To Rebuild or to Refurbish? An Analysis of the Financial Convenience

of Interventions on Urban Consolidated Contexts

M. LOCURCIO1, F. TAJANI2,*, P. MORANO1, F. DI LIDDO1, D. ANELLI2

1Department of Civil, Environmental, Land, Building Engineering and Chemistry,

Polytechnic University of Bari, Via Edoardo Orabona, 4, 70126, Bari, ITALY

2Department of Architecture and Design, Sapienza University of Rome

Via Flaminia, 359, 00196, Rome, ITALY

Abstract:- In the current historical moment of post-crisis recovery, the real estate sector has a dual role: i)

through the construction industry and its impacts on related economic sectors, it is called upon to be an active

part of the economic recovery; ii) the enhancement of existing property assets is of primary importance in the

containment of greenhouse gases and the achievement of the objectives set by the United Nations [1]. In this

context, the various players involved in the real estate market have outlined the importance of being supported

by assessment methodologies. That allows to point out not only the opportunities of the investment, but also the

risks that may invalidate the initial forecasts, nullifying the success of the initiative. To this end, this research

develops a multi-criteria Key Performance Indicator aimed at analyzing the feasibility of real estate initiatives

that allows to provide a synthetic scoring on the financial sustainability of each investment and to compare

different types of initiatives (e.g. new construction, demolition and reconstruction, renovation, etc.).

Key-Words: - financial feasibility, sustainable index, return on investment, renovation, real estate market,

performance indicator

Received: June 12, 2021. Revised: November 17, 2021. Accepted: December 19, 2021. Published: January 15, 2022.

1 Introduction

Through the Green Deal [2] the European Union

aims at achieving climate neutrality by 2050 and the

intermediate target of a 55% reduction in CO2 by

2030, in order to contain global warming by 1.5°C.

For these reasons, it is essential to direct

investments towards sustainable projects and

activities, making financial flows compatible with a

path that leads to a development with low

greenhouse gas emissions.

The real estate sector, in general, and the

construction sector, in particular, have a decisive

role in achieving these objectives; in fact, in Europe

buildings and the construction sector are responsible

for 35% of energy consumption and 38% of annual

CO2 emissions [3]. Therefore, 8 of 17 Sustainable

Development Goals (SDGs) defined within the 2030

Agenda [4] are related to the real estate sector

which, in addition to being a powerful driver of the

global economy, is also a crucial sector for the

achievement of many of the SDGs. In this

perspective, many studies [5-7] have highlighted the

need to limit new construction ad to promote the

recovery of the existing building stock, that is highly

energy intensive, also by virtue of the absence of a

housing demand related to the almost constant

number of European inhabitants [8], the high

demand for more comfortable residences form the

thermo-hygrometric point of view and the need to

contain the soil sealing [9].

The paper is structured as follows. In the second

Section, the aim of the research is illustrated. In the

third Section, the proposed model is explained. In

the Conclusions, possible future applications are

highlighted.

2 Aim

In the outlined scenario, real estate developers need

to understand whether initiatives to rehabilitate

existing property assets, in addition to being more

sustainable from an environmental point of view,

are more or less financially feasible than new

construction/demolition and reconstruction

operations. To answer this question, this research

proposes a multi-criteria Key Performance Indicator

(KPI) called Financial Feasibility Index (If), which

aggregates various parameters used in the analysis

of the financial feasibility of real estate development

interventions, by considering not only the yield of

the initiative but also its riskiness with respect to the

market in which it is located. This indicator allows:

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i) real estate developers, to compare different

initiatives and identify the one that better performs;

ii) professional investors (pension funds, retirement

funds, etc.), to customize asset management with

respect to different asset classes; iii) public entities

involved in initiatives, to assess their chances of

success. The Financial Feasibility Index thus

provides a scoring of each real estate initiative

analyzed, making it possible to compare different

types of property investment in order to identify the

best one in terms of profitability expectations and

risk appetite of the individual investor.

3 Method

The selected parameters for the definition of

belong to two different typologies, analyzed with

respect to the specific characteristics of the Italian

property market: the first typology concerns the

financial feasibility of the single property initiative,

whereas the second one characterizes the real estate

market in which the initiative is located.

The financial feasibility of the single property

initiative is carried out considering the expected

future cash flows of the real estate investment and

elaborating them through a Discounted Cash Flow

Analysis (DCFA) [10]; the corresponding

parameters are:

· Internal Rate of Return (IRR), that is the

actualization rate for which the Net Present Value of

the initiative is equal to zero, i.e. the sum of the

actualized revenues is equal to the sum of the

corresponding costs;

· Return On Sale (ROS), that is the ratio

between the operating profit, calculate as earnings

before interest and tax, and the market value of the

property at the end of the initiative;

· Return On Investment (ROI), that is the

increase in the current value of investment

compared to the cost of investment given by the

historical cost;

· Revenues/Costs Ratio (RC), that is the

ratio between the sum of the actualized revenues

and the sum of the actualized costs.

It should be noted that, among the various

parameters used to describe financial feasibility of

an initiative, only the dimensionless ones have been

deliberately considered, making subsequent

normalization operations easier and reducing

possible subjective aspects in the construction of .

In order to characterize the real estate market in

which the initiative is located, three parameters have

been constructed, by starting from the range of

quotations provided every six months by the Italian

Real Estate Observatory (OMI) of the Revenue

Agency for the period 2005-2020. Specifically, in

order to dimensionalize the parameters, it has been

necessary to build the hystorical series of average

fixed-base quotations (quotation I semester 2005

=100) for the specific area in analysis; the first two

considered parameters are:

· market risk, given by the standard deviation (



)

of the average quotations on a fixed basis;

· market trend, determined through the angular

coefficient (m) of the linear regression line

constructed from the fixed-base average

quotations.

A low-risk market is characterized by a zero

standard deviation of quotations (



= 0); a market

will have a growing trend if the quotations tend to

increase over time and therefore the angular

coefficient of the regression of quotations is positive

(m > 0), and vice versa.

The last parameter used of the construction of the

is constituted by the market deviation (



MV), i.e.

the percentage variation between the market value

(MV) per unit saleable surface at the end of the

construction/refurbishment and the maximum

quotation provided for the area where the

intervention is located according with OMI in the

second half of 2020 (QMAX):

The greater



MV the more the initiative is

misaligned with respect to the property market in

which it is located, and this represents a potential

obstacle to the marketing of the property when the

intervention is completed; it should be noted that in

the definition of



MV the maximum quotation has

been considered, as it is reasonable to expect that, at

the end of the intervention, the overall quality of the

property will be higher than the corresponding

average one in the reference area, and therefore the

comparison should be carried out with respect to the

maximum values of the area.



MV could also be

much higher than zero in the event that the real

estate development aims at intercepting a potential

unexpressed demand and therefore not adequately

detected through the OMI surveys.

Once all parameters that flow into the formation

of If are defined, they are aggregated using the

weighted sum model, after determining the

normalized value (Vi) of each parameter and

assigning the importance, i.e. the corresponding

weight (wi):

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The normalization consists in translating into the

same scale (in the case in analysis “0-1”) the values

associated with the parameters characterized by

either different units of measurements or very

different ranges of possible values; in the present

work the second situation has been considered, as all

the indicators are dimensionless. In order to

correctly normalize the values assumed by the

different parameters, it is appropriate to define: i)

the range of possible values; ii) the function to be

used for the normalisation operation. The range of

the possible values assumed by the parameters has

been defined with reference to the Italian context,

whereas both the definition of the individual

normalization functions and the assignment of

weights have been delegated to a later phase; in this

phase the list of the main normalization functions

has been performed, delegating to a later date the

calibration of the functions to be associated with

each parameter and the assignment of the weights

with respect to the specific risk/return profile (core,

value added or opportunistic) of the investor, i.e. the

decision-maker.

In Table 1, for each parameter, the goal of the

investor and the range defined with reference to the

Italian market have been reported; named RMIN and

RMAX the values assumed by the parameters Pi, if the

rare situations of exceeding the limits of the range

are verified, the

minimum/maximum normalized value (Vi) will be

assigned, depending on the specific case study:

· if and

In order to identify and RMIN and RMAX of the

parameters IRR, ROS, ROI, RC and



MAX, several

real estate development initiatives carried out by

Italian property companies have been analyzed.

In order to define RMIN and RMAX of the

parameters



and m, the corresponding database has

been built for all the intended uses and all the areas

of the series of fixed-based quotations for the period

2005-2020. In this case the data have been reported

in a chart (Fig. 1), outlining almost normal

distributions as confirmed by statistical tests, and

the extremes of the range at the percentile of order

20 and 80 have not been considered. This

assumption allows to avoid that specific conditions

(Pi < RMIN or Pi > RMAX) determines an excessive

contribute in the normalization.

Table 1. Main characteristics of the parameters

No.

Parameter

Acronym

Goal

Internal Rate of Return

MAX

30%

Return On Sale

MAX

30%

Return On Investment

MAX

10%

35%

Revenues/Costs Ratio

MAX

Market risk

MIN

4.19

16.45

Market trend

MAX

-0.85

0.52

Market deviation

MIN

40%

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Fig. 1: Frequency distribution of



(on the left) and m (on the right)

Once the range of possible values has been

defined, the function to be used for the

normalization operation, i.e. the function Vi = f(Pi),

can be chosen; in Fig. 2 the main normalization

functions reported in the reference literature [11]

and the relative equations have been summarized.

The last step necessary for the definition of If is

constituted by the assignment of the weight (wi) to

the single parameters, according to the importance

they have for the subject involved in the analysis of

the different real estate interventions; it could be

observed that investors with a low risk appetite will

aim at assigning high weights to wRC, w



, wm and



MV, whereas investors interested in opportunistic

initiatives will give higher weights to wIRR, wROS and

wROI. Considering the limited number of parameters,

one of the most effective procedures for assigning

weights is represented by the Analytic Hierarchy

Process (AHP), which provides the assumption that

the decision-maker, during its choice, applies, more

or less consciously, a hierarchy of all the several

elements that are involved in the decisional process

[12]. For the identification of wi the decision-maker

is called to perform a series of pairwise comparisons

among the criteria through some verbal judgments

subsequently translated into numerical scores

according to the semantic scale of Saaty [13].

Linear function

Bilinear function

for

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Exponential function

Logarithmic function

Fig. 2: Normalization functions

4 Conclusions

The current climate changes and the objectives of

limiting the rise in temperature and consequently of

CO2 emissions require a global review of the

established development model; in this context of

high uncertainty, international investors are

directing their capitals towards Environmental,

Social e Governance (ESG) compliant investments,

that have reached in 2020 an Asset Under

Management (AUM) equal to 270 billion dollars

globally [14], surpassing in terms of market

capitalization the Oil & Gas sector [15]. In general,

the real estate and the construction sectors have a

decisive role in the current change through ESG

compliant investment products that, by

implementing sustainable strategies for the

enhancement of existing real estate assets, seek to

overcome the ordinary cultural resistance of a sector

that is not prone to be modified. To this end, in the

present research a Financial Feasibility Index (If)

has been defined, in order to allow the comparison

among different types of property investments in

terms of risk/return. This approach aims at

highlighting that, in poorly predictable evolutionary

contexts, the most resilient real estate investments,

i.e. those able to elastically react to the shocks of a

possible crisis, are characterized by energy-efficient

properties, with high living comfort and located in

built-up infrastructured areas. New constructions,

realized in peripheral areas without urbanizations,

characterized by a residential vocation and the

absence of commercial activities, represent risky

investments due to their location, that could cause

rather long marketing times and consequently a high

unsold.

Possible future developments of this work, also

aimed at sorting out specific limits of the proposed

method, could be: i) the development of a for

different real estate initiatives, in order to outline

their strengths and possible weaknesses; ii) the

creation of a web tool for the application of the

Financial Feasibility Index; iii) the appropriate

definition of the ranges for all the considered

parameters; iv) the choice of the percentile for the

range definition of the market risk and the market

trend; v) the real estate market characterization, that

in this research has been carried out by considering

only the data published by the Italian Revenue

Agency.

References:

[1] United Nations. The Sustainable Development

Goals Report 2020 Available online:

https://unstats.un.org/sdgs

[2] European Green Deal 2021 Available online:

https://ec.europa.eu/info/strategy/priorities-

2019-2024/european-green-deal/delivering-

european-green-deal_en#documents

[3] 2020 Global status report for builindigs and

construction. Towards a zero-emissions,

efficient and resilient buildings and

construction sector. UN environment

programe. Global Alliance for Building and

Construction

[4] United Nations. Agenda 2030 2015 Available

WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT

DOI: 10.37394/232015.2022.18.24

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Volume 18, 2022

online: https://unric.org/it/agenda-2030/

[5] Morano P, Tajani F, Di Liddo F, Amoruso P

2021 The public role for the effectiveness of

the territorial enhancement initiatives: A case

study on the redevelopment of a building in

disuse in an Italian small town Buildings,

11(3), 87.

[6] Morano P, Tajani F, Di Liddo F, Anelli D

2020 A feasibility analysis of the

refurbishment investments in the Italian

residential market Sustainability, 12(6), 2503.

[7] Morano P, Locurcio M, Tajani F, Guarini

M.R. 2014 Urban redevelopment: a multi-

criteria valuation model optimized through the

fuzzy logic, in Murgante B. et al.,

Computational Science and its Applications,

LNCS 8581, part. III, pp. 161-175, ISBN:

978-3-319-09149-5.

[8] United Nations Department of Economic and

Social Affairs (UN DESA). Historical and

projected population by world region

https://www.eea.europa.eu/data-and-

maps/indicators/total-population-outlook-

from-unstat-3/assessment-1 (avaible on line

14 July 2021)

[9] Morano P, Tajani F, Locurcio M 2015 Land

use, economic welfare and property values: an

analysis of the interdependencies of the real

estate market with zonal and macro-economic

variables in the municipalities of Apulia

Region (Italy) International Journal of

Agricultural and Environmental Information

Systems, Vol.6, No. 4, pp. 16-39, ISSN: 1947-

3192.

[10] Tajani F, Morano P, Di Liddo F, Locurcio M

2018 An innovative interpretation of the

DCFA evaluation criteria in the public-private

partnership for the enhancement of the public

property assets, In: New Metropolitan

Perspectives. Proceedings. SMART

INNOVATION, SYSTEMS AND

TECHNOLOGIES, Springer, ISSN: 2190-

3018, Reggio Calabria.

[11] Ishizaka A and Nemery P 2013 Multi-criteria

Decision Analysis: Methods and Software.

John Wiley & Sons., New Delhi.

[12] Saaty T L 1988 Multicriteria decision making

- the analytic hierarchy process. Planning,

priority setting, resource allocation,

Pittsburgh: RWS Publishing.

[13] Saaty T L 2008 Relative measurement and its

generalization in decision making: why

pairwise comparisons are central in

mathematics for the measurement of

intangible factors – the analytic

hierarchy/network process RACSAM-Revista

de la Real Academia de Ciencias Exactas,

Fisicas y Naturales. Serie A. Matematicas,

Vol.102 No.2, pp. 251-318.MCSI 2020 ESG

Investing. Better investments for a better

world

[14] MCSI 2020 ESG Investing. Better

investments for a better world

[15] FTSE Russel 2020 Investing in the green

economy – sizing the opportunity

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