Assist. Prof. Dr. Omar Mohammed Nasser Al-Ashari, a faculty member in the Department of Operations Research at our College, has published a joint research paper with student Dhamia Hamed in a Scopus-indexed journal, entitled:
“Measuring Technical Efficiency Using Stochastic Frontier Analysis (SFA) for the Factories of the Iraqi General Cement Company.”
The study aims to measure technical efficiency and evaluate the performance of the factories of the Iraqi General Cement Company using the Stochastic Frontier Analysis (SFA) technique. This approach provides a means of identifying the extent to which factories efficiently perform their activities and utilize their available resources. The study was conducted at the Iraqi General Cement Company during 2023 and covered a sample of 13 factories out of a total of 18 factories.
The researchers employed parametric methods, represented by the Stochastic Frontier Analysis (SFA) model. The Cobb–Douglas production function was used to estimate input productivity, while technical efficiency was analyzed and measured using the stochastic production frontier, with the assistance of the Frontier 4.2 software.
The results revealed that, out of the 13 factories included in the study, only three factories—Najaf, Samawah, and Sinjar—achieved a relatively acceptable level of efficiency, although none reached full efficiency of 100%. These factories accounted for 23% of the total factories covered by the study, which is considered a low proportion. The more efficient factories may therefore serve as benchmarks for improving performance and rationalizing the use of resources (inputs) in the less efficient factories.
The estimation results obtained using the stochastic frontier model also demonstrated that the independent variables (inputs), namely capital, the value of raw materials, and energy and fuel, had a positive and statistically significant effect on the technical efficiency of cement production.
Furthermore, the estimated average technical efficiency reached 0.751, equivalent to 75.1%, indicating considerable potential for improving the technical efficiency of the factories.
The study concluded that the Maximum Likelihood Estimation (MLE) method is more appropriate than the Ordinary Least Squares (OLS) method for estimating the stochastic frontier model. The OLS method is based on determining the values that minimize the sum of squared deviations between the observed values and the values predicted by the frontier function.
The study highlights the importance of adopting quantitative and econometric approaches to assess industrial efficiency and identify opportunities for improving resource utilization and production performance in the cement industry.
