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This research aims to develop conceptual phase building project cost forecasting models by exploring the relationship of existing plan shape complexity indices and general design morphology parameters with total construction cost.

Plan shape indices proposed to date by the literature for measuring building design complexity are critically reviewed. Building morphology is also dictated by town planning restrictions such as plot coverage ratio or number of storeys. This study analyses historical data collected from 49 residential building projects to develop multiple linear regression (MLR) and artificial neural network (ANN) models for forecasting construction cost. Existing plan shape coefficients are calculated to evaluate the geometrical complexity of sampled projects. Ten regression-based cost estimating equations are totally derived from stepwise backward and forward methods, and their predictive accuracy is contrasted: to performance levels reported in past studies and to ANN models developed in this research with multilayer perceptron architecture.

Analysis of plan shape indices revealed that 85.7% of examined past projects possess a high degree of design complexity, hence resulting in expensive initial decisions. This highlights the need for more effective early design stage decision-making by developing new building economic tools. The most accurate regression model, with a mean absolute percentage error (MAPE) of 19.2%, predicts the log of total cost from wall to floor index and total building envelope surface. Other explanatory variables resulting in MAPE values in the order of 20%–22% are total volume, volume above ground level, gross floor area below ground level, gross floor area per storey and total number of storeys. The overall MAPE of regression-based equations is 24.3% whilst ANN models are slightly more accurate with MAPE scores of 21.8% and 21.6% for one hidden and two hidden layers, respectively. The most accurate forecasting model in the research is the ANN with two hidden layers and the sigmoid activation function which predicts total building cost from total building volume (19.1%).

This paper introduces MLR-based and ANN-based conceptual construction cost forecasting models which are founded solely on building morphology design parameters and compare favourably with previous studies with an average predictive accuracy less than 25%. This paper is expected to be beneficial to both practitioners and academics in the built environment towards more effective cost planning of building projects. The methodology suggested can further be implemented in other countries provided that accurate and relevant data from historical projects are used.

The main purpose of this paper is the incorporation of life-cycle costs (LCC) and whole-life costing (WLC) method and the taxation environment into the investment appraisal procedure for commercial real property projects.

The paper initially presents the methodologies of LCC and WLC together with the NPV measure for the evaluation of real estate investments. These methods are incorporated into a decision-making model using mathematical approaches. The model is applied to a typical commercial property project (office building) in order to explore the significance of impacts from changes in structured variables and the taxation environment by introducing direct, indirect and property taxes in the evaluation of commercial real estate projects.

Testing of the methodology on the Greek economic environment revealed that time, cost, the tax regime, the financial variables of funding and the monetary and fiscal environment in a commercial real property project are the main variables of net present value (NPV) of the investment.

From the calibration of any impact from affected variables, decision-making aiding tools can be extracted for controlling the project throughout its entire life-cycle.

An integrated WLC mathematical model for the investment appraisal of commercial property projects is introduced. The herein proposed methodology contributes to taxation policy and real estate theory in general and assists industry professionals in effective commercial property management and decision-making.