Although numerous works have been done on shopping behaviour in

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 potential of blockchain technology (BCT) to modify and innovates established business structures and frameworks has received widespread attention. Academia and businesses are becoming increasingly curious about how this technology could be used to improve and refine consumer services and operations. Despite the growing popularity of blockchain research in consumer services, there remains a dearth of detailed summaries in the literature. Hence, this bibliometric analysis, combined with a systematic literature review (SLR) using SPAR‐4‐SLR protocol with the theories, characteristics, contexts, and methods framework (A hybrid review), aims to convey qualitative and quantitative knowledge on the ever‐evolving subject of blockchain application in consumer services in an organized manner. Specifically, this article analyses: (1) the current publication trends in studies devoted to blockchain‐based applications for consumers, (2) the most important publications and themes of research in this field, (3) the evolution of blockchain in consumer service over the years, and the most current trends in this field, (4) the advantages and challenges of incorporating BCT into consumer services, (5) gaps in the existing literature that future researchers should investigate. In addition, this review also describes the widely used theories, characteristics, and methods in the application of blockchain in consumer service research by examining the most applied theories, methods, constructs, and study contexts and paving the way for new research directions. The review includes 417 documents after searching for scholarly publications in two databases (Web of Science and Scopus) and choosing documents based on their relevance to the stated goals.