;225
14.4.2;4.2 Construction of Functional Curves;225
14.4.3;4.3 Functional Clustering;229
14.4.4;4.4 Functional Principle Component Analysis;230
14.4.5;4.5 Functional Regression;231
14.5;References;232
15;A Software Application to Optimize the Visits of Sales/Marketing Agents to Their Customers in a Brewing Company;234
15.1;1 Introduction;234
15.2;2 Problem Description;235
15.3;3 Initial Goals and Final Scope;236
15.4;4 Software Applications;237
15.5;5 Mathematical Model;238
15.5.1;5.1 Static Planning;239
15.5.2;5.2 Dynamic Planning;242
15.6;6 Algorithm Development;244
15.6.1;6.1 Software Tools;244
15.6.2;6.2 Solution Algorithms;245
15.6.2.1;6.2.1 Static Planning;245
15.6.2.2;6.2.2 Dynamic Planning;248
15.7;7 Computing Results;248
15.7.1;7.1 Static Planning Results;249
15.7.2;7.2 Dynamic Planning Results;249
15.8;8 Conclusions;250
15.9;References;252