TABLE OF CONTENTS

ABSTRACT

COVER PAGE

BIOGRAPHY

ACKNOWLEDGEMENTS

TABLE OF CONTENTS

LIST OF TABLES

LIST OF FIGURES

LIST OF ABBREVIATIONS

1 INTRODUCTION

1.1 Overview of the Research Topic

1.2 Organization of the Dissertation

2 LITERATURE REVIEW

2.1 History of Electronic Data Processing (EDP) in the Textile and Apparel Industry

2.2 Current Computer Technology Utilized in TABIS

2.2.1 Speed, Capacity, and Capability of Today's Desktop Computers

2.2.2 Current Networking Capabilities

2.2.3 Data Warehousing and Relational Databases

2.3 Applicable Data Analysis Techniques

2.3.1 Using Tables to Analyze Data

2.3.2 Graphical Analyses Using Plots

2.3.3 Graphical Analyses Using Maps

2.3.4 Forecasting with Regression Techniques

2.3.5 Potential Application of Neural Networks

2.4 Sources of Textile- and Apparel-Related Data

2.4.1 Compilations and Lists of Data Sources

2.4.2 Data Sources Used in this Research

2.5 Existing Textile- and Apparel-Related Database and Analysis Systems

2.6 Need Analysis for a Textile and Apparel Data Warehouse

3 RESEARCH OBJECTIVES

3.1 Creation of a Unique Data Warehouse of Econometric and Demographic Information Relating to Textiles and Apparel

3.2 Creation of the Textile and Apparel Business Information System (TABIS)

3.3 Utilization of TABIS's Unique Data Analysis and Graphical Presentation Capabilities

4 DATA WAREHOUSE INFRASTRUCTURE DESIGN

4.1 Systems Level Design Considerations

4.1.1 Hardware Selection

4.1.2 Software Selection

4.2 Data Acquisition from Unintegrated Public and Private Sources

4.3 Data Integration by Conversion to Standard ASCII format, then to Relational Database Tables

4.4 Database Optimization for Increased Query Speed

4.4.1 Conversion to Database Format

4.4.2 Indexing Large Data Sets

4.4.3 Pre-Calculating Frequently Accessed Values

4.4.4 Reducing Data Set Size by Optimizing the Number of Bytes Used to Store Values

4.4.5 Rewriting Queries to Improve Efficiency

5 USER INTERFACE DESIGN

5.1 A Unique, Architecture-Independent Interface Utilizing the C Programming Language and the SAS System

5.2 Accessing Simple ASCII Tables and Plots

5.3 Accessing Publication Quality Plots, Maps and Graphics

5.4 Writing Extensions to Provide Enhanced Query and Data Analysis Capabilities

6 RESULTS

6.1 Integrating Data from Disparate Sources to Improve the Quality and Forecastability

6.1.1 Using Deflators to Convert Current Dollar Values to Constant Dollar Values

6.1.2 Using Population Data to Calculate Per Capita Expenditures

6.1.3 Comparing State Populations Using Total and Per Square Mile Values

6.1.4 Integrating Data by Overlaying Plots

6.2 Summarizing Large Data Sets with High-Resolution Graphics

6.2.1 Projected Changes in the Age Distribution of the U.S. Population

6.2.2 Projected Changes in the Geographical Distribution of the U.S. Population

6.2.3 Geographical Distribution of the U.S. Textile and Apparel Manufacturing Employment by County

6.2.4 Apparel Consumption Profiles by State

6.2.5 Apparel Consumption Profiles by Income Level Using Three Dimensional Plots

6.3 Using Animations to Analyze the Dynamic Nature of Time Series Data

6.3.1 Animating Monthly Apparel Consumption to Detect Trends and Outliers

6.3.2 Animating the U.S. Population Projections to Visualize Shifts in Age Distribution

6.4 Programmatically Trying Forecasting Models

6.4.1 Forecasts from NPD Apparel Consumption Data Integrated with Census Population Projections

6.4.2 Forecasts from MRCA Apparel Consumption Data Integrated with Census Population Projections

6.4.3 Interactive Data Analysis and Exploration Utilizing TABIS and SAS/Insight in a Combined Approach

6.5 Evaluating Methods for Accessing TABIS Using Various Networking Techniques

6.5.1 Direct Access From Unix Workstations

6.5.2 Remote Access Using Telnet and X Windows

6.5.3 Remote Access Using Telnet and ASCII

6.5.4 Remote Dial-In Access

6.5.5 World Wide Web (WWW) Access

6.6 Application to Real World Information Needs

6.6.1 Forecasting U.S. Apparel Demand to the Year 2010 by Age and Product Type

6.6.2 Performing Customized Analyses for the American Apparel Manufacturers Association (AAMA)

6.6.4 Recruiting Textile Students by Developing a TABIS World Wide Web (WWW) Page

6.6.5 Using TABIS as a Teaching Tool in Textile Classes

6.6.6 Using TABIS in Graduate Research Projects

7 RECOMMENDATIONS FOR FUTURE WORK

7.1 Training Potential TABIS Users

7.2 Technology Transfer of TABIS to Industry

7.3 Development of a Graphical User Interface

7.4 Database Updates and Enhancements

7.5 Development of Forecasting Models

8 SYNOPSIS

9 LIST OF REFERENCES

10 APPENDICES

10.1 Appendix 1: Paper Published in 1994 SouthEast SAS Users Group (SESUG) Conference Proceedings

10.2 Appendix 2: Paper Published in 1995 SAS Users Group International (SUGI) Conference Proceedings