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Historically, Russia is a country with colossal territory and strategic location (known as Eurasia which includes parts of Asia and Europe). In the context of its military capability Russia is known for its massive military capability historically as its neighbors' policy of expansion and attack by European powers and Mongols. After worth of the Second World War, USSR became one of the world's superpower in opposition of United States of America. Consequently Cold War began between two superpowers. During Cold War Period from 1945 to 199, Russia's military capabilities were the major factor to sustain its status as a superpower for long time. After the disintegration of USSR in December 1991, Modern Russia came into picture. After disintegration of USSR Russia had been gripped by its unstable domestic problem, therefore could not take care of its military capabilities. After 1999, Vladimir Putin came into power, which helped Russia to regain its military strength of past. In the world politics theater, Russia's position is against the unipolarity which directly threatens USA's hegemony in world politics. Contrary, Russia's military capability has been weakening to counter USA's hegemony.

Continuous-monitoring applications in sensor network applications require periodic data transmissions to the base-station (BS), which may lead to unnecessary energy depletion. The energy-efficient data aggregation solutions in sensor networks have evolved as one of the favorable fields for such applications. Former research works have recommended many spatial-temporal designs and prototypes for successfully minimizing the data-gathering overheads, but these are constrained to their relevance. This work has proposed a data aggregation technique for homogeneous application set-ups in sensor networks. For this, the authors have employed two ways of model generation for reducing correlated spatial-temporal data in cluster-based sensor networks: one at the Sensor nodes (SNs) and the other at the Cluster heads (CHs). Building on this idea, the authors propose two types of data filtration, first at the SNs for determining temporal redundancies (TRs) in data readings by both relative deviation (RD) and adaptive frame method (AFM) and second at the CHs for determining spatial redundancies (SRs) by both RD and AFM.

This study analyses the dynamics of consumption inequality among various occupational groups using household survey data from National Sample Survey (NSS). Three rounds of NSS data namely, the 50th (1993–1994), 61st (2004–2005), and 66th (2009–2010) were taken for the purpose of analysis. Various measures such as Gini coefficient, overlapping index, and raking matrices are estimated for the whole as well as the subgroups using ANOGI methodology. From the analysis, it is found that the level of overall inequality as well as the between‐group inequality is on the rise during the period of analysis. Further, the measures such as relative overlap index and ranking matrices give conclusive evidence that the difference between various groups in terms of consumption expenditure pattern is increasing over time. From the ranking matrices, it is seen that the last six groups, constituting households with occupation in the unorganized sector and low level organized workers falls below the 30th percentile of consumption expenditure distribution of the first group groups that consists of individuals holding to technical, administrative, managerial, and executive occupations. Worsening inequality across various occupational groups is a matter of concern, especially from the policy perspective. As economic growth without equitable distribution of income is not a desirable outcome.

We test the possible presence of weak‐form informational efficiency in the Indonesian forex (FX) market using daily bilateral exchange rate return of Indonesian Rupiah against U.S. Dollar from January 24, 2001 to March 29, 2019. First, we employ a battery of statistical tests including variance ratio tests, tests for linear dependence and Hurst coefficient on the full dataset as well as on four non‐overlapping sub‐samples of equal length. The tests provide a mixed result, whereas Hurst coefficient values identify long‐run persistence in the market. Based on this evidence, we test the possibility of adaptive nature of Indonesian FX market. The adaptive market hypothesis is tested using the newly proposed adaptive index (AI) in order to quantify the degree of information inefficiency in the Indonesian FX market at any given point. The AI values conclusively prove that Indonesian FX market is adaptive and periodically switches between states of efficiency and inefficiency. Moreover, various macroeconomic and financial events influencing Indonesian FX market efficiency are identified.

The pandemic has put a toll on businesses across the globe, especially power generation as an essential service. The role of leadership is exemplary in driving job engagement in the power sector. The study aims to explore the impact of a leader's inspirational motivation and individualized consideration on employee job engagement in the Indian power sector. This study is quantitative exploratory research. Using a validated questionnaire, 444 survey responses were taken from executives of major Indian electricity generation utilities. Inspirational motivation and individualized consideration were taken as independent variables, while employee engagement and its components were taken as dependent variables. Statistical methods of simple and multiple correlations were performed using SPSS version 25. According to the findings, the components of transformational leadership have a positive and significant impact on employee engagement (r = 0.463) and its facets of vigor (r = 0.425), dedication (r = 0.455), and absorption (r = 0.267), respectively. In addition, the finding outlines that transformational leaders propagate their high power and enthusiasm to their workers through inspirational motivation to increase their job engagement. The paper also highlights the role of a leader as a coach and mentor through individualized consideration to cater to followers' need for growth and achievement. These findings expand the literature on leadership and employee engagement in the Indian power sector.

Manuscript type: An empirical analysis of the relationship between country-level governance and share markets in the Asia-Pacific region was carried out using dynamic value at risk (Dynamic VaR), mixed data sample (MIDAS) and exponential generalised autoregressive conditional heteroskedasticity (EGARCH) models. Research question/issue: Is there a relationship between a country's governance and stock market in terms of the level of returns and share price volatility? We hypothesise that stock returns for countries with higher levels of governance will have lower ex ante expected returns and less volatility than countries with lower levels of governance. Research findings/insights: It is evident from the empirical findings that there is still significant diversity in both corporate-level governance and country-level governance within the Asia-Pacific region. The results from using mixed data sample-autoregressive distributed lag (MIDAS-ADL) model correlation between world governance index (WGI) and the dynamic VaR suggest that the estimators of high frequency slope for India, China and Malaysia are negative. In addition, their t statistics show that the correlation is significant; meanwhile, their goodness of fit is also very high confirming the explanation power of MIDAS-AD model. Consequently, the capital market performances of India, China and Malaysia are negatively related to their corporate-level governance and country-level governance. However, China has a positive correlation between WGI and corporate-level governance and country-level governance. This uncommon phenomenon may be the result of its special political system and the segregation of the capital market and the real economy. Theoretical/academic implications: The linkage between country-level governance and volatility of stocks in Asia-Pacific markets indicates there is scope to reduce stock price volatility through enhanced national governance. Volatility as an indicator of risk reflects market uncertainty in terms of processing information signals to find the equilibrium return risk nexus. Consequently, researchers have to incorporate the data of different frequency into the same equation using robust methods. Practitioner/policy implications: Regulatory frameworks encompassing stock markets will benefit from a more focussed consideration of the way in which governance and risk are correlated. Findings from the generalised autoregressive conditional heteroskedasticity (GARCH) and VaR analysis are that stock market volatility is a suitable proxy for the governance of a country. As country governance indices are annual at best, volatility measures give more timely readings. An increase in volatility suggests there is a decline in national governance, and this has implications for those involved in trade, donor organisations and international lending agencies such as the World Bank.