Praveen Srivastava, Niraj Mishra, S. Srivastava, Shradha Shivani
{"title":"使用聊天机器人办理银行业务:人口统计学和个性特征的作用","authors":"Praveen Srivastava, Niraj Mishra, S. Srivastava, Shradha Shivani","doi":"10.1177/23197145241227757","DOIUrl":null,"url":null,"abstract":"This research seeks to investigate the influence of performance expectancy, effort expectancy, facilitating conditions, habit and hedonic motivation on behavioural intention in the context of chatbot utilization within the banking industry. Additionally, the study explores the moderation effects of age, gender and personality type on the relationships between behavioural intention and use behaviour. The study employs a quantitative survey of banking customers, and the data have been analysed using partial least squares structural equation modelling and artificial neural network. The findings suggest that the use and acceptance of chatbots in banking are influenced by a range of factors, including performance expectancy, facilitating conditions and hedonic motivation. The study also reveals that only personality types can moderate the relationship between behavioural intentions and use behaviour. The study provides insights for banks and other financial institutions that are considering the implementation of chatbots as part of their customer service strategy.","PeriodicalId":53215,"journal":{"name":"FIIB Business Review","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Banking with Chatbots: The Role of Demographic and Personality Traits\",\"authors\":\"Praveen Srivastava, Niraj Mishra, S. Srivastava, Shradha Shivani\",\"doi\":\"10.1177/23197145241227757\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research seeks to investigate the influence of performance expectancy, effort expectancy, facilitating conditions, habit and hedonic motivation on behavioural intention in the context of chatbot utilization within the banking industry. Additionally, the study explores the moderation effects of age, gender and personality type on the relationships between behavioural intention and use behaviour. The study employs a quantitative survey of banking customers, and the data have been analysed using partial least squares structural equation modelling and artificial neural network. The findings suggest that the use and acceptance of chatbots in banking are influenced by a range of factors, including performance expectancy, facilitating conditions and hedonic motivation. The study also reveals that only personality types can moderate the relationship between behavioural intentions and use behaviour. The study provides insights for banks and other financial institutions that are considering the implementation of chatbots as part of their customer service strategy.\",\"PeriodicalId\":53215,\"journal\":{\"name\":\"FIIB Business Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-02-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"FIIB Business Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/23197145241227757\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"FIIB Business Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/23197145241227757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS","Score":null,"Total":0}
Banking with Chatbots: The Role of Demographic and Personality Traits
This research seeks to investigate the influence of performance expectancy, effort expectancy, facilitating conditions, habit and hedonic motivation on behavioural intention in the context of chatbot utilization within the banking industry. Additionally, the study explores the moderation effects of age, gender and personality type on the relationships between behavioural intention and use behaviour. The study employs a quantitative survey of banking customers, and the data have been analysed using partial least squares structural equation modelling and artificial neural network. The findings suggest that the use and acceptance of chatbots in banking are influenced by a range of factors, including performance expectancy, facilitating conditions and hedonic motivation. The study also reveals that only personality types can moderate the relationship between behavioural intentions and use behaviour. The study provides insights for banks and other financial institutions that are considering the implementation of chatbots as part of their customer service strategy.