| Abstract: |
In the active landscape of contemporary urban development, the intricate
interplay between tourism dynamics and the real estate market has emerged as a
critical area of concern. Tourist cities, characterized by their diverse urban
functions and services, face complex phenomena that reverberate through the
real estate markets. This research addresses the need to make explicit and
quantify the impacts of tourism on residential real estate values within the
context of these multifaceted urban environments.The purpose of this work is
further to spatially evaluate the urban impacts on housing prices resulting
from tourism dynamics, taking into account the shift of residential real
estate from the ordinary market to the short-term market. By tracking changes
over time, this research aims to unveil the spatial patterns and trends in
real estate market dynamics in response to touristification processes,
ultimately assessing the correlation between tourism dynamics and housing
prices change.This work is part of a research that aims to develop a valuation
framework that enables decision-makers to understand and visualize the
complexities of tourism and real estate issues comprehensively. This
integrated approach acknowledges the need for decision-makers to navigate the
intricate relationship between tourism and real estate values relying on
robust multi-scalar and multi-dimensional monitoring tools, offering a
practical solution for informed policy formulation and urban planning
strategies.The research methodology considers a data-driven approach in a GIS
environment, within the perspective of developing an innovative Spatial
Decision Support System (SDSS) capable of informing decision-makers in a
structured way by means of a spatial-temporal analysis of market values to be
overlaid with different variables (housing market, short-term rentals,
activities development and cultural processes).These issues are addressed
through a case study of Rotterdam, starting from a mapping conducted from
fine-grained spatial data on housing transactions over the past dozen
years.The resulting maps, obtained through specific data aggregation
procedures and classification methods, show the overlay of the considered
variables, bringing out spatial patterns, new tourism hotspots and areas of
(non-)homogeneous growth with respect to short- and long-term market values,
facilitating an effective way of reading the city and its complex evolutionary
dynamics.This work provides an advancement in implementing a variable set for
evaluating real estate evolutionary dynamics of tourist cities within a
spatial-temporal framework, acknowledging such a tool as a key instrument for
fostering sustainable urban development models, providing actionable insights
for informed decision-making in the complex intersection of tourism and real
estate. |