Evaluating the site-selection process for photovoltaic (PV) plants is essential for securing available areas for solar power plant installation in limited spaces. Although the vicinities of highway networks can be suitable for installing PV plants, in terms of economic feasibility, they have rarely been investigated because the impacts of various factors, including geographic or weather patterns, have not been analyzed. In this respect, this study conducts a case study on selecting the site for PV-panel installation in the vicinity of a highway (e.g., slopes) by integrating geographic information system (GIS) and building information model (BIM) techniques. Using location (e.g., highways, lakes, rivers), monthly solar power output, and orographic (e.g., slope) data, suitable regions are identified with the geo-spatial analysis; then, the amount of power that can be generated is evaluated in the regions. For the proposed sites, the surface conditions and potential PV systems are transformed and visualized in a BIM environment. In the results, the power output at optimal sites selected from the case area was computed at a total of 8227 MWh and was transformed into solar-panel families in three-dimensional environments. Thus, this study may help to identify optimal sites for PV plants in the unused areas near highways.

Construction projects are complex as various project entities involve and collaborate with each other. This complexity not only causes issues such as project delays but also makes it difficult to manage projects. Previous research has often used productivity and efficiency interchangeably, but they are not the same. The field of construction efficiency has not been fully studied to understand its entire potential in a practical context. Toward this end, this research aims to support efficient construction project management by exploring the inefficiency factors as well as identifying the perception gaps between different occupations and the interrelationships between the factors. Twenty inefficiency factors were identified through a comprehensive literature review; then, the importance of the factors and the perception gaps among stakeholders were studied by analyzing online survey data using RII (relative importance index), Welch’s t-test, and factor analysis. In addition, interviews with field engineers and managers allowed us to explore cause-and-effect relationships among the factors and determine triggering and critical factors based on their chain reactions. This research found that a major perception gap among project stakeholders was in the factor of unrealistic scheduled dates. The research contributes to project risk management and strategic planning for construction project efficiency.