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Abdalla, A, Li, X and Yang, F (2024) Expatriate construction professionals' performance in international construction projects: The role of cross-cultural adjustment and job burnout. Journal of Construction Engineering and Management, 150(03).
Chen, S, Chen, D, Li, L, Miramini, S and Zhang, L (2024) Optimized bridge maintenance strategies: A system reliability-based approach to enhancing road network performance. Journal of Construction Engineering and Management, 150(03).
Do, Q, Le, T and Le, C (2024) Uncovering critical causes of highway work zone accidents using unsupervised machine learning and social network analysis. Journal of Construction Engineering and Management, 150(03).
Gu, J and Guo, F (2024) Promoting digital sustainability through project digital responsibility implementation: An empirical analysis. Journal of Construction Engineering and Management, 150(03).
Guo, J and Kato, H (2024) Role of government equity investment in capital structure of project finance: Global evidence from PPP projects in developing countries. Journal of Construction Engineering and Management, 150(03).
Halder, A and Batra, S (2024) Navigating the ethical discourse in construction: A state-of-the-art review of relevant literature. Journal of Construction Engineering and Management, 150(03).
Harode, A, Thabet, W and Leite, F (2024) Formulation of feature and label space using modified Delphi in support of developing a machine-learning algorithm to automate clash resolution. Journal of Construction Engineering and Management, 150(03).
Heydari, M, Heravi, G, Raeisinafchi, R and Karimi, H (2024) A dynamic model to assess the role of site supervision systems in the safety performance of construction projects. Journal of Construction Engineering and Management, 150(03).
Ibrahim, A, Nnaji, C, Namian, M and Shakouri, M (2024) Evaluating the impact of hazard information on fieldworkers' safety risk perception. Journal of Construction Engineering and Management, 150(03).
Ko, T, Lee, J and David Jeong, H (2024) Project requirements prioritization through NLP-driven classification and adjusted work items analysis. Journal of Construction Engineering and Management, 150(03).
Lee, D, Nie, G Y and Han, K (2024) Automatic and real-time joint tracking and three-dimensional scanning for a construction welding robot. Journal of Construction Engineering and Management, 150(03).
Li, Q, Yang, Y, Yao, G, Wei, F, Xue, G and Qin, H (2024) Multiobject real-time automatic detection method for production quality control of prefabricated laminated slabs. Journal of Construction Engineering and Management, 150(03).
Oguz Erkal, E D, Hallowell, M R, Ghriss, A and Bhandari, S (2024) Predicting serious injury and fatality exposure using machine learning in construction projects. Journal of Construction Engineering and Management, 150(03).
Qureshi, A H, Alaloul, W S, Murtiyoso, A, Hussain, S J, Saad, S and Musarat, M A (2024) Automated scaling of point cloud rebar model via aruco-supported controlled markers. Journal of Construction Engineering and Management, 150(03).
Rajabi Asadabadi, M and Zwikael, O (2024) Unrealistic project goals: Detection and modification. Journal of Construction Engineering and Management, 150(03).
Sadeghi, N, Dehghani, M S and Ingolfsson, A (2024) Choice of probability distributions for activity durations in project networks with limited sample size. Journal of Construction Engineering and Management, 150(03).
Seo, W, Kim, B, Bang, S and Kang, Y (2024) Identifying key financial variables predicting the financial performance of construction companies. Journal of Construction Engineering and Management, 150(03).
- Type: Journal Article
- Keywords: artificial neural network; construction company; financial performance; industry difference; panel regression
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-13959
- 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.
Tarekegn Gurmu, A and Mahmood, M N (2024) Critical factors affecting quality in building construction projects: Systematic review and meta-analysis. Journal of Construction Engineering and Management, 150(03).
Withrow, J, Dadi, G, Nassereddine, H and Sturgill, R (2024) Asphalt material e-ticketing workflow: Qualitative and quantitative analysis. Journal of Construction Engineering and Management, 150(03).
Zhang, Y, Ren, X, Zhang, J and Ma, Z (2024) A method for deformation detection and reconstruction of shield tunnel based on point cloud. Journal of Construction Engineering and Management, 150(03).