Customers are displaying heightened awareness and involvement in their banking arrangements, and they are actively assessing and remembering information to make informed decisions regarding the allocation of their financial resources towards environmental protection solutions such as clean energy, sustainable construction, climate change control and social protection. Based on the current theoretical gap of factors influencing customer satisfaction and thereby encouraging continued engagement in green finance initiatives, this study aims to identify the factors influencing customer satisfaction as a means of fostering greater participation in green finance amongst customers of commercial banks in Ho Chi Minh City. Using data from a survey of 479 individuals who are customers at commercial banks in Ho Chi Minh City, this study analyses and evaluates the impact of factors influencing customer satisfaction and the role of customer satisfaction in green finance continuance behaviour. Combining basic analysis techniques in quantitative research such as statistics, evaluation of Cronbach’s alpha reliability, exploratory factor analysis (EFA), measurement models and Partial Least Squares structural equation modelling (PLS-SEM) from SPSS and SMART PLS software. the results of this research indicate that: (1) Green Banking initiative (GB), Information Support (IS) and Emotional Support (ES) positively impact Customer Satisfaction (SA); (2) Customer Satisfaction (SA) positively impacts Green Finance Continuance Behaviour (GF).

The present research is on the propagation of Rayleigh waves in a homogenous thermoelastic solid half-space by considering the compact form of six different theories of thermoelasticity. The medium is subjected to an insulated boundary surface that is free from normal stress, tangential stress, and a temperature gradient normal to the surface. After developing a mathematical model, a dispersion equation is obtained with irrational terms. To apply the algebraic method, this equation must be converted into a rational polynomial equation. From this, only those roots are filtered out, which has satisfied both of the above equations for the propagation of waves decaying with depth. With the help of these roots, different characteristics are computed numerically, like phase velocity, attenuation coefficient, and path of particles. Various particular cases are compared graphically by using phase velocity and attenuation coefficient. The elliptic path of surface particles in Rayleigh wave propagation is also presented for the different theories using physical constants of copper material for different depths and thermal conductivity.

Smart electric meters play a pivotal role in making energy systems decarbonized and automating the energy system. Smart electric meters denote huge business opportunities for both public and private companies. Utility players can manage the electricity demand more efficiently whereas customers can monitor and control the electricity bill through the adoption of smart electric meters. The study examines the factors affecting the adoption intention of smart electric meters in Indian households. This study draws a roadmap that how utility providers and customers can improve the smart electric meters adoption. The study has five independent variables (performance expectancy, effort expectancy, social influence, environmentalism, and hedonic motivation) and one dependent variable (adoption intention). The sample size for the study is four hundred and sixty-two respondents from Delhi and the National Capital Region (NCR). The data was analysed using structural equation modelling (SEM). The results of this study have confirmed that performance expectancy, environmentalism, and social influence have a significant impact on the intention of adopting smart electric meters. Therefore, utility providers can improve their strategies to attract more customers to adopt smart electric meters by focusing more on the performance of smart electric meters and by making them environmentally friendly. This research offers meaningful insights to both customers and utility providers to make energy systems decarbonized and control energy consumption.

Urbanization and suburbanization have led to high population growth in certain city regions, resulting in increased population density and mobility. Therefore, there is a need for a concept to address congestion, public transportation, information and communication systems, and non-motorized vehicles. Smart mobility is a concept of urban development as part of the smart city concept based on information and communication technology. Through this concept, it is expected that transportation services will be easily accessible, safe, comfortable, fast, and affordable for the community. This research aims to analyze smart mobility and its relationship with regional transportation planning and the development of South Tangerang, as well as to design a policy strategy model for the planning and development of South Tangerang with smart mobility. The research method used in this study is a mixed method, including analyzing the relationships and weighting of relationships between variables using the Cross Impact Multiplication applied to a classification (MICMAC) matrix. Multi-criteria decision analysis (MCDA) with Promethee software is also used to obtain the necessary policies. The results of this research indicate that the measurement of relationships between variables shows that smart mobility influences regional transportation planning, smart mobility affects regional development, and regional planning affects regional development. This research also provides alternative policies that policymakers should implement in a specific order. First, ensure the availability of public transportation; second, improve public transportation safety; third, enhance public transportation security; fourth, improve public transportation routes; fifth, provide real-time information access; sixth, improve transportation schedules; and seventh, increase the number of bicycle lanes.

This study aims to explore the asymmetric impact of renewable energy on the sectoral output of the Indian economy by analyzing the time series data from 1971 to 2019. The nonlinear autoregressive distributed lag approach (NARDL) is employed to examine the short- and long-run relationships between the variables. Most studies focus on economic growth, ignoring sectoral dynamics. The result shows that the sectoral output shows a differential dynamism with respect to the type of energy source. For instance, agricultural output responds positively to the positive shock in renewable energy, whereas industry and service output behave otherwise. Since the latter sectors depend heavily on non-renewable energy sources, they behave positively towards them. Especially, electricity produced from non-renewable energy sources significantly influences service sector output. However, growing evidence across the world is portraying the strong relationship between the growth of renewable energy sources and economic growth. However sectoral dynamism is crucial to frame specific policies. In this regard, the present paper’s result indicates that policies related to promoting renewable energy sources will significantly influence sectoral output in the long run in India.