Customer experience in AI-enabled products: Scale development and validation

Ping Wang, Kunyang Li, Qinglong Du and Jianqiong Wang

Journal of Retailing and Consumer Services, 2024, vol. 76, issue C

Abstract: Artificial Intelligence (AI) is an enabling technology that can be integrated into products to provide emerging capabilities and craft novel customer experience (CX); many companies have widely adopted AI-enabled products to provide customers with service interactions. However, meager researchers have studied CX in AI-enabled products. Utilizing qualitative and quantitative methods, this study developed a scale of CX in AI-enabled products using Churchill's (1979) scale development framework. The scale underwent several stages of development including item generation, scale purification, scale validation, cross-testing, and nomological validity testing. Finally, five dimensions were identified to represent CX in AI-enabled products, such as data capture experience, classification experience, delegation experience, social experience, and anthropomorphic experience. Based on assemblage theory, the study develops the scale from the perspective of integrating human-centric and object-oriented anthropomorphic metaphors. Establishment of this scale extends traditional CX research, expands emerging CX research, and presents the first operationalized definition of the CX in AI-enabled products. The development of this scale provides a framework for marketers to enhance the CX in emerging consumer environments.

Keywords: Artificial intelligence; Assemblage theory; Customer experience; AI-enabled products; Scale development (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:joreco:v:76:y:2024:i:c:s0969698923003296

DOI: 10.1016/j.jretconser.2023.103578

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