Towards a taxonomy for real estate and land automated valuation systems

Abstract

PurposeAutomated valuation models have been in use at least for the last 50 years in both academia and practice, while automated valuation recently re-emerged as very important with the rise of digital infrastructure. The current state of the art, therefore, justifies the dual contributions of this paper: organising existing knowledge and providing a new framework.Design/methodology/approachThis paper provides much-needed analysis and synthesis of the accumulated body of knowledge by proposing an updated classification of automated valuation approaches based on two criteria, and a taxonomy adapted to new trends. The latter requires a paradigm shift from models to automated valuation systems. Both classification and taxonomy arose after literature review.FindingsThis paper provides a framework for an explicit context under which automated valuation is carried out. To do so, authors propose a definition of automation valuation systems; contextualise the differences among theories, approaches, methods, models and systems present in automated valuation and introduce a classification of automated valuation approaches and a non-hierarchical taxonomy of automated valuation systems.Research limitations/implicationsPerhaps, a systematic literature review process instead of a selective list of 100 references could additionally validate the proposed classification and taxonomy.Practical implicationsThe new framework, underlying various dimensions of the automated valuation process, can help practitioners surpass judging models based purely on their predictive accuracy. Also, the automated valuation system is a more generic term that can better accommodate future research coming from a multitude of disciplines, more diverse business areas and enlarged variety of practical users.Originality/valueThis is the first paper that develops a taxonomy of automated valuation systems.

Leveraging supplementary modalities in automated real estate valuation using comparative judgments and deep learning

“…real estate valuation are used to establish a price estimate for an individual property or parcel of land through a structured decision-making process (Glumac and Des Rosiers, 2020). In its application, an AVM is essentially reliant on the data, the approach, and the method used.…”

“…Computer-aided valuation of properties can be traced back to the 1970s (Carbone and Longini, 1977) and was initially introduced under the term Automated Assessment System (Case, 1978). Today, an Automated Valuation System (AVS) is defined as data analysis software consisting of single or multiple AVMs and a user interface; these elements combined are used to establish a price estimate for an individual property or parcel of land through a structured decision-making process (Glumac and Des Rosiers, 2020). In its application, an AVM is essentially reliant on the data, the approach, and the method used.…”

“…Needless to say, these will be variables that the analyst assumes will have a marginal effect (in statistical terms) on the price of a property. Hedonic-based AVMs, in particular, use pooled information derived from multiple sources like real market transactions, offer data, or other proprietary and non-proprietary data sources (Glumac and Des Rosiers, 2020). Due to the continuous development in the field of Machine Learning and in order to maximize potential data sources, companies and data analysts increasingly extract information from additional modalities, such as visual or textual data (e.g.…”

Real Estate Valuation Models Performance in Price Prediction

“…Nowadays, ANN (as a version of AVM -Automated Valuation Model) is not restricted only to researchers, but it is used by practitioners to estimate value for various purposes, mainly for mortgage lending, and tax purposes (Glumac & Des Rosiers, 2021b). We could also add the review of real estate valuation reports, which is a relevant issue for the valuation profession, as an emerging specialization.…”

Automation of Negative Infrastructural Externalities Assessment Methods to Determine the Cost of Land Resources Based on the Development of a “Thin Client” Model

“…Additionally, the spatial analysis of the territory helps the appraiser to substantiate the obtained result of the assessment, to automate some elements of the assessment and to obtain a more reliable result in a short time [6]. Glumac, B. and Des Rosiers, F. [20] introduced the concept of automated real estate and land valuation systems, described their advantages over automated models and developed their generalization and classification. The authors proposed their own taxonomy, which is not hierarchical, since all systems, in their opinion, are equivalent to each other.…”