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This paper aims to consider the role of geopolitical risk in explaining tourism demand in India, a major tourist destination of the Asian region. Furthermore, the study also considers how in addition to geopolitical risk, economic policy uncertainty, economic growth, exchange rate, inflation and trade openness impact tourism demand.

The Bayer and Hanck (2013) method of cointegration is applied to explore the relationship between geopolitical risk and tourism demand. Furthermore, the study has also used the auto distributed lag model to determine whether there is a long-run cointegrating association between tourism demand, geopolitical risk, economic policy uncertainty, economic growth, exchange rate and trade openness. Finally, the vector error correction model confirms the direction of causality across the set of the major variables.

This paper finds that geopolitical risk adversely impacts inbound international travel to India. This study also obtains the consistency of the results across different estimation techniques controlling for important macro variables. The Granger causality test confirms the unidirectional causality from geopolitical risk to tourism and further from economic uncertainty to tourism. The findings from the study confirm that geopolitical risks have long-term repercussions on the tourism sector in India. The results indicate that there is an urgent need to develop a pre-crisis management plan to protect the aura of Indian tourism. The tourism business houses should develop skilful marketing strategies in the post-crisis to boost the confidence of the tourists.

This paper provides valuable practical implications to tourism business houses. The tourism business houses can explore geopolitical risk measure and economic policy uncertainty measure to analyse the demand for international tourism in India. Further, the major stakeholders can establish platforms to help tourists to overcome the fear associated with geopolitical risk.

This study is the first of its kind to explore the geopolitical risks and their long-run consequences in the context of tourism in India. The study puts emphasis on the role of national policy to maintain peace otherwise it would be detrimental to tourism.

This study explores the response of consumer confidence in policy uncertainty in the Japanese context. The study also considers the dynamism of stock market behavior and financial stress and its impact on consumer confidence, which has remained unaddressed in the literature. The role of these control variables has important implications for policy discussions, particularly when other countries can learn from Japanese experiences.

The nonlinear autoregressive distributed lag model postulated by Shin et al. (2014) was used for studying the asymmetric response of consumer confidence to policy uncertainty. This method has improved estimates compared to traditional linear cointegration methods.

The findings confirm the asymmetric impact of policy uncertainty on the consumer confidence index in Japan. The impact of the rise in policy uncertainty is greater than that of a fall in asymmetry on consumer confidence in Japan. Furthermore, the Wald test confirmed asymmetric behavior.

The contribution of this study is threefold. First, this study contributes to the extant literature by analyzing the asymmetric response of consumer confidence to policy uncertainty, controlling for both the financial stress and stock price indices. Second, to test the robustness of the exercise, the study utilized different frequencies of observations. Third, this study is the first to utilize the concept of Arbatli et al. (2017) to formulate a combined index of uncertainty based on economic policy uncertainty index, along with uncertainty indices such as fiscal, monetary, trade and exchange rate policies to study the overall impact of policy uncertainty.

This paper attempts to investigate through empirical exercise how the chances of female employment opportunities rise in a developing country like India, against the backdrop of changes in institutions that are associated with globalization.

The paper develops a simultaneous equation model through a growth equation, gender equation and globalization equation to identify the factors impacting female labor market opportunities in India, based on annual time series data 1991–2019.

The major results of this study are as follows: (1) It is social globalization that positively impacts gender equality in employment opportunities apart from economic growth and trade diversification; (2) Evidence of “feminization of labor force” in the context of trade diversification is found; and (3) Equal gender opportunities reflect in equalizing outcomes in the labor market.

Growth strategies need to be constructed in such a way in India that it has redistributive implications and benefits women. The state agency needs to optimize the productive base of human resources and increase women's empowering capability through social and legal sanctions.

The uniqueness of the present paper lies in contributing to the existing literature on how gender inequality impacts trade diversification and how trade diversification impacts gender.

This study attempts to explore the determinants of tourism demand that impact tourist arrivals in Australia from Asia using an augmented panel gravity model.

The augmented panel gravity model was utilised to analyse the demand for Australian tourism from 15 major countries of Asia over the period 1991 to 2018. Tourist arrivals were the dependent variable while per capita gross domestic product (GDP) and weighted distance were important explanatory variables. Further other indicators like population, money supply, globalisation, price index, exchange rate, uncertainty and two dummy variables were added as control variables.

The results demonstrate based on the novel methodology of Pesaran (2006), namely CCE (common correlated effects) that tourist arrivals are impacted positively and significantly by per capita GDP of both the country of origin and destination country, globalisation also impacts tourist flows positively. However, tourist arrivals are adversely affected by distance and prices confirming the economic theory.

Gravity models have been intensively used in the recent literature on tourism; however, this study has attempted to explore tourism demand from Asia into Australia which is indeed an unexplored area further the study has used the CCE methodology which takes care of the problems of cross-sectional dependence unlike the earlier methods widely used in the literature like the DOLS and the FMOLS. Last by utilising a wide-ranging set of macro factors the study contributes a novel assessment to the recent literature on tourism demand model.

The outbreak and the spreading of the COVID-19 pandemic have impacted the global financial sector, including the alternative clean and renewable energy sector. This paper aims to assess the impact of the pandemic, COVID-19 on the stock market indices of the clean energy sector using quantile regression methods.

This study utilized daily data sets on the four major categories of stocks: (1) Morgan Stanley Capital International Global Alternative Energy Index, (2) WilderHill Clean Energy Index, (3) Renewable Energy Industrial Index (RENIXX) and (4) the S&P 500 Global Clean Index. The study adopts a multifactor capital asset pricing model.

Clean and alternative energy stocks are powerful instruments for diversification. However, the impact of the volatility index induced by infectious disease is negative and significant across quantiles.

For investors and policymakers, considering how the uncertainty caused by COVID-19 and the geopolitical index influences renewable energy markets is of great practical importance. For investors, it throws insights into portfolio diversification. For policy makers, it helps to devise strategies to reboot the economy along the lines of the deployment of renewables. This study sheds light on a global green-energy transition and has practical implications for renewable energy resilience in post-pandemic times.

This paper can be considered as a pioneer that explores the nexus between oil prices, interest rates, volatility index, and geopolitical risk upon the stock indices of clean and alternative sources of (renewable) energy in the COVID-19 pandemic situation. The results have important insights into the area of energy and policy decision-making. Additionally, the paper's novelty lies in using the explanatory variables associated with the Covid 19 pandemic.

The purpose of this study is to examine how renewable energy consumption moderates the relationship between inequality and carbon dioxide (CO₂) emissions for Brazil, Russia, India, China and South Africa (BRICS). The nexus between energy use and geopolitical tensions has also been explored.

This study has used distinctive data sets from 1990 to 2018 to explore the interconnections on emission, energy use, inequality and geopolitics. To do away with the difficulties related to heterogeneity and cross-sectional dependence (CD), this paper uses recent estimation methods that are robust to panel heterogeneity and CD.

The results of the panel augmented mean group (AMG) estimation and common correlated effects mean group (CCEMG) estimation verify the environmental Kuznets curve. The findings show that a 1% rise in Gini inequality leads to a 0.24% rise in the CO₂ emission (AMG) method and a 0.17% rise in emissions CCEMG (method). As far as the moderating impact of renewable energy upon Gini measure of inequality is concerned, it is −0.10 AMG and CCEMG methods of estimation, respectively. However, the moderating impact of renewable energy on the geopolitical index leads to a mitigating impact on CO₂ emissions, 0.55% decline in AMG method.

This research makes a distinctive contribution by investigating for the first time to the best of the authors’ knowledge the main pillars of sustainable ecological development in the context of the BRICS nations.

The purpose of this paper is to examine the asymmetric impact of economic policy uncertainty (EPU) on the volatility of the housing price index (RP) based on quarterly observations from major European countries, namely, France, Germany, Sweden, Greece Italy and the UK.

The nonlinear autoregressive distributed lag model method is used to investigate the asymmetric impact of EPU on RP. In addition to considering EPU as the explanatory variable, industrial production (IP) (as a proxy for economic growth), interest rate (I), inflationary tendency (Consumer Price Index) and share prices (S) are included as major control variables. The period of the observations runs from 1996Q1 to 2019Q1.

The Wald test confirms the long-run asymmetric relationship for all countries. The alternative specification of the data sets reconfirms the asymmetric impact on RP in the long run, thereby verifying the robustness of the study.

The study has implications for investors seeking to incorporate housing price behaviour within their portfolio structure. The analysis and findings are constrained by the availability of data.

This is one of the few studies on housing price dynamics related to the major economies of the European region that explore asymmetries. Additionally, it is the first to explore the asymmetry dynamics using the EPU variable.

Greenko, a renewable power generating company investing in biomass, small and medium hydro power and wind power projects, had projected to achieve 1GW (Giga Watt = 1000 Mega Watt) of installed capacity by March 2015. The company had been financing its projects with debt from Indian banks and financial institutions on a project finance basis and it had to now decide whether to refinance the project finance debt with an international bond issue of USD 550 million. The case provides an opportunity to discuss the public policy and financing aspects of renewable energy in India.

Mucorales has been described to be widely distributed during the most recent COVID-19 pandemic, with a greater frequency of disease in India, particularly among those with immune deficiencies. This study aims to use computational tools to develop a vaccine.

The authors investigated at Mucorales proteins that had previously been associated to virulence factors. Recent research suggests that a vaccine based on high-level cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B-cell lymphocyte (BCL) epitopes from diverse proteins might be developed. Furthermore, the vaccine assembly contains the targeted epitopes as well as PADRE peptides to induce an immune response. Computational approaches were used to analyze the immunological parameters used to build the suggested vaccine and validate its TLR-3 binding.

These studies show that the vaccination is capable of triggering a particular immune response. The authors offer a technique for developing and evaluating candidate vaccines using computational tools. To the best of their knowledge, this is the first immunoinformatic research of a prospective mucormycosis vaccine.

During this audit, a successful attempt was made to create a subunit MEV against black fungus. In the current study, MEV has been proposed as a suitable neutralizer candidate since it is immunogenic, secure, stable and interacts with human receptors. A stream study, on the other hand, is produced via a mixed vaccinosis approach. Following that, vaccinologists may perform more exploratory testing to evaluate whether the vaccine is effective.

The purpose of this paper is to prepare a new modified activated carbon fibers (ACFs) of high specific capacitance used for electrode material of supercapacitor.

In this study, the specific capacitance of ACF was significantly increased by using the phenolic resin microspheres and melamine as modifiers to prepare modified PAN-based activated carbon fibers (MACFs) via electrospinning, pre-oxidation and carbonization. The symmetrical supercapacitor (using MACF as electrode) and hybrid supercapacitor (using MACF and activated carbon as electrodes) were tested in term of electrochemical properties by cyclic voltammetry, AC impedance and cycle stability test.

It was found that the specific capacitance value of the modified fibers were increased to 167 Fg^-1 by adding modifiers (i.e. 20 wt.% microspheres and 15 wt.% melamine) compared to that of unmodified fibers (86.17 Fg^-1). Specific capacitance of modified electrode material had little degradation over 10,000 cycles. This result can be attributed to that the modifiers embedded into the fibers changed the original morphology and enhanced the specific surface area of the fibers.

The modified ACFs in our study had high specific surface area and significantly high specific capacitance, which can be applied as efficient and environmental absorbent, and advanced electrode material of supercapacitor.