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This article seeks to offer an answer. It explores the criteria on which commercial property market participants can develop strategies in hugely challenging circumstances. For this purpose, a survey-based approach was developed with work conducted with property-market professional in the United Kingdom (UK), France, Germany and Sweden to produce a criteria-based tool supporting adaption to changing market circumstances.

The data have been analyzed using statistical analysis. The data's statistical analysis included Cronbach's alpha's application to evaluate the respondents' replies' reliability. A entral tendency test was used to identify the means of relevance of the criteria. The Mann–Whitney U test was used to determine potential material differences between the UK and other countries with Bonferroni corrections applied to minimize type-I errors.

Thirty characteristics have been identified that impact the dynamics of the commercial property market. Their relevance to the commercial property market was determined using a survey. The literature analysis showed that the researchers paid more attention to quantitative criteria and their comparison. The survey showed that the relevance of criteria to the commercial property market dynamics is unequal. However, the survey results showed that it is most important to pay attention to emotional criteria to adapt to uncertainty changing conditions. The problem of the environment has been on the agenda for the last four decades. Therefore, the fact that the results of the study showed that the environmental criteria are the least significant is unexpected.

The study involved economically developed countries of Europe. Extending the study's geographical scope would be valuable in revealing whether the same differences exist in other geographical areas (such as Australia or the USA).

The practical implication of the analysis may be to facilitate the decision-making process of either selecting a country for commercial property investment or selecting the most sensitive and relevant criteria for the decision-making.

Criteria for commercial property market performance which promote successful property investment have been developed. Moreover, the criteria affecting the commercial property market have been weighted by their relevance to the market and their sequence of relevance has been established. And finally, the developed criteria have been placed into five groups that could serve as a foundation for a macro-level assessment of commercial property market dynamics.

The purpose of this paper is to empirically test for submarket existence based on an understanding of the residential rental housing market in Ghana.

Based on extant literature and market observations, the authors provide key concepts and an overview of the residential rental market dynamics in Ghana. Reseachers appreciate that submarkets may exist in the Ghanaian rental market but have ignored the empirical testing for submarket existence due to data asymmetries. Based on real estate experts and stakeholder consultations, a priori delineation of submarkets are constructed based on spatial, structural and a nested approach. Submarket existence is tested using the Kruskal–Wallis H test and Hedonic modelling techniques.

By using fieldwork data from Accra rental market, the analysis provides credence to the conceptualisation of submarkets and how to empirically test for same. It is argued that researchers should use alternative methods to compare results to make far-reaching conclusions.

Examining the hypothesis that differential rental values exists for submarkets has implications for policy decisions to target submarket constructs differently to improve market maturity.

The research provides stakeholder investors in the rental space an understanding of market dynamics for profit maximisation, and end-users to maximise utility in deciding where to live – and as such households could benefit from making informed investment decisions on housing.

This research is one of the first attempts to empirically identify and test for submarkets existence in Ghana’s residential rental housing market.

Primarily based on Alonso’s bid-rent model, the purpose of this paper is to examine the dynamics of the Singapore’s overall retail rental market by adopting a vector error correction model (VECM) estimation.

This paper uses the proxy for the overall retail rental value, which is indicated by a combination of the shop rent index from 2004 to 2013 and the retail rent index (RRI) in 2014, maintained by the Urban Redevelopment Authority (URA). The independent factors are the real gross domestic product (GDP), monthly earnings of individuals and vacancy rates (VR).

Such a behavioral model examines the dynamic structures that overshoot and/or diverge from equilibrium.

The variables LOGGDP and VR are co-integrated of order one, I(1), while variables LOGME and LOGSRI are co-integrated of order two, I(2), to enable them to be employed in the VECM model.

The VECM model shows a good fit that allows the error correction term (ecm) together with the economic, financial and rental variables to jointly explain about 79.2 percent of the variation in the overall RRI. With a positive CoinEq1 coefficient that is positive and statistically significant at 5 percent level, it would take a long time for the system to return to its equilibrium once it has been shocked. Another variable that shows significant explanatory relationships includes past rents (index points) in the second order lags [D(LOGSRI(−2))]. The variable [D(LOGGDP(−3))], with a significant t-statistic value at 2.916, also helps to explain the changes in the overall rents.

This paper highlights the importance of the first and third differences of the lagged macroeconomic variables of the monthly earnings of individuals is moderately significant. The VR in the first and second differences is significant in accounting for the variation in changes of overall retail rents with their t-statistics values being above 3.0. It is thus meaningful for policy makers to so enhance their in-depth understanding.

This paper fulfills an identified need to study how the results from the ex post forecasting estimates from the VECM for overall retail rents in Singapore can be enabled.

This study aims to review the approaches used in the analysis of rental income of residential property in Abuja, Nigeria, to strengthen the existing investment performance approaches initially relied upon by property investors towards having a better and reliable performance evaluation for property investment decision-making.

With the adoption of combined methodological approaches, quantitative data on rental history (2006–2016) were collected on the randomly selected residential investment properties (block of flats) available in the portfolio of estate surveying firms in the different locations/sub-markets of the study area. Data collected were analysed with the frequency mean and growth rate.

All the methodological approaches adopted for analysis displayed varying performance results. No particular sub-market maintains the same ranking position in any of the approaches. The developmental phases previously used as an indication of yield in the study area do not correspond with the status of rental income of sub-markets. Yield has been observed to be a mere attraction to property investment; it does not translate to income growth. Mean income (though a good indicator of changes in rental income) is not a reliable indicator of growth in income, and growth in the rate of income omitted the changes in rental income during the holding period.

The study was restricted to historical rental income data on a block of flat-type residential property, and it does not include capital value analysis or inquire into the factors responsible for variation in rental income during the study period. The outcome of this study is only applicable to a block of 4 number three-bedroom flats residential property type.

Multiple simple methods of analysing rental income performance should be preferred to the single complex method. This will simplify investors’ rental income characteristics of investment towards a better understanding of rental property investment analysis. That rental value appreciates with time does not translate to an increase in the actual rental income of residential investment property.

Through these performance approaches, ranking of the sampled properties in the study area sub-markets will enhance investors’ traditional diversification planning across the study area for an enhanced combination that can achieve latent profitability. The attention of investors is hereby called to these multiple approaches to enable them to merge their investment objectives with any or a combination of these approaches towards making rational investment decisions.

This seems to be the first advocacy for methodological paradigm shift applicable to direct residential property investment performance in Nigeria, using transaction rather than appraisal data.

The prediction of Airbnb listing prices predominantly uses a set of amenity-driven features. Choosing an appropriate set of features from thousands of available amenity-driven features makes the prediction task difficult. This paper aims to propose a scalable, robust framework to predict listing prices of Airbnb units without using amenity-driven features.

The authors propose an artificial intelligence (AI)-based framework to predict Airbnb listing prices. The authors consider 75 thousand Airbnb listings from the five US cities with more than 1.9 million observations. The proposed framework integrates (i) feature screening, (ii) stacking that combines gradient boosting, bagging, random forest, (iii) particle swarm optimization and (iv) explainable AI to accomplish the research objective.

The key findings have three aspects – prediction accuracy, homogeneity and identification of best and least predictable cities. The proposed framework yields predictions of supreme precision. The predictability of listing prices varies significantly across cities. The listing prices are the best predictable for Boston and the least predictable for Chicago.

The framework and findings of the research can be leveraged by the hosts to determine rental prices and augment the service offerings by emphasizing key features, respectively.

Although individual components are known, the way they have been integrated into the proposed framework to derive a high-quality forecast of Airbnb listing prices is unique. It is scalable. The Airbnb listing price modeling literature rarely witnesses such a framework.

The purpose of this paper is to examine the structure and dynamics of Singapore's Central Area office market. A long-run equilibrium relationship is tested and a short-run adjustment error correction model are estimated, incorporating appropriate serial error correction. The long-run equation is estimated for office rent, with office employment and available stock.

With the vector error correction model (VECM), the lagged rent, available stock, office employment, vacancy and occupied stock (OS) can impact the rental adjustment process. Equilibrium rent on the whole reacts positively to lagged rents, available stock, office employment, OS and negatively to vacancy rates (VC). Past levels of positive change in VC and rental growth can have negative effects on current OS.

While good economic conditions signaled by increases in rents increase the supply of new stock (available space), higher rents and VC dampen the long-term occupied space (space absorption) in accordance with economic theory. Available stock can be forecasted by past rent and absorption levels owing to the developer's profit-driven nature.

An understanding of the interaction between the macroeconomic variables and the Central Area office market is useful to domestic and foreign investors and developers, who then can better evaluate their decision making in commercial real estate investment and development projects.

It is implicit that the Singapore Central Area office market requires at least a year before any rental increase can potentially dampen the space demanded. Firms are attracted to locate there owing to agglomeration economies and they are willing to pay premium office rents in conjunction with office space intensification in the Central Area. Newly built space is positively affected by past rents. Urban Redevelopment Authority and private real estate developers should be wary of excess office sector vacancies by avoiding over supply, even though an increase in the supply of office space in the Central Area can have a positive impact on office rent in the longer term. Most of the office space development would tend to meet the demand in the long run. Rental stickiness is exemplified as rental changes are affected by lagged rent.

Policy makers are better enabled to stabilize the office sectors of the real estate market if so required.

The paper adopts the VECM and validated by empirical evidence, to investigate the long-run equilibrium relationship and short-term corrections underlying the dynamics of the Singapore Central office market. Delay in the restoration of equilibrium in real estate markets is attributed to factors like lease terms and supply lags.

This paper aims to contribute to the banking and housing market literature by proposing an alternative measure of rate of return for Islamic banks that is based on the rental rate of the property. This alternative Islamic mortgage pricing mechanism could be adopted by Islamic banks as a replacement for mortgage rates if it is found to be independent from any form of interest rates as required by Islamic law.

By investigating the short run and long run dynamics between rental price index (RPI) and the proposed Islamic Rental Rate (RR-I) and, three selected macroeconomic indicators in the UK via autoregressive distributed lag model, the authors examine the link between RPI, RR-I and the real economy.

The findings provide evidence that while RPI in the UK is significantly related to three leading macroeconomic variables, namely, gross domestic product (GDP), real effective exchange rate and interest rates measures, while RR-I is only impacted by changes in GDP. More importantly, the authors show that there is no short or long run dynamics between the rental rate and any form of interest rates.

This paper did not attempt to investigate the impact of the physical attributes of the rental property to formalize the model describing the relationship between RPI and RR-I. Also, other macroeconomic factors like household income growth, risk, house value growth rate and taxation could be included in future models.

As Rental Rate is not linked to the macroeconomic determinants, it is therefore more stable, resilient and sustainable and, at the same time, making the financing less risky for both parties, as they are less susceptible to economic vulnerabilities.

Some calculations incorporating the proposed RR-I can also be extended to the pricing of products based on other contracts such as Tawarruq, Bai Bithaman Ajil or even Murabahah for a fairer and just pricing to both the banks and customers.

The results suggest that Islamic banks should consider incorporating the proposed rental rate (RR-I) when pricing their home financing products, as this will lead to less dependence on interest rates for benchmarking. In addition, using the proposed rental rate (RR-I) reduces the exposure to the subjective evaluation by property valuators and speculative macroeconomic elements.

The purpose of this study is to highlight the determinants of market rents and to build a hedonic market rent index for each urban area and rental sector in France for the period 1970–2013. The authors also analyse the market rent dynamics over this period, with a special attention to the turning points in the French housing policy.

For this purpose, the authors implement a hedonic model, called stratified time dummy variable, using the Box–Cox transformation as a functional form.

The contribution of this study to the housing research is threefold: First, the study improves our understanding of the French’s rental submarket specificities and their valuation. It sheds new light on the determinants of rents. Second, this study builds a hedonic market rent index over the period 1970–2013 for each geographical and sectoral segment (Paris urban area, urban areas of more and less than 100,000 inhabitants and private and public rental sectors). Third, this study explains rent dynamics focusing on the turning points in the French housing policy.

Finally, the authors provide the first long-term market rent index in France by submarket (geographical and sectoral). In the case of the French market, no long-term market rent exists. The only long series available is an indexed rent.

Short-term rentals (STRs) (like Airbnb) are reshaping social behaviour, notably in gastronomy, altering how people dine while travelling. This study delves into revenue management, examining the impact of seasonality and dining options near guests’ Airbnb. Machine Learning analysis of Airbnb data suggests owners enhance revenue strategies by adjusting prices seasonally, taking nearby food amenities into account.

This study analysed 220 Airbnb establishments from Madrid, Spain, using consistent monthly price data from Seetransparent and environment variables from MapInfo GIS. The Machine Learning algorithm calculated average prices, determined seasonal prices, applied factor analysis to categorise months and used cluster analysis to identify tourism-dwelling typologies with similar seasonal behaviour, considering nearby supermarkets/restaurants by factors such as proximity and availability of food options.

The findings reveal seasonal variations in three groups, using Machine Learning to improve revenue management: Group 1 has strong autumn-winter patterns and fewer restaurants; Group 2 shows higher spring seasonality, likely catering to tourists, and has more restaurants, while Group 3 has year-round stability, fewer supermarkets and active shops, potentially affecting local restaurant dynamics. Food establishments in these groups may need to adapt their strategies accordingly to capitalise on these seasonal trends.

Current literature lacks information on how seasonality, rental housing and proximity to amenities are interconnected. The originality of this study is to fill this gap by enhancing the STR price predictive model through a Machine Learning study. By examining seasonal trends, rental housing dynamics, and the proximity of supermarkets and restaurants to STR properties, the research enhances our understanding and predictions of STR price fluctuations, particularly in relation to the availability and demand for food options.

While the declining rate of urban security and its potential effects have been globally acknowledged, the ways urban neighborhood security shapes real estate markets in African cities remain largely unexplained. The purpose of this paper therefore is to present the findings from a study of the nexus between urban neighborhood security and home rental prices in Lagos, Nigeria.

This paper is based on the hedonic price theory, an objectively derived urban neighborhood security index (UNSI) and property rental price data in Ojo, Lagos, Nigeria. This is a quantitative cross-sectional study that employs multistage sampling survey procedure. Data are analyzed using descriptive statistics, nonparametric correlation and hedonic price function with ordinary least squares (OLS).

Results show that nearly 50% of the study area is prone to insecurity and average rental values in Ojo, Lagos range from N151329.41 ($302.66) to N167333.33 ($334.67) per annum. Correlation analysis shows that home rental prices have high, positive and significant correlations (rs = 0.725 and p < 0) with UNSI. After controlling for neighborhood and structural factors, it is found that urban neighborhood security positively influences home rental values as a unit improvement in security leads to N81000.00 ($162.00) increase in rental value per annum.

Urban neighborhood security risk threatens residential property values, creates unintended residential mobility and destabilizes families. Findings from this study point to the facts that security is a key component of urban housing values and developers, and real estate investors must ensure that this component is well factored into property design, construction and valuation.

This is perhaps the first study that uses an objectively derived UNSI to study home rental price dynamics in Nigeria. The study extends knowledge on urban housing price determinants and contributes to literature on the crucial place of security in property management.