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The study sets out to explore the mediating role of intellectual capital (IC) dimensions (i.e. human, structural and relational) between scholars' affiliation to online academic networks and institutional knowledge capitalization. Online academic networks are tackled through the lens of knowledge networks which have been of primary importance for new relevant knowledge acquisition during the COVID-19 pandemic.

A questionnaire-based survey of 305 academics from 35 different countries was conducted from July to December 2021, employing a partial least squares structural equation modelling technique. The database was initially filtered to ensure the adequacy of the sample, and data were analyzed using the statistics software package SmartPLS 3.0.

Evidence was brought forward that the proposed conceptual model accounted for 52.5% of the variance in institutional knowledge capitalization, the structural and relational capital availed by knowledge networks exerting strong positive influence on the dependent variable.

The study has both research and managerial implications in that it approaches a topical phenomenon, namely the capitalization of online academic networks in the COVID-19 context, which has dramatically altered the way that research and teaching are conducted worldwide.

The most important contribution of the paper resides in the comprehensive research model advanced which covers individual, organizational and network multifaced layers, starting with the personal and institutional motives to join a specialized network, continuing with the opportunities provided by knowledge networks in terms of intellectual capital harnessing, and ending with its influence on higher education organizations.

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.

The purpose of this study is providing a possible methodological solution to the valuation of cyclical.assets. International Valuation Standards introduce a brand new definition of property: the cyclical asset (International Valuation Standards Council 2017, IVS 105, p. 39 and p. 41). Among different property valuation methods, normally this kind of properties is appraised using income approach. In this group of methodology, the opinion of value is based on a proportional relationship between property value and rent. In the past years, a group of methods called cyclical capitalization has been proposed (d’Amato, 2003; d’Amato, 2013;d’Amato, 2015; d’Amato, 2017a; d’Amato 2017 b; d’Amato, 2017c). This method proposes an integration between property valuation and property market cycle.

Cyclical capitalization method is applied using a time series of property market rent of offices in prime location in the South Bank area in London. It consists of the determination of more than one all-risk yield to reproduce the property market cycle.

A comparison between the cyclical capitalization and two traditional capitalization rate shows how the proposed model is able to provide a stable opinion of value.

The method may represent a contribution for the determination of the value of cyclical assets or for the mortgage lending value.

This paper provides the possibility to have a property valuation method less sensitive to upturn and downturn of the property market.

The valuation based on cyclical capitalization are less sensitive to the upturn and the downturn of the market.

It is one of the first scientific paper addressing the problem of the determination of the value of cyclical assets.

This paper aims to investigate the effect of non-normality in returns and market capitalization of stock portfolios and stock indices on value at risk and conditional VaR estimation. It is a well-documented fact that returns of stocks and stock indices are not normally distributed, as Indian financial markets are more prone to shocks caused by regulatory changes, exchange rate fluctuations, financial instability, political uncertainty and inadequate economic reforms. Further, the relationship of liquidity represented by volume traded of stocks and the market risk calculated by VaR of the firms is studied.

In this paper, VaR is estimated by fitting empirical distribution of returns, parametric method and by using GARCH(1,1) with Student’s t innovation method.

It is observed that both the stocks, stock indices and their residuals exhibit non-normality; therefore, conventional methods of VaR calculation are not accurate in real word situation. It is observed that parametric method of VaR calculation is underestimating VaR and CVaR but, VaR estimated by fitting empirical distribution of return and finding out 1-a percentile is giving better results as non-normality in returns is considered. The distributions fitted by the return series are following Logistic, Weibull and Laplace. It is also observed that VaR violations are increasing with decreasing market capitalization. Therefore, we can say that market capitalization also affects accurate VaR calculation. Further, the relationship of liquidity represented by volume traded of stocks and the market risk calculated by VaR of the firms is studied. It is observed that the decrease in liquidity increases the value at risk of the firms.

This methodology can further be extended to other assets’ VaR calculation like foreign exchange rates, commodities and bank loan portfolios, etc.

This finding can help risk managers and mutual fund managers (as they have portfolios of different assets size) in estimating VaR of portfolios with non-normal returns and different market capitalization with precision. VaR is used as tool in setting trading limits at trading desks. Therefore, if VaR is calculated which takes into account non-normality of underlying distribution of return then trading limits can be set with precision. Hence, both risk management and risk measurement through VaR can be enhanced if VaR is calculated with accuracy.

This paper is considering the joint issue of non-normality in returns and effect of market capitalization in VaR estimation.

The purpose of this study is to investigate the impact of foreign capital inflows and economic growth on stock market capitalization in Pakistan by using the annual time series data from the period of 1976 to 2011.

The autoregressive distributed lag bound testing cointegration approach, the error correction model and the rolling window estimation procedures have been performed to analyze the long run, short run and behavior of coefficients, respectively.

Results indicate that foreign direct investment (FDI), workers’ remittances and economic growth have significant positive relationship with the stock market capitalization in long run as well as in short run. Results of the dynamic ordinary least square and the fully modified ordinary least square suggest that the initial results of long-run coefficients are robust. Results of variance decomposition test show the bidirectional causal relationship of FDI and economic growth with stock market capitalization. However, unidirectional causal relationship is found in between workers’ remittances and stock market capitalization.

It is suggested that in Pakistan, investors can make their investment decisions through keeping an eye on the direction of the considered foreign capital inflows and economic growth.

This paper makes a unique contribution to the literature with reference to Pakistan, being a pioneering attempt to investigate the effects of foreign capital inflows and economic growth on stock market by using long time series data and applying more rigorous techniques.

The last two centuries, roughly from the publication of Adam Smith's The Wealth of Nations, have witnessed a remarkable process of globalization of Western capitalism. The principal institutions facilitating this process were originally the chartered companies and, in the more recent times, the multinational corporations headquartered in the West. Search for global profits has always been the driving force behind this globalization. But the deeper inner logic of this process is capitalization on a world‐scale.

The purpose of this paper is to bridge the gap between the existing theoretical and empirical studies by examining the asymmetric return–volume relationship. Indeed, the authors aim to shed light on the return–volume linkages for French-listed small and medium-sized enterprises (SMEs) compared to blue chips across different market regimes.

This study includes both large capitalizations included in the CAC 40 index and listed SMEs included in the Euronext Growth All Share index. The Markov-switching (MS) approach is applied to understand the asymmetric relationship between trading volume and stock returns. The study investigates also the causal impact between stock returns and trading volume using regime-dependent Granger causality tests.

Asymmetric contemporaneous and lagged relationships between stock returns and trading volume are found for both large capitalizations and listed SMEs. However, the causality investigation reveals some differences between large capitalizations and SMEs. Indeed, causal relationships depend on market conditions and the size of the market.

This paper explains the asymmetric return–volume relationship for both large capitalizations and listed SMEs by incorporating several psychological biases, such as the disposition effect, investor overconfidence and self-attribution bias. Future research needs to deepen the analysis especially for SMEs as most of the literature focuses on large capitalizations.

This empirical study has fundamental implications for portfolio management. The findings provide a deeper understanding of how trading activity impact current returns and vice versa. The authors’ results constitute an important input to build and control trading strategies.

This paper fills the literature gap on the asymmetric return–volume relationship across different regimes. To the best of the authors’ knowledge, the present study is the first empirical attempt to test the asymmetric return–volume relationship for listed SMEs by using an accurate MS framework.

This study investigates the relation between residential property values and both property taxes and public services in Georgia’s counties. Capitalization theory predicts that property values relate negatively to property taxes, and positively to public services. Palmon and Smith (1998) state that errors in public service measures create a capitalization coefficient bias that makes it difficult to isolate tax effects from public service effects. This paper is a first step in defining and quantifying public services and their marginal effect on housing values. It develops public service measures in four quality-of-life areas – economy, education, health, and public safety. The models suggest a strong negative relation between effective tax rates and property values, and a significant positive association between the public service measures and property values. Analyses indicate that property taxes are capitalized into housing prices at greater than 100%, suggesting prior underestimations based on measurement errors in public service variables.

This study aims to analyze the effect of cryptocurrency capitalization market development on bank deposits variability in the United Arab Emirates (UAE) spanning the period 2005M1–2020M4 using the novel nonlinear autoregressive distributive lag (NARDL).

The study employs the NARDL recently developed by Shin et al. (2014) to estimate the long and short-run relationships between the variables rather than the widely known ARDL (Pesaran et al., 2001), which suffers from a complex structure in the estimation equation that usually includes lags and differences in both short and long terms. The implementation of NARDL required several proceedings after plotting the descriptive data, commencing with unit root tests, selection of lag length, estimating the long-and-short variables coefficients, heteroscedasticity test and Wald test for symmetries.

The long-run estimations of the positive and negative asymmetric coefficients indicate that cryptocurrencies capitalization has a negative impact on bank deposits in the UAE. Further, the short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decrease bank deposits.

The study has applied to the UAE spanning the period 2005M1–2020M4 using the NARDL.

The short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decreases bank deposits, which means that the increase in the magnitude of cryptocurrencies capitalization stimulates depositors and speculators to adjust their portfolios towards contracting their deposits in banks to invest partially in cryptocurrencies, on the other hand, the decline in cryptocurrencies capitalization process spur depositors and speculators to reduce their deposits for purchasing cryptocurrencies at lower prices.

The study infers that individuals and businesses are cautious when investing in cryptocurrencies, and they need more certainty and trust to include these types of assets in their portfolios. The fluctuation in cryptocurrencies capitalization prompts speculators to change their deposits according to the cryptocurrencies' prices.

This study explores the short-and long-run asymmetric impacts of cryptocurrencies capitalization development on bank deposits volatility in the UAE, based on a NARDL, for providing a manifest depiction of whether the cryptocurrencies industry might be a threat to conventional banking system performance in the potential future.

The paper examines whether, along with the financial performance, the disclosure of research and development (R&D) expenses, patent portfolios, patent citations and innovation activities affect the market capitalization of Russian companies.

The paper opted for a set of techniques including bag-of-words (BoW) to retrieve additional innovation-related data from companies' annual reports, self-organizing maps (SOM) to perform visual exploratory analysis and panel data regression (PDR) to conduct confirmatory analysis using data on 74 Russian publicly traded companies for the period 2013–2019.

The paper observes that the disclosure of nonfinancial data on R&D, patents and primarily product and marketing innovations positively affects the market capitalization of the largest Russian companies, which are mainly focused on energy, raw materials and utilities and are operating on international markets. The study suggests that these companies are financially well-resourced to innovate at risk and thus to provide positive signals to stakeholders and external agents.

Our findings are important to management, investors, financial analysts, regulators and various agencies providing guidance on corporate governance and sustainability reporting. However, the authors acknowledge that the research results may lack generalizability due to the sample covering a single national context. Researchers are encouraged to test the proposed approach further on other countries' data by using the compiled lexicons.

The study aims to expand the domains of signaling theory and market valuation by providing new insights into the impact that companies' reporting on R&D, patents and innovation activities has on market capitalization. New nonfinancial factors that previous research does not investigate – innovation disclosure indicators (IDI) – are tested.