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The role of local authorities is crucial in addressing the essential needs of communities, and they possess the right to impose property taxes on all properties within their territory. Property taxes are levied on all properties, contributing to approximately 60% of the local authority’s finances. However, their role in this policy is not frequently understood, primarily in executing property tax reassessment. Hence, this paper aims to reveal property tax reassessment implementation and identify its key challenges.

The latest tone of the list record was extracted from the local government division, Ministry of Housing and Local Government Malaysia, to answer the research objective. The data were received on November 2021 by email. Furthermore, through the literature review, the most significant challenges in property tax reassessment were identified, compared and presented.

The results highlight that property tax reassessment implementation in West Malaysia is at the level of concern where only two councils have the latest tone of the list. However, larger councils have a higher performance compared to smaller councils. The findings also reveal various challenges in property tax reassessment, such as insufficient human resources, inadequate property systems and software and lack of financial capacity. Others include a shortage of competent assessors, lower public education, political interference and socioeconomic uncertainty.

This study offers practical implications to policy and decision-makers in the West Malaysian local authorities. Despite inferior performance by West Malaysian local authorities, there is a need for conducting property tax reassessment activity to ensure the quality and uniformity of the assessment. This study suggests that local government stakeholders and managers should devote more attention to formulating long-term plans and promoting the property tax reassessment practice. The property tax reform could solve the current situation of substandard reassessment activity.

This study explains, compares and interprets the actual statistical data through the figures and summarises the challenges of property tax reassessment activity among local authorities.

Properties with specific orientations are preferred in South Korea, depending on the real estate market. This preference is usually considered during property transactions and in designing buildings. Despite the importance of property orientation, the magnitude of preference for favored orientation has rarely been empirically estimated in the literature. This study attempts to estimate the value of favored orientation in a quantitative manner and interpret the results.

Using a geographically weighted regression model, this study obtains nationwide property price data and estimates the strength of orientation preference, that is, the premium for favored orientation. Among the various property types, residential sites and forests were investigated because the orientation of these two property types is known to influence their sales prices in the Korean real estate market.

The results show that premiums for south-facing residential sites exist in the market, varying locally and ranging from zero to 13.2%, over residential sites with non-south orientations. The results for forests are mixed in that a south-facing forest commands a maximum of 33.1% premium in a certain region, over a forest with a non-south direction, while it also commands a maximum of 33.8% negative premium (discount) in another region, indicating significant local variations in premiums.

These findings are expected to be utilized in fields such as property valuation, house architecture and design.

The green building (GB) market is maturing after years of practice; therefore, incentives for promoting GB should be adapted to reflect the market transformation. Adapting incentives can positively influence stakeholders' motives, which in turn change stakeholders' behavioural intention towards GBs. Hence, this study aims to examine the parameters influencing the decision to adopt GB and to ascertain how incentive mechanisms promote the uptake of GB in South Africa.

Using a scoping literature review and a sequential mixed research method, primary data were acquired from GB experts in four South African provinces. In analysing the quantitative data, the factors were ranked hierarchically using the mean ranking technique and factor analysis was computed to identify the underlying GB incentives. The qualitative data were analysed using content analysis.

The results indicate that incentive payment from a utility energy efficiency programme, rebates and discounts relating to environmentally friendly materials and products and providing grants to homeowners and developers to go towards certification were the most essential monetary incentives for promoting GB. In the category of non-monetary incentives, recognition of consultant team members and developers and free marketing/good publicity were the most important incentives. The incentive mechanisms were subsequently categorised as “Economic incentives” and “Reward scheme and technical support”.

This study was confined to four metropolitan areas in South Africa. Nevertheless, the outcomes have practical implications for GB projects in general and may serve as a good reference for other provinces in South Africa.

The findings of the study are a valuable resource for stakeholders such as the government, municipal assemblies, professional bodies and the Green Building Council of South Africa (GBCSA) in developing effective incentive mechanisms to promote GB adoption. This study adds to the body of knowledge relevant to GB incentivisation in South Africa.

Income from investment properties can fluctuate depending on the state of the economy. The idea that there is always a potential exit (sale) value whenever the property stops performing at its optimum or deflation in the economy will always appeal to investors. To determine housing prices, investors would rely on a direct comparison approach (DCA) of recent substitute sales in the open market. Appraisers use this approach to develop an opinion of value when there is a plethora of recent sales to analyse.

The study was designed to establish the use of the analytical hierarchy process (AHP) approach as a support tool for deciding property appraisals. A case study of an industrial single-storey stand-alone building with grade-level parking in the south-east of Calgary, Canada, was investigated with the AHP approach. The result was cross-referenced with the DCA.

Using a consistency index of 0.077321 and a consistency ratio of 0.085912, the matrix multiplication was determined to be 0.456706. The average valuations derived from the adjusted price per square foot using the direct comparison method and the unadjusted price per square foot using the AHP were deemed the best value estimate in the light of available comparables. The implications of the findings suggest that AHP, as a quantitative technique, can support and validate the use of similar non-recent sale comparables when appraising investment properties with the DCA.

AHP is an alternative aid in quantitatively deciding the most significant value attribute for comparison before subjective adjustments. When intuitively applied in the DCA, these subjective adjustments almost always lead to an overvaluation of properties.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

This paper investigates the internal factors driving public-private partnership (PPP) adoption for water services in South Korea and Singapore.

This study utilizes a comparative cross-national case study of PPPs in the area of water services by focusing on the similarities and differences between the two countries.

The findings show that while South Korea has employed the PPP model mostly to expand and modernize their sewage systems, Singapore has used PPPs to build and operate desalination facilities that produce potable water through the treatment and filtration of wastewater. The study also demonstrates that fiscal stress and political incentives stemming from socio-economic pressures are the respective critical factors in South Korea and Singapore’s execution of PPP-driven water infrastructure.

Through exploring why and how PPPs have been adopted in the specific context, this paper might be helpful to enhance our understanding of the variations and common factors in the policy adoption process within the Asian context.

This is the first article to apply a machine learning approach to the analysis of time on market on real estate markets.

The random survival forest approach is introduced to the real estate market. The most important predictors of time on market are revealed and it is analyzed how the survival probability of residential rental apartments responds to these major characteristics.

Results show that price, living area, construction year, year of listing and the distances to the next hairdresser, bakery and city center have the greatest impact on the marketing time of residential apartments. The time on market for an apartment in Munich is lowest at a price of 750 € per month, an area of 60 m2, built in 1985 and is in a range of 200–400 meters from the important amenities.

The findings might be interesting for private and institutional investors to derive real estate investment decisions and implications for portfolio management strategies and ultimately to minimize cash-flow failure.

Although machine learning algorithms have been applied frequently on the real estate market for the analysis of prices, its application for examining time on market is completely novel. This is the first paper to apply a machine learning approach to survival analysis on the real estate market.

The essence of finance has become essential in the sustainability discussion in recent times as a result of the capital intensive nature of sustainable projects. This has motivated financial experts and institutions to develop various financial instruments and mechanisms to further advance the course of protecting the environment, and decreasing the release of excess carbon and GreenHouse Gases. This is to also provide the opportunity for funding Green or sustainable infrastructure development. This chapter advances a discourse on matters relating to sustainable financing of infrastructure projects. The fundamentals of sustainable or green funding of infrastructure projects, and sustainable schemes of financing green infrastructure projects are discussed.

The paper aims to examine the role played by property tax in influencing strategic decisions regarding marital separation and divorce in Italian municipalities.

The empirical analysis is conducted on a sample of 6,458 Italian municipalities by applying the ordinary least squares (OLS) and instrumental variables (IVs) approaches.

The estimation results show a small increase in marital separations and divorces as the difference between the municipal secondary and primary home tax rate increases. Specifically, an increase of 1‰ in the property tax rate differentials is accompanied by an increase of six marital separations and four divorces per 1,000 inhabitants.

The main limitation of the analysis is that the strategic behavior of the married couple is inferred from econometric analysis with data aggregated at the municipal level. To investigate this phenomenon more precisely, it would be useful to have individual data collected by surveys on strategic divorce decisions due to property tax incentives.

This study contributes to the scant existing literature on the tax incentives for strategic divorce. It is the first study to empirically investigate the effects of property tax on separation and divorce decisions by investigating the Italian context. In Italy, a property tax was introduced in 1993, encouraging “false” divorces by spouses with a second home since the tax on the secondary home was set at a rate higher than that on the primary residence. Moreover, there were no tax deductions and no additional tax breaks on the secondary home, while they were established on the primary one. Higher property taxes and the absence of tax breaks on the secondary home may have encouraged a strategic behavior whereby many married couples filed for false separation and divorce in order to recover part of property tax rebates.

Creating a mindset for research, including the development of professional research skills and critical thinking, is of the utmost importance in preparing students for the business world. To help faculty with this mindset, we discuss novel approaches for incorporating professional research and interactions into the undergraduate classroom, although the recommendations can apply to the entire curriculum. We describe three scenarios where our recommendations might apply – research/financial, tax, and accounting information system courses. Using a professional accounting research course and a financial course as examples, we start out broadly discussing a practitioner-coauthored professional case study approach that is applicable to any course, at any level. We then present a capstone undergraduate tax research course followed by an introduction of a specific project in an accounting information systems course. We include suggested syllabi, projects, and assessment rubrics throughout the discussion.