MacLeamy's time-effort distribution curves are amongst the most oft-cited sources for researchers interested in mainstreaming Building Information Modeling (BIM) implementation in the architecture, engineering, and construction (AEC) industry. Succinctly, the curves offer a clever answer to the question: How can BIM benefit AEC processes? However, despite their significant theoretical and practical value, little previous research has been conducted to elaborate the time-effort distribution curves of any real-life projects. This research aims to demystify the time-effort distribution curves through comparison of a representative BIM project and a non-BIM project. Applying a set of innovative approaches, the actual time-effort distribution curves of two public housing construction projects in Hong Kong are produced and analyzed in-depth. The curves vividly show that BIM implementation increases the effort spent at design stagethat is, throughout the architecture and engineering processes,but the extra effort pays off at the building stage. Further, the curves are found to be a useful graphical analytic tool for other purposes, such as adjusting the fee structure amongst AEC processes and informing improved BIM adoption.
This study investigates the roles of developer’s status and competitive intensity in presale pricing in residential markets. The study examines various competitive factors in Hangzhou, China, within a spatial-temporal framework. These factors include competitive intensity and developer’s status, plus two independent variable groups: external attributes and project features. To overcome the shortcomings of traditional valuation methods, the estimation makes use of spatial and temporal data via three different approaches. They are the Geographically and Temporally Weighted Regressions (GTWR), Spatial Temporal Hedonic Model (STHM) and Spatial Temporal Autoregressive Model (STAR). The analysis reveals that there exists spatial and temporal dependence in the Hangzhou real estate market. Not only does this study provide new findings and a better understanding of the factors affecting presale pricing, but it also offers valuable implications about competitive intensity for policymakers and urban planners in the spatio-temporal context.
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