Purpose: The purpose of this paper is to inform project management practice on the business benefits of building information modelling (BIM) adoption.Design/methodology/approach: BIM needs to compete against well‐ingrained methods to deliver projects in a fragmented and rather traditional industry. This paper investigates 47 value propositions for the adoption of BIM under a multiple case study investigation carried out in Australia and Hong Kong. The selected case study projects included a range of public (1) and private (4) sector building developments of small and large‐scale. Findings are coded, interpreted and synthesised in order to identify the challenges and business drivers, and the paper focuses mainly on challenges and benefits for architectural and engineering consultants, contractors and steel fabricators. As a condition for the selection criteria all case studies had to be collaborating by sharing BIM data between two or more consultants/stakeholders. As practices cannot afford to ignore BIM, this paper aims to identify those immediate business drivers as to provoke debate amongst the professional and academic community.Findings: Shared understanding on business drivers to adopt BIM for managing the design and construction process of building projects raging from small commercial to high‐rise.Originality/value: The originality of the research reported in this paper is that it breaks from a proliferating series of articles on BIM as industry “aspiration” and as a “marketing” statement. The elicited drivers for BIM underwent industry, academic and peer validation.

This study presents a comprehensive analysis of the costs and benefits of the two main construction methods in the prefabricated homes category: panelized and modular. The main goal is to provide a framework of the implications and tradeoffs of both construction methods for single family homes, as well as determine which is more cost effective. The methodology consists of a qualitative analysis that includes the overview of the benefits of each construction method over the other, and quantitative analysis which compares the cost of the finished homes per square foot to determine which one is more cost effective. Both analyses are conducted by evaluating two case studies of single family homes with similar characteristics, one built with panels and the other with modules. The benefits identified for panelized homes have to do with transportation, equipment and machinery, and insulation technology; on the other hand, the benefits for modular homes are related to quality control, on-site work and trades. The quantitative results showed that the modular construction method is only marginally more cost effective than the panelized construction method under the given circumstances. As a second part of the quantitative analysis, the panel case study was calculated as if it would be built with modules, and the results of both analyses were consistent, but both with the same limitations. Through the proposed method, it is possible to evaluate the cost effectiveness of the two construction methods for single family prefabricated home projects which could serve as a valuable tool for decision making

In improving energy efficiency of buildings, windows play a significant role as they largely influence the energy load. Although there are many studies about the energy efficient window design, a rigorous study is missing which analyzes the mutual impact of windows’ size, position and orientation on the energy load. This study aims to address this gap through a case study on a single family house. For this aim, 65 different design scenarios are created which vary by window size, position and orientation. Building information models (BIMs) are created for each scenario via Autodesk Revit®, and are used for the calculation of the total energy load conducted by Autodesk Green Building Studio®. In the first analysis stage, window-to-wall ratio (WWR) and the windows’ position are studied to assess their effect on the energy load. The preliminary results at this stage indicate that the total energy load increases when the WWR grows, and the windows’ position has the biggest impact on the load when the WWR is 20. Using these results, in the next stage, the position of windows in different orientation is studied to assess how the energy load changes by windows’ position in each orientation. The results show that the building requires the lowest load when the windows are located in the middle height in all orientations, and the east windows’ positioning affects the total energy load the most