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In response to the dramatic increase in social media usage among the young generation, the patterns of manufacturing and consumption have changed. Social media has altered the green consumption market and completely changed consumer psychology and attitude. The influence of social media on the younger generation’s behavior regarding green consumption through subjective norms and perceived green value is hardly discussed in the earlier literature with special reference to China. This study has the objective to explore the impact of social media on the green purchase intentions of young people in the presence of subjective norms and perceived green value. A survey of 303 young people in China is conducted and multiple statistical techniques are applied to determine the reliability and validity of the data such as the Fisher F test, White’s test, the Durbin–Watson test, the Shapiro–Wilks test, and confirmatory factor analysis. The mediating impact of the variables are explored through the bootstrap method and multiple regression is applied for finding the relationship among dependent and independent variables. The findings of this study reveal that information shared on social media has a positive relationship with green consumption among the younger generation in China. In addition, perceptions about green environment and “subjective norms” have a strong mediating impact on increasing the intentions of consumers for purchasing of green products. Moreover, the occupation of consumers also has a mediating role in moderating the subjective norms regarding green consumption. The findings of the study have theoretical contributions as well as practical implications. It is found that social media has a stimulus role for green consumption among the younger generation to devise their subjective norms and perceptions. The practical implications of the present findings are helpful for policy makers to understand how social media is effective in combatting environmental deterioration in the context of China’s recent economic expansion. The future research may be extended through a splitting sample considering the location of respondents and in terms of responses’ quartiles.

This research article aims to disclose the features of nanofluidic flow manifested with Cattaneo-Christov model of heat and mass flux over non-linearly stretching surface. An incompressible visco-elastic nanofluid saturates the given porous medium through Darcy-Forchheimer relation. A non-uniformly induced magnetic effect is considered to accentuate the electro-magnetic and thermal conductivity of the base fluid. The model is restricted to small magnetic Reynolds. Boundary layer assumptions are incorporated for the given flow model. Governing equations are remodeled into non-linear ordinary differential equations through transformations. So formulated nonlinear system is solved through homotopy analysis method (HAM) to achieve series solutions for velocity field, concentration of nanoparticles and temperature distribution. It is noticed that the temperature distribution and corresponding thermal boundary layer pattern shows declination for Cattaneo-Christov model of heat and mass flux as compared to classical Fourier's law of heat flux/conduction. Furthermore, the intensive resistance offered by the addition of porosity factor in the flow model results in rise of temperature profile, however, opposite behavior is noticed in concentration of nanoparticles. The wall-drag intensity, the heat flux and the mass flux are discussed on the premise of numerical information obtained upon simulation of the problem.

This research paper delves into the behavioral factors that have impact on decision making of Chinese investors in stock markets. As one of the world’s most dynamic and rapidly evolving financial landscapes, stock markets of China have witnessed significant growth and transformation in recent years. However, the role of behavioral biases in shaping investment decisions remains a relatively understudied aspect. Drawing upon a detailed review of studies, psychological theories, and empirical studies, this research explores various behavioral factors affecting the decision of investors at Beijing, Shanghai and Shenzhen stock markets. Through a structured questionnaire and by collecting a sample of 521 respondents, this paper investigates that herding, overconfidence, prospect, market, gamble’s fallacy, and anchoring-ability bias often lead investors to deviate from rational decision-making and contribute to market inefficiencies. While herding, prospect, and heuristic affect the investment performance in stock markets of China. Moreover, the research underscores the need for investor education programs and regulatory interventions that acknowledge the presence of behavioral biases and encourage more informed decision-making. By shedding light on these dynamics, it provides valuable insights for policymakers, financial institutions, and investors seeking to navigate the intricacies of this rapidly growing financial landscape.

In the process of development, global economies are prioritizing environmental protection and firms are also recognizing the importance of minimizing environmental impact during production along with maximization of profits through green investments. It is vivid that green investments are vital for environmental preservation. So this paper contributes to literature by investigating the role of internal and external factors affecting the decision making of Chinese firms regarding adoption of green investments and impact of green investments on environmental, social, and economic performance of firms. The data is collected from directors/senior managers of the firms. We received 463 valid responses from listed companies with Shenzhen, Beijing, and Shanghai Stock Exchange. The “structural equation modeling” with “maximum likelihood estimation” is employed for empirical analysis. The empirical findings reveal that adaptation to climate change and its mitigation is the most important driver of green investment. Moreover, green investment positively contributes to enhancing the social, economic, and environmental performances of Chinese firms. Based on the findings of the study, green investment should be adopted as a corporate strategy by firms for profit maximization, competitive advantage, and improvement in social well-being without compromising the environment. Policy makers can promote green investment by offering policy instruments such as tax incentives, guaranteed credits, grants, and investor education. Training courses may be offered to raise environmental awareness among firms and the general public.

Social media is emerged as a powerful communication tool over the past ten years. The Z generation’s green buying habits and purchase intentions are being reshaped by social media, which is helping to advance the development of a sustainable environment. The consumption of non-organic products has raised carbon emissions, so changing consumption patterns and purchase intentions is necessary for a more sustainable future. Moreover, earlier literature has the absence of a comprehensive behavior change model that explains the mechanism through which social media influences sustainable behaviors This study explores that how social media affects patterns of consumption for Z generation of China while considering the role of environmental concerns, subjective norms, eco-branding and eco-labeling on the basis of theory of planned behavior. A questionnaire is used to get information from the 563 Z generation respondents of China. The data is analyzed using Smart-PLS and empirical outcomes show that social media has a statistically significant influence on shaping and affecting green consumption behavior of China’s Z generation because it has the potential to reach a vast audience and spread awareness about environmental issues, leading to increased intention towards a sustainable environment and reduction in carbon emissions. It also provides a platform for individuals to express their opinions and engage in discussions on environmental issues. These developments are promising for the future of environmental sustainability as they indicate a growing interest in preserving the planet among the Z generation of China. It can be recommended as a policy tool that government and other organizations should support the development of informative content on social media platforms, highlighting the importance of environmental sustainability and eco-friendly habits.

Over time, environmental concerns have gained much importance and main debatable issue. Green products are becoming popular due to their positive impact on environment and their role in the green economy. However, the significance of environmental awareness, perceived cost, face culture and policy incentives on green consumption behavior is not fully examined in prior research. This research aimed to analyze the various dimensions impacting behavior regarding green consumption in China. Moreover, the moderating impact of policy incentives, perceived cost, and face culture is also explored. An internet-based survey was undertaken and findings indicate that environmental awareness serves as foundation for eco-friendly consumption. The transition from awareness to action is influenced by various factors. Among these, the perceived cost by consumers represents a significant barrier to green consumption, while face culture has a significant impact in encouraging green consumption. Interestingly, policy incentives do not exhibit any notable direct effect or moderating influence on green consumption practices of consumers.

The effects of economic development on natural environment is explored by momentous literature, this study focuses on exploring the role of institutional quality for environmental protection in the selected One Belt One Road (OBOR) economies. The main goal of the paper is to find the threshold level of institutional quality that may minimize CO 2 emissions in the atmosphere due to widespread industrialization and transportation. The data is selected for the panel of 33 OBOR economies over the time period of 1986–2018. The panel threshold regression technique is applied to determine the threshold level of institutional quality. The estimated results of the study reveal that 2.315 is the threshold level of institutional quality in selected partner OBOR countries. If quality of institutions is above the threshold level then CO 2 emission do not contribute significantly for environmental deterioration in spite of growing industrialization and transportation and vice versa. The study emphasized to improve the institutional quality up to threshold level to get potential gains from industrialization and transportation.

The importance of digital transformation (DGT) for increasing productivity cannot be negated and Chinese firms are rapidly embracing the digital transformation for their sustainability. But the mechanism and impact of digital transformation on total factor productivity (TFP) of firms is still unclear and this study is intended to fill this gap using the data of 3112 listed firms of China during 2011 to 2022. We applied various econometric techniques like stepwise regression analysis, instrumental variable approach, differences in difference approach, and mediating analysis to determine the relationship between digital transformation and TFP and robustness of estimated findings. The findings indicate that DGT has a positive impact on overall TFP of firms in China while operating efficiency, cheaper costs, and a stronger capacity for innovation mediates this relationship. Moreover, it is explored that conventional information and communication technologies have not significant impact on TFP of firms. The findings of the study remain valid even applying many robustness checks and attempts to control the issue of endogeneity. To fully leverage the potential benefits of digital transformation on TFP, it is essential to focus on enhancing digital literacy and skills among the workforce. Governments and relevant stakeholders should prioritize and invest in comprehensive digital literacy and skills training programs to empower the workforce with the knowledge and expertise needed to navigate the digital age effectively.

The Belt and Road Initiative (BRI) represents a substantial development strategy spearheaded by China. Its central aim is to foster connectivity across a vast geographical area that includes countries spanning Asia, Europe, and Africa. This project played a pivotal role to develop the region on the one side and also raised serious environmental concerns on the other side. There is extensive literature explored the various dimensions affecting the environment in BRI partner countries but there is hardly any study examining the impact of productive capacities, energy poverty, FDI, urbanization, and institutional quality on CO2 emission in the BRI region. Moreover, pollution halo impact is also explored so this study used panel data of 52 nations engaged in the BRI covering time span of 2001–2022 by applying OLS, Difference GMM, System GMM, Cross sectional-ARDL techniques. The results suggest that enhancing productive capacities, FDI and institutional quality significantly reduces carbon emissions in the region, while energy poverty, urbanization and economic growth is linked to higher carbon emissions. Moreover, ‘pollution halo effect’ is proved because of adoption of eco-friendly technologies through foreign corporations lead to reduction in carbon emission. The study advocates for policy measures that emphasize the promotion of productive capacities, the utilization of renewable energy sources, the adoption of practices regarding sustainable urban development, the implementation of efficient institutional structure, and inflow of eco-friendly technology through FDI.

China is in a phase of high-quality development, where scientific and technological innovations are serving as the primary driving force for its development strategy. This emphasis on innovations is expected to fuel the upgrading of the industrial structure. This study investigates the role of scientific and technological innovations in industrial upgradation in China using spatial econometric analysis. Leveraging the data of 31 provinces of China from 2005 to 2022, we employed a spatial Durbin model to determine the spatial spillover effects of scientific and technological innovations on industrial upgradation. Our findings reveal the significant positive spatial spillover effects, indicating that provinces with higher levels of scientific and technological innovations tend to experience greater industrial upgradation, which in turn contributes to regional economic development. Furthermore, the findings suggest a strong spatial correlation between innovation and the upgrading of industrial structures, indicating that regional innovations have the potential to drive China’s industrial upgradation. These results underscore the critical role of scientific and technological innovations in promoting industrial upgradation and regional development in China.