Assessment of the expected construction company’s net profit using neural network and multiple regression models
Net profit is an important financial performance indicator for any construction firm. Firm financial managers should strive to maximize this net profit. Modeling company’s net profit helps to investigate the serious effects of the different financial conditions on the expected net profit for the con...
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447912001165 |
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doaj-2e061f0c691a4422bf238444697ef4c82021-06-02T02:34:54ZengElsevierAin Shams Engineering Journal2090-44792013-09-014337538510.1016/j.asej.2012.11.008Assessment of the expected construction company’s net profit using neural network and multiple regression modelsH.H. MohamadA.H. IbrahimH.H. MassoudNet profit is an important financial performance indicator for any construction firm. Firm financial managers should strive to maximize this net profit. Modeling company’s net profit helps to investigate the serious effects of the different financial conditions on the expected net profit for the construction companies working in the Egyptian market. It simply helps financial managers to make sure that their companies business operations are running in a profitable manner. This research aims to develop a mathematical model for assessing the expected net profit of any construction company. To achieve the research objective, four steps were performed. First, the main factors affecting firms’ net profit were identified. Second, pertinent data regarding the net profit factors were collected. Third, two different net profit models were developed using the Multiple Regression (MR) and the Neural Network (NN) techniques. The validity of the proposed models was also investigated. Finally, the results of both MR and NN models were compared to investigate the predictive capabilities of the two models.http://www.sciencedirect.com/science/article/pii/S2090447912001165Construction company’s net profitNeural networkMultiple regressions |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
H.H. Mohamad A.H. Ibrahim H.H. Massoud |
spellingShingle |
H.H. Mohamad A.H. Ibrahim H.H. Massoud Assessment of the expected construction company’s net profit using neural network and multiple regression models Ain Shams Engineering Journal Construction company’s net profit Neural network Multiple regressions |
author_facet |
H.H. Mohamad A.H. Ibrahim H.H. Massoud |
author_sort |
H.H. Mohamad |
title |
Assessment of the expected construction company’s net profit using neural network and multiple regression models |
title_short |
Assessment of the expected construction company’s net profit using neural network and multiple regression models |
title_full |
Assessment of the expected construction company’s net profit using neural network and multiple regression models |
title_fullStr |
Assessment of the expected construction company’s net profit using neural network and multiple regression models |
title_full_unstemmed |
Assessment of the expected construction company’s net profit using neural network and multiple regression models |
title_sort |
assessment of the expected construction company’s net profit using neural network and multiple regression models |
publisher |
Elsevier |
series |
Ain Shams Engineering Journal |
issn |
2090-4479 |
publishDate |
2013-09-01 |
description |
Net profit is an important financial performance indicator for any construction firm. Firm financial managers should strive to maximize this net profit. Modeling company’s net profit helps to investigate the serious effects of the different financial conditions on the expected net profit for the construction companies working in the Egyptian market. It simply helps financial managers to make sure that their companies business operations are running in a profitable manner.
This research aims to develop a mathematical model for assessing the expected net profit of any construction company. To achieve the research objective, four steps were performed. First, the main factors affecting firms’ net profit were identified. Second, pertinent data regarding the net profit factors were collected. Third, two different net profit models were developed using the Multiple Regression (MR) and the Neural Network (NN) techniques. The validity of the proposed models was also investigated. Finally, the results of both MR and NN models were compared to investigate the predictive capabilities of the two models. |
topic |
Construction company’s net profit Neural network Multiple regressions |
url |
http://www.sciencedirect.com/science/article/pii/S2090447912001165 |
work_keys_str_mv |
AT hhmohamad assessmentoftheexpectedconstructioncompanysnetprofitusingneuralnetworkandmultipleregressionmodels AT ahibrahim assessmentoftheexpectedconstructioncompanysnetprofitusingneuralnetworkandmultipleregressionmodels AT hhmassoud assessmentoftheexpectedconstructioncompanysnetprofitusingneuralnetworkandmultipleregressionmodels |
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