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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.

Real estate is one of the fundamental growth engines for developing economies as it contributes urbanization and infrastructure development. In recent years, Somalia has witnessed massive real estate development in both housing and commercial buildings. The purpose of this study is twofold. First, the study examines the determinants of residential property rents. Second, it investigates whether residential property rents are fairly valued.

This study uses two-stage modeling. A hedonic regression model is used in the first stage, while an artificial neural network is applied in the second stage.

After analysis, this study established that size, location and security of a residential property have a significant influence on its monthly rents. Alternatively, the study identified that residential property rents are not fairly valued in Mogadishu and overvaluation is more frequent than undervaluation.

This implies that Somalia’s real estate industry is more speculative-driven than real demand-driven. Though Somali real estate is an infant industry with huge potentials in the long run, it may end up disastrously following the well-known bubble-then-burst behavior. To avoid such crisis, this study recommends formulating government policies that regulates, supervises and protects the infant real estate industry without undermining the needs of the poor and low-income citizens.

Housing prices in Brazil have displayed an impressive growth in recent years, raising some concerns about the existence of a bubble in housing markets. In this paper, the authors implement an empirical methodology to identify whether or not there is a bubble in housing markets in Brazil.

Based on a theoretical model that establish that, in the absence of a bubble, a long-run equilibrium relationship should be observed between the market price of an asset and its dividends. The authors implement two methodologies. First, the authors assess whether there is a cointegration relationship between housing prices and housing rental prices. Second, the authors test whether the price-to-rent ratio is stationary.

The authors’ results show that there is evidence of a bubble in housing prices in Brazil. However, given the short span of the data, the authors perform a Monte Carlo simulation and show that the cointegration tests may be biased in small samples. Therefore, the authors should be caution when assessing the results.

The results obtained from the cointegration analysis can be biased for small samples.

The information on the excessive increase of the prices of the properties in relation to their fundamental value can help in the decision-making on investment of the economic agents.

These results corroborate the hypothesis that Brazil has an excessive appreciation in housing prices, and, as Silva and Besarria (2018) have suggested, this behavior explains, in part, the fact that the central bank has taken this issue into account when deciding about the stance of monetary policy of Brazil.

The originality is linked to the use of the Gregory-Hansen method of cointegration in the identification of bubbles and discussion of the limitations of the research through Monte Carlo simulation.

Real estate developers often operate in oligopolistic environments. Pricing strategies must be made in an interactive framework that makes empirical evaluation difficult. This study appeals to economic experiments to examine how developers price their properties, especially when there is an option to market pre‐completed units. In addition, the interaction between bidding for land and pricing the end product is examined. The results indicate that competitor actions are important considerations in pricing decisions. In particular, the profit maximizing pricing strategy depends critically on being competitive, not necessarily being the most aggressive. Interestingly, pre‐completed units sell only at prices that incorporate future price expectations, and successful bids tend to precipitate more aggressive pricing. Finally, competitive bidding and pricing strategies appear to the best profit maximizing strategy.

The purpose of this paper is twofold: to explore the distribution and pricing characteristics of Airbnb listings in Malta as at May 2019; and to develop a pricing model to determine the factors which have a statistically significant impact on price per night of listings.

A descriptive analysis of location and pricing of listings was undertaken via heat mapping techniques. A cross-sectional ordinary least squares (OLS) regression was run to determine the statistically significant variables.

Listings tend to cluster around not only in traditional tourist towns but also in rural areas which opens up new opportunities for tourist lodging. The Southern Harbour region was found to be the most expensive with the Gozo and Comino region being the least expensive. The coefficients of the pricing regression model were in line with a priori expectations.

The study is based on a cross-sectional data set and thus fails to account for seasonal changes in prices. Likewise, the use of an OLS regression without incorporating quantile regression methods or spatial autocorrelation econometric techniques is another limitation of this study.

The paper is one of the few related to sharing economy rental platforms, particularly in Malta. It is also the first study in Malta to develop a comprehensive pricing model to determine what affects a listing’s price per night and the extent to which certain factors do so.

The purpose of this paper is to investigate the role of distinct types of heating technology and their price impact in German residential real estate markets, considering a wide range of other housing market determinants. The authors aim to test and to verify specifically, whether the obsolescence of heating technology leads to a significant price discount and whether higher technological standards (and environmental friendliness) come with a price premium on the market.

The authors create housing market models for rental and sales segments by constructing generalized additive models with explicit multi-layered spatial components. To elaborate a profound and contemporary answer using these models, the authors perform large-sample regression analyses based on more than 400,000 observations covering German residential properties in 2015.

First and foremost, the heating system indeed shows significant explanatory importance for measuring housing rents and purchasing price. Second, the authors find that it makes a difference whether clean “green” technologies are implemented or whether “brown” systems with obsolete technology or fossil energy sources is on hand. Ultimately, the authors conclude that while low energy consumption indeed comes with a price premium, this needs to be interpreted together with the property’s heating type, as housing markets seem to outweigh the “green premium” by “brown discounts” if low energy consumption figures are powered by a certain type of heating technology system.

Aside of a possible omitted variable bias, the main research limitation is constituted by the integration of asking prices in the analysis, as actual transaction prices are not systematically transparent on national level in Germany. Limitations are discussed at the end of the paper.

This work supports investors who face the challenge of making environmental- and energy-related decisions as well as appraisers who deliver financial fundamentals for such. Third, the paper supports both asset managers as well as investment strategists in argumentation pro-environmental investments beyond all ecological necessity.

This paper contributes to the current discussion on climate change and the eclectic role of real estate in this context. The authors deliver evidence on pricing effects as a measure of socioeconomic acceptance of progressive heating technology and environmental friendliness as an imperative of twenty-first century societies.

This is the first study on “green premiums” or “brown discounts” that includes heating technology as a potential and distinct driver of value and rents. It is a contemporary contribution and delivers original information on the quantitative impact of contemporary and anachronistic technology in heating to researchers as well as investors and appraisers.

The purpose of the study is to understand the relative impacts of structural characteristics of house, its locational attributes and neighbourhood characteristics on the choice of house and the rent paid by the individual tenants. The micro level study helps in understanding the issues of urban housing and help in policy formulation.

This paper tried to identify the socio-economic, locational and neighbourhood factors that influence tenant households in determining their residential choices in an urban area of North-east India. Also, the extent of impacts of those characteristics on the monthly rent for housing is analysed. The analysis is based on the primary data collected from the sample residents of Dimapur Town in Nagaland. The sample units are selected by cluster sampling technique from all the wards. Regression technique is used under hedonic pricing technique to examine the impacts of various potential factors on the rent.

The analysis reveals that family size, income, education of the head of family, water availability, security, convenience to access workplace, road conditions, etc. have significant positive impacts on the monthly rent. However, the impacts of some locational and neighbourhood variables vary across social and economic groups.

Time series data on the growth of house price are not available, so that the authors could examine the escalation of house price and rising scarcity of houses in the selected town.

Rental housing accounts for a significant percentage of housing in many urban centres. It is particularly important for the migrants and urban poor for whom it is the only source of accommodation. Location choice depending on capability, availability, requirement and neighbourhood conditions are integral parts of selection of accommodation in a city. Hence the present study has its relevant practical implications.

Housing choice in a hilly urban area like Dimapur assumes a special significance for the presence of heterogeneous ethnic, social and cultural groups with majority of Tribal inhabitants with varied requirements and lifestyle.

No study on housing choice or pricing of residential accommodation has been done in North-East India. Here along with the socio-economic characteristics of the individuals, structural characteristics of house, neighbourhood and locational characteristics are used simultaneously to find out the impact of various factors on the total prices through hedonic pricing method.

Cost of construction of residential properties as well as its subsequent rent trends remain a major challenge to stakeholders in the property rental markets of emerging economies. This study examined the relationship between housing construction costs and house rents fluctuations in Osogbo, Nigeria, to provide information for informed investment decisions.

The authors conducted a survey, where three sets of questionnaires were administered on building contractors; estate surveyors and valuers and private residential property owners. The data required comprise the estimated average construction costs and average market rents for two and three-bedroom bungalows in the study area from 2008 to 2018. These data were respectively sourced from all the 15 firms of building contractors and 25 firms of estate surveyors and valuers in Osogbo, Nigeria. Stratified random sampling was employed to select 180 property owners from three medium-density residential districts of Osogbo. Secondary data on macroeconomic variables were sourced from the Central Bank of Nigeria. Data collected were analysed using descriptive and inferential statistical tools.

The authors found a significant positive relationship (0.749) between construction costs and house rents trends; both variables maintained ascending trends. Construction costs and house rents inflation rates exhibited random fluctuations with the former having a higher mean inflation rate (10.47%). However, the difference was not statistically significant (p-value = 0.317 > 0.05). Respondents identified consumer price index (CPI) inflation among other macroeconomic variables as the strongest predictor of both construction costs and house rents fluctuations. However, evidence from further analysis of the time series suggested otherwise.

The result confirms construction cost as one of the vital supply factors of the housing market, which is often pass through to house rents. The positive relationship between construction costs and house rents trends should trigger new development which, will, in turn, allow rental housing investments to expand into new areas with prospects for profits that could be earned by domestic and foreign investors.

This study to the best knowledge of the researchers is the first to relate housing construction cost to house rent in Osogbo, Nigeria; thereby adding to the body of knowledge in this field.

There is a general consensus that residential submarkets exist, but the basis upon which these are specified remains the subject of debate. The purpose of this paper is to model data on different residential locations in Ghana to show how the submarkets have performed over the past 16 years.

The paper employs hedonic modelling based on 3,250 sale transactions and 1,130 rental transactions from 1992 to 2007.

The results demonstrate that five residential real estate characteristics – location, detached, landscaping quality, gross internal areas and plot size – predominate in the explanation of both rental and transactions prices across all submarkets. They also highlight points of variation between the submarkets. An understanding of the impact of these features on residential price and rent is important for capital and rental valuation.

This paper analyses historic performance of the residential market, both at the aggregate and disaggregate level to place the housing market in an investment context.

Chinese housing market has been growing fast during the past decade, and price-related forecasting has turned to be an important issue to various market participants, including the people, investors and policy makers. Here, the authors approach this issue by researching neural networks for rent index forecasting from 10 major cities for March 2012 to May 2020. The authors aim at building simple and accurate neural networks to contribute to pure technical forecasting of the Chinese rental housing market.

To facilitate the analysis, the authors examine different model settings over the algorithm, delay, hidden neuron and data spitting ratio.

The authors reach a rather simple neural network with six delays and two hidden neurons, which leads to stable performance of 1.4% average relative root mean square error across the ten cities for the training, validation and testing phases.

The results might be used on a standalone basis or combined with fundamental forecasting to form perspectives of rent price trends and conduct policy analysis.