The principle behind sustainable city movements is represented by the idea of “good living”, which is the possibility of having solutions and services that allow citizens to live in an easy, simple, and enjoyable way. Policies for urban quality play a central role in the slow cities manifesto, often suggesting the use of Information and Communication Technologies (ITC) in the development of interactive services for citizens. Among these, an interesting possibility is to offer citizens digital real estate consultancy services through the implementation of automated evaluation methods. An automated appraisal action—which is already complex in itself owing to the need to collect data in a consistent, standardized, but also differentiated way so as to require the adoption of real estate due diligence—collides on the operational level with the concrete difficulty of acquiring necessary data, much more so since the reference market is dark, atypical, and viscous. These operational difficulties are deepened by the epistemological nature of the appraisal discipline itself, which bases its methodology on the forecast postulate, recalling the need to objectify as much as possible the evaluation from the perspective of an intersubjective sharing argument. These circumstances have led, on the one hand, to the definition of internationally accepted uniform evaluation rules (IVS, 2017) and, on the other, to the testing of automated valuation methods aimed at returning computer-based appraisals (AVM). Starting from the awareness that real estate valuation refers essentially to information and georeferences, this paper aims to demonstrate how real estate appraisal analysis can be further improved through information technology (IT), directing real estate valuation towards objectivity in compliance with international valuation standards. Particularly, the paper intends to show the potential of combining geographic information systems (GISs) and building information models (BIMs) in automated valuation methods through the depreciated reproduction cost. The paper also proposes a BIM-GIS semi-automatic prototype based on the depreciated reconstruction cost through an experimentation in Rende (Italy).

The current regulations on the energy certification of buildings represent for the real estate market and the building sector a real cultural revolution. In recent years, the focus on the energy efficiency of buildings has grown exponentially. It is therefore necessary that the property valuations and methodologies used for this purpose bear in mind the energy quality of buildings. This study aims to determine the contribution of an energy performance feature to the real estate property value. This information can help, on the one hand, to understand the energy savings and the corresponding savings income in the property management and, on the other, to control the air pollution from CO₂ emission reduction. The energy performance hedonic price and the CO₂ emission price are appraised in the Market Comparison Approach (MCA).

This research tries to investigate, in the current condition of the Italian real estate market, the economic advantage of investing in energy retrofitting of existing buildings or in expenditure aimed at obtaining higher energy performances in the construction phase of new buildings. A cost-benefit analysis is developed referring to the construction industry entrepreneur. Firstly, the increase in value due to a different measurement of the energy performance of new buildings or newly redeveloped residential buildings is achieved through an innovative statistical approach. Energy performance is measured by taking as a reference the category of energy certification, as required by European legislation. In the estimate of the contribution, the measurement of energy performance, expressed on an ordinal scale, is treated as a categorical variable in the implementation of an iterative regression model, called the alternating least squares model. Afterwards, this contribution is compared to the cost of sustainable building, trying to define a percentage increase in cost compared to a minimum condition according to different and increasing levels of energy performance. In the developed case studies, the comparison between likely benefits and investment spending showed that the entrepreneur would have no convenience at an expense for energy retrofitting while obtaining a positive balance in the construction phase of new buildings. The financial advantage grows if the investment is aimed at achieving the best energy performance and in areas where the price level of the real estate market is lower. The finding can be used as a guide for construction industry investors to make decisions in energy-efficient residential buildings production or transformation.

The proposed evaluation scheme is a uni-equation model to evaluate properties of Mass Appraisal (MA) in terms of widespread availability of sample data. It all allows the use of statistical models and in the opposite conditions of the absence of data of comparable properties, the functions of similar market areas are known as well as the ones near to those for which you want to estimate the function. Of course, the accuracy of the evaluation increases with the amount of available data, with other equal conditions and evaluations carried out without data (but in the presence of other market information). It requires extra-statistical appraisal procedures involving a complete knowledge of the real estate market. However, such knowledge is also required in the MA performed by quantitative models with regard to the data sampling and performance monitoring process. The model considers micro-level characteristics of the properties and macro-level parameters of the real estate market segments. The appraisal model defines the prediction function with both the statistical models and estimation procedures. For this purpose, the model considers four specific situations: the construction of a statistical model operating with a sufficiently large sample of market prices; the construction of a prediction function operating with a very few number of market prices samples; in this situation, the appraisal function of market value is defined by using a sample of market prices referred to comparable properties, and these are few for statistical use but perfectly suitable to the appraisal process; the construction of a prediction function operating with only one market price; the construction of a prediction function operating in the absence of real estate data but with similar functions of market areas with other estimated proprieties. The presented model provides a uniform method of estimating the market value of properties (and fees), through the modular functions. The model studied is able to operate also with reduced information, considering the practical circumstances, the boundary conditions, the application precautions and the significance of the results.

Applied to real estate markets analysis, the resampling methods aim to contribute to the knowledge growth of real estate market dynamics, overcoming the issues related to the data scarcity and operational limits of traditional statistical theory. Among resampling methods, the Bootstrap technique appears to be the most suitable for the interpretation of real estate phenomena. In this study, for residential properties located in Cosenza (Calabria Region, Italy), a Bootstrap approach has been used in order to determine the marginal prices of the real estate characteristics detected, comparing the results with those obtainable with a traditional Multiple Regression Analysis.