An investigation on the influencing factors of elderly people's intention to use financial AI customer service
Abstract
Purpose: With the great changes brought by information technology, there is also a challenge for the elderly's acceptance. This study aimed to determine the antecedents of elderly people's usage intention of financial artificial intelligent customer service (FAICS) and to examine the relationships between various factors and thus to help them better adapt to the digital age. Design/methodology/approach: A mixed method, including the qualitative and quantitative study, was utilized to explore answers of the research questions. As the qualitative study, the authors used semi-structured interviews and data coding to uncover the influencing factors. As the quantitative study, the authors collected data through questionnaires and tested hypotheses using structural equation modeling. Findings: The results of data analysis from interviews and questionnaires suggested that perceived anthropomorphism and virtual identity of elderly users have a positive impact on their perceived ease of use, and the perceived intelligence of elderly users positively influences their perceived ease of use, satisfaction and perceived usefulness. Additionally, the elderly's cognition age can moderate the effects of perceived usefulness and satisfaction on their usage intention of FAICS. Originality/value: This study contributes to the literature by taking the elderly group as the research participants and combining those influencing factors with technology acceptance model and information systems success model. The findings provide a basis for accelerating the promotion of FAICS and help address the problem that the elderly have difficulty adapting to a new technology.
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AI and DL can be used to personalize the customer experience by analyzing data on passenger preferences and behavior, and providing recommendations for entertainment, food, and other services.
“AI and DL can be used to personalize the customer experience by analyzing data on passenger preferences and behavior, and providing recommendations for entertainment, food, and other services [130] .”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [130]
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Artificial intelligence, machine learning and deep learning in advanced robotics, a review
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- Authors
- Cheng, X., Qiao, L., Yang, B., & Li, Z.
- Affiliations
- Renmin University of China (CN)
- University of International Business and Economics (CN)
- Venue
- Internet Research
- Publisher
- Emerald
- Published
- 2023-03-16
- Volume
- 34
- Issue
- 3
- Pages
- 690-717
- ISSN
- 1066-2243 (ISSN-L)
- OpenAlex
- W4324370621
- Cited by
- 76
- References
- 15
- Citations by year
- 2026: 22 · 2025: 37 · 2024: 14 · 2023: 3
- FWCI
- 15.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Internet Research (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Demography › Technology Use by Older Adults
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- elderly users, intention to use, technology acceptance, perceived anthropomorphism, virtual identity, perceived ease of use, perceived usefulness, user satisfaction, perceived intelligence, moderating effect, digital divide
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