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' p...

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Main Authors: Bouteraa, Mohamed, Chekima, Brahim, Thurasamy, Ramayah, Bin-Nashwan, Saeed Awadh, Al-Daihani, Meshari, Baddou, Abderrahmane, Sadallah, Mouad, Ansar, Rudy
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Published: Elsevier 2024
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Online Access:http://eprints.um.edu.my/44775/
https://doi.org/10.1016/j.joitmc.2024.100216
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spelling my.um.eprints.447752024-11-15T08:29:31Z http://eprints.um.edu.my/44775/ Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers' Willingness to Embrace Open-AI ChatGPT Bouteraa, Mohamed Chekima, Brahim Thurasamy, Ramayah Bin-Nashwan, Saeed Awadh Al-Daihani, Meshari Baddou, Abderrahmane Sadallah, Mouad Ansar, Rudy HG Finance T Technology (General) 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. © 2024 The Authors Elsevier 2024 Article PeerReviewed Bouteraa, Mohamed and Chekima, Brahim and Thurasamy, Ramayah and Bin-Nashwan, Saeed Awadh and Al-Daihani, Meshari and Baddou, Abderrahmane and Sadallah, Mouad and Ansar, Rudy (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 (1). p. 100216. ISSN 2199-8531, DOI https://doi.org/10.1016/j.joitmc.2024.100216 <https://doi.org/10.1016/j.joitmc.2024.100216>. https://doi.org/10.1016/j.joitmc.2024.100216 10.1016/j.joitmc.2024.100216
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic HG Finance
T Technology (General)
spellingShingle HG Finance
T Technology (General)
Bouteraa, Mohamed
Chekima, Brahim
Thurasamy, Ramayah
Bin-Nashwan, Saeed Awadh
Al-Daihani, Meshari
Baddou, Abderrahmane
Sadallah, Mouad
Ansar, Rudy
Open Innovation in the Financial Sector: A Mixed-Methods Approach to Assess Bankers' Willingness to Embrace Open-AI ChatGPT
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. © 2024 The Authors
format Article
author Bouteraa, Mohamed
Chekima, Brahim
Thurasamy, Ramayah
Bin-Nashwan, Saeed Awadh
Al-Daihani, Meshari
Baddou, Abderrahmane
Sadallah, Mouad
Ansar, Rudy
author_facet Bouteraa, Mohamed
Chekima, Brahim
Thurasamy, Ramayah
Bin-Nashwan, Saeed Awadh
Al-Daihani, Meshari
Baddou, Abderrahmane
Sadallah, Mouad
Ansar, Rudy
author_sort Bouteraa, Mohamed
title 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_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_sort open innovation in the financial sector: a mixed-methods approach to assess bankers' willingness to embrace open-ai chatgpt
publisher Elsevier
publishDate 2024
url http://eprints.um.edu.my/44775/
https://doi.org/10.1016/j.joitmc.2024.100216
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