The purpose of this research is to examine the impact of artificial intelligence(AI)on customer performance and identify the factors contributing to its effectiveness by employing a quantitative approach,specifically ...The purpose of this research is to examine the impact of artificial intelligence(AI)on customer performance and identify the factors contributing to its effectiveness by employing a quantitative approach,specifically the partial least squares method,to test the hypotheses and explore the relationships between various variables.The findings indicate that effective business practices and successful AI assimilation have a positive impact on customer performance.Additionally,the results of this study provide valuable insights for both academic and practical communities.This study highlights the importance of specific variables,such as organizational and customer agility,customer experience,customer relationship quality,and customer performance in AI assimilation.By exploring these variables,it contributes significantly to the academic,managerial,and social aspects of AI and its impact on customer performance.展开更多
Services may be investigated from many perspectives. They encapsulate over 65% of global business, yet many gaps in the services knowledge base exist – particularly from areas including information technology, oper...Services may be investigated from many perspectives. They encapsulate over 65% of global business, yet many gaps in the services knowledge base exist – particularly from areas including information technology, operational, customer targeting, and services provision. This research investigates an emerging and truly disruptive business scenario – the service value network, from a marketing, an operations and services approach. The service value network is defined as the flexible, dynamic, delivery of a service, or product, by a business’s coordinated value chains (supply chains and demand chains working in harmony), such that a value-adding, specific, service solution is effectively, and efficiently, delivered to the individual customer. The ‘physical and virtual service value network customer – business encounter model’ is developed. Impediments to the development of a service value networks are investigated. Eight key areas related to website customer encounters are offered as investigation areas. The customer ‘touch-points’ across the virtual service encounter offers a raft of new research possibilities and possible new pathways to competitive advantage. Approaches to measure service network encounter effectors are explained. Current and future areas of business research are described. This paper frames the research agenda for service value networks.展开更多
文摘The purpose of this research is to examine the impact of artificial intelligence(AI)on customer performance and identify the factors contributing to its effectiveness by employing a quantitative approach,specifically the partial least squares method,to test the hypotheses and explore the relationships between various variables.The findings indicate that effective business practices and successful AI assimilation have a positive impact on customer performance.Additionally,the results of this study provide valuable insights for both academic and practical communities.This study highlights the importance of specific variables,such as organizational and customer agility,customer experience,customer relationship quality,and customer performance in AI assimilation.By exploring these variables,it contributes significantly to the academic,managerial,and social aspects of AI and its impact on customer performance.
文摘Services may be investigated from many perspectives. They encapsulate over 65% of global business, yet many gaps in the services knowledge base exist – particularly from areas including information technology, operational, customer targeting, and services provision. This research investigates an emerging and truly disruptive business scenario – the service value network, from a marketing, an operations and services approach. The service value network is defined as the flexible, dynamic, delivery of a service, or product, by a business’s coordinated value chains (supply chains and demand chains working in harmony), such that a value-adding, specific, service solution is effectively, and efficiently, delivered to the individual customer. The ‘physical and virtual service value network customer – business encounter model’ is developed. Impediments to the development of a service value networks are investigated. Eight key areas related to website customer encounters are offered as investigation areas. The customer ‘touch-points’ across the virtual service encounter offers a raft of new research possibilities and possible new pathways to competitive advantage. Approaches to measure service network encounter effectors are explained. Current and future areas of business research are described. This paper frames the research agenda for service value networks.
