Mousa Al-Kfairy , Dheya Mustafa , Ahmed Al-Adaileh , Samah Zriqat , Obsa Sendaba
{"title":"约旦电信业用户对人工智能语音助手的接受程度","authors":"Mousa Al-Kfairy , Dheya Mustafa , Ahmed Al-Adaileh , Samah Zriqat , Obsa Sendaba","doi":"10.1016/j.chbr.2024.100521","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose:</h3><div>This study aims to understand factors influencing consumer acceptance of artificial intelligence (AI) voice assistants used in customer support within telecom companies in Jordan.</div></div><div><h3>Methodology:</h3><div>A survey was conducted involving 248 individuals who have experience with telecom support services. To evaluate consumer acceptance, the study incorporates the Unified Theory of Acceptance and Use of Technology (UTAUT) framework and extends it with attributes specific to AI, such as Perceived Reliability, Voice Quality, and Quality of Information. Advanced statistical methods, including structural equation modeling with SPSS AMOS 28 and SmartPLS, were utilized to analyze the collected data.</div></div><div><h3>Findings:</h3><div>The results revealed that Perceived Reliability and Quality of Information were significant predictors of AI voice assistant adoption in the telecom sector, while traditional factors such as Perceived Usefulness and Trust showed no significant impact. These findings suggest that performance-related elements play a more crucial role in user acceptance of AI in this context compared to earlier technological acceptance models.</div></div><div><h3>Implications:</h3><div>The study offers an expansion to traditional technology acceptance models by highlighting the importance of AI-specific attributes over conventional factors like Perceived Usefulness and Trust. For telecom operators in developing markets, this research provides guidance on enhancing customer engagement with AI voice assistants. It suggests focusing on improving the reliability and quality of information provided by AI systems to boost user acceptance.</div></div><div><h3>Originality/value:</h3><div>The study provides valuable insights into the changing dynamics of consumer acceptance of AI in customer support, emphasizing a shift toward performance-based criteria. Telecom companies in Jordan can use these findings to inform their AI adoption strategies and enhance customer satisfaction.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100521"},"PeriodicalIF":4.9000,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"User acceptance of AI voice assistants in Jordan’s telecom industry\",\"authors\":\"Mousa Al-Kfairy , Dheya Mustafa , Ahmed Al-Adaileh , Samah Zriqat , Obsa Sendaba\",\"doi\":\"10.1016/j.chbr.2024.100521\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose:</h3><div>This study aims to understand factors influencing consumer acceptance of artificial intelligence (AI) voice assistants used in customer support within telecom companies in Jordan.</div></div><div><h3>Methodology:</h3><div>A survey was conducted involving 248 individuals who have experience with telecom support services. To evaluate consumer acceptance, the study incorporates the Unified Theory of Acceptance and Use of Technology (UTAUT) framework and extends it with attributes specific to AI, such as Perceived Reliability, Voice Quality, and Quality of Information. Advanced statistical methods, including structural equation modeling with SPSS AMOS 28 and SmartPLS, were utilized to analyze the collected data.</div></div><div><h3>Findings:</h3><div>The results revealed that Perceived Reliability and Quality of Information were significant predictors of AI voice assistant adoption in the telecom sector, while traditional factors such as Perceived Usefulness and Trust showed no significant impact. These findings suggest that performance-related elements play a more crucial role in user acceptance of AI in this context compared to earlier technological acceptance models.</div></div><div><h3>Implications:</h3><div>The study offers an expansion to traditional technology acceptance models by highlighting the importance of AI-specific attributes over conventional factors like Perceived Usefulness and Trust. For telecom operators in developing markets, this research provides guidance on enhancing customer engagement with AI voice assistants. It suggests focusing on improving the reliability and quality of information provided by AI systems to boost user acceptance.</div></div><div><h3>Originality/value:</h3><div>The study provides valuable insights into the changing dynamics of consumer acceptance of AI in customer support, emphasizing a shift toward performance-based criteria. Telecom companies in Jordan can use these findings to inform their AI adoption strategies and enhance customer satisfaction.</div></div>\",\"PeriodicalId\":72681,\"journal\":{\"name\":\"Computers in human behavior reports\",\"volume\":\"16 \",\"pages\":\"Article 100521\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in human behavior reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2451958824001544\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in human behavior reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451958824001544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
User acceptance of AI voice assistants in Jordan’s telecom industry
Purpose:
This study aims to understand factors influencing consumer acceptance of artificial intelligence (AI) voice assistants used in customer support within telecom companies in Jordan.
Methodology:
A survey was conducted involving 248 individuals who have experience with telecom support services. To evaluate consumer acceptance, the study incorporates the Unified Theory of Acceptance and Use of Technology (UTAUT) framework and extends it with attributes specific to AI, such as Perceived Reliability, Voice Quality, and Quality of Information. Advanced statistical methods, including structural equation modeling with SPSS AMOS 28 and SmartPLS, were utilized to analyze the collected data.
Findings:
The results revealed that Perceived Reliability and Quality of Information were significant predictors of AI voice assistant adoption in the telecom sector, while traditional factors such as Perceived Usefulness and Trust showed no significant impact. These findings suggest that performance-related elements play a more crucial role in user acceptance of AI in this context compared to earlier technological acceptance models.
Implications:
The study offers an expansion to traditional technology acceptance models by highlighting the importance of AI-specific attributes over conventional factors like Perceived Usefulness and Trust. For telecom operators in developing markets, this research provides guidance on enhancing customer engagement with AI voice assistants. It suggests focusing on improving the reliability and quality of information provided by AI systems to boost user acceptance.
Originality/value:
The study provides valuable insights into the changing dynamics of consumer acceptance of AI in customer support, emphasizing a shift toward performance-based criteria. Telecom companies in Jordan can use these findings to inform their AI adoption strategies and enhance customer satisfaction.