The effect of Arabic language type on banking chatbots adoption

Abstract

Recently many banks around the world are adopting chatbots to communicate with their customers. However, the success of banking chatbots relay on customer adoption of this new technology. Although chatbots use in the banking sector is expanding globally, the Arabic world is still behind in using the technology, and chatbot applications in the Arab world are still immature. One reason behind this lag is the complexity of the Arabic language. This study comes to bridge the gap in the literature regarding what technology aspects affect customer adoption of bank chatbots in the Arabic world, and which type of Arabic language is the most effective in communicating with Arabic language speakers. UTAUT2 was used to figure what factors afect customer adoption. The data for this study was collected from two separate groups, with a total of 429 participants. Results showed that there is a significant difference between the model testing Arabic Fusha and Dialect Fusha. Results showed that Effort expectancy influences adoption only when dialect Arabic is used. Performance expectancy was also found to have no effect on the adoption of bank chatbot in both groups.

Keywords

• UTAUT2
• Chatbot
• Arabic language
• AI
• Banking