index.Rmd

---
title: "Data Envelopment Analysis Using R"
author: "Timothy R. Anderson"
date: "`r Sys.Date()`"
output: pdf_document
header-includes:
  - \usepackage{imakeidx}
  - \makeindex
bibliography: book.bib
biblio-style: apalike
link-citations: yes
colorlinks: yes
lot: yes
lof: yes
site: bookdown::bookdown_site
description: An introduction to data envelopment analysis using R.
github-repo: "prof-anderson/DEA_Using_R"
graphics: yes
documentclass: krantz
---

```{r setup1, include=FALSE}
knitr::opts_chunk$set(tidy = FALSE)
options(htmltools.dir.version = FALSE)

# in line 5, change output to 
#output: pdf_document

```

# Preface {.unnumbered}

This book uses R, rmarkdown, and bookdown to create a living book for the field of Data Envelopment Analysis. There are many other books out there on DEA. This book explains issues in building your own toolset for DEA in R. It will also cover some of the challenges to watch out for along the way. The majority of the book emphasizes how to implement a variety of DEA models in R. This is generally done with a focus on readability rather than computational efficiency. Pedagogically, this enables the reader to appreciate how tools work and not simply treat a program for doing DEA as a black box. Later chapters demonstrate the use of a variety of DEA R packages and richer applications.

Along the way, readers may learn some optimization and gain fluency with R.

There are multiple target audiences for this book. The first audience would be people wanting to use DEA that are familiar with R. These readers will see how to do linear programming and DEA. The emphasis on building R models will enable the development of new DEA models in R.

Readers unfamiliar with R but knowledgeable about DEA may use this book as an opportunity to learn about R.

This book can be used as a supplement for a graduate course on productivity analysis with papers drawn from the literature.

All of the code for the book is available in a github repository at <https://github.com/prof-anderson/DEA_Using_R>.

## Instructor Notes {.unnumbered}

This book can be used in support of an advanced elective or graduate course to help people understand the approach and implementation of Data Envelopment Analysis. This can be then supplemented by readings and projects associated with the specific application area(s) of interest such as health care, education, manufacturing, economics, or government policy.

## Acknowldegements {.unnumbered}

This book has benefited from the interactions of many people over the years. In particular, I would like to thank the following students and graduates from over the recent years that have made direct or indirect contributions to this effort.

-   Tim Calderwood
-   Jiali Ju
-   Tom Shott
-   Kevin van Blommestein
-   Ambica Sogal
-   Navdeep Singh
-   William (Ike) Eisenhauer
-   Riad Alharithi
-   Ketsaraporn Kaewkhiaolueang
-   Saumya Saxena
-   Isa Mostachetti
-   Duane Murray

I would also like to thank earlier doctoral graduates for rich mutual interactions:

-   Dr. Janice Forrester
-   Dr. Gerald Williams
-   Dr. Lane Inman
-   Dr. Scott Leavengood
-   Dr. Dong-Joon Lim
-   Dr. Maoloud Dabab
-   Dr. Nina Chaichi
-   Dr. Aurobindh Kalathil Puthanpura

Various colleagues have helped over the years including:

-   Dr. John Ruggiero
-   Dr. Shawna Grosskopf
-   Dr. Rolf Fare
-   Dr. Chester Ismay
-   Dr. Andy Johnson
-   Dr. Ole Olesen
-   Dr. K. Louis Luangkesorn
-   Dr. Jili Hu
-   Dr. Joe Zhu
-   Dr. Larry Seiford

In particular, the frequent discussions of DEA at INFORMS have been very helpful.

Also, this work makes extensive use of the `ompr` package authored by Dirk Schumacher. The rich algebraic modeling capabilities of `ompr` have made this book significantly more accessible.

I want to thank Dr. Gunter Sharp and Dr. Ronald Bohlander for their support during my time at the Georgia Institute of Technology along with Dr. Steven Hackman who introduced me to DEA.

Lastly, I would like to thank my family, Carrie, Trent, and Paige. Their patience as Dad toiled at the computer over the years was always appreciated.

> Tim Anderson `r Sys.Date()`