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The Department of Industrial and Systems Engineering
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This page was last updated on July 22, 2006.
Biographical Sketch
Andrew Johnson has recently completed a Ph.D.
degree in the Department of Industrial and Systems Engineering (ISyE) at Georgia Institute of
Technology (GT). He received a Master
of Science Degree (2002) from Georgia Tech, and a Bachelor of Science Degree
(2001) in the Department of Industrial and
Systems Engineering at Virginia
Polytechnic Institute and State University. His research interests
include applied operations research, productivity and efficiency measurement,
mircoeconomics, warehouse design, material handling and Internet based database
applications. He is a member of the German
Club of Virginia Tech, Instintute of Industrial Engineers (IIE), National Eagle Scout Association and
Tau Beta Pi (TBP).
Research
Abstract: A set of technical issues are addressed related to benchmarking best practice and performance in warehouses. In order to identify best practice, first performance needs to be measured. There are a variety of tools available to measure productivity and efficiency. One of the most common tools is data envelopment analysis (DEA), which assesses individual performance relative to a peer group. For a system that consumes inputs to generate outputs, previous work in production theory can be used to develop basic postulates about the production possibility space and to construct an efficient frontier which is used to quantify efficiency. Beyond inputs and outputs warehouses typically have practices (techniques used in the warehouse) or attributes (characteristics of the environment of the warehouse including demand characteristics) which also influence efficiency. Previously in the literature, a two-stage method has been developed to investigate the impact of practices and attributes on efficiency. When applying this method to two sets of warehouse data, two issues arose: how to measure efficiency in small samples and how to identify outliers. The small sample efficiency measurement method developed in this thesis is called multi-input / multi-output quantile based approach (MQBA) and uses deleted residuals to estimate efficiency. The outlier detection method developed in this thesis introduces the inefficient frontier. Both overly efficient and overly inefficient outliers can be identified by constructing an efficient and an inefficient frontier. The outlier detection method incorporates an iterative procedure previously described, but not implemented in the literature. Further, this thesis also discusses issues related to selecting an orientation in super efficiency models. Super efficiency models are used in outlier detection, but are also commonly used in measuring technical progress via the Malmquist index. These issues are addressed using two data sets recently collected in the warehousing industry. The first data set consists of 390 observations of various types of warehouses. The other data set has 25 observations from a specific industry. For both data sets, it is shown that significantly different results are realized if the methods suggested in this document are adopted.
Keywords: Distribution center,
productivity, efficiency, DEA.
Advisors: My advisor
representing manufaturing and logistics is Dr. Leon McGinnis.
For a comprehensive list of the other works that I have been involved with,
see my curriculum vitae.
My SSRN
Author Page
Present Position
I was a Research Assistant in the Virtual
Factory Lab (VFL), Georgia Institute of Technology until May
2006. Beginning this fall I will be an assistant professor in the Industrial and Systems Engineering
Department of Texas A&M. The
project I am currently involved in is iDEAs. Since early 1990, the Georgia Tech faculties
have been exploring new methods for performance assessment of industrial
systems with particular emphasis on warehousing operations. The methodology being
developed is related to data envelopment analysis (DEA). iDEAs makes the DEA
methodology accessible via the internet, and enables firms to perform a
self-assessment and benchmark themselves against other firms in their industry.
Recalling "Garbage In, Garbage Out," the self-assessment is only as
good as the data supplied. Click here to learn more about iDEAs.
Conference Presentations
Integrating Theory and Methods for System Performance Assessment, poster presentation, NSF Design, Service and Manufacturing Grantees and Research Conference, St. Louis MO July 2006
An Application of the Hyperbolic Oriented Efficiency Measure to Outlier Detection, North American Productivity Workshop (NAPW), NY June 2006
Performance
Measurement and Benchmarking with Applications to Warehousing, Young
Researchers Conference at
A Tool to Help Warehouses
Measure and Benchmark Performance, presented at Expo Logistica in
Estimates on the Data Requirements to
Define the Production Frontier for Warehouses, presented at IIE’s national meeting in
Warehouse Operations: Performance Assessment and Benchmarking,
presented at ProMat 2005 Material Handling and Logistics Trade Show in Chicago , IL
A Reference Model for Order Picking,
presented at INFORMS national meeting in
Outside Links