Search results

Presents the findings of the first comparative econometric investigation into the influence of demand side forces on retail rent determination in European cities. Examines five major retail centres ‐ Amsterdam, Brussels, Hamburg, London and Paris ‐ over the period 1980 to 1994. Estimates for each city a theory consistent model which tests influences of GDP, retail sales and consumer expenditure on changes in retail rents. Univariate and multivariate regressions show that the relative explanatory capabilities of these influences exhibit a notable degree of variation between the cities. A time series cross‐sectional analysis demonstrates that contemporaneous changes in GDP are the most important common determinant of retail rents across the cities and that the process of rent determination in Paris is influenced by different structural factors from the other cities examined.

The paper aims to form system dynamics modeling in introduced in conjunction with econometric analysis and planned scenario analysis which will uniquely structure the process whereby the ex ante capital values of the prime retail real estate sector.

The integrated system dynamics model investigates the structural factors affecting a unique expectation‐centered capital value (CV) formation of the prime retail real estate sector, through system dynamics modeling, econometric analysis , and the analysis of planned scenarios. This model extends beyond the usual lags and time line aspect of the price discovery process. The retail real estate sector is investigated within the Singapore context, as this sector changes dynamically and non‐linearly in relation to rental, cost and general demand expectations and to exogenous shocks like the Severe Advanced Respiratory Syndrome (SARS) outbreak. These macroeconomic factors are introduced to investigate their impact on retail space CVs through sensitivity analysis, during the simulation period of 20 quarters from the zero reference quarter (2Q2002).

The paper finds that simulation runs of the expectations‐centered system dynamics model are based on three scenarios. Sensitivity analysis is conducted for each scenario. Optimistic scenarios' CVs are lower than those of the likely scenario, owing to developers forming excessively high expectations that cannot be met by the actual rental levels. Pessimistic scenarios' CVs are highest. Based on bounded logic and the conditions for all scenarios, there are huge differences in expectations resulting in a large disparity in the endogenous CVs. Low actual rents are primarily due to poor informational efficiency, as the prime retail real estate sector is not transparent enough, and that many transactions are privately closed. Expectations cannot be met as the market information is not disseminated extensively through the agents and players. The scenarios clearly highlight the problem of informational non‐availability in the sector. The main policy implication is a need for a more transparent system of sharing rental and pricing information for the retail real estate sector, which is meaningful for real estate developers, investors and urban planners to sustain the retail real estate sector's viability.

This paper takes system dynamics modeling to the next level of incorporating econometric analysis, to estimate the sensitivity of retail rent to cost and the change in retail rent, for effectively structuring the dynamic process whereby the ex ante CVs of the prime retail sector in Singapore are formed and assessed, through a unique and rigorous expectations‐centered system dynamics model of rents, cost, retail stock, general demand and exogenous factors.

Considers the potential impact of seven‐day trading on the spatial pattern of retail rents. Notes that the Institute of Fiscal Studies predicts that Sunday trading will have no appreciable effect on the overall level of turnover in the retail sector resulting in a decline in the real value of retail rents. Concludes that shopping areas in large town centres are most vulnerable to a decline in retail activity.

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.

The purpose of this paper is to investigate the factors that affect the retail rent of shopping centres in Wuhan, an important city in central China.

The study uses a data set of 68 shopping centres in urban Wuhan. A regression model is constructed to estimate the impact on retail rent of a composite range of variables that would capture the physical characteristics, spatial characteristics, potential attractiveness of shopping centres and market condition.

The empirical findings suggest the ceiling height, closeness to metro line station, being situated in commercial central area, vacancy rate and income have significant impact on rental level. Unexpected, the retail mix has a significant negative impact on rent. The impact of the more determining factors found in Western research – size, age, parking space and anchor tenant – is not supported in the Wuhan study.

While 68 shopping centres are included in the test, the sample size is relatively small. The comparatively short history of retail market in Wuhan would not allow to test the rent adjustment process.

This is the first paper to investigate retail rent determinants in a second-tier city in China. The results of the study give designers, developers and investors critical insights into the determinants of retail rent in an emerging market.

The purpose of this paper is to estimate the determinants of the retail space rent in Shanghai.

Hedonic model and spatial regression models are used in the paper. The problem of spatial autocorrelation is tested by Moran's I statistics, and the root mean square error (RMSE) test is performed to find out the best model.

The significant explaining variables are the age, the area of retail space, the distance to the Jing An CBD centre, the type of the retail and the district of the property. A new classification of district in retail research context is suggested in this paper, and it is proved to be better than the districts set up by government to explain the retail rent variation.

This paper presents the first empirical study about the retail rental market in Shanghai. The research helps retail property investors and retail tenants deepen their understanding of the retail market in Shanghai. Spatial econometrics techniques are first introduced into the empirical retail rent research to produce a more precise estimation.

From the perspective of the macro‐economy and real estate sector interaction, this paper aims to examine the maturing prime retail real estate sector versus the developing suburban retail real estate sector.

This paper adopts a highly specific dynamic computable general equilibrium model under system dynamics programming to structure the resulting system complexity within the context of Singapore.

Ex post and ex ante model estimations find that the suburban retail real estate sector is on the whole more susceptible to gross domestic product (GDP) growth policy that affects both GDP expansion and retail rents in actual and expectation terms as well as returns.

The DCGE model ex ante estimations for the planned scenarios, under low or high GDP growth for the prime and suburban retail real estate sectors, enhances understanding of structural factors and dynamic interaction in the maturation phase of the prime retail real estate sector in Singapore.

In comparison, Singapore's suburban retail real estate sector is found to be in a developing phase.

There is limited local research on the underlying relationship between the economy and the retail real estate sector, although Singapore's retail sector and retail real estate sector form an integral part of sustainable economic expansion.

The purpose is to increase knowledge of rent negotiations by investigating differences in beliefs held by property landlords and retailers on factors that they deem important in rent negotiation.

This study investigates differences in subjective beliefs held by landlords and retail trade tenants on factors that affect rent levels during the rent negotiation process using a factor analysis approach. Semi-structured interviews were made with seven large real estate owners/landlords and retailers and eight experts in negotiating retail rent to elicit variables that have an impact on retail rent. Thereafter, a web-based survey was sent to 421 respondents who had experience in rent negotiation. Several factors were extracted using factor analysis. The data collection was made in Sweden during the coronavirus disease 2019 (COVID-19) pandemic in late spring 2021

Significant differences are found in beliefs held by landlords and retail trade tenants in four out of seven-factor: regional growth, e-commerce, customer focus and trust. Landlords rate these factors higher than retailers do. There are also systematic differences between landlords and retailers depending on their education levels on the following factors: rent and vacancies, e-commerce and customer focus. The number of years of experience did not prove to be significant instead differences are found to exist in factors

Not only do traditional factors of importance, such as lease structure, the effect of location, size and anchor or non-anchor tenants, have an effect on negotiated rent levels. Differences in other factors also exist, such as regional growth, e-commerce, customer focus and trust factors that may play an important role in the negation of retail rent.

The findings provide new insights into the different views on factors that affect rent negotiations between landlords and retail tenants. Knowledge of such differences may increase the overall transparency in the negotiation process. Transparency may be increased by putting forward information on these factors before a negotiation takes place, in order to smooth differences in their beliefs.

If transparency in the negotiation process of retail rent increases, time to reach an agreement, stress and anxiety can be reduced by putting forward information on factors where differences exist between landlords and retailers

New insights on retail rent negotiation have been put forward in this research paper. Not only do traditional factors such as lease structure matters, but subjective beliefs on factors such as regional growth and the level of education are also important, as this study has shown using a factors analysis approach.

The aim of this research is to provide a new understanding of the concept of visibility in the realm of property research. Further, this study could propose a more accurate way of calculating retail unit rental price based on visibility. An accurate visibility quantification can influence rent negotiations between shopping mall management and potential tenants. This study can also assist shopping center management, shop owners and architects to have a better mechanism for determining the visibility value and the effect on the retail unit rental price.

The study uses data from 153 indoor retail stores in Jakarta and a sequential-transformative mixed method to answer an important question for modern retail management: How much would indoor store visibility affect rent? The authors developed a method to accurately measure an indoor retail store's object-based isovist – a visual field in which a number of observers can view the particular indoor store.

The study found that on average, each additional square meter person of visibility increases indoor retail rent price as much as IDR 40.74/sq m/month (USD 0.0027). Since visibility value is a variable with the greatest inter-store variation in this data set, the rent price difference between two stores with maximum and minimum visibility can reach IDR 100,904.62/sq m/month (USD 6.90). This finding is not just statistically but also financially significant since indoor inter-store retail rent price variation that can be directly attributed to visibility is about 38.4% of the average rent price in this data set.

Along with the rapid growth of e-commerce, numerous commercial properties are struggling to provide customers with a positive and distinct experience. Improving visibility can be a key spatial factor that will help shopping center designers, owners and management. The authors’ research can help shopping mall managers determine each store's optimum rent based on its visibility when negotiating with potential tenants.

The aim of this research is to provide a new understanding of the concept of appearance in the realm of property research. Further, this study could propose a more accurate way of calculating retail unit rental price according to the concept of visibility.

Examines the methodological issues that arise in generating standardised transaction data for use in analysing the determinants of retail rents. Looks at the issues raised by the use of comparative information and the existence of widely accepted conventions for adjusting comparative evidence to allow for the specific physical and legal characteristics of individual properties. Concludes by questioning the need to test valuation convention against market evidence and the notion of open market value is reassessed.