Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers’ Willingness to Embrace Open-AI ChatGPT
As open innovation and Artificial Intelligence (AI) become more prevalent in financial institutions, early adoption of Chatbots will have a competitive advantage. However, ChatGPT is still less common in the financial sector than in other industries. This study attempts to understand bankers’ percep...
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| Format: | Article |
| Language: | English English |
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Elsevier B.V.
2024
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| Online Access: | https://eprints.ums.edu.my/id/eprint/38917/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/38917/2/FULL%20TEXT.pdf |
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| author | Mohamed Bouteraa Brahim Chekima Ramayah Thurasamy Saeed Awadh Bin-Nashwan Meshari Al-Daihani Abderrahmane Baddou Mouad Sadallah Rudy Ansar |
| author_facet | Mohamed Bouteraa Brahim Chekima Ramayah Thurasamy Saeed Awadh Bin-Nashwan Meshari Al-Daihani Abderrahmane Baddou Mouad Sadallah Rudy Ansar |
| author_sort | Mohamed Bouteraa |
| collection | UMS |
| description | As open innovation and Artificial Intelligence (AI) become more prevalent in financial institutions, early adoption of Chatbots will have a competitive advantage. However, ChatGPT is still less common in the financial sector than in other industries. This study attempts to understand bankers’ perceptions towards using ChatGPT. Towards this, the study employed an exploratory sequential mixed-methods approach. Eventually, 10 bank professionals participated in the preliminary semi-structured interviews to gain insight into their perceptions. Sequentially, the study cross-sectionally examined the identified factors among 368 bankers to triangulate the framework with empirical evidence. The Thematic Content Analysis (TCA) analysis identified seven new factors related to bankers’ use of ChatGPT, which were primarily validated in PLS-SEM assessments. The results showed the positive effect of performance expectancy, social influence, facilitating conditions, awareness, innovativeness, and system quality on ChatGPT usage and the negative effect of technology self-efficacy and IT features. Intriguingly, the moderating effects of central bank support were positively confirmed for innovativeness and social influence, but negative for the relationship between technology self-efficacy, awareness, and bankers’ intention. This study offers a highly predictive model contemplating the applicability of an extended UTAUT model to explain the use of ChatGPT in the banking sector. Accordingly, we suggest that decision-makers should emphasize improving the individual attributes of their human capital towards technology and improving AI system quality, as well as working closely with government-powered authorities that would facilitate the diffusion process of AI Chatbots in the banking sector. |
| first_indexed | 2024-09-24T00:49:42Z |
| format | Article |
| id | ums.eprints-38917 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-09-24T00:49:42Z |
| publishDate | 2024 |
| publisher | Elsevier B.V. |
| record_format | dspace |
| spelling | ums.eprints-389172024-06-26T04:05:14Z https://eprints.ums.edu.my/id/eprint/38917/ Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers’ Willingness to Embrace Open-AI ChatGPT Mohamed Bouteraa Brahim Chekima Ramayah Thurasamy Saeed Awadh Bin-Nashwan Meshari Al-Daihani Abderrahmane Baddou Mouad Sadallah Rudy Ansar HG1811-2351 Special classes of banks and financial institutions TK7800-8360 Electronics As open innovation and Artificial Intelligence (AI) become more prevalent in financial institutions, early adoption of Chatbots will have a competitive advantage. However, ChatGPT is still less common in the financial sector than in other industries. This study attempts to understand bankers’ perceptions towards using ChatGPT. Towards this, the study employed an exploratory sequential mixed-methods approach. Eventually, 10 bank professionals participated in the preliminary semi-structured interviews to gain insight into their perceptions. Sequentially, the study cross-sectionally examined the identified factors among 368 bankers to triangulate the framework with empirical evidence. The Thematic Content Analysis (TCA) analysis identified seven new factors related to bankers’ use of ChatGPT, which were primarily validated in PLS-SEM assessments. The results showed the positive effect of performance expectancy, social influence, facilitating conditions, awareness, innovativeness, and system quality on ChatGPT usage and the negative effect of technology self-efficacy and IT features. Intriguingly, the moderating effects of central bank support were positively confirmed for innovativeness and social influence, but negative for the relationship between technology self-efficacy, awareness, and bankers’ intention. This study offers a highly predictive model contemplating the applicability of an extended UTAUT model to explain the use of ChatGPT in the banking sector. Accordingly, we suggest that decision-makers should emphasize improving the individual attributes of their human capital towards technology and improving AI system quality, as well as working closely with government-powered authorities that would facilitate the diffusion process of AI Chatbots in the banking sector. Elsevier B.V. 2024 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/38917/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/38917/2/FULL%20TEXT.pdf Mohamed Bouteraa and Brahim Chekima and Ramayah Thurasamy and Saeed Awadh Bin-Nashwan and Meshari Al-Daihani and Abderrahmane Baddou and Mouad Sadallah and Rudy Ansar (2024) Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers’ Willingness to Embrace Open-AI ChatGPT. Journal of Open Innovation: Technology, Market, and Complexity, 10. pp. 1-13. ISSN 2199-8531 https://doi.org/10.1016/j.joitmc.2024.100216 |
| spellingShingle | HG1811-2351 Special classes of banks and financial institutions TK7800-8360 Electronics Mohamed Bouteraa Brahim Chekima Ramayah Thurasamy Saeed Awadh Bin-Nashwan Meshari Al-Daihani Abderrahmane Baddou Mouad Sadallah Rudy Ansar Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers’ Willingness to Embrace Open-AI ChatGPT |
| title | Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers’ Willingness to Embrace Open-AI ChatGPT |
| title_full | Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers’ Willingness to Embrace Open-AI ChatGPT |
| title_fullStr | Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers’ Willingness to Embrace Open-AI ChatGPT |
| title_full_unstemmed | Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers’ Willingness to Embrace Open-AI ChatGPT |
| title_short | Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers’ Willingness to Embrace Open-AI ChatGPT |
| title_sort | open innovation in the financial sector a mixed methods approach to assess bankers willingness to embrace open ai chatgpt |
| topic | HG1811-2351 Special classes of banks and financial institutions TK7800-8360 Electronics |
| url | https://eprints.ums.edu.my/id/eprint/38917/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/38917/2/FULL%20TEXT.pdf |
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