<div>Through connectivity with the electric grid, electric vehicles (EVs) minimize or eliminate the need for fossil fuels. Despite the rapid adoption of EVs in recent times, most government adoption objectives have not been attained. This article aims to comprehend the reasons behind the limited uptake of electric scooters in India and the driving aspects. This research used a grounded theory methodology. Using a snowball sampling technique, we conducted 25 in-depth interviews with EV owners, mainly based in Delhi and Mumbai. As an outcome of the study, four drivers and four impediments to the adoption of EVs have been formulated. The study shows that there are Financial, Technological, Operational, and Psychological drivers and Technological/Infrastructural, Operational, and Psychological impediments to the adoption. The study identifies the key concern areas in the form of categories of drivers and impediments, which can be considered in industrial and public policymaking. This research broadens our understanding of India’s uptake of EVs and provides key insights to organizations and policymakers regarding EV adoption in India.</div>

Providing quality customer service is one of the crucial matters of concern for any organization as it ensures the best customer satisfaction levels. Organizations all around the globe are widely using newly evolving technologies like artificial intelligence (AI) and machine learning applications to provide the best customer experience. The banking and financial services industry is on the front line to adopt AI-driven technologies in various departments worldwide. However, the adoption rate of these technologies is low in India in comparison with developed economies. In this article, we discussed the significance of various factors (customer satisfaction, AI knowledge among employees, and third-party tie-ups) on implementing the AI-driven technologies from employees’ perspectives at various levels of the organization. We analysed the usefulness of these newly evolving technologies to increase customer satisfaction and studied the role of crucial factors like data security issues and third-party tie-ups on AI technology implementation. The study is based on the primary data collected from 97 employees working in the Indian banking and financial sector across various metro cities of India (Hyderabad, Mumbai, Delhi) in various departments. We identified and analysed various factors that could impact the implementation of the AI-driven technologies at various departments, and we used logistic regression to investigate their significance. Chi-square test was used to check the associations between different factors. The study identifies and examines three key factors—customer satisfaction, AI knowledge among employees, and third-party tie-ups—that could impact AI-driven technologies implementation. According to this study, AI technology considerably decreases the cost and improves the customer experience of services. However, despite of many advantages the adoption rate of AI technology in the Indian banking and financial sector found extremely low. The implications of this study can be extended to the organizations for 360 degrees comprehensive understanding about the AI implementation and repercussions as there is a limited study about this topic from the bottom of the organizational verticals. This analysis is purely based on survey responses received from banking and financial sector employees across various metro cities of India (Hyderabad, Mumbai and Delhi).

No abstract

The manufacturing industry is poised to undergo a paradigm shift with the advent of the Fourth Industrial Revolution, popularly known as ‘Industry 4.0’, which will integrate the physical and digital worlds. As a widely acknowledged phrase among research institutions and universities, the ‘Industry 4.0’ paradigm has attracted significant interest from the academic, business and scientific communities. Even though the concept is not new and has been at the forefront of scholarly research for many years with many interpretations, the ‘Industry 4.0’ concept has just recently been introduced. It is widely accepted not only in the research field but also in the manufacturing ecosystems. However, there is a need to comprehend industry-specific research advancements, trends and gaps due to the diverse applications of different technologies. This article systematically reviews and comprehensively evaluates the research on different Industry 4.0 efforts and their applicability in the textile and manufacturing industries. This article aims to map the current Industry 4.0 literature in the textile and apparel industry to analyse and categorize existing research and identify research gaps. We utilized the PRISMA framework to conduct a systematic review of the literature and 34 research publications on Industry 4.0 in the textile and apparel industry were located using a well-organized keyword search of the Web of Science and Scopus databases. The findings indicate that, of all Industry 4.0 technologies, the internet of things (IoT) and RFID applications are the most extensively investigated in the textile and manufacturing industries. Despite the extensive applications of additive manufacturing (AM)/3D printing and augmented reality (AR), research in both fields is still in its infancy. The study revealed that Germany is the country that has published the most literature on Industry 4.0 projects in the textile and apparel industries. We urge that future academics focus on determining the relevance of Industry 4.0 initiatives to small and medium-sized enterprises (SMEs) as the textile and apparel industry is dominated by SMEs in many developing countries.

No abstract