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In any stock market, volatility is a significant factor in strengthening their asset pricing. The upsurge in volatility in the stock market can activate and bring changes in the financial risk. According to financial conventional theory, the stakeholders (investors) are selected to be balanced and variations in pertinent risk are also to be anticipated due to the outcome of the drive-in basic factors in Indian stock markets. The hypothesis shows that there are actions in systematic and unsystematic risks that are determined by volatility. It is allied to sentiment-driven in the trader movement.

The paper used the methodology of generalized autoregressive conditional heteroskedasticity-in mean GARCH-M and exponential GARCH-M (E-GARCH-M) methods on the Indian stock market. The data have been covered from 2000 to 2019.

Finally, the study suggests that due to the unfitness of the capital asset pricing model (CAPM), the selection has enhanced with sentiment is an important risk factor.

The investor sentiment and stock return volatility statement are established by using the investor sentiment amalgamated stock market index built.

The outcome of the study shows that there is an important association between stakeholder (investor) sentiment and stock return, in case of volatility behavioural finance can significantly explain the behaviour of stock returns on the Indian Stock Exchange.

Can digital financial inclusion (DFI) as an emerging and innovative financial service encourage economic development?

Based on a Bayesian macroeconomic investigation framework, this research study presents the level of internet growth as a threshold variable and examines the influence of DFI on economic development based on state panel data from 2008 to 2021 in India.

The outcome of DFI on economic development through various mediation models. The results illustrate that DFI growth substantially contributes to economic development.

Encouraging small and medium-sized enterprise entrepreneurship and motivating populations’ utilization are two significant networks through which DFI progress affects economic growth.

The stock market has shown fluctuating degrees of volatility because of the recent COVID-19 pandemic in India. The present research aims to investigate the effect of the COVID-19 on the stock market volatility, and whether the economic package can control the market volatility or not, measured by a set of certain sector-level economic features and factors such as resilience variables.

We examine the correlation matrix, basic volatility model and robustness tests to determine the sector-level economic features and macroeconomic factors helpful in diminishing the volatility rising because of the COVID-19.

The outcomes of this study are significant as policymakers and financial analysts can apply these economic factors to set policy replies to handle the unexpected fluctuation in the stock market in sequence to circumvent any thinkable future financial crisis.

The originality of the paper is to measure the variables affecting the stock market volatility due to COVID-19, and understand the impact of capital market macroeconomic variables and dummy variables to theoretically explain the COVID-19 impact on stock market volatility.

This paper aims to analyze the status of infrastructure, workforce and basic amenities at public health-care facilities in rural India and draw a comparison with its urban counterparts.

Rural Health Statistics data and National Sample Survey Office Report for the period 2019–10 were used to analyze lower-level public health facilities, namely, subcenters, primary health centers and community health centers (CHCs). Selected tracer indicators under World Health Organization’s (WHO) Service Availability and Readiness Assessment (SARA) mechanism such as health center density, core health workforce density and basic amenities were used to carry out the analysis. The extent of facility coverage was measured using the National Rural Health Mission (NRHM) guidelines and the proportion of facilities satisfying the Indian Public Health Standards (IPHS) was measured to assess the service provision quality in rural public health-care facilities.

Results indicated that the density of public health centers is higher in rural areas than in urban areas. Almost all public health-care facilities lack basic amenities in rural areas. Working positions for health specialists in CHCs barely meet the total requirement. Almost all of the public health facilities functioning in rural areas do not meet the IPHS norms.

To the best of the authors’ knowledge, the present paper is the first initiative to assess the status of rural public health-care facilities on the national level using WHO’s SARA indicators as well as NRHM and IPHS guidelines. The study is significant in terms of policy input for achieving universal health coverage in India.

The modernization of the agro-based industry has encouraged the application of inorganic fertilizers to increase productivity. However, such fertilizer emissions may pose harmful environmental effects in the long run. This study aims to empirically explore the matter by applying the environmental Kuznets curve (EKC) hypothesis in the Indian agro-based industry.

The study builds two models considering nitrous oxide emission levels from inorganic (synthetic) and organic (manure) fertilizers to evaluate the safer option for the environment. The validity of an industry-specific EKC (IEKC) is tested for the models considering time series data from 1975 to 2019. Here, the autoregressive distributed lag model is applied for the 45 years long time series analysis to test the hypothesis with respect to inorganic and organic fertilizers emissions.

The existence of the IEKC is rejected by the inorganic fertilizer emissions model. Its U-shaped curve implies that applying such fertilizers will gradually cause degrading environmental effects. On the other hand, the organic fertilizer emissions model supports the existence of an inverted U-shaped IEKC. It proves that organic fertilizers are a better choice for safeguarding the environment in the long run.

Applying the EKC hypothesis on an industrial level can signify whether an industry worsens the environment in the long run. However, very few studies have explored such an application of the hypothesis in the past. Moreover, the literature could not find any previous study exploring the environmental effects of inorganic and organic fertilizers by analyzing the EKC hypothesis. The hypothesis can offer such insights with simplified empirical assessment.

This study aims to examine the short- and long-term equilibrium relationship between All share price index (ASPI), macroeconomic variables and the economic crisis in Sri Lanka.

Monthly time series data for inflation (CPI), industrial production (IP), an exchange rate (EX), an interest rate (TB), short-term interest rate (CD) and economic crisis were used from 2010 to 2021. The ADF test, the bound testing approach, the CUSUM test and the CUSUMQ test were used in this study.

The findings show a long-run stable relationship between stock price, macroeconomic variables and political crisis (i.e., CPI, IP, ER, TB, CD and economic crisis). The results of the Johansen cointegration test suggest that there is at least one cointegrating equation, indicating that there is a long-run equilibrium relationship between macroeconomic variables and stock prices in Sri Lanka.

The vector error correction estimates show that the coefficient of the error correction term is significant with a negative sign, indicating that a long-run dynamic relationship exists between macroeconomic variables and stock prices. In the short term, economic crisis has had a big effect on stock prices suggesting that Sri Lanka’s domestic financial markets are linked to the stability of the country.

This research establishes the links between stock returns, macroeconomic variables and economic crisis. So far, research has been unable to establish the empirical nature of such links. The authors believe that this paper fills that gap.

The purpose of this study is to construct a new index to assess the impact of an energy price shock on macroeconomic indicators of India. This paper also shows a comparative analysis of the constructed index along with pre-existing World Bank and International Monetary Fund indices on energy.

This paper uses three vector autoregressions and compute the long-term impact of the indices on the considered macroeconomic variables through impulse response functions.

This paper finds that an energy price shock has a detrimental impact on the macroeconomic indicators of India in the long run. This study also finds that the constructed index acts as a relatively more sensitive index in comparison to the International Monetary Fund and World Bank indices, which is bespoke to a developing economy case. This sensitivity is ascribed to dynamic weighting for a different basket of energy components, which are more pertinent to an Indian context.

The novelty of this research lies in the construction of a new index and its comparison to the existing ones. This study justifies why a developing economy would require a different measure of energy as opposed to the existing indices.

This paper aims to explore the drivers of sustainable healthcare supply chain (SHCSC) performance measurement through extensive literature review and experts' opinions. The drivers are then scrutinized and their priority vector is calculated to provide quality and cost-effective healthcare supply chain (HCSC) services.

The drivers of the SHCSC performance measurement are validated using the grey-Delphi technique. After validating the drivers, they are prioritized using the grey-analytic hierarchy process (G-AHP), a multi-criteria decision-making tool.

The findings of the study highlight the prioritized drivers based on the preferences given by the experts. The findings of the study highlight the most prioritized drivers of healthcare (HC) by-product management system, coordinating and facilitating green suppliers in the HCSC and green packaging of pharmaceutical as well as other essential items.

The HCSC managers should coordinate with all the stakeholders across the supply chain and involve them in the decision-making process to make products and services greener and become complicit in complying with the sustainable policy guidelines. The study highlights the strategic policy and managerial implications for implementing sustainability in the HCSC.

The validation and prioritization of the drivers of SHCSC in developing nations' contexts is the key contribution of the study. Grey-AHP enables a practical approach towards enhancing the sustainability of the HCSC and opening the doors for generalizing the study for future research works.

With the rising needs of health-care (HC) services during the health outbreaks, it is essential to upgrade the existing HC delivery infrastructure. The study aims to prioritize and highlight the interrelationships among the key factors of the smart health-care supply chain (HCSC) by implementing the concept of Industry 4.0.

The key factors of implementing Industry 4.0 in HCSC have been identified through extensive literature review and stakeholders' opinions. To achieve the abovementioned objectives, the present study proposed hybrid multi-criteria decision-making (MCDM) tools, namely, the fuzzy-analytic hierarchy process (AHP) and fuzzy- decision-making trial and evaluation laboratory (DEMATEL). The Fuzzy-AHP prioritized the factors of implementing Industry 4.0 in HCSC, while the cause–effect relationships among the factors have been explored using fuzzy-DEMATEL.

The results of the study indicated that HC logistics management (HCLM) is the most prioritized factor of implementing Industry 4.0 in HCSC, followed by the integrated HCSC, then sustainable HCSC practices, HCSC innovation and technological aspects, HCSC institutional perspectives, HCSC competitiveness, social aspects and economic factors of HCSC. The cause–effect analysis has highlighted integrated HCSC, HCLM, HCSC competitiveness and social aspects as the cause group factors and they are the critical success parameters for implementing Industry 4.0 in the HCSC.

The results of the study can be useful for policymakers, humanitarian organizations, health administrators and other decision makers considering the smartening of HCSC to enhance the operational performance of health facilities.

This is one of the few studies to have been conducted so far in which the subfactors of HCSC implementing Industry 4.0 have been identified and analyzed using the fuzzy-AHP and fuzzy-DEMATEL hybrid approach.

Understanding which market to invest in for a well-diversified portfolio is fundamental in economies that are highly vulnerable to fluctuations in exchange rates. Extant literature that has considered phenomenon hardly juxtapose the markets. The purpose of this study is to examine the effects of exchange rate volatility on the Stock and Real Estate market of South Africa. The essence is to determine whether the fluctuations in the exchange rate influence the markets prices differently.

The Generalised Autoregressive Conditional Heteroskedasticity [GARCH (1.1)] model was used in establishing the effect of exchange rate volatility on both markets. This study used monthly South African data between 2000 and 2020.

The results of this study showed that increased exchange rate volatility increases stock market volatility but decreases real-estate market volatility, both of which revealed weak influences from the exchange rates volatility.

This study has implication for policy in using the exchange rate as a policy tool to attract foreign portfolio investment. The weak volatility transmission from the exchange rate market to the stock and real estate market indicates that there is prospect for foreign investors to diversify their investments in these two markets.

This study investigated which of the assets market, stock or housing market do better in volatile exchange rate conditions in South Africa.