Investigating factors influencing AI customer service adoption: an integrated model of stimulus–organism–response (SOR) and task-technology fit (TTF) theory

Asia Pacific Journal of Marketing and Logistics, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 29, 2024

Purpose Artificial intelligence (AI) customer service has grown rapidly in recent years due to the emergence of COVID-19 and growth e-commerce industry. Therefore, this study employs integration stimuli–organism–response (SOR) task-technology fit (TTF) frameworks understand factors that affect individuals’ intentions towards AI adoption Malaysia. Design/methodology/approach The utilised a survey-based research approach investigate data were collected by conducting an online survey targeting individuals aged 18 or above who had prior interaction experience with human agents but not yet adopted service. A sample 339 respondents was used evaluate hypotheses, adopting partial least squares structural equation modelling as symmetric analytic technique. Findings PLS-SEM analysis revealed social influence anthropomorphism have positive direct relationship emotional trust. Furthermore, communicative competence, technology characteristics perceived positively correlated TTF. Moreover, trust significantly impacts adoption. In addition, readiness moderates association between task Practical implications provides insights individuals, organisations, government educational institutions improve features its development Originality/value originality is found SOR theory TTF affecting Additionally, it incorporates moderating variables during analysis, adding depth findings. This introduces new perspective on impact offers valuable for practitioners seeking formulate effective strategies promote

Language: Английский

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Preservice Teachers’ Behavioural Intention to Use Artificial Intelligence in Lesson Planning: A Dual-Staged PLS-SEM-ANN Approach

Computers and Education Artificial Intelligence, Journal Year: 2024, Volume and Issue: unknown, P. 100307 - 100307

Published: Sept. 1, 2024

Language: Английский

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Exploring the impact of hedonic and utilitarian drivers of gamified learning in metaversity: A multi-group analysis

Education and Information Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Language: Английский

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Exploring adoption of humanoid robots in education: UTAUT-2 and TOE models for science teachers

Education and Information Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 15, 2025

Language: Английский

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Extending UTAUT model to examine the usages of ChatGPT among Indian students in higher education: a structural equation modelling approach

The TQM Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

Purpose This study used extended Unified Theory of Acceptance and Use Technology (UTAUT) model to examine the effect personal expectancy (PE), efforts (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), price value (PV) habit (H) on behavioural intention (BI) use Chat Generative Pre-Trained Transformer (ChatGPT) in higher education for an Indian context. The also examined moderating effects students’ self-innovativeness (SIN) integrity (INT) relationship between BI behaviour (UB) ChatGPT. Design/methodology/approach A sample 311 students has been selected from Northern states India by applying stratified proportionate random sampling method four disciplines – engineering, business administration, science fine arts were as different strata selection process. Partial least squares structural equation modelling (PLS-SEM) approach data analysis assess proposed theoretical model. Findings found PE, FC, PV H significantly account actual ChatGPT, whereas EE, SI HM showed a negligible impact BI. was non-significant predicting usage moderation SIN INT UB. Research limitations/implications limited size its focus constrain generalizability findings other parts world. Originality/value helps understand nuances associated with advanced artificial intelligence (AI)-driven tool such ChatGPT application best-practices. Therefore, this aims bridge gap examining determinants version UTAUT context using additional constructs INT.

Language: Английский

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Unveiling the Complexity of Designers’ Intention to Use Generative AI in Corporate Product Design: A Grounded Theory and fsQCA

Systems, Journal Year: 2025, Volume and Issue: 13(4), P. 275 - 275

Published: April 9, 2025

While generative artificial intelligence (Gen AI) is accelerating digital transformation and innovation in corporate product design (CPD), limited research has explored how designers adopt this technology. This study aims to identify the key factors causal configurations that influence designers’ intentions Gen AI CPD. involved 327 in-service as participants, employed semi-structured interviews a questionnaire collect data, applied grounded theory fsQCA analyze data. The findings indicate following: (1) Personal innovativeness, technological anxiety, perceived usefulness, task–technology fit, risk, social influence, organizational support are influencing adoption of AI. (2) None these constitute necessary condition for (3) High intention results from interaction multiple factors, which can be categorized into three driving logics: “task demand-driven”, “organizational environment-driven”, “individual characteristics-driven”. It recommended managers establish an training framework, foster supportive environment, implement tailored strategies facilitate integration new technologies. clarifies CPD provides framework companies effectively integrate systems design.

Language: Английский

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Investigating the factors influencing the adoption and use of artificial intelligence applications among Pakistani university research scholars: An empirical study

Information Development, Journal Year: 2025, Volume and Issue: unknown

Published: April 13, 2025

The widespread use and adoption of Artificial Intelligence (AI) applications among university students has drastically transformed the educational landscape. Recognizing importance this transformation, study aims to investigate factors affecting AI Pakistani research scholars. This used an extended version unified theory acceptance technology model innovative resistance theory. data were collected from 235 scholars through a questionnaire. Descriptive statistics multiple linear regression test analyze data. found that various for purposes such as ChatGPT, Grammarly, ChatPDF, SciSpace. personal innovativeness, performance expectancy, social influence, trust significantly influence scholars’ behavioral intention applications. In contrast, impact effort facilitating conditions, innovation on students’ tools was statistically insignificant. findings offer actionable insights educators, policymakers, developers aiming enhance in higher education.

Language: Английский

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Comparing and modeling the use of online recommender systems

Computers in Human Behavior Reports, Journal Year: 2024, Volume and Issue: 15, P. 100449 - 100449

Published: July 6, 2024

This study explores a new way to model the adoption of AI, specifically online recommender systems. It aims find factors that can explain variation in usage terms differences between individuals and over technologies. We analyzed survey data from users platforms U.S. using two-level structural equation (SEM) (N = 1007). In this model, dependent variable was rate, which defined as share time person used particular system (e.g., "People You May Know") when they use platform Facebook). The individual responses (within-systems level) were clustered 26 systems (between-systems level). hypothesized three technology-specific factors, adapted Diffusion Innovations (DOI) theory Unified Theory Acceptance Use Technology 2 (UTAUT2), could variations at both levels: perceived performance expectancy (PE), effort (EE), hedonic motivation (HM). Our estimated showed associated with PE HM within-system level only between-system level. A considerable part across be explained by (R2 0.30). most important contribution practitioners is provides evidence for idea there are inherent, measurable technologies affect their rates, it finds usefulness key factor. potentially valuable app developers marketeers who look promote novel main literature presents proof-of-concept AI adoption, conceptualizing an effect applications. finding policymakers, better predictive models might enable improved assessments AI's social implications. future studies, approach presented here applied other forms such voice assistants, chatbots, or Internet Things (IoT).

Language: Английский

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Data analytics and Artificial Neural Network framework to profile academic success: case study

Cogent Education, Journal Year: 2024, Volume and Issue: 11(1)

Published: Dec. 3, 2024

Academic success in higher education has attracted interest from the scientific community because of its implications for personal development and societal progress. Programmes such as Tecnologico de Monterrey's Leaders Tomorrow aim to nurture students' potential promote academic success. This study examines attributes participating students associated with The focus is on personality socio-demographic factors that influence excellence. research contribution this work data analysis supported by artificial neural networks establish relationship between tests background information performance. findings were: (a) high school GPA predicts university success; (b) first-generation degree status GPA; (c) gender differences performance vary context; (d) profiles are not role predicting prospective discussed.

Language: Английский

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Fostering Continuous Innovation in Creative Education: A Multi-Path Configurational Analysis of Continuous Collaboration with AIGC in Chinese ACG Educational Contexts

Sustainability, Journal Year: 2024, Volume and Issue: 17(1), P. 144 - 144

Published: Dec. 27, 2024

AI-generated content (AIGC) is uniquely positioned to drive the digital transformation of professional education in animation, comic, and game (ACG) industries. However, its collaborative application also faces initial novelty effects user discontinuance. Existing studies often employ single-variable analytical methods, which struggle capture complex mechanisms influencing technology adoption. This study innovatively combines necessary condition analysis (NCA) fuzzy-set qualitative comparative (fsQCA) applies them field ACG education. Using this mixed-method approach, it systematically explores conditions configurational educational users’ continuance intention adopt AIGC tools for design learning, aiming address existing research gaps. A survey 312 Chinese users revealed that no single factor constitutes a their tools. Additionally, five pathways leading high adoption three low were identified. Notably, absence or insufficiency task–technology fit, perceived quality do not hinder willingness actively reflects creativity-driven learning characteristics, flexible diverse tool demands discipline. The findings provide theoretical empirical insights enhance effective synergy sustainable development between

Language: Английский

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