Search results

The purpose of this study is to use vector error-correction modeling together with directed acyclic graphs (DAG) for analyzing dynamic relations among monthly retail property price indices of 10 major cities in China from 2005–2021.

This paper apply both the PC and Linear Non-Gaussian Acyclic Model (LiNGAM) algorithms for inference of the DAG, with the former leading to the causal pattern and the latter leading to the causal path. This paper carry out innovation accounting analysis based on the causal path according to the LiNGAM algorithm.

Their results show sophisticated dynamics among processes of price adjustments following shocks. The results do not reveal clear evidence that supports dominance of the price series of the top-tier cities.

These results suggest that it could be beneficial to design policies at granular levels regarding regional retail property prices in China.

Profitability is crucial for a company’s sustainability. This study aims to examine the influence of profitability and specific variables on the value of real estate companies in Indonesia.

The study uses a sample of 42 real estate companies listed on the Indonesia Stock Exchange from 2017 to 2023. A static panel regression approach was adopted, with the best model being the fixed effect model, verified through a robustness test.

The results indicate that the fixed effect model is the most effective in explaining firm value. Profitability, proxied by return on assets (ROAs), does not significantly impact firm value. This finding is confirmed by robustness tests using another profitability measure, return on equity (ROE). Additionally, company size negatively and significantly impacts firm value, while activity ratio and leverage have a positive and significant effect. Liquidity and company growth do not significantly affect firm value.

The research is limited to Indonesian real estate firms, cautioning against broad generalization to other countries or industries. The study could not demonstrate the influence of profitability on the value of real estate companies. Instead, firm value is influenced by company size, activity ratio and leverage.

Real estate firms should increase their activity, optimize funding and consider company size to enhance firm value.

This study contributes to the Indonesian real estate sector by revealing that profitability does not enhance firm value. Indonesian real estate companies generally have low profitability and firm value.

This study aims to identify determinants of single-family residential property values and fill the gap by analyzing respondents’ willingness to pay/receive data alongside real transaction data. Ordinal logistic regression and ordinal least square regression were used.

Ordinal logistic regression effectively analyzes willingness-to-pay/receive data, accommodating the ordered nature of property value responses while incorporating multiple influencing factors. Ordinal least square regression quantifies the impact of continuous and categorical predictors on real transaction data.

Findings revealed strong associations between property values and several variables. Analysis of willingness-to-pay/accept data from 232 respondents showed significant impacts of factors such as the number of rooms, site area, construction material, property orientation, property age and proximity to bus stations and the central business district (p < 0.05). Similarly, ordinal least square regression analysis of transaction data confirmed the significance of most of these factors, except for property orientation, which indicates the difference of preference in the local market or reporting inconsistencies, demand further investigation. Variables such as views, proximity to wetlands, roads, green areas, religious institutions and schools were statistically insignificant across both data sets (p > 0.05).

It provides a robust basis for housing and urban development strategies. The stakeholders such as real estate developers, urban planners and policymakers are encouraged to incorporate these findings into housing policies, land value capture initiatives and urban planning frameworks to enhance residential property value and align with sustainable urban development goals.

This study contributes original insights into single-family residential property valuation by integrating willingness-to-pay and transaction data, substantiating the determinants of property value.

The paper aims to estimate the house rental values for the purpose of customizing mass appraisals in Bahir Dar City, Ethiopia. It seeks to identify the critical factors affecting the rental values of residential properties and customize a mass appraisal model for such properties. The study focuses on identifying attributes that significantly affect house rental values.

The paper adopted a survey research design, utilizing a survey questionnaire, expert group discussion and document analysis. The data were analyzed using thematic, descriptive and inferential statistical analysis, including correlation and hedonic regression analysis.

Among the variables included in the model, the number of rooms, availability of schools, land value grading, type of nearest road, housing typology, built-up area, plot area, walling material, traveling cost and fencing materials were the most significant factors for predicting the annual rental value of residential properties in the city.

The findings of this study will provide valuable insights to tax assessors, property owners and local government authorities, including municipalities, concerning the key determinants of the rental values of residential properties. Besides, these findings will serve as a useful tool for valuers and researchers in the field of property value modeling.

This study represents the first attempt to develop a framework for mass appraisal of residential properties using annual rental values in the Ethiopian context.

This paper aims to propose a model for democratization of Islamic home financing to tackle the issue of sustainability of homeownership affordability.

A conceptual framework and fractional equity model (FEM) are developed to incorporate big data analytics, artificial intelligence and blockchain technology in an ecosystem for affordability and sustainability of homeownership via the proposed financing model. In addition, the FEM adopts the simulation approach to show its validity in terms of liquidity when compared with traditional home financing. In this regard, this paper is focused on developing and demonstrating the feasibility of a new financing model, rather than testing specific hypotheses or relationships. This is to propose the democratization model for Islamic Home Financing that will not benefit the prospective home buyers without compromising the profitability of the financial institutions.

The findings indicate that the proposed end-to-end solution within the financing ecosystem can lead to more efficient matching market between the buyers and sellers of houses, reduced transaction costs, greater transparency and enhanced efficiency which in the end could lead to lower costs of owning homes and sustained financial resilience among house owners. The findings indicate that the FEM model is able to increase homeownership with more elements of liquidity, marketability and sustainability for homebuyers.

This research highlights the potential of big data and blockchain technology in democratizing Islamic home financing and evidence that the transfer of ownership is possible through tokenization. However, this will require a mature financing environment to adapt the technology for practical application.

The model proposes a solution to propagate shared prosperity among stakeholders such as the house buyers/owners, sellers, investors as well the government agencies. The proposed FEM model provides alternative home financing that is more marketable, flexible and sustainable for households/buyers and financiers.

It is hoped that with the proposed financing ecosystem to promote affordability and sustainability of homeownership via big data analytics, artificial intelligence and blockchain technology can lead to greater financial resilience for homeowners which can then be translated to enhanced well-being, increased productivity and can further promote economic growth.

This research is a concept paper based on academic research and industry collaboration with a technology provider.

Decision-makers often struggle to combine advice with their own intuition. This study examines how advice-giver traits and decision-makers’ intuition influence advice uptake. We present a novel typology based on decision-makers’ trust in advice-givers and their perceived expertise.

This qualitative study uses a sample of publicly available interview data with 51 elite performers. Using inductive and content analysis, we explore the mediation between decision-makers’ intuitive competence (ability to effectively deploy intuition in interface with advice) and their autonomy (self-endorsement from past performance).

We identify four sources of advice: mentor advice, specialist advice, confidant advice and commentator advice. Drawing on instances of different sources of advice along varying degrees of trust and expertise, we propose a framework for interaction between intuitional competence and advice characteristics.

We offer a novel way of contextualising nuanced forms of advice and provide a structured typology of sources, characterised by trust and expertise. This typology and our findings help reconcile contradictions in decision-making research. Finally, we offer practical guidance for the uptake of advice.

This paper aims to explore the barriers and facilitators to psychosocial well-being among ethnic Nepali Bhutanese American older adults from the perspective of health care and service providers working with this population. Specifically, the authors aimed to understand health-care and service providers’ perceptions of the psychosocial well-being in this community and appropriate interventions.

Qualitative research methods were used to collect and analyze data in collaboration with a community-based organization. A total of ten participants were interviewed. Interviews were conducted in either English or Nepali, based on participant preference. An inductive thematic analysis approach was used to analyze the data.

Three major themes were generated from the analysis. The first two were in reference to perceived barriers to mental well-being among Bhutanese American older adults: isolation that older adults faced in the USA and shifting responsibilities and lifestyles that arose from the cultural and structural barriers in the USA. Throughout these themes, there was an understanding that acculturation threatened families’ connections to each other and impacted older adults’ connections with younger generations. The third theme, a perceived facilitator of well-being, was the power of storytelling to counteract feelings of isolation and disempowerment caused by shifting lifestyles felt by older adults, especially amid community events.

Bhutanese American older adults, many of whom have limited English proficiency, face numerous challenges, psychosocial stressors and factors contributing to well-being. Care for this population should prioritize dignity, empowerment and the incorporation of strengths within their narratives. Interventions and services tailored for older Bhutanese American adults need to be adapted to integrate multiple care systems.