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In English valuation practice, when valuing small to medium size (StMS) shops, rental analysis is undertaken using zoning based on the argument that shop fronts including window displays attract customers to shops and that most trading takes place in the internal frontage area making it the most valuable part of shops. Albeit zoning has been critiqued, it remains the preferred method of rental analysis. The paper aims to answer two research questions: are shop fronts including window displays the only factor that attracts customers to shops? And is the frontage space within shops the area most trading takes place?

The exploratory qualitative research methodology was used, and primary data collected by observing 178 shops in selected five shopping areas. The observational data were complemented with the use of secondary data.

The study has shown that shop fronts are not the only factor attracting clientele to shops as there are other varied factors including location, availability of Internet and hoardings. There is no evidence to suggest most goods in shops are displayed at the frontage space that attract most customers to that area, thereby, making the area the most valuable part, which decreases backwards.

These findings coupled with extant research evidence implies zoning can lead to under or over valuation of StMS shops (which is not good for retail real estate (RE) management or market), and turnover generated from shops is the overarching determinant of rental values in valuation.

This is the first time the very foundation/underpinning principles of zoning have been subjected to scrutiny in England.

The purpose of this paper is to investigate whether information asymmetry mediates the relationship between disclosure and cost of equity.

The study is based on a sample of 500 companies listed in Bombay Stock Exchange for a period of six years from 2015 to 2021. Panel data regression is applied to analyze the relationship between voluntary disclosure, cost of equity and information asymmetry. Mediation effect of information asymmetry is tested with the help of Barron and Kenny’s (1986) approach.

Findings suggest that in case of Indian companies, disclosure reduces cost of equity directly and indirectly through mediation of information asymmetry. Indian investors value credible information for better estimation of future returns, supporting the validity of estimation risk and stock market liquidity hypothesis, which proposes an inverse relationship between disclosure and cost of equity.

Managers can use the findings to strategize their disclosure policy and secure funds at lower cost. Shareholders can monitor managerial actions by demanding credible disclosures. Government too can encourage voluntary disclosure by providing special incentives to the firms.

This study is a pioneering research that investigates the mediating influence of information asymmetry between disclosure and cost of equity with reference to the Indian corporate landscape.

This study aims to investigate how the intangible intensive nature of firms affects the value relevance of earnings and the book value of equity between profit- and loss-reporting firms. The study also examines how firms’ intangible intensity affects the value relevance of R&D outlays between profit- and loss-reporting firms.

An empirical analysis based on Ohlson’s (1995) framework is used. A total of 54,421 firm-year observations of Indian listed firms from financial years 1992–2016 constitute the study sample.

The findings suggest that the difference in the value relevance of earnings and the book value of equity between profit- and loss-reporting firms is more significant in non-intangible intensive firms than in intangible firms. Specifically, earnings are more value relevant in profit-reporting and non-intangible intensive firms, whereas book value of equity is more value relevant in loss-reporting and intangible intensive firms. The results also suggest that the difference in the incremental value relevance of R&D information between profit- and loss-making firms is higher in intangible intensive firms than in non-intangible intensive firms.

The findings of this study can help managers, standard-setters and investors make effective decisions.

This study offers insights into the impact of intangible intensity on the value relevance of aggregated and disaggregated accounting information between profit- and loss-making firms in institutional settings where capitalization of R&D expenditures is allowed.

This paper aims to examine the extent to which sell-side analysts efficiently incorporate firms’ corporate social responsibility (CSR) activities into their earnings forecasts. In addition, this paper also investigate the CSR information efficiency of analysts vis-à-vis that of investors.

This paper measures CSR activities by using CSR strength and CSR concern scores from the Morgan Stanley Capital International Environmental, Social and Governance database. This paper uses analysts’ earnings forecast errors and dispersion as proxies for their information efficiency. To compare the CSR information efficiency of analysts to that of investors, this paper uses the Vt/Pt ratio, which is the equity value estimates inferred from analysts’ earnings forecasts (a proxy for analysts’ CSR information efficiency) to the stock price of the focal company (a proxy for investors’ CSR information efficiency).

The regression analysis indicates that analysts’ earnings forecasts are optimistically biased and more dispersed for firms with positive CSR activities. The paper also finds that analysts’ forecasts are more optimistically biased than investors in interpreting CSR activities.

The lack of standardized protocols in CSR reporting and activities has raised the risk of mispricing by analysts, threatening the stability of sustainable investments. This paper suggests that regulators and standard-setters should establish a uniform framework governing firms’ CSR activities, along with their reporting and measurement, to ensure more consistent and reliable evaluations of CSR practices.

Analysts’ mispricing of CSR activities may distort sustainable investing, as it can overly focus on the positive impacts of stakeholder theory, overlooking agency theory’s warnings about managerial self-interest. Investors need to assess CSR efforts with a dual perspective, acknowledging their societal value but also examining their alignment with shareholder interests.

To the best of the authors’ knowledge, this research is the first to assess the efficiency of analysts versus investors in processing CSR information amidst growing sustainable investment interests. Furthermore, building on Dhaliwal et al. (2012), which found that voluntary CSR disclosures correlate with more accurate analyst forecasts, this research provides fresh perspectives on the evolving nature of how analysts assimilate CSR information over time.

Geopolitical risks associated with the return of great power politics and growing nationalism have generated new challenges for foreign investors across industries. Oil and gas companies are well acquainted with such risks and have developed strategies to manage them. This paper reviews five of these strategies: divorcing ownership control from operating control in designing collaborative ventures; proactively managing stakeholder relationships; ensuring transparency and communication; diversifying risks while proactively positioning for emerging opportunities; and deliberately planning for exit should such an eventuality arise. Firms outside of oil and gas can draw on these strategies as they navigate the emerging geopolitical context.

This paper reviews five strategies that oil and gas companies can use to manage geopolitical risk: divorcing ownership control from operating control in designing collaborative ventures; proactively managing stakeholder relationships; ensuring transparency and communication; diversifying risks while proactively positioning for emerging opportunities; and deliberately planning for exit should such an eventuality arise.

This study identifies several strategies that oil and gas companies have used to manage geopolitical risks. These tools will be increasingly important in the shifting global political landscape.

Drawing on the experiences of oil and gas companies, this study has identified several strategies that companies can use to shield themselves from the risks that are currently emanating from geopolitics. While these best practices originate in the experiences of oil and gas firms, the ability to deftly manage geopolitical risks is becoming an important prerequisite for companies across industries.

The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is general market-wide sentiments, while the second is biased approaches toward specific assets.

To achieve the goal, the authors conducted a multi-step analysis of stock returns and constructed complex sentiment indices that reflect the optimism or pessimism of stock market participants. The authors used panel regression with fixed effects and a sample of the US stock market to improve the explanatory power of the three-factor models.

The analysis showed that both market-level and stock-level sentiments have significant contributions, although they are not equal. The impact of stock-level sentiments is more profound than market-level sentiments, suggesting that neglecting the stock-level sentiment proxies in asset valuation models may lead to severe deficiencies.

In contrast to previous studies, the authors propose that investor sentiments should be measured using a multi-level factor approach rather than a single-factor approach. The authors identified two distinct levels of investor sentiment: general market-wide sentiments and individual stock-specific sentiments.

The purpose of this research is to ascertain the extent to which the income capitalization approach reflects the pattern of emerging rental income in Enugu property market.

The survey research design was used in this study. Data from the field was gathered through a data collection pro forma administered to 40 valuers in Enugu metropolis in the manner of conducting interviews. This study used key valuation details of 54 sampled income generating properties valued by the respondent valuers between 2015 and 2022 using the income capitalization approach. The same sampled properties were then revalued by the researchers using annuity due assumption/formulas of the income capitalization approach. Descriptive and inferential statistics were used to analyze the data.

The study revealed that the income capitalization approach used by most valuers in Enugu does not reflect the property rental income pattern prevailing in Enugu property market where rents are paid in advance. The study further shows that the application of the income capitalization approach for valuation of annually in-advance property rental income cash flow results in a higher capital value of 3.49% in Enugu property market.

The limitations to this study are that past valuation done by valuers were used in the analysis instead of actual property sales and a relatively small number of sampled valuers and properties are used in the study The implication of the study is that ordinary annuity assumptions or formulas is inaccurate and not suitable for valuation of income generating property in an emerging market like Nigerian where timing of cash flow is annually in advance. Based on the result of this study it seems that ordinary annuity approach negate the principle of estimating value using income capitalization method by converting future cash flow from income generating property into an estimate of property value.

The study advocates the adoption of the use of annuity due formulas in the valuation of income generating properties in Nigeria as its practice standard to avoid undervaluation as this assumption is logical and provides more accurate value due to prevailing lease structure and rent payments patterns in the country. The implication of the study is that the use of ordinary annuity assumptions or formulas is inaccurate and not suitable for the valuation of income generating property in an emerging market like Nigerian where timing of cash flow is annually in advance.

This is one of the very few empirical studies carried out in Nigeria to ascertain the extent to which the income capitalization approach used by valuers reflects the rental income pattern that prevails in the Nigeria property market.

Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.

This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.

Four domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.

This paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

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 study aims to examine the relationship between corporate governance (CG) voluntary disclosure (VD) and firm valuation (FV). Moreover, the study also investigates whether VD mediates the impact of CG on FV or not.

The study is based on a panel data set of top 100 listed firms on Bombay Stock Exchange (BSE) over the period of 2014–2018 and develops CG index and VD index (VDI) in order to capture both the constructs respectively. The author adopts suitable panel data model to examine the relationship between CG, VD and FV as well as indirect impact of CG on FV through mediation of VD. Further, the author uses instrumental variables regression model for robustness check.

The author's findings reveal significant positive impact of CG on FV. Likewise, VD also exhibits significant positive impact on FV. Notably, the interaction of CG and VD complements each other in making positive contribution towards FV. In addition, the author observes that VD partially mediates the impact of CG on FV. Specifically, the outcome suggests that CG apart from having direct impact on FV also influences the same through the mediation of VD. Moreover, as the direction of indirect impact coincide with direct impact, such indirect impact has complementary relationship with the direct impact, implying that when CG makes direct contribution towards improving FV, CG's contribution toward FV through mediation of VD also increases.

To the best of the author's knowledge, this is the first endeavor in the extant literature that examines the interaction performance impact of CG and VD. Further, the author also provides primary evidence on the mediating impact of VD in the relationship between CG and FV.