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The paper aims to quantitatively investigate vacant industrial land valuation accuracy in China, given the importance of the industrial market as an underlying pillar to promote urban growth especially in emerging economies.

In China, the government formulates a Land Benchmark Price (LBP) to serve as a price reference point to sell land rights. To gain an in-depth understanding of the valuation practice by LBP, this paper uses correlation analysis to investigate the varying dynamics between the transaction-based prices and LBP appraisal-based estimates. Furthermore, a margin of error examination investigates the distortion in LBP land appraisals, with an amended LBP presented to improve the accuracy of the current LBP method.

Different influencing factors are identified to impact the actual market transaction prices and the LBP construction, leading to a large discrepancy in industrial land appraisals. A systematic problem is recognised that the construction of the LBP follows urban bid curve theory, whereas the land transaction prices do not, demonstrating that an urgent LBP update is needed to capture the market dynamics for industrial market.

The paper sets out discrepancies in valuation accuracy surrounding the application of the LBP valuation approach in China. This has practical implications for valuers in terms of raising their awareness of the deficiencies in the approach and the pitfalls they need to guard against in their appraisals. It also has implications for developers and investors who rely on valuer appraisals to assess the viability of land purchases; hence, they need to express caution in the appraisal advice sought. Finally, the results demonstrate to the standard setters how they need to modify the LBP equations to better capture market dynamics.

The paper examines valuation accuracy in transitional economies, through valuation differentials between appraised price and the transacted price. The value of the work lies in the analysis of the fundamental differentials between market price and appraised value, which is of importance to investors/developers, practicing valuers, as well as government officials responsible for setting the valuation standards.

Unstructured data such as images have defied usage in property valuation for a long time. Instead, structured data in tabular format are commonly employed to estimate property prices. This study attempts to quantify the shape of land lots and uses the resultant output as an input variable for subsequent land valuation models.

Imagery data containing land lot shapes are fed into a convolutional neural network, and the shape of land lots is classified into two categories, regular and irregular-shaped. Then, the intermediate output (regularity score) is utilized in four downstream models to estimate land prices: random forest, gradient boosting, support vector machine and regression models.

Quantification of the land lot shapes and their exploitation in valuation led to an improvement in the predictive accuracy for all subsequent models.

The study findings are expected to promote the adoption of elusive price determinants such as the shape of a land lot, appearance of a house and the landscape of a neighborhood in property appraisal practices.

The success of a neural network depends on, among others, an architecture that is appropriate for the task at hand. This study attempts to identify an optimal architecture of a neural network in the context of property valuation, and aims to test the ability of connecting related neural networks to reduce the property valuation error.

This study explores efficient network architectures to estimate land and house prices in Seoul, South Korea. The input is structured data, and the embedding technique is used to process high-cardinality categorical variables.

The shared architecture of a network for simultaneous estimation of both land and houses was revealed to be the best performing network. Through weight sharing between relevant layers in networks, the root-mean-square error (RMSE) for land price estimation was reduced significantly, from 0.55–0.68 using the baseline architecture, to 0.44–0.47 using the shared architecture.

The study results are expected to encourage active investigation of efficient architectures by using domain knowledge, and to promote interest in using structured data, which is still the dominant type in most industries.

The rising concern for the accuracy of residential valuations in Nigeria has created the need for key stakeholders in the residential property markets in the study areas to know the level of accuracy of valuations in order to make rational residential property transactions, amongst other purposes.

A blend of descriptive and causal designs was adopted for the study. Data were collected via structured questionnaire administered to 179 estate surveying and valuation (ESV) firms in the study areas using census sampling technique. Analytical techniques such as median percentage error (PE), mean and relative importance index (RII) analysis were employed in the analysis of data collected for the study.

The study found that valuation accuracy is greater in the residential property market in Abuja than in Minna, with inappropriate valuation methodology as the most significant cause of valuation inaccuracy.

The practical implication of this study is that a reliable databank should be established for the property market to provide credible transaction data for valuers to conduct accurate valuations in these cities. Strict enforcement of national and international valuation standards by the regulatory authorities as well as retraining of valuers on appropriate application of valuation approaches and methods are the recommended corrective measures.

No study has comparatively examined the accuracy of valuations in two extremely different residential property markets in the country using actual valuation and transaction prices.

The purpose of this paper is to add to the academic discourse by developing a methodology by which a block of land’s goodwill, or lack of goodwill, can be factored into its valuation.

The research was undertaken utilising a mixed-methods approach, which involved doctrinal research, together with qualitative and quantitative analysis of the impact of neighbourhood disputes on real property value. The disputes engaged with for exemplar purposes were those of tree disputes resolved by QCAT order.

A dispute can adversely affect a property’s goodwill, which can impact both its saleability and value.

Due to the sensitive nature of the valuation process and the potential negative impact that any identification of a property may have on its value, it was not appropriate to identify any properties specifically or the area in which these are located. Further, as regards the available details of disputes, the authors were only able to engage with disputes for which an order existed.

The methodology developed can be applied to other real property interests, for example, lots in freehold retirement village complexes or those within other strata title schemes of either residential or commercial use.

As the number of neighbourhood disputes throughout Australia grows, addressing the impact that a dispute has for property value is a concern relevant to all valuers and owners.

The authors add to the academic discourse by developing a methodology by which a property’s goodwill, or lack of goodwill, can be factored into its valuation.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

The causes of valuation inaccuracy, the approaches, basis and procedures used for value estimation were not profoundly identified in Ethiopia. Particularly, the causes of property valuation inaccuracy for court decisions have not been assiduously studied by scholars. Hence, the ultimate goal of this study aims to identify the determinant variables of valuation inaccuracy, the approaches, basis and procedures used for court execution purposes.

This study employed both qualitative and quantitative approaches. The target populations of the study were the courts at the federal and regional levels. A purposive sampling technique was employed to undertake this study. The survey data was analyzed using the Relative Importance Index (RII).

The finding of this research revealed that courts have not outshined and uniform valuation manuals and guidelines that clearly state the approaches, procedures and bases of valuation. As a consequence, courts execute based on the opinion of value determined by other institutions. The insignificant numbers of independent valuation institution with the lack of uniform standards in the country prejudice the implementation of the decision of the court and faced injustice. The finding also reveals as there are several causative variables for real property valuation inaccuracy.

To alleviate the problem, the government should strengthen the valuation sector by creating an independent institution for advancing valuation regulation and policymaking.

This study was the first of all and could be a pointer for different government and non-government bodies regarding the limitations of valuation for judgment execution purposes.