## Abstract

The purpose of this chapter is to present data envelopment analysis (DEA) as a two-dimensional plot that permits an easy, graphical explanation of the results. Due to the multiple dimensions of the problem, graphical presentation of DEA results has proven somewhat elusive up to now. Co-Plot, a variant of multidimensional scaling, places each decision-making unit in a two-dimensional space in which the location of each observation is determined by all variables simultaneously. The graphical display technique exhibits observations as points and variables (ratios) as arrows, relative to the same center-of-gravity. Observations are mapped such that similar decision-making units are closely located on the plot, signifying that they belong to a group possessing comparable characteristics and behavior. In this chapter, we will analyze 19 Finnish Forestry Boards using Co-Plot to examine the original data and then to present the results of various weight-constrained DEA models, including that of PCA-DEA.

Original language | American English |
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Title of host publication | Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis |

Publisher | Springer US |

Pages | 171-187 |

Number of pages | 17 |

ISBN (Print) | 9780387716060 |

DOIs | |

State | Published - 2007 |

### Bibliographical note

Funding Information:★ Partially supported by FAPERJ (Proc. E-26/150.715/2003) and by CNPQ, through Edital Universal 01/2002 (Proc. 476817/2003-0).

## Keywords

- Co-Plot
- Data envelopment analysis
- Multi-dimensional scaling