| description abstract | The purpose of this study is to develop a model for predicting the financial performance of construction companies based on their financial statement data. Several models for predicting financial performance have been developed in the general finance field over the past few decades. However, these conventional models are not always suitable for the construction industry, which operates on a project-based system. While there have been attempts to develop financial models specific to the construction industry, the proposed model in this study stands apart, as it is designed based on the differences between the construction and manufacturing industries. For this research objective, financial variables presumably affecting a construction company’s financial performance are identified through literature review, industry expert interviews, and statistical tests, which explore differences between construction and manufacturing companies’ financial characteristics. Taking the identified variables from these approaches, this study proposed a prediction model for the return on asset and enterprise value per share of construction companies. The prediction model was applied to construction and manufacturing companies’ financial data, and it was verified that it showed significantly higher explanatory power in the construction data. In addition, a panel regression analysis was applied to examine how each variable is correlated with the financial performance of construction companies. Based on the identification of difference between the construction and manufacturing sectors, this study developed a more appropriate explanation model for the financial performance of construction companies. In this regard, this study adds empirical evidence that the factors influencing financial performance vary by industry. Further, the identification of financial variables that affect the performance of construction companies can assist practitioners in establishing investment and financial strategies. | |
