The current Internet revolution has changed the entrepreneurial opportunities and trends. This study explores the relationship between entrepreneurial characteristics (e.g., innovation, leadership, planning, and sociability) and the performance of entrepreneurial vloggers in India. In addition, this study considers the mediating effect of entrepreneurial intentions. This study is cross-sectional, and it considered 128 entrepreneurial vloggers for the analysis. The SmartPLS application was used to estimate the structural equation modeling (SEM) analysis for the estimation of reliability and validity along with the path relationship. The findings are more important as the entrepreneurial characteristics can meaningfully predict the performance of entrepreneurial vloggers in a positive direction. Moreover, the relationship between entrepreneurial characteristics and the performance of entrepreneurs is partially mediated by entrepreneurial intentions. These findings have important implications for vloggers in Indian or other countries with similar nature. This study has also put some future research directions at the end.
The basic aim of the study was to understand the role of the Big Five model of personality in predicting emotional intelligence and consequently in triggering the entrepreneurial behavior of the employees. The emotional intelligence of the individuals plays a very important role in decision making, enhancement of quality of living, and many other social realms. Hence, the intelligent use of emotions can make or break an individual's future considering their attitude toward exploiting the entrepreneurial opportunities available. This study has measured the impact of personality traits on emotional intelligence and EI's role in digital entrepreneurial behavior. The population used in this study was the middle management employees in the corporate sector of the mainland in China. The sample size taken in this study was 260 and selected through convenient sampling. The data was collected through a structured questionnaire measuring each variable. The data collected was employed to SmartPLS 3.3 for analyzing through structural equation modeling to measure the hypotheses. The study has found the partial effect of the Big Five model of personality on emotional intelligence, which significantly predicted the digital entrepreneurial behavior of the employees. The organizations can use the study findings to anticipate the employees' possible prospects and endeavors regarding their digital entrepreneurial behaviors.
It is observed that an educated labor force can increase the absorption capacity of the economy and improve the effectiveness of green technologies that lead to a reduction in potential CO2 emissions. The study investigates whether an educated labor force contributes to the management of the green economy or not in BRCS economies. Panel ARDL-PMG and NARDL-PMG approaches have been employed for empirical analysis for data ranging from 1995 to 2019. According to the ARDL-PMG results, a highly educated labor force contributes to alleviating CO2 emissions in the long run. In contrast, the findings of NARDL-PMG infer that positive component of a highly educated labor force has a significant negative impact on CO2 emissions, while negative component of a highly educated labor force has a positive impact on CO2 emissions in the long run. The study suggests that BRCS countries' policymakers should promote education and training for the labor force to maintain a reduction in CO2 emissions.
Over the last three decades, the world has been facing the phenomenon of the ecological deficit as the ecological footprint is continuously rising due to the persistent decline of the per-capita bio-capacity. Moreover, there is a substantial increase in globalization and electricity consumption for the same period, and transportation is contributing to economic prosperity at the cost of environmental sustainability. Understanding the determinants of ecological footprint is thus critical for suggesting appropriate policies for environmental sustainability. As a result, this study analyzes the impacts of economic globalization, transportation, coal rents, and electricity consumption in ecological footprint in the context of the USA over the period 1995 to 2018. The data have been extracted from "Global Footprint Network," "Swiss Economic Institute," and "World Development Indicators." The current study has also applied the flexible Fourier form nonlinear unit root test to examine the stationarity among variables. For the empirical estimation, a novel technique, the "quantile auto-regressive distributive lag model," is applied in the study to deal with the nonlinear associations of the variables and to evaluate the long-term stability of variables across quantiles. The study's findings indicate that coal rents, transportation, and globalization significantly and positively contribute to the deterioration of ecological footprints at different quantile ranges in the short and long run. Electricity consumption is found to have a positive and significant impact at lower quantile ranges in the long run but not have a significant impact in the short run. The study suggested that lowering the dependence of the transport sector on fossil fuels, more use of hydroelectricity, and stringent strategies to curb coal consumption would be helpful to reduce the positive influence of these variables on ecological footprints in the USA.
The role of risk assessment and capital structure is vital for the sustainable growth of firms and increasing the shareholders' wealth. This research explores the correlation between firm risk and capital structure using datasets from the sugar and cement sectors of Pakistan as a developing economy. This study is unique as it involved two firms of different nature (sugar firms operate seasonally while cement firms operate yearly) to view the real picture on the impact of risk and structure assessment on firms' credibility and shareholders' wealth. For this purpose, 15-year data (2000-2014) containing the financial statements of the target sectors were collected and the ANOVA analysis was applied with credit risk, liquidity risk, systematic risk, and firm size were used as the regressor variables, firm growth and dividend payout ratio as the control variables, and leverage as the regression variable. The findings showed that credit risk and liquidity risk are significantly correlated with leverage. This suggests that decision-makers pertaining to firms' risk and efficiency must focus more on risk to pursue a stronger and sustainable increase in shareholder wealth.