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This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market.

The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region.

The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values.

The robustness of the models would be enhanced by the addition of further spatial levels and larger data sets.

The methods introduced in this study can be used by real estate agents, valuers and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments.

The application of these methods is intended to inform a fairer approach to setting insurance premiums and a better basis for determining policy interventions and public investment designed to mitigate potential earthquake risk.

The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach.

The purpose of this study is to examine the influence of key hotel attributes on the room rates of selected hotels in the Greater Gaborone Region, Botswana.

Using hedonic pricing analysis, the effect of eight attributes collected from 80 standard double rooms on Booking.com in the area was analysed using quantile regression.

The estimated results from quantile regression suggested the importance of the 10th quantile as the best predictor of hotel room price distribution. Overall, the presence of a fitness centre and the availability of meeting and conference facilities were positively significant for the lowest- and premium-priced hotels, respectively.

The study advanced the literature in hedonic pricing models by confirming the applicability of hotel room rate attribute research in unexplored environments.

Hotel managers should be aware of the influence of key attributes, such as meeting and conference space availability and locational factors, on the pricing decisions of room rates in the Greater Gaborone Region. The study also presented opportunities for business-to-business marketing between hotel and tour operators in the region.

The study is one of the few that uses quantile regression in the hedonic pricing analysis of hotel room rates.

This study aims to measure the occurrence of gentrification and to relate gentrification with housing values.

The authors have used Getis-Ord statistics to identify and quantify gentrification in different residential areas in a case study of Stockholm, Sweden. Gentrification will be measured in two dimensions, namely, income and population. In step two, this measure is included in a traditional hedonic pricing model where the intention is to explain future housing prices.

The results indicate that the parameter estimate is statistically significant, suggesting that gentrification contributes to higher housing values in gentrified areas and near gentrified neighbourhoods. This latter possible spillover effect of house prices due to gentrification by income and population was similar in both the hedonic price and treatment effect models. According to the hedonic price model, proximity to the gentrified area increases housing value by around 6%–8%. The spillover effect on price distribution seems to be consistent and stable in gentrified areas.

A few studies estimate the effect of gentrification on property values. Those studies focussed on analysing the impacts of gentrification in higher rents and increasing house prices within the gentrifying areas, not gentrification on property prices in neighbouring areas. Hence, one of the paper’s contributions is to bridge the gap in previous studies by measuring gentrification’s impact on neighbouring housing prices.

The world over is becoming urbanized, and people are migrating to cities in large numbers in search of opportunities. The increased urbanization has posed challenges such as congestion, rising crime, and growing urban poverty. The governments respond by providing amenities such as schools, hospitals, and housing to meet to increase in demand for these facilities. However, there is a need for the provision of facilities that meets the expectations of the people, particularly on the proximity of amenities and bundles of utility-bearing housing characteristics. In an attempt to address the challenge mentioned, the study estimated the hedonic characteristics influencing the willingness to accept and willingness to pay for housing facilities in the Eastern Cape Province, South Africa. Using a multiple linear regression model and artificial neural network, the study found out that properties with a bathroom, garage and large floor size have a higher value compared to properties without these facilities.When making decisions to acquire a property, buyers consider the availability of discounts and the prevailing property price. Overall, willingness to pay and accept decisions are mainly determined by location and the price at which homogeneous neighborhood properties were sold. Therefore, the study recommends that urban town planners and other housing authorities prioritize the construction of properties with larger floor areas, parking bays, and bathrooms using a cost-effective mechanism that makes the properties affordable to residents.

The purpose of this study is to analyse the trends regarding housing segregation over the past 10–20 years and determine whether housing segregation has a spillover effect on neighbouring housing areas. Namely, the authors set out to determine whether proximity to a specific type of segregated housing market has a negative impact on nearby housing markets while proximity to another type of segregated market has a positive impact.

For the purposes of this paper, the authors must combine information on segregation within a city with information on property values in the city. The authors have, therefore, used data on the income of the population and data on housing values taken from housing transactions. The case study used is the city of Stockholm, the capital of Sweden. The empirical analysis will be the estimation of the traditional hedonic pricing model. It will be estimated for the condominium market.

The results indicate that segregation, when measured as income sorting, has increased over time in some of the housing markets. Its effects on housing values in neighbouring housing areas are significant and statistically significant.

A better understanding of the different potential spillover effects on housing prices in relation to the spatial distribution of various income groups would be beneficial in determining appropriate property assessment levels. In other words, awareness of this spillover effect could improve existing property assessment methods and provide local governments with extra information to make an informed decision on policies and services needed in different neighbourhoods.

On housing prices emanating from proximity to segregated areas with high income differs from segregated areas with low income, policies that address socio-economic costs and benefits, as well as property assessment levels, should reflect this pronounced difference. On the property level, positive spillover on housing prices near high-income segregated areas will cause an increase in the number of higher income groups and exacerbate segregation based on income. Contrarily, negative spillover on housing prices near low-income areas might discourage high-income households from moving to a location near low-income segregated areas. Local government should be aware of these spillover effects on housing prices to ensure that policies intended to reduce socioeconomic segregation, such as residential and income segregation, produce desirable results.

Furthermore, a good estimation of these spillover effects on housing prices would allow local governments to carry out a cost–benefit analysis for policies intended to combat segregation and invest in deprived communities.

The main contribution of this paper is to go beyond the traditional studies of segregation that mainly emphasise residential segregation based on income levels, i.e. low-income or high-income households. The authors have analysed the spillover effect of proximity to hot spots (high income) and cold spots (low income) on the housing values of nearby condominiums or single-family homes within segregated areas in Stockholm Municipality in 2013.

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.

The authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.

The results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.

To the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.

This paper aims to investigate whether developers’ ask lower prices on homes in redevelopment sites than they do on similar units in smaller developments completed over a shorter time span. It also investigates whether developers price units differently at different stages of the redevelopment process. The development of designated redevelopment areas often consists of multiple projects spread across several years, some in parallel, some sequential. New units are put on the market in a piecemeal fashion, and infrastructure, shared green spaces and shared facilities are installed successively.

A hedonic price model is used to analyse sales prices of 7,000 new apartments in Oslo sold between 2011 and 2015, all else being equal. The paper distinguishes between infill as one-stage projects, and multi-staged competitive and multi-staged monopolistic redevelopments.

Dwellings in redevelopment projects sell at a lower price than similar dwellings in infill projects. In competitive redevelopments, those in charge of the last projects put a slightly higher price on apartments. In redevelopments involving only one developer, the last stages ask the lowest prices.

This research expands our understanding of developers’ pricing behaviour. Developers supplying housing for the private market through redevelopments land are willing to take risks particularly in the initial stage.

The findings indicate that credit institutions financing developers’ projects need to take into account the structure of selling prices, including lower prices and higher risk of pursuing redevelopment projects.

Gaining a better understanding of developers’ pricing behaviour deepens our insights into the dynamics of market-led urban brownfield developments; this knowledge may moreover inform policies on sustainable urban growth.

An original investigation of housing transactions in urban brownfield sites in Oslo provides fresh insights into developers’ pricing behaviour.

The purpose of this study is to investigate tourist in-destination consumption patterns in the context of bundled holiday packages in different resort categories to identify demand behavior that allows implementing profit-enhancing policies through attractive bundled offers for specific tourist segments.

This study relies on data gathered in a quasi-experiment to analyze differences in consumption patterns at resort bars over a two-year period (summer 2018 and 2019) before and after the introduction of an all-inclusive soft drinks package.

The findings inform on bundling strategies according to different degrees of price consciousness and resort category. In particular, guests in upscale resorts are more likely to under-consume items included in a pre-paid bundle and significantly engage in additional spending than economy resort guests.

The quasi-experiment provides the actual in-destination consumption patterns and offering managerial insights and tools to tailor the form and content of bundles according to resort category.

本研究的目的是调查游客目的地消费模式在不同度假村类别的捆绑度假套餐的背景调查及研究。本研究旨通过深入了解市场需求, 来针对特定游客细分市场提供对其具有吸引力的捆绑优惠, 目的是让完善定价决策, 从而达到更优化利润。

本研究依赖于通过准实验收集的数据, 该准实验侧重于分析度假村客人在两年期间（2018 年和 2019 年夏季）在推出全包无酒饮料套餐前后在度假村酒吧的消费模式的变化。

研究结果为如何根据度假村类别相关的不同价格意识程度来运用捆绑策略。到达目的地后, 高档度假村的客人更有可能对预购捆绑包中包含的物品消费不足, 并且与入住经济型度假村的游客相比, 大幅增加额外支出。

我们的准实验审查了几乎没有被研究学习过的客人在目的地的实际消费模式。本研究对有用的管理工具的认识有更进一步的贡献：捆绑包的内容重点应由经济度假村的从业人员精心设计; 而在高档度假村, 应该以混合捆绑作为捆绑策略的一种形式。

El objetivo de este estudio es investigar los patrones de consumo de los turistas en destino en el contexto de los paquetes vacacionales combinados en diferentes categorías de complejos turísticos. Esta investigación persigue la adquisición de un conocimiento profundo del comportamiento de la demanda que permita la aplicación de políticas de precios que aumenten los beneficios mediante la orientación de ofertas con paquetes atractivos a segmentos específicos de turistas.

El estudio actual se basa en los datos recogidos a través de un cuasi-experimento centrado en el análisis de las diferencias en los patrones de consumo de los huéspedes del resort en los bares del mismo durante un período de dos años (temporadas de verano 2018 y 2019), antes y después de la introducción de un paquete de refrescos con todo incluido.

Los resultados del estudio informan sobre cómo aprovechar las estrategias de agrupación según los diferentes grados de conciencia de los precios asociados a la categoría del complejo turístico considerado. Una vez que llegan al destino, los huéspedes de los complejos turísticos de categoría superior son más propensos a no consumir los artículos incluidos en un paquete precomprado y a realizar un gasto adicional significativo en comparación con los turistas alojados en complejos turísticos económicos.

Nuestro cuasi-experimento examina empíricamente las pautas de consumo reales de los huéspedes en el destino, que apenas han sido examinadas. Este estudio contribuye además al reconocimiento de herramientas de gestión útiles: los profesionales de los complejos turísticos económicos deberían diseñar cuidadosamente el enfoque del paquete en términos de su contenido, mientras que el paquete mixto como forma de estrategia de agrupación debería favorecerse en los complejos turísticos de alto nivel.

The role of list price is often discussed in a narrative describing sellers’ preferences or sellers’ price expectations. This paper aims to investigate a set of list price strategies that real estate brokers have available to influence the outcome of the sale, which may be many times self-serving.

By analyzing real estate brokers’ arguments on the choice of the list price level, a couple of hypotheses are formulated with regard to different expected outcomes that depend on the list price. This study empirically tests two hypotheses for the underlying incentives in the choice of list price from the real estate broker’s perspective: lower list price compared to market value leads to the higher sales price, lower list price compared to market value leads to a quicker sale. To investigate the two hypotheses, this paper adopts different methodological frameworks: H1 is tested by running a classical hedonic model, while H2 is tested through a duration model. This study further tests the hypotheses by splitting the full sample into two different price segments: above and below the median list price.

The results show that H1 is rejected for the full sample and for the two sub-samples. That is, contrary to the common narrative among brokers that underpricing leads to a higher sales price, underpricing lower sales price. H2, however, receives support for the full sample and for the two sub-samples. The latter result points to that brokers may be tempted to recommend a list price significantly below the expected selling price to minimize their effort while showing a high turnover of apartments.

Although there are a large number of previous studies analyzing list price strategies in the housing market, this paper is one of the few empirical studies that address the effect of list price choice level on auction outcomes of non-distressed housing sales.

Weaknesses in the grades and standards system in low-income countries across Sub-Saharan Africa undermine the transparency of agricultural markets. In the Democratic Republic of the Congo (DRC), Ghana and Mozambique rice is predominately sold in open bags and if rice price does not reflect its quality, then inefficiencies may lead to consumer welfare losses. Importantly, it is possible that impoverished communities are priced out of the market due to inflated and inefficient prices. The objective of this study is to examine determinates of rice price by estimating the impact of selected rice quality attributes on rice prices in Democratic Republic of the Congo, Ghana and Mozambique.

We collected 363 rice samples from open air markets in Bukavu (DRC), Nampula (Mozambique) and across Ghana in 2019. Each rice sample was analyzed in a food science lab for the quality attributes: percentage of chalk and brokens, chalk impact, length and length-to-width ratio. We used multiple regression analysis to estimate if and to what extent quality attributes were the drivers of price.

Findings suggest that there are irregularities in the Ghanaian market for broken rice and that regardless of quality, imported rice is priced higher than domestic rice. In the DRC and Mozambique, our results indicate price is driven by length and length-to-width ratio in the former and length-to-width ratio in the latter.

Rice samples were purchased from market vendors and thus consumer preferences for attributes were not revealed.

These results provide valuable insight to policymakers regarding the need for proper labeling and regulation of open bag rice sales in an effort to increase consumer welfare and improve food security.