Disentangling Housing Supply to Shift towards Smart Cities: Analysing Theoretical and Empirical Studies

Abstract

The search for a pleasant home has concerned people ever since. Paradoxically, people are facing strong difficulties in finding a decent place to settle their lives in cities. As such, the housing market regained momentum in connection with the development of Smart Cities, where life quality of residents is strongly emphasized. Well-being in the metropolis is affected by a wide variety of factors with housing supply being among the most important, hence stirred by financing costs, construction costs, vacancy rate, sales delay, inflation rate, housing stock, price of agricultural land, and regulation. The present article reviews empirical studies on housing supply for a better understanding of the dynamics in this market, shedding some light on the expectable outcomes of policy actions in the promotion of sustainable housing towards the smart city transition. Our review shows that the long-run price elasticity of housing supply is larger than the short-run, as well as the existence of substantial differences in the price elasticity across countries and regions. As such, overall, the hypothesis of a perfectly elastic supply is rejected. In addition, our review highlights that housing supply is negatively related to financial costs, inflation, sales delay, and the existence of regulatory or physical constraints. Also, the elasticity is lower when there are regulatory constraints. Newfangled strategic interaction models, though overlooked in the literature, reinforce that housing does not fit the perfect competition frame. The review proves that we are in face of a non-competitive market in which policy intervention is required to maximize social welfare; policy packages to grant people access to the housing market may be required. However, policy interventions should be carefully designed and clear, to mitigate their potentially negative impact on the housing supply as adverse results may be harmful to the transition towards a smart city.

The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities

“…The open data gathered covers a wide range of specific urban indicators, from mobility (bus stops and proximity to subway and train stations) [44,55,56], quality of life and wellbeing (culture, commerce, education, health, leisure, and environment) [35,[57][58][59][60][61], and governance (housing licensing, safety, and security) [21,62,63] to broader macroeconomic and financial indicators (inflation rate, unemployment, gross domestic product, and bank appraisals) [24,33,64,65]. These indicators play a crucial role in influencing the functionality and growth of a smart city and are instrumental in cities' assessment and evaluation.…”

“…Factors like distance to key locations and the number of commercial establishments within a certain radius can significantly impact a house's price per meter value [19]. Additionally, the housing market in major cities tends to experience more volatility and higher price fluctuations than in other regions [24]. Differences in housing market characteristics, regulations, and cultural preferences also contribute to variations in housing prices and supply across regions [25].…”

“…Vacancy rates and sales delays have been found to have a negative impact on housing starts, indicating that longer selling times can lead to fewer housing starts [20]. Regulatory constraints, such as land regulation and planning controls, can influence the housing supply, with more restrictive regulations leading to fewer housing starts [24]. The housing market in smart cities is not always perfectly competitive, and policy interventions may be necessary to maximize social welfare and ensure affordability and inclusion [19,24].…”

“…Regulatory constraints, such as land regulation and planning controls, can influence the housing supply, with more restrictive regulations leading to fewer housing starts [24]. The housing market in smart cities is not always perfectly competitive, and policy interventions may be necessary to maximize social welfare and ensure affordability and inclusion [19,24]. Other factors also play crucial roles in measuring and understanding housing supply, such as housing stock, demolitions and renovations, market availability, and geographical distribution.…”

Smart ‘Tourist Cities’ Revisited: Culture-Led Urban Sustainability and the Global Real Estate Market

“…With this perspective, smart cities are commonly thought to be about new technologies; however, they are much more. The smart city is an expression of a very contemporary drive to envisage and influence the city's and urban society's future; a city featuring efforts for economic development, governance, transportation, and sustainable housing (see [46,47]). Unsurprisingly, the 'smart' initiatives could not be applied horizontally, and are-to a large extent-dependent on local governments and cultures, possibly unraveling how the development of smart cities has remained mostly heterogeneous [48].…”