Top Research Papers on Real Estate

Funding Information: This work was supported by Aalto University’s Smartland-project, which is funded by Finnish Strategic Research Council at the Academy of Finland (decision No. 327800 ). Publisher Copyright: © 2022 The Authors

Urbanization is an important engine of modernization and economic growth, and appears to be an inevitable trend in human socioeconomic development around the world. However, China's unusually rapid urbanization rate has attracted increasing attention. Our research suggests that understanding the country's real estate market is the key to understanding the country's rapid urbanization. The booming real estate market represents a major source of funding for urban infrastructure construction, and has accelerated the migration of rural residents to cities. We describe how four typical Chinese citi...

We show that the COVID-19 pandemic brought house price and rent declines in city centers, and price and rent increases away from the center, thereby flattening the bid-rent curve in most U.S. metropolitan areas . Across MSAs, the flattening of the bid-rent curve is larger when working from home is more prevalent, housing markets are more regulated, and supply is less elastic. Housing markets predict an urban revival with urban rent growth exceeding suburban rent growth for the foreseeable future, as working from home recedes.

Abstract We show that housing markets provide information about the appropriate discount rates for valuing investments in climate change abatement. Real estate is exposed to both consumption and climate risk and its term structure of discount rates is downward sloping, reaching 2.6% for payoffs beyond 100 years. We use a tractable asset pricing model that incorporates features of climate change to show that the term structure of discount rates for climate-hedging investments is thus upward sloping but bounded above by the risk-free rate. At horizons at which risk-free rates are unavailable, th...

The current study explores the literature focused on blockchain smart contracts in smart real estate and proposes a conceptual framework for its adoption in smart cities and can help the users enjoy a more immersive, user-friendly, and visualized contracting process.

21 key barriers to digitalisation and innovation are identified based on a comprehensive review of 72 systematically retrieved and shortlisted articles to pave the way for DDT adoption and innovation in the Australian real estate sector and move towards smart real estate.

Abstract This is the first paper to examine how the COVID-19 shock transmitted from the asset markets to capital markets. Using a novel measure of the exposure of commercial real estate (CRE) portfolios to the increase in the number of COVID-19 cases (GeoCOVID), we find a one-standard-deviation increase in GeoCOVID on day t-1 is associated with a 0.24 to 0.93 percentage points decrease in abnormal returns over 1- to 3-day windows. There is substantial variation across property types. Local and state policy interventions helped to moderate the negative return impact of GeoCOVID. However, there ...

Prefabrication construction method has been considered an effective way for enhancing the environmental performance and sustainable development of the construction industry. Many countries have imposed policies to stimulate the implementation of prefabrication. However, the efficiency of the incentive policies in China did not turn out as expected because of the existing benefit game between real estate enterprises and the government under the influence of consumers' purchasing intention. An evolutionary game model was established on the basis of 16 variables influencing the strategy selection...

Purpose This paper aims to contribute to the existing capital structure and board structure literature by examining the relationship among corporate governance, ownership structure and capital structure. Design/methodology/approach The paper uses a panel data of 595 firm-year observations from a unique and comprehensive data set of 119 Chinese real estate listed firms from 2014 to 2018. It uses fixed effect and random effect regression analysis techniques to examine the hypotheses. Findings The results show that the board size, ownership concentration and firm size have positive influences on ...

The results show that big data can tackle the ever-present issues of customer regrets related to poor quality of information or lack of information in smart real estate to increase the customer satisfaction using an intermediate organization that can process and keep a check on the data being provided to the customers by the sellers and real estate managers.

This paper estimates the value firms place on access to city centers and how this has changed with COVID-19. Pre-COVID, across 89 U.S. urban areas, commercial rent on newly executed long-term leases declines 2.3% per mile from the city center and increases 8.4% with a doubling of zipcode employment density. These relationships are stronger for large, dense "transit cities" that rely heavily on subway and light rail. Post-COVID, the commercial rent gradient falls by roughly 15% in transit cities, and the premium for proximity to transit stops also falls. We do not see a corresponding decline in...

This paper aims to explore the impact of the COVID-19 pandemic on retail real estate and high street landscape through acceleration of e-commerce and digitalization. The retail business have been evolving over the past several decades, accentuated by the evolution and development of digital technologies. Almost all parts of the world have witnessed the changes in consumer behavior, the nature of retail, and reshaping of the high street landscape due to the e-commerce revolution and continued expansion. Especially due to the COVID-19 pandemic, the retail platforms powered by digital technology ...

Although previous research has highlighted that virtual reality (VR) technologies can enhance customer experience, the efficacy of VR technologies in real estate remains unclear. Therefore, this study examines the effects of offering consumers a non-immersive VR experience via a widely available technology, that allows them to view real estate products. Participants accessed the website of a real estate agency that presented apartments through either static photos or interactive 360° visits. The latter condition was associated with better “visiting” experiences and more positive attitudes towa...

In this study, the possible effects and impacts of the COVID-19 outbreak on real estate development and management processes were examined by making an evaluation and an insight on administrative and media records. Crises and global effects of pandemics were described as an unforeseen event which have negatively affect project development in the real estate sector, sales operations of existing real estate, costs estimates, values and rates of return of existing real estate sector in general. The inception of new policy and precaution measures, especially travel bans and restrictions on domesti...

This work develops a disentangled image dehazing network (DID-Net), which disentangles the feature representations into three component maps, respecting the physical model of a haze process, and encourages the coarse predictions and refinements of each disentangling component to be consistent between the student and teacher networks by using a consistency loss on unlabeled real data.

The results showed that the performance of the high-level visual task (i.e. face detection) can be effectively improved by using the enhanced results obtained by the R2RNet method in low-light conditions.

A hybrid demand response mechanism considering three types of participants: power grid operator (PGO), retailers and end users, which can better motivate retailers to participate by providing them with monetary incentives from PGO for load shifting and the results verify its advantages over traditional demand response mechanisms.

This work extends the powerful ESRGAN to a practical restoration application (namely, Real-ESRGAN), which is trained with pure synthetic data and employs a U-Net discriminator with spectral normalization to increase discriminator capability and stabilize the training dynamics.

It is concluded that as a common non‐respiratory symptom of COVID‐19, headache should not be overlooked, and its characteristics should be recorded with scrutiny.

The purpose of this review is to offer an outline of the current information on RWE, its advantages and disadvantages, as well as the associated challenges and ways to overcome them, while also throwing some light on the future of RWE.

In Pluriversal Politics Arturo Escobar engages with the politics of the possible and how established notions of what is real and attainable preclude the emergence of radically alternative visions of the future. Reflecting on the experience, philosophy, and practice of indigenous and Afro-descendant activist-intellectuals and on current Latin American theoretical-political debates, Escobar chronicles the social movements mobilizing to defend their territories from large-scale extractive operations in the region. He shows how these movements engage in an ontological politics aimed at bringing ab...

Artificial intelligence (A.I.) is a multidisciplinary field aimed at automating tasks that currently need human intelligence.Despite its lack of general familiarity, artificial intelligence (AI) is a technology that is revolutionizing every aspect of life.This article aims to educate laypeople about AI and encourage them to utilize it as a tool in many disciplines to rethink how we combine data, analyze it, and make choices.We quickly covered what artificial intelligence (AI) is, how it works, and how it may be applied in our daily lives in this article.

A large-scale empirical study of semantic visual navigation methods comparing representative methods with classical, modular, and end-to-end learning approaches across six homes with no prior experience, maps, or instrumentation found that modular learning works well in the real world, attaining a 90% success rate.

Transforming RWD EHR data for research and for real-world evidence using ML requires knowledge of the EHR system and their differences from existing observational data to ensure that studies incorporate rigorous methods that acknowledge or address factors such as access to care, noise in the data, missingness and indication bias.

In this review, the studies which have been successfully applied to the developed drug samples and also to many real samples, with high recovery rates are highlighted.

In the proposed approach, an approximate optimal policy based on neural network is designed to learn the optimal DR scheduling strategy and can directly learn from high-dimensional sensory data of the appliance states, real-time electricity price, and outdoor temperature.

It is hypothesise that therapeutically targeting a state of ‘no evident inflammatory disease activity’ (NEIDA) cannot sufficiently prevent disability accumulation in MS, meaning that treatment should also focus on other brain and spinal cord pathological processes contributing to the slow loss of neurological function.

An electrochemical, aptamer-based sensor (EAB) is developed against Neutrophil Gelatinase-Associated Lipocalin (NGAL), a protein that, if present in urine at levels above a thresh-old value, is indicative of acute renal/kidney injury (AKI).

We propose a deep videorealistic 3D human character model displaying highly realistic shape, motion, and dynamic appearance learned in a new weakly supervised way from multi-view imagery. In contrast to previous work, our controllable 3D character displays dynamics, e.g., the swing of the skirt, dependent on skeletal body motion in an efficient data-driven way, without requiring complex physics simulation. Our character model also features a learned dynamic texture model that accounts for photo-realistic motion-dependent appearance details, as well as view-dependent lighting effects. During tr...

What capital allocation role can China's stock market play? Counter to perception, stock prices in China have become as informative about future profits as they are in the US. This rise in stock price informativeness has coincided with an increase in investment efficiency among privately owned firms, suggesting the market is aggregating information and providing useful signals to managers. However, price informativeness and investment efficiency for state-owned enterprises fell below that of privately owned firms after the postcrisis stimulus, perhaps reflecting unpredictable subsidies and sta...

Inspired by physically adaptive, agile, reconfigurable and multifunctional soft-bodied animals and human muscles, soft actuators have been developed for a variety of applications, including soft grippers, artificial muscles, wearables, haptic devices and medical devices. However, the complex performance of biological systems cannot yet be fully replicated in synthetic designs. In this Review, we discuss new materials and structural designs for the engineering of soft actuators with physical intelligence and advanced properties, such as adaptability, multimodal locomotion, self-healing and mult...

This research work was focused to evaluate the concentration of heavy metals (i.e., Cr, Pb, Mn, Cu and Fe) in sediment samples collected from the Dhaleshwari River near the area of a newly established tannery industrial estate, Savar, Bangladesh. The heavy metals in sediment samples were ascertained by the atomic absorption spectrophotometer (AAS). This study revealed that the metal concentration for chromium (Cr), lead (Pb), manganese (Mn), copper (Cu) and iron (Fe) were found to be 14.8–748 (186 ± 241) mg/kg, 2.38–21.1 (8.78 ± 6.15) mg/kg, 1.59–6.29 (3.12 ± 1.38) mg/kg, 0.36–4.75 (1.76 ± 1.4...

Correcting misconceptions about RWD and RWE requires recognition that the degree of reliance on RWD varies with the type of study design and that RCTs that incorporate RWD generate RWE, and that even when strict eligibility criteria may limit the generalizability of trial results, trial participants exist, and their outcomes occur, in the “real world”.

The proposed architecture relies on the fast spatial attention, which is a simple yet efficient modification of the popular self-attention mechanism and captures the same rich spatial context at a small fraction of the computational cost, by changing the order of operations.

This paper introduces an original technique named Latent Replay where, instead of storing a portion of past data in the input space, it is proposed to store activations volumes at some intermediate layer, which can significantly reduce the computation and storage required by native rehearsal.

A fully learning-based approach for real-world humanoid locomotion that takes the history of proprioceptive observations and actions as input and predicts the next action, and is a causal transformer that enables real-world humanoid locomotion.

Bats performed truly original shortcuts, supporting the hypothesis that they can perform large-scale map-based navigation, and documented how young pups developed their visual-based map, exemplifying the importance of exploration and demonstrating interindividual differences.

A real-time, high-resolution background replacement technique which operates at 30fps in 4K resolution, and 60fps for HD on a modern GPU, based on background matting, where an additional frame of the background is captured and used in recovering the alpha matte and the foreground layer.

Abstract Financial markets have a central role in allocating resources in modern economies. One of the main functions of financial markets is the discovery of information. This information in turn helps guide decisions in the real side of the economy. The literature on the “feedback effect” of financial markets explores this channel. Empirical work tries to identify the informational feedback from markets to corporate decisions. Theoretical work explores implications that this feedback effect has for the equilibrium in financial markets and for economic efficiency. Current trends in informatio...

The combination of synthetic biology and materials engineering enabled the development of biosensors that produce electrical readouts and real-time detection capabilities, providing a new platform for miniature, low-power bioelectronic sensors that safeguard ecological and human health.