Bibliometric Analysis of Customer Ex-perience and Artificial Intelligence

Document Type : Research Paper

Authors

1 Ph.D Student, Department of Business Administration, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

2 Professor, Department of Business Administration, Tarbiat Modares University, Tehran, Iran,

3 Assistant Professor, Department of Business Administration, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

Abstract

Recent advancements in digital data collection, cloud computing, the Internet of Things, and machine learning have contributed to the emergence of artificial intelligence as a leading technology. AI significantly enhances customer experience through personalization, chatbots, virtual assistants, virtualization, and predictive analytics. The objective of this study is to analyze and elucidate the current state of scientific literature pertaining to customer experience and artificial intelligence. This research employs scientometric techniques to examine articles indexed in the Web of Science database from 2019 to 2023, aiming to identify prevalent research topics and uncover potential gaps in the literature.
Methodology: This research is descriptive and applied. A total of 203 articles authored by 588 researchers, published across 80 journals and extracted from the Web of Science database, were analyzed using the R bibliometric package. The statistical population comprises all English-language scientific publications related to customer experience and artificial intelligence, particularly those connected to business management, business, financial affairs, and data analysis. Data analysis was conducted using outputs generated by Biblioshiny software. The software used is Biblioshiny, a Java-based web application developed for conducting functional combination research using the bibliometric package within RStudio.
Findings: Scientific output in the fields of customer experience and artificial intelligence has shown an upward trend. The countries with the most publications are the United States, China, England, Australia, and India. Key terms include trust, technology acceptance, experience, word-of-mouth marketing, satisfaction, and technology. Popular and emerging topics include the adoption of information technology, personalized experiences, chatbots, and the analysis of customer sentiments across various industries such as tourism and healthcare. The utilization of artificial intelligence has transformed the customer experience since 2019. Specifically, machine learning predicts and analyzes customer sentiment through feedback and comments to enhance the experience, benefiting both customers and service providers. The United States has demonstrated a significant increase in the number of studies related to customer experience and AI, with 1,229 citations and 161 studies conducted in 2023. This represents a substantial rise from the 13 studies conducted in 2019. The keyword analysis of the article revealed a shift in focus from creativity and word-of-mouth to experience and artificial intelligence, highlighting their increasing importance. Topics such as influence and trust, which are closely related to technology adoption, remained popular in 2022 and 2023, particularly during and after the COVID-19 pandemic. The literature on customer experience and artificial intelligence can be broadly categorized into three primary themes. The first theme encompasses acceptance, information technology, and the technology acceptance model. The second theme covers topics such as tourism, hotels, and the leisure industry. Lastly, the third theme focuses on innovation, encompassing issues such as vision, consumer acceptance, and customer acquisition. Providing customers with positive experiences that consider their feelings and motivations is crucial, as customers prefer experiences that are both pleasant and appropriate. Prominent themes over the past year have included ethics, people, resistance to innovation, behavioral research, and information systems.
Conclusion: Iran has limited scientific productions and international collaborations in the fields of customer experience and artificial intelligence. The keywords experience, vision, influence, and trust are closely associated with technology adoption during the COVID-19 era. The results of the thematic map analysis have provided numerous insights for researchers in this area. The Technology Acceptance Model remains a prominent theme, continuing to attract significant research interest. In contrast, the theme of resistance to innovation has declined in importance and is receiving less attention. The main themes identified are technology and customer satisfaction. Additionally, analyzing customer sentiments through feedback comments is crucial for improving their experience. Employing artificial intelligence and customer personalization technologies enables businesses to provide a distinctive and engaging shopping experience, which in turn enhances customer satisfaction and loyalty. Research on customer experience and artificial intelligence has primarily focused on technology acceptance. Additionally, this area highlights factors influencing both acceptance and resistance to innovation, emphasizing the critical roles of trust and ethics. The impact of these technologies on human interactions and relationships is particularly evident in the healthcare sector. Within the literature on customer experience and artificial intelligence, the use of bots is recognized as a significant trend in service marketing; however, customer acceptance remains a significant barrier to their widespread adoption in service contexts. According to Mora's study, analyzing customers' emotions through feedback and comments is essential for improving their experience. Selecting an appropriate strategy based on emotional and perceptual analysis is crucial for technology acceptance, enabling brands to deliver a delightful experience through artificial intelligence.

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References

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