Maurizio d’Amato

Life cycle process model of a market-oriented and student centered higher education

There is not a single definition/explanation about market-orientation education. Two opposite definitions/explanations of pure market-oriented education ( Cato , 2010) and social-market-oriented education (Amaratunga, 2009) are provided in the paper. Integrated multiple criteria analysis at the micro-, meso- and macro-levels are needed to increase efficiency of the market-oriented higher education reforms. Market-oriented higher education reforms management involves numerous aspects that should be considered in addition to making educational, pedagogical, didactical, economic, political and legal/regulatory decisions. These must include social, culture, ethical, psychological, environmental, technological, technical, organizational and managerial aspects. This article presents a Life Cycle Process Model of a Market-Oriented and Student Centered Higher Education (developed during BELL-CURVE (Built Environment Lifelong Learning Challenging University Responses to Vocational Education) projects activities) for such considerations and discusses certain composite parts of it. To demonstrate the application of this research, two Case Studies from Lithuania are submitted for consideration.

The Valuation of Hope Value for Real Estate Development

Abstract In the valuation of a property subject to development, the valuer may consider the potential aspect of the value of both land to be improved and a building to be refurbished. These kinds of valuations are complex, especially when a prudent assessment of value is required. In general terms, all properties may have potential development which, in some cases, can be termed “hope”. In particular, uncertainty regarding the change in the legal framework may create expectations as to the uncertain variation of property value in the future. In these cases, it may be necessary to deal with hope value or future value, trying to reach the value of a property subjected to uncertain changes. Hope value is the difference between the existing use value and the price that the market might pay for future transformation. The main aim of the paper is the elaboration of a methodology to determine the hope value. In this work, a real option model for the valuation of hope value in the real estate market will be applied to a small sample of residential properties located in Olsztyn that are subject to possible transformation. The possibility of a transformation may create expectations and may influence the value of the property. Although the applications of these methods to real estate valuation are fairly recent, the International Valuation Standards have included real option theory in the income approach as a valuation method since 2011.

An Application of Short Tab MCA to Podgorica

The work is based on the application of particular version of an Italian approach to Sales Comparison Approach (Simonotti 1997) to define an “hedonic” relationship between property price and characteristics. This version is also known as Short Tab Market Comparison Approach (d’Amato 2015a, b, c). The method was originally proposed to provide a forecast for the price of residential properties to be built on underdeveloped land. In this case will be used to provide an estimation of an appraisal function and relative hedonic prices based on few data. The proposed methodology may be useful to try to create an appraisal “function” in emerging real estate market where few comparables are available. The model will be applied to a small group of comparables in the city of Podgorica in Montenegro.

Dealing with Spatial Modelling in Minsk

The contribution is focused on comparing different automated valuation models dealing in different ways with location variable. Using a sample of 290 observations in Minsk, several different AVM models will be compared. A linear and log linear model of AVM with constant location variable will be applied. Therefore, after the determination of spatial correlation using the Moran I test the application of mixed regressive model integrating the geographic variable with the specific technical characteristics of the property. The results confirm an increasing quality of the model. Further works can be required to include also temporal variable in this class of models (Borst 2015).

An Application of Regressed Discounted Cash Flow as an Automated Valuation Method: A Case in Bari

The application of automated valuation methodology (AVM) procedure to income approach normally deals with direct capitalization. This happens although the great diffusion of discounted cash flow (DCF) analysis. The main objectives of paper are twofold: first, we aim to propose an AVM procedure based on the relationship between the DCF inputs and outputs. Second, we seek to determine discount rate and local risk premium in the case of Bari commercial market The study also refines discussions on risk premium factor in the regressed DCF application. The study also and identifies the room for enhancing the suggested methodology. The solution proposed is the model A of Regressed DCF (d’Amato and Kauko 2012).

Short Tab Market Comparison Approach. An Application to the Residential Real Estate Market in Bari

The Italian real estate market is characterised by the general absence of an organized set of data. Real estate market information is rarely available because is not repeatable in time and space, as in the case of exact sciences. Consequently, appraisal methods, which work on small samples, may be useful. The present work proposes a new methodology to calculate appraisal functions based on a reduced number of comparables (d’Amato, Stima del valore di trasformazione utilizzando la funzione di stima. Il MCA a tabella dei dati ridotta, Territorio Italia 2015a; d’Amato, MCA a Tabella dei Dati Ridotta e Sistema Integrativo di Stima. Un SecondoCaso a Bari, Territorio Italia b), named “Short Tab Market Comparison Approach”. With reference to this method, MCA is used to define an appraisal function (Simonotti 1997) whose dependent variable is the price while independent variables are the characteristics of the analysed property. Specifically, this method has been applied to the residential market segment in Bari.

Appraisal Methods and the Non-Agency Mortgage Crisis

Since the global economic crisis of 2007–08 an increasing amount of attention has been directed to the links between the financial system and the real estate industry. This paper ties to this discussion insofar as it focuses on the relationship between the methodology of property valuation and the recent non-agency or subprime crisis. After a brief discussion of the crisis various questions are raised concerning both the theoretical background and the application of property valuation, property management and automated valuation modelling. Despite the magnitude of the crisis in terms of the financial loss suffered, our observation is that the mainstream real estate academia is still essentially preoccupied with the task of integrating financial and property markets. Apparently, after the crisis financial models based on the concept of perpetual increasing income are still used, and deterministic relations between value and property characteristics still constitute the dominant paradigm. In the hope of avoiding repeating the errors that led to the crisis we identify the need to analyse this crisis from a property valuation point of view. We contend that in-depth analysis of the tools used in property valuation is necessary to understand why and how valuation methods should be improved given recent experiences.

Location Value Response Surface Model as Automated Valuation Methodology a Case in Bari

The paper is focused on the third application in the Italian context of Location Value Response Surface Modelling for Automated Valuation Modelling. LVRS (Connor in Locational Valuation Derived Directly from the Real Estate Market with the Assistance of Response Surface Techniques 1982) modelling is a procedure normally applied for automated valuation method purposes. In this context has been tested for a group of property prices exploring its use as automatic valuation methodology. The results showed that this method may have a potential role in those automated valuation model dealing with spatial autocorrelation.

A Brief Outline of AVM Models and Standards Evolutions

The paper is a brief outline of the methodological evolution of Automated Valuation Modelling along the time. A further outlook is dedicated to the evolution of standards on Automated Valuation Methodology. Both the profiles may be useful to understand the increasing role of Automated Valuation Methodologies and the growth of their importance especially for the stability of the economic and social system and how they changed over the time.

An Application of RST as Automated Valuation Methodology to Commercial Properties. A Case in Bari

The lack or unavailability of data poses one of the greatest obstacles hindering the exploration of real estate market information. Due to the small number of observations (cases), there are limited possibilities of using statistical methods, which are generally based on the assumption of a larger number of cases compared to the data describing them. This work provides an application of Rough Set Theory to a small sample of commercial properties as an Automatic Valuation Method. RST has been proposed as an automatic procedure for small sample (d’Amato 2002). It may happen in the application of RST that it is possible to deal with small samples. The rough set theory was applied taking into account the specific nature of information referring to the real property market. This theory is dedicated to examine imprecision, generality and unavailability in the process of data analysis that often occurs on the real estate market. It has been highlighted that one of the problem in AVM application may be the scarcity of data (Downie and Robertson 2007). The model allows the opportunity to reach the results of a single point estimate using if then rules providing a causal non deterministic relationship between price and property characteristics. The model has been applied to a small sample of commercial properties in the city of Bari.