A Sectoral Performance Evaluation: DEA and Logistic Regression Approach
A Sectoral Performance Evaluation: DEA and Logistic Regression Approach

Summary/Abstract: The main purpose of this study is to analyze the efficiency and productivity levels of leading companies operating in the Turkish white goods sector and to reveal the financial determinants affecting these levels. In the study, seven white goods manufacturing companies were examined with data covering the period 2015–2022. The technical and total efficiencies of the companies were measured with Data Envelopment Analysis (DEA); and productivity changes over time were evaluated through the Malmquist Total Factor Productivity (TFP) Index. Financial indicators affecting efficiency were tested using the binary logistic regression model. The findings show that the companies generally remained below the full efficiency level, but there was a slight increase in their productivity over time. While the main source of this increase was technological change, decreases in technical efficiency limited productivity gains in some periods. According to the regression analysis, while ratios such as profitability and receivables turnover have a positive and significant effect on efficiency, financial leverage and tangible fixed asset density have a negative effect. The results obtained reveal that technological investments should be increased, the debt structure should be carefully managed and financial performance indicators should be improved in order to ensure the sustainable growth and competitiveness of the sector.

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