{"title":"Determinants and consequences of trust in AI-based customer service chatbots","authors":"A. V. Prakash, Arun Joshi, Shubhi Nim, Saini Das","doi":"10.1080/02642069.2023.2166493","DOIUrl":null,"url":null,"abstract":"ABSTRACT According to industry reports, artificial intelligence-based chatbots could transform online customer service. Though businesses are increasingly implementing chatbots to automate customer service, the lack of consumer trust and acceptance continues to cause worry. Although trust is critical to acceptance, research on the drivers and consequences of trust in AI-based chatbots is limited. Hence a study was conducted to identify the antecedents of consumers’ trust in text-based customer service chatbots and examine the influence of trust on behavioral intentions. The data collected from 221 users was analyzed using the structural equations modeling method. Results reveal that conversational cues influence the perceived functional and social attributes of the chatbot, and these, along with personal disposition to trust technology, further influence trust formation. Finally, trust determines behavioral intentions. Incidentally, privacy risk turned out to be a non-significant predictor of trust. The study provides measures to improve trust and suggests directions for future research.","PeriodicalId":22929,"journal":{"name":"The Service Industries Journal","volume":"95 1","pages":"642 - 675"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Service Industries Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/02642069.2023.2166493","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
ABSTRACT According to industry reports, artificial intelligence-based chatbots could transform online customer service. Though businesses are increasingly implementing chatbots to automate customer service, the lack of consumer trust and acceptance continues to cause worry. Although trust is critical to acceptance, research on the drivers and consequences of trust in AI-based chatbots is limited. Hence a study was conducted to identify the antecedents of consumers’ trust in text-based customer service chatbots and examine the influence of trust on behavioral intentions. The data collected from 221 users was analyzed using the structural equations modeling method. Results reveal that conversational cues influence the perceived functional and social attributes of the chatbot, and these, along with personal disposition to trust technology, further influence trust formation. Finally, trust determines behavioral intentions. Incidentally, privacy risk turned out to be a non-significant predictor of trust. The study provides measures to improve trust and suggests directions for future research.