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The results indicate that land prices exert pressure on retail performance (RP) and that the enhancement of digital means has a positive effect on RP. Additionally, digital instruments (DI) play a significant moderating role in the relationship between land prices and RP.

This paper empirically examines the impact of land prices on RP using panel data from 239 Chinese cities between 2011 and 2022.

The use of lagged land prices as instrumental variables effectively alleviates endogeneity issues. Both two-stage least squares (2SLS) and generalized method of moments (GMM) regression results suggest that higher land prices are associated with improved RP. Further analysis reveals that the increase in land prices leads to scale effects, structural effects and technological effects, contributing to the enhancement of RP. The impact of land prices on RP becomes more pronounced in larger cities and economically developed regions experience the pressure from land prices earlier.

The findings of this study have practical implications for discussions on retail industry development, site selection for retail businesses and the establishment of sustainable mechanisms for expanding domestic demand.

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.

Promoting enterprises' green innovation is vital to realize the sustainable growth of cities and environmental protection and the rise of urban housing prices might affect the green innovation of enterprises to a certain extent. This study aims to discuss the aforementioned objective.

Based on the data of listed companies and urban housing prices of main cities in China from 2011 to 2019, this paper examines the impact of housing prices on enterprises' green innovation and analyzes the mechanism of rising housing prices on enterprises' green innovation.

The rise of urban housing prices can significantly promote the quality of green innovation of enterprises, but it has no significant impact on the quantity of green innovation. The heterogeneity test results show that the rising house prices have a more significant role in promoting the green innovation of non-state-owned enterprises, enterprises listed on the main board, enterprises in the central and western regions, and enterprises in non-first-tier cities. The mechanism research finds that the rise of urban housing prices has a financing relief effect and cost-pushing effect on the green innovation of enterprises.

Firstly, it thoroughly examines the influence of housing prices on corporate green innovation. Second, it explores the differential impact of housing prices on enterprises' green innovation based on variations among enterprises and regions, offering valuable insights for the government to formulate proper policy. Lastly, it elucidates the influencing mechanism of housing prices on enterprise green innovation from the perspectives of corporate financing and costs, providing empirical support for enterprises to appropriately perceive the opportunities and challenges posed by rising housing prices and actively promote green innovation.

The purpose of the study is to elicit risk factors that are peculiar to public-private partnership (PPP)-procured mass housing in Nigeria from the expert perspectives in ensuring the success of the scheme thereby reducing housing deficit in the country.

The risk inherent in construction projects had been established through literature in general. The risk in PPP projects is emerging because of the recent acceptance of the procurement option by governments all over the globe. The Nigerian Government has also adopted the procurement option in bridging the housing deficit in the country. This study, therefore, conducts a Delphi survey on the probability of risk occurrence peculiar to PPP mass housing projects (MHPs) in Nigeria. Pragmatic research approach through the mixed method of both quantitative and qualitative methods was adopted for this study. The quantitative method adopts the administration of questionnaires through the Delphi survey, whereas the qualitative method used interviews with the respondents. A two-stage Delphi questionnaire was administered to construction practitioners that cut across academics, the public and the private sectors by adopting convenient sampling techniques and following the Delphi principles and procedures. A total of 63 risk factors were submitted to the expert to rank on a Likert scale of 7 and any risk factors that the mean item score (MIS) falls below the grading scale of the five-point benchmark is deemed not necessary a risk factor associated with PPP MHPs and thereby expunged from the second round of the Delphi Survey. The interview was subsequently applied to the respondents to substantiate the risk factors that are peculiar to PPP-procured mass housing in the study area.

The findings show that risk factors such as maintenance frequent than expected, life of facility shorter than anticipated and maintenance cost higher than expected fall below 5.0 benchmark with MIS of 4.64 and 4.55 indicating that the risk factors are not peculiar to PPP mass housing in Nigeria.

The implication for practise of this research is that these risk factors provide the PPP stakeholders with the comprehensive checklists that can aid in developing PPP risk assessment guidelines in the sector though both partners should be aware of the dynamic nature of risk because new ones might be emerging.

The authors hereby declare that the research findings are a product of a thorough research conducted in the study area and have not to be submitted or published by another person or publisher and due acknowledgement was made where necessary.

This paper aims to explore the relationship between market pricing and design quality within the development industry. Currently, there is a lack of research that examines real estate at the property level. Development quality is widely believed to have diminished over the past decades, while many investors seem uninterested in the design process. The study aims to address these issues through a pricing model that integrates design attributes. It is hoped that empirical findings will invite broader stakeholder interest in the design process.

The research establishes a framework for assessing spatial compliance across residential developments within London. Compliance is assessed across ten boroughs, with technical space guidelines used as a proxy for design quality. Transaction prices and spatial assessments are aligned within a hedonic pricing model. Empirical findings are used to establish whether undermining spatial standards presents a significant development risk.

Findings suggest a relationship between sale time and unit size, with “compliant” units typically transacting earlier than “non-compliant” units. Almost half of the 1,600 apartments surveyed appear to undermine technical guidelines.

It is suggested that an array of design attributes be explored that extend beyond unit size. Additionally, future studies may consider the long-term implications of design quality via secondary transaction prices.

Practical implications include the development of a more scientific approach to design valuation. This may enhance the position of product design management within the development industry and architectural services.

Social implications may include improvement in residential design.

An innovative approach combines a thorough understanding of both design and economic principles.

Valuers should independently assess market value. The purpose of this article is to analyze whether the valuation behavior remains independent when commissioned by publicly listed companies in Taiwan.

This study used both quantitative and qualitative methods. Quantitative data analysis was used to examine the estimated premium ratio and estimated divergent ratio with the independent sample t test and Wilcoxon-Mann-Whitney test. To complement and validate the quantitative analysis, open-ended questionnaires were conducted, providing additional insights into the research findings.

The results showed that there is a significant difference in estimated valuations commissioned by representatives of buyers and sellers, and the estimated premium ratios commissioned by representatives of buyers were higher than those of sellers. Furthermore, the open-ended questionnaires results indicate that these findings may be influenced by clients for less experienced appraisers. However, for senior appraisers, this is seen as an action to gain a better understanding of the valuation purpose and always within a reasonable price range. In addition, client influence is not a static factor; it may transform into the valuer's behavior as the appraiser's experience grows and deepens.

It is difficult to obtain valuation reports commissioned by representatives of both buyers and sellers for the same property transactions. In this study, data were obtained from the Market Observation Post-System (MOPS) in Taiwan. As valuation reports could not be obtained, estimated valuations and transaction prices are used to calculate estimated premium ratio and estimated divergent ratios.

Previous investigations of the client effect have been conducted using qualitative methods including questionnaire surveys, in-depth interviews and experimental design. However, these studies are subject to moral hazard. This study may be the first study that has access to data on valuations for both buyers and sellers in such a formal setting.

Challenges of property data in developing markets have been reported by several authors. However, a deep understanding of the actual nature of this phenomenon in developing markets is largely lacking as in-depth studies into the actual nature of data challenge in such markets are scarce in literature. Specifically, the available literature lacks clarity about the actual nature of data challenges that developing markets pose to valuers and how this affects valuation practice. This study provides this understanding with focus on the Lagos property market.

This study utilises a qualitative research approach. A total of 24 valuers were selected using snowballing sampling technique, and in-depth semi-structured interviews were conducted. Data collected were analysed using thematic analysis with the aid of NVivo 12 software.

The study finds that the main data-related challenge in the Lagos property market is the lack of database of market property transactions and not the lack or absence of transaction data as it has been emphasised in previous studies. Other data-related challenges identified include weak property rights institution with attendant transaction costs, underhand dealings among professionals, undocumented charges, undisclosed information, scarcity of data relating to specialised assets and limited access to the subject property and required documents during valuation. Also, the study unbundles the factors responsible for these challenges and how they affect valuation practice.

The study has implication for practice in the sense that the deeper knowledge of data challenges could provide insight into strategy to tackle the challenges.

This study contributes to the body of knowledge by offering a fresh and in-depth perspective to the issue of data challenges in developing markets and how the peculiar nature of the real estate market affects the nature of data challenges. The qualitative approach adopted in this study allowed for a deep enquiry into the phenomenon and resulted into an extended insight into the peculiar nature of data challenges in a typical developing property market.

The purpose of this study paper is to highlight certain related barriers and issues of housing affordability and examine the factors that influence housing affordability in Malaysia.

This study used panel data including several variables, namely, household expense, population, home financing, interest rate, inflation rate (IF) and rental rate (RR). The regression models of panel data, namely, the ordinary least square model, the fixed effects model and the random effects model, were evaluated for their suitability.

The findings revealed that RR and IF have a positive and significant impact towards housing affordability. The results provide strong evidence that RR as alternative in determining the home affordability as it helped in reducing the cost and the financing duration period of houses while at the same time increasing the level of capability of homeownership. Meanwhile, the level of IF has positive and significant impact towards housing affordability because it will cause a drop or increase in the purchasing power of households, as well as a decline or increase in the capability to own a house.

The most significant aspects to consider when analysing housing affordability in Malaysia are demand and supply. However, this study focuses on only five variables and only covers Malaysia. As a result, future researchers should analyse the study’s location, such as by region or district, and include additional variables from both the demand and supply sides. Homeownership of affordability requires a broader and more realistic definition in the current context of a more disruptive environment where technology such as fintech, blockchain and the internet of things acts as enablers for not only promoting homeownership but also ensuring homeownership sustainability. As a result, democratising Islamic home financing appears to be a viable option that requires rethinking, and further research is recommended.

The study proposes an end-to-end solution to promote homeownership levels by considering the level of RR as significant variables among stakeholders such as the house buyers/owners, sellers, investors as well the government agencies in influencing affordability in Malaysia.

This paper discusses the indicators of housing affordability index over the 21-year period of 2000–2020, covering all states in Malaysia. The comparison of affordability level can be seen through all states and by regions. Besides that, the findings revealed that RR and IF have a positive and significant impact towards housing affordability. RR is considered an essential variable in promoting homeownership in Malaysia and warrants further investigation towards policy implication. This paper also provides contribution on data on RR by states in Malaysia that can be used by policymakers to some extent.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.