The Evaluation of Financial Performances of Logistics Companies in Turkey: A Data Envelopment Analysis Approach

In this study, the financial performance of 10 logistics companies operating in the storage, transport and logistics services sector in Turkey is evaluated for years from 2011 to 2017 by using the Data Envelopment Analysis (DEA) method. In accordance with the purpose of the study, the input variables are composed of variables such as total assets, equity, number of employees whereas the output variables are net sales, profit before interest and tax, amount of exports. In measuring the financial performances of firms listed in the data set, the Charnes, Cooper, Rhodes (CCR) model based on the assumption of constant returns to scale and the Banker, Charnes, Cooper (BCC) model based on the assumption of variable return to scale are employed in the input-oriented DEA model. As a result of our study, efficient and ineffective logistics companies are identified for years from 2011 to 2017. The reference sets for ineffective companies are determined, and the extent to which ineffective companies should improve according to the companies they refer to is determined. The results of DEA CCR-I model suggests that 2015 has the highest number of active companies (7). The year in which the average efficiency scores of the companies is the highest (89.2%) is 2016. According to the DEA BCC-I model, 2015 is associated with the largest number of active firms (9) and the average productivity scores of these firms are the highest (99.1%) in that particular year.

Anahtar Kelimeler:

Lojistik, Firma performansı, Veri Zarflama Analizi, Doğrusal Programlama

The Evaluation of Financial Performances of Logistics Companies in Turkey: A Data Envelopment Analysis Approach

In this study, the financial performance of 10 logistics companies operating in the storage, transport and logistics services sector in Turkey is evaluated for years from 2011 to 2017 by using the Data Envelopment Analysis (DEA) method. In accordance with the purpose of this study, the input variables are selected as total assets, equity and number of employees whereas the output variables are net sales, profit before interest and tax and amount of exports. In measuring the financial performances of firms listed in the data set, the Charnes, Cooper, Rhodes (CCR) model based on the assumption of constant returns to scale and the Banker, Charnes, Cooper (BCC) model based on the assumption of variable return to scale are employed in the input-oriented DEA model. As a result of our study, efficient and ineffective logistics companies are identified for years from 2011 to 2017. The reference sets for ineffective companies are determined, and the extent to which ineffective companies should improve according to the companies they refer to is determined. The results of DEA CCR-I model suggests that 2015 has the highest number of active companies (7). The year in which the average efficiency scores of the companies is the highest (89.2%) is 2016. According to the DEA BCC-I model, 2015 is associated with the largest number of active firms (9) and the average productivity scores of these firms are the highest (99.1%) in that particular year.

Keywords:

Logistics, Firm Performance, Data Envelopment Analysis, Linear Programming,

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