Dynamic DEA Slack-Based Model

Overview

This repository contains Python code replicating the Dynamic DEA Slack-Based Model proposed by Tone & Tsutsui's (2010). The Dynamics SBM DEA is a DEA model widely used for analyzing the evolving structure of dynamic networks. This project aims to provide an open-source implementation for researchers and practitioners interested in understanding and applying the Dynamic SBM.

A brief summary of the Dynamic DEA Slack-Based model (Tone & Tsutsui's, 2010):

The SBM model is non-radial and can deal with inputs/outputs individually, contrary to the radial approaches that assume proportional changes in inputs/outputs. Furthermore, according to the characteristics of carry-overs, we classify them into four categories, i.e. desirable, undesirable, free and fixed. Desirable carry-overs correspond, for example, to profit carried forward and net earned surplus carried to the next term, while undesirable carry-overs include, for example, loss carried forward, bad debt and dead stock. Free and fixed carry-overs indicate, respectively, discretionary and non-discretionary ones.

Table of Contents

• Installation
• Usage
• Example
• Reference
• Documentation
• Contributing
• License

Installation

1. Clone the repository:

   git clone https://github.com/georgia-max/DynamicsSBM.git 

2. Navigate to the project directory:

   cd DynamicSBM

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

• First Step: Download the Sample Dataset Folder Here, and add them to the folder.
• Second Step: To run the test code, check out Jupyter Notebook DSBM_DEA_function_example.ipynb for step-by-step guidelines.

Example

cd DynamicSBM
python ./Main.py

Reference

1. Tone, K., & Tsutsui, M. (2010). Dynamic DEA: A slacks-based measure approach. Omega, 38(3-4), 145-156.