EVALUATION OF RELATIVE EFFICIENCY OF BUSINESSES BY USING DATA ENVELOPMENT ANALYSIS: AN APPLICATION TO MANUFACTURING INDUSTRY
In study, quarterly data of year 2012 gathered from financial reports of 26 businesses –of which stocks being traded in Borsa İstanbul- operating through a sub-sector of manufacturing industry, namely “Stone and Earth Industry” was evaluated. Performance analysis of business is very vital on one han...
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | article |
| Lenguaje: | DE EN FR TR |
| Publicado: |
Fırat University
2019
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/83cc84b662154209b9bd7936fdb6c4db |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | In study, quarterly data of year 2012 gathered from financial reports of 26 businesses –of which stocks being traded in Borsa İstanbul- operating through a sub-sector of manufacturing industry, namely “Stone and Earth Industry” was evaluated. Performance analysis of business is very vital on one hand for business owners or employers, managers, competitors and creditors and current and potential investors on the other. The aim of study is to evaluate performance of aforementioned businesses and make a comparison between their performance rates. In this context, Data Envelopment Analysis (DEA) is used to evaluate business efficiency, relative efficiency of input-output and determination of decision-making units. As Data Envelopment Analysis is relevant to input and output, input and output data included in study was collected in accordance with literature. Ratios such as current ratio, acid-test ratio, receivable turnover ratio, stock turnover ratio and total debt to total asset ratio were used as input data while ratios like net profit to total asset ratio, net profit to equity ratio and net profit to net sales ratio were used as output data. After analysis, full efficient firms were determined and necessary increase or decrease rates for input and output data were established in order to transform inefficient firms into efficient ones. In addition, it was shown that some firms were efficient during all periods while some others had varying levels of efficiency periodically. |
|---|