{"title":"More trust or more risk? User acceptance of artificial intelligence virtual assistant","authors":"Yiwei Xiong, Yan Shi, Quanlin Pu, Na Liu","doi":"10.1002/hfm.21020","DOIUrl":null,"url":null,"abstract":"<p>Artificial intelligence (AI) virtual assistants are rapidly growing, permeating people's daily lives and work. However, some trust and risk issues prevent the acceptance and use of AI virtual assistants by users. Thus, understanding the roles of trust and perceived risk in user acceptance of AI virtual assistants is crucial. This study develops a comprehensive research model based on unified theory of acceptance and use of technology (UTAUT) to explain user acceptance of AI virtual assistants. This model extends UTAUT by adding users' perception of trust and risk. The research model and hypotheses are validated through structural equation modeling with a sample of 926 AI virtual assistant users. Results show that gender is significantly related to behavioral intention to use, education is positively related to trust and behavioral intention to use, and usage experience is positively related to attitude toward using. UTAUT variables, including performance expectancy, effort expectancy, social influence, and facilitating conditions, are positively related to behavioral intention to use AI virtual assistant. Trust and perceived risk respectively have positive and negative effects on attitude toward using and behavioral intention to use AI virtual assistants. Trust and perceived risk play equally important roles in explaining user acceptance of AI virtual assistants. Theoretical and practical implications of the current AI virtual assistant acceptance model and directions for future research are discussed.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Factors and Ergonomics in Manufacturing & Service Industries","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hfm.21020","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) virtual assistants are rapidly growing, permeating people's daily lives and work. However, some trust and risk issues prevent the acceptance and use of AI virtual assistants by users. Thus, understanding the roles of trust and perceived risk in user acceptance of AI virtual assistants is crucial. This study develops a comprehensive research model based on unified theory of acceptance and use of technology (UTAUT) to explain user acceptance of AI virtual assistants. This model extends UTAUT by adding users' perception of trust and risk. The research model and hypotheses are validated through structural equation modeling with a sample of 926 AI virtual assistant users. Results show that gender is significantly related to behavioral intention to use, education is positively related to trust and behavioral intention to use, and usage experience is positively related to attitude toward using. UTAUT variables, including performance expectancy, effort expectancy, social influence, and facilitating conditions, are positively related to behavioral intention to use AI virtual assistant. Trust and perceived risk respectively have positive and negative effects on attitude toward using and behavioral intention to use AI virtual assistants. Trust and perceived risk play equally important roles in explaining user acceptance of AI virtual assistants. Theoretical and practical implications of the current AI virtual assistant acceptance model and directions for future research are discussed.
期刊介绍：
The purpose of Human Factors and Ergonomics in Manufacturing & Service Industries is to facilitate discovery, integration, and application of scientific knowledge about human aspects of manufacturing, and to provide a forum for worldwide dissemination of such knowledge for its application and benefit to manufacturing industries. The journal covers a broad spectrum of ergonomics and human factors issues with a focus on the design, operation and management of contemporary manufacturing systems, both in the shop floor and office environments, in the quest for manufacturing agility, i.e. enhancement and integration of human skills with hardware performance for improved market competitiveness, management of change, product and process quality, and human-system reliability. The inter- and cross-disciplinary nature of the journal allows for a wide scope of issues relevant to manufacturing system design and engineering, human resource management, social, organizational, safety, and health issues. Examples of specific subject areas of interest include: implementation of advanced manufacturing technology, human aspects of computer-aided design and engineering, work design, compensation and appraisal, selection training and education, labor-management relations, agile manufacturing and virtual companies, human factors in total quality management, prevention of work-related musculoskeletal disorders, ergonomics of workplace, equipment and tool design, ergonomics programs, guides and standards for industry, automation safety and robot systems, human skills development and knowledge enhancing technologies, reliability, and safety and worker health issues.
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