Adoption of AI-based chatbots for hospitality and tourism

International Journal of Contemporary Hospitality Management, Journal Year: 2020, Volume and Issue: 32(10), P. 3199 - 3226

Published: Sept. 10, 2020

Purpose This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality tourism in India by extending technology adoption model (TAM) with context-specific variables. Design/methodology/approach To understand AUE AI-powered tourism, mixed-method design was used whereby qualitative quantitative techniques were combined. A total 36 senior managers executives from travel agencies interviewed analysis interview data done using NVivo 8.0 software. 1,480 customers surveyed partial least squares structural equation modeling technique analysis. Findings As per results, predictors chatbot (AIN) are perceived ease use, usefulness, trust (PTR), (PNT) anthropomorphism (ANM). Technological anxiety (TXN) does not influence AIN. Stickiness traditional human agents negatively moderates relation AIN provides deeper insights into manager’s commitment providing planning services AI-based chatbots. Practical implications research presents unique practical practitioners, industry, system designers developers technologies antecedents travelers. TXN is a vital concern customers; so, should ensure that easily accessible, have user-friendly interface, be more human-like communicate various native languages customers. Originality/value contributes theoretically TAM provide better explanatory power human–robot interaction constructs – PTR, PNT, ANM examine first step direction empirically test validate theoretical chatbots’ usage, which disruptive sector an emerging economy such as India.

Language: Английский

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Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations

International Journal of Production Economics, Journal Year: 2019, Volume and Issue: 226, P. 107599 - 107599

Published: Dec. 24, 2019

Language: Английский

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The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions

International Journal of Information Management, Journal Year: 2020, Volume and Issue: 57, P. 102225 - 102225

Published: Sept. 14, 2020

Language: Английский

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What makes an AI device human-like? The role of interaction quality, empathy and perceived psychological anthropomorphic characteristics in the acceptance of artificial intelligence in the service industry

Computers in Human Behavior, Journal Year: 2021, Volume and Issue: 122, P. 106855 - 106855

Published: May 6, 2021

Language: Английский

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Artificial intelligence in information systems research: A systematic literature review and research agenda

International Journal of Information Management, Journal Year: 2021, Volume and Issue: 60, P. 102383 - 102383

Published: July 8, 2021

AI has received increased attention from the information systems (IS) research community in recent years. There is, however, a growing concern that on could experience lack of cumulative building knowledge, which overshadowed IS previously. This study addresses this concern, by conducting systematic literature review between 2005 and 2020. The search strategy resulted 1877 studies, 98 were identified as primary studies synthesise key themes are pertinent to is presented. In doing so, makes important contributions, namely (i) an identification current reported business value contributions AI, (ii) practical implications use (iii) opportunities for future form agenda.

Language: Английский

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Service robot implementation: a theoretical framework and research agenda

Service Industries Journal, Journal Year: 2019, Volume and Issue: 40(3-4), P. 203 - 225

Published: Oct. 3, 2019

Service robots and artificial intelligence promise to increase productivity reduce costs, prompting substantial growth in sales of service research dedicated understanding their implications. Nevertheless, marketing on this phenomenon is scarce. To establish some fundamental insights related domain, the current article seeks complement robots' human-likeness with investigations factors that managers must choose for implemented setting. A three-part framework, comprised robot design, customer features, encounter characteristics, specifies key within each category need be analyzed together determine optimal adaptation different components. Definitions overlapping concepts are clarified, previous knowledge variable gaps solved. This framework final questions provide a agenda guide scholars help practitioners implement successfully.

Language: Английский

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Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption

Journal of Business Research, Journal Year: 2020, Volume and Issue: 122, P. 180 - 191

Published: Sept. 14, 2020

Language: Английский

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Trustworthy Artificial Intelligence: A Review

ACM Computing Surveys, Journal Year: 2022, Volume and Issue: 55(2), P. 1 - 38

Published: Jan. 18, 2022

Artificial intelligence (AI) and algorithmic decision making are having a profound impact on our daily lives. These systems vastly used in different high-stakes applications like healthcare, business, government, education, justice, moving us toward more society. However, despite so many advantages of these systems, they sometimes directly or indirectly cause harm to the users Therefore, it has become essential make safe, reliable, trustworthy. Several requirements, such as fairness, explainability, accountability, reliability, acceptance, have been proposed this direction This survey analyzes all requirements through lens literature. It provides an overview approaches that can help mitigate AI risks increase trust acceptance by utilizing also discusses existing strategies for validating verifying current standardization efforts trustworthy AI. Finally, we present holistic view recent advancements interested researchers grasp crucial facets topic efficiently offer possible future research directions.

Language: Английский

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What factors contribute to the acceptance of artificial intelligence? A systematic review

Telematics and Informatics, Journal Year: 2022, Volume and Issue: 77, P. 101925 - 101925

Published: Dec. 14, 2022

Artificial Intelligence (AI) agents are predicted to infiltrate most industries within the next decade, creating a personal, industrial, and social shift towards new technology. As result, there has been surge of interest research user acceptance AI technology in recent years. However, existing appears dispersed lacks systematic synthesis, limiting our understanding technologies. To address this gap literature, we conducted review following Preferred Reporting Items for Systematic Reviews meta-Analysis guidelines using five databases: EBSCO host, Embase, Inspec (Engineering Village host), Scopus, Web Science. Papers were required focus on both Acceptance was defined as behavioural intention or willingness use, buy, try good service. A total 7912 articles identified database search. Sixty included review. Most studies (n = 31) did not define their papers, 38 participants. The extended Technology Model (TAM) frequently used theory assess Perceived usefulness, performance expectancy, attitudes, trust, effort expectancy significantly positively intention, willingness, use behaviour across multiple industries. some cultural scenarios, it that need human contact cannot be replicated replaced by AI, no matter perceived usefulness ease use. Given methodological approaches present literature have relied self-reported data, further naturalistic methods is needed validate theoretical model/s best predict adoption

Language: Английский

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Use of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives

BMC Medical Informatics and Decision Making, Journal Year: 2020, Volume and Issue: 20(1)

Published: July 22, 2020

Abstract Background Several studies highlight the effects of artificial intelligence (AI) systems on healthcare delivery. AI-based tools may improve prognosis, diagnostics, and care planning. It is believed that AI will be an integral part services in near future incorporated into several aspects clinical care. Thus, many technology companies governmental projects have invested producing medical applications. Patients can one most important beneficiaries users applications whose perceptions affect widespread use tools. should ensured they not harmed by devices, instead, benefited using for purposes. Although enhance outcomes, possible dimensions concerns risks addressed before its integration with routine Methods We develop a model mainly based value due to specificity field. This study aims at examining perceived benefits devices decision support (CDS) features from consumers’ perspectives. online survey collect data 307 individuals United States. Results The proposed identifies sources motivation pressure patients development devices. results show technological, ethical (trust factors), regulatory significantly contribute healthcare. Of three categories, technological (i.e., performance communication feature) are found significant predictors risk beliefs. Conclusions sheds more light factors affecting proposes some recommendations how practically reduce these concerns. findings this provide implications research practice area CDS. Regulatory agencies, cooperation institutions, establish normative standard evaluation guidelines implementation Regular audits ongoing monitoring reporting used continuously evaluate safety, quality, transparency, services.

Language: Английский

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