In this paper, we present a benchmarking study of industrial transportation companies traded in the New York Stock Exchange (NYSE). There are two distinguishing aspects of our study: First, instead of using operational data for the input and the output items of the developed Data Envelopment Analysis (DEA) model, we use financial data of the companies that are readily available on the Internet. Secondly, we visualize the efficiency scores of the companies in relation to the subsectors and the number of employees. These visualizations enable us to discover interesting insights about the companies within each subsector, and about subsectors in comparison to each other. The visualization approach that we employ can be used in any DEA study that contains subgroups within a group. Thus, our paper also contains a methodological contribution.

Ulus, F., Kose, O, Ertek, G. and Sen, S. (2006). “Financial benchmarking of transportation companies in the New York Stock Exchange (NYSE) through data envelopment analysis (DEA) and visualization.” 4th International Logistics and Supply Chain Congress, İzmir, Turkey.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

Download
Financial Benchmarking Of Transportation Companiesin The New York Stock Exchange (nyse) Throughdata Envelopment Analysis (dea) And Visualization

Dr. Gürdal Ertek recommends the following related books:

Business Ratios and Formulas: A Comprehensive Guide Hardcover – April 3, 2012

Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References 2006th Edition

 

 

 

Data Envelopment Analysis (DEA) is a mathematical methodology for benchmarking a group of entities in a group. The inputs of a DEA model are the resources that the entity consumes, and the outputs of the outputs are the desired outcomes generated by the entity, by using the inputs. DEA returns important benchmarking metrics, including efficiency score, reference set, and projections. While DEA has been extensively applied in supply chain management (SCM) as well as a diverse range of other fields, it is not clear what has been done in the literature in the past, especially given the domain, the model details, and the country of application. Also, it is not clear what would be an acceptable number of DMUs in comparison to existing research. This paper follows a recipe-based approach, listing the main characteristics of the DEA models for supply chain management. This way, practitioners in the field can build their own models without having to perform the detailed literature search. Further guidelines are also provided in the paper for practitioners, regarding the application of DEA in SCM benchmarking.

Ertek, G., Akyurt, N., Tillem, G., 2012, “Dea-based benchmarking models in supply chain management: an application-oriented literature review”, X. International Logistics and Supply Chain Congress 2012, November 8-9, Istanbul, Turkey.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

Download
Dea-based Benchmarking Models In Supply Chain Management: An Application-oriented Literature Review

Download SUPPLEMENT Data
Supplement Data

Dr. Gürdal Ertek recommends the following related books:

• Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References 2006th Edition
• Supply Chain Management (5th Edition) 5th Edition