Shiyong Zheng

Taking the Brand Management course as the research object, this paper explores the necessity and path innovation of the course's Civic and Political construction. From the three dimensions of excavating the current situation of brand management course civic politics construction, dissecting the current problems of the ‘Brand Management’ course, and solutions, it analyses how to deeply integrate socialist core values, professional ethics education and brand management professional knowledge, and help students' all-round development. Through case teaching, scenario simulation and other diversified teaching practices, this paper summarises the implementation strategy of course civics, which provides new ideas and reference experiences for the construction of course civics in universities.

Green innovations are the most critical factor in promoting environmental sustainability worldwide. Trade can speed up the adoption of green innovations by facilitating the transfer of information, skills, and technology. However, trade policy uncertainty can create significant challenges for businesses investing in eco-innovations, leading to increased risk, reduced investment, and slower progress toward sustainable technologies. Recently, a growing number of researchers have shown their interest in finding the factors that can impact green innovations, but none have investigated the influence of trade policy uncertainty on green innovations in the USA and China. In addition, none of the past studies has relied on the nonlinear assumption. This analysis fills these gaps by examining the nonlinear impacts of trade policy uncertainty on eco-innovations in China and the USA over 2000Q1–2021Q4 by employing a nonlinear ARDL model. The finding reveals that a positive shock in trade policy uncertainty results in a decrease in green innovation in the USA and China, while a negative shock in trade policy uncertainty leads to an increase in green innovation in the USA over the long run. The nonlinear models also indicate that a positive shock in trade policy uncertainty harms green innovation in both the USA and China in the short run. The robustness of these results is confirmed by the NQARDL model, which confirms that an upsurge in trade policy uncertainty lowers green innovation in most quantiles in the USA and China in the short and long run. Conversely, negative shocks in trade policy uncertainty stimulate green innovation at most quantiles in both China and the USA, in the short and long run. Thus, policymakers need to consider the potential impact of trade policies on eco-innovations and work to create stable and predictable trade environments that support the growth of renewable technologies and other sustainable solutions.

In order to reduce environmental deterioration and promote sustainable growth, green innovation—which includes ecologically friendly technology and practices—has become a top priority of policymakers worldwide. This research investigates how formal and informal finance affects green innovation in highly polluted high, middle-, and low-income economies, using data spanning from 2007 to 2021. For analyzing the empirical link between formal finance, informal finance, and green innovation, we have employed the 2SLS and GMM estimation techniques. The primary estimates of the analysis suggest that formal and informal funding methods significantly impact environment-related technologies in high-income and middle- and low-income nations. Moreover, the GDP, carbon emissions, trade openness, human capital, research and development, financial stability, and digital finance are essential factors in promoting environment-related technologies in high-, middle-, and low-income nations, respectively. The policymakers in both groups of countries should foster collaboration between the formal and informal sectors to promote green innovations, which is essential for achieving sustainable development goals.

Maintaining operations in the face of crises like COVID-19 is difficult. Using the stakeholder theory, this study examines the impact of corporate social responsibility (CSR) programs targeting company employees. Their social position and the likelihood of a green economic rebound (GER) are evaluated. Evidence shows that employee-focused CSR activities implemented by tourism boost organizational GER by fostering a more trusting work environment for their staff. Management and non-management staff at Chinese Tourism were polled using a non-probabilistic convenience sample and a 5-point Likert scale. Structured equation modeling was used to conduct structural analyses. Employee-focused CSR is a significant predictor of a firm reputation in the Chinese tourism industry. In addition, it is found that trust inside the organization acts as a go-between. The evidence also supports the hypothesis that a company’s rising profile triggers GER. This research delves deeply into the connection between employees’ perceptions of a company’s employee-focused CSR initiatives, that company’s reputation in the community, and employees’ general enthusiasm for their job, a group that has been understudied until now. The findings are helpful for tourism management because they show them how to employ employee-focused CSR activities to strengthen connections with internal stakeholders while also using that reputation to shift to a greener way of doing business.

Due to the depletion of fossil fuels, empirics began looking at the factors that might encourage investment in renewable energy. Socioeconomic productivity can encourage renewable energy development by encouraging authorities, businesses, and families to rely more on renewable energy sources. Therefore, this analysis is the first-ever effort to detect the impact of socioeconomic productivity on renewable energy development. We have used the panel ARDL and QARDL to examine the estimates. The results of the panel ARDL model predict that national income, financial development, productive capacity index, human capital, ICT, institutional quality, and structural changes are beneficial for renewable energy development in the long run. In the short run, only financial development, productive capacity index, human capital, and ICT promote renewable energy development. Likewise, the panel QARDL model estimates that the national income, financial development, and productive capacity index promote renewable energy development in the long run. However, in the short run, only the productive capacity index and financial development promote renewable energy development. Therefore, by integrating productive assets, entrepreneurial skills, and industrial connections, policymakers must work to boost the productive socioeconomic potential.

Environmental reformation of old-fashioned sectors and the establishment of new pro-ecological businesses via green investment are the main driving forces behind the revolution in the Chinese industrial sector. Green investment aids in the growth of environmentally friendly industries. Hence, the primary objective of the analysis is to investigate the impact of green investment and technological progress on green industrial development. The results of the unit root tests encourage us to apply the ARDL model. The short and long-run estimates attached to R&D expenditures are positively significant, confirming that increasing R&D expenditures help improve the industrial structure. Similarly, the short and long-run estimates attached to green finance investment are positively significant, signifying that green investment benefits the industrial structure. Empirical findings show that technology significantly aggravates industrial structure development in only the long run. Thus, for green industrial development in China, there is a need to increase green investment and technological development up to top-level design.

In an effort to reduce environmental pollution and energy consumption, the Chinese government strongly promotes the usage of electric vehicles. However, studies focusing on assessing consumers’ willingness to pay (WTP) for electric vehicles (EVs) are limited in the country. This research aims to address this research gap by examining influencing factors of consumers’ WTP for EVs in the Chinese perspective. Combined with the existing consumers’ intention factors, the current study further contributed by augmenting the theoretical framework of the Theory of Planned Behavior by including three new dimensions (performance expectancy, information loaded, and perceived risk) to comprehensively analyze the willingness of Chinese consumers. Analysis is performed on survey data from 498 consumers using EVs in Beijing, China. To evaluate formulated hypotheses, structural equation modeling approach is employed. Empirical findings reveal that environmental knowledge and performance expectancy positively and significantly influence behavioral intention. In contrast, overloaded information has a negative impact on behavioral intention. Moreover, subjective norms are significantly and positively related to behavioral intention. The research outcomes further disclose that perceived risk is positively and significantly related to behavioral intention. Finally, behavioral intention has a significant and positive association with WTP for EVs. The study contributes to the literature on sustainable consumption behavior and provides academics and practitioners with essential future directions.