ArticleHeliyon2023
The effect of Arabic language type on banking chatbots adoption.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.