Enhancing financial success among electrical contractors
This paper provides electrical contractors with significant information related to enhancing company financial performance. The methodology involves understanding the determinants of contractor financial success through: (1) an extensive literature review; (2) collection of financial- and management-related data from electrical contractors; and (3) analysis of data to identify management trends that are more prevalent in profitable firms. Ninety-six usable responses were collected from small, medium, and larger electrical contracting companies. General trends reveal that more profitable firms place greater emphasis in the areas of certain management initiatives (higher lines of credit and supporting continuing education), marketing initiatives (involvement in formal alliances and partnering), and technology initiatives related to spending more capital resources on computers and software. Significant differences are revealed with financial ratios as well. A Financial Success Scorecard is created for firms to compare their management inputs to those of successful firms. Findings from this study could provide helpful guidelines for nonelectrical contracting firms. Recommendations for achieving future financial success are also provided.
Modeling and Likelihood Prediction of Prefabrication Feasibility for Electrical Construction Firms
AbstractElectrical contracting firms have consistently pursued industrializing their business through the implementation of prefabrication, lean production, and supply chain integration. Despite the pioneering prefabrication efforts of electrical contractors, there is still no clear understanding of the determinants of electrical prefabrication feasibility in terms of supply chain collaboration and surrounding industry requirements. Accordingly, this paper presents the development of prediction models of prefabrication feasibility for electrical contractors. The research tasks of this study were performed in three main phases. The first phase included various data collection tasks, including conducting semistructured interviews, providing an online questionnaire, and obtaining relevant local economic data of the respondents’ metropolitan areas. The second phase involved the utilization of the collected questionnaire responses and economic data to develop logistic regression models that relate the prefabri...
Predicting Contract Surety Bond Claims Using Contractor Financial Data
This paper describes the results of a study to predict contract bond claims based upon contractor financial data. Financial statements of 87 contractors (36 claim and 51 nonclaim) were obtained from four companies underwriting construction-contract surety bonds. A claim contractor was defined as one that defaulted on a bond, many times requiring the surety to pay a loss. A nonclaim contractor was defined as one that has not defaulted on a surety bond. A predictive model was developed using discrete choice modeling. Variables identified in the model are cost monitoring, underbillings/sales, total current liabilities/sales, retained earnings/sales, and net income before taxes/sales. This model predicts the probability of experiencing a claim in the accounting period following the period in which the financial statement was prepared. Considering each variable, recommendations are presented for reducing the probability of claim. Additionally, questions related to the variables have been developed for consideration by the management of construction companies. The model can assist construction-industry professionals by providing them with a quantitative tool to evaluate contractors.