The study’s aim is to investigate how FinTech users’ perceived risk influences their continuance intention to use FinTech services. The new model, which was based on the Expectation Confirmation Model, was created to achieve the study’s aim. The Partial Least Square Structural Equation Model was used to investigate the proposed model and the relationship between the adopted constructs. The sample consists of 802 individual survey responses from northern India from April to June 2022. The proposed model explains 45.4% of the variance in the continuance intention of FinTech users, which is significantly influenced by perceived usefulness and satisfaction. Furthermore, perceived risk, as a moderator, significantly moderates continuance intention through satisfaction and satisfaction through confirmation. However, perceived risk was found to have an insignificant moderating effect on the relationship between perceived usefulness and satisfaction as well as perceived usefulness and continuance intention. The findings provide insights to FinTech service providers about the factors that influence users’ intent to continue using FinTech services.

Amidst rapid computerized progression, the universal economy faces three significant encounters: environmental variation, energy restraints, and financial crises. The pursuit of pecuniary progress often comes at the disbursement of environmental degradation. Green finance is a promising solution to strike a harmonious balance between the economy and nature. This chapter delves into a comprehensive exploration of existing literature on green finance while shedding light on the future potential of green finance in India. By promoting and investing in environmentally conscious projects, green finance is key to fostering sustainable development while addressing pressing ecological concerns. It is a beacon of hope, guiding the path toward a greener and more resilient global economy.

Rapid change in social, economic, and ecological environment bringing persistent challenges in every nation. The demand of knowledge, skills, education is changing drastically and coping with such changes is the big problem for every economy. From the time when SDG have emphasized more on vocational training program for sustainable growth, nations initiated to focus on vocational training programs and constantly updating training accordance with the changes as vocational training playing a significant role in manpower development and sustainable quality education. It is well known fact that efforts will be productive if the efforts are effective in nature. Government bodies, institutions are putting tremendous efforts towards making vocational training effective, but results are still questionable. With raising importance of vocational training worldwide, this is the original empirical study to examines the effectiveness of vocational training and explore its relationship with employment outcomes and quality education. Therefore, the aim of the paper is to identify those critical factors who can contribute to make training more effective. Secondly, paper is not also examining the role and contribution of effective vocational training in employment outcomes but also identifying the relation between quality education and employment outcome. The study collected data from 513 trainees and 25 training centre managers through self-administered questionnaire. Various tools like factor analysis, descriptive analysis, structured equations modelling, and analysis of variance was applied to analyse the data. The result uncovered four major factors: Trainee’s characteristics, Environment support, Training atmosphere and Interaction process among parties which can enhance the effectiveness of vocational training. Furthermore, result also stated that there is a positive relationship between effective vocational training and employment outcomes and positive relationship between quality education and employment outcomes.

Algo trading is the manifested form of artificial intelligence. Algo trading, also called algorithmic trading, is used in financial markets to place orders Algo trading is the manifested form of artificial intelligence. Algo trading, also called algorithmic trading, is used in financial markets to place orders