Exploring User Adoption of ChatGPT: A Technology Acceptance Model Perspective

International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 15

Опубликована: Фев. 22, 2024

In the rapidly evolving landscape of technology, emergence Chat Generative Pre-trained Transformer (ChatGPT) marks a pivotal milestone in realm Artificial Intelligence (AI). However, little research has reported predictors people's intentions to use ChatGPT. This pioneering study empirically examines user adoption through lens Technology Acceptance Model (TAM) using convenience sampling method. The surveyed 784 ChatGPT users China, whom 58.93% were males. results have revealed several key findings: (1) perceived usefulness, ease use, behavioral intention, and behavior positively correlated with each other; (2) intention acted as mediating factor relationship between usefulness behavior, well behavior; (3) played chain-mediated role (4) exhibited greater strength among females compared males; (5) association was found be stronger urban comparison their rural counterparts; (6) connections observed individuals higher educational backgrounds relative those lower backgrounds. These findings provide crucial nuanced insights advance practical application ChatGPT, emphasizing need for enhanced usability use. this exclusively captured usage behaviors within Chinese base. Future investigations could encompass diverse demographics across multiple countries, enabling cross-cultural comparisons.

Язык: Английский

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Determinants of Generative AI in Promoting Green Purchasing Behavior: A Hybrid Partial Least Squares–Artificial Neural Network Approach

Business Strategy and the Environment, Год журнала: 2025, Номер unknown

Опубликована: Фев. 11, 2025

ABSTRACT In the era of rapid technological advancement, generative artificial intelligence (AI) has emerged as a transformative force in various sectors, including environmental sustainability. This research investigates factors and consequences using AI to access information influence green purchasing behavior. It integrates theories such adoption model, value–belief–norm theory, elaboration likelihood cognitive dissonance theory pinpoint prioritize determinants usage for Data from 467 participants were analyzed hybrid methodology that blends partial least squares (PLS) with neural networks (ANN). The PLS outcomes indicate interactivity, responsiveness, knowledge acquisition application, concern, ascription responsibility are key predictors use information. Furthermore, concerns, values, personal norms, responsibility, individual impact, emerge ANN analysis offers unique perspective discloses variations hierarchy these predictors. provides valuable insights stakeholders on harnessing promote sustainable consumer behaviors

Язык: Английский

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Effects of ChatGPT’s AI capabilities and human-like traits on spreading information in work environments

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Апрель 2, 2024

Abstract The rapid proliferation and integration of AI chatbots in office environments, specifically the advanced model ChatGPT, prompts an examination how its features updates impact knowledge processes, satisfaction, word-of-mouth (WOM) among workers. This study investigates determinants WOM workers who are users ChatGPT. We adopted a quantitative approach, utilizing stratified random sampling technique to collect data from diverse group experienced using hypotheses were rigorously tested through Structural Equation Modeling (SEM) SmartPLS 4. results revealed that system updates, memorability, non-language barrier attributes ChatGPT significantly enhanced acquisition application. Additionally, human-like personality traits increased both utilitarian value satisfaction. Furthermore, showed application led significant increase which subsequently WOM. Age had positive influence on WOM, while gender no impact. findings provide theoretical contributions by expanding our understanding chatbots' role particularly

Язык: Английский

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Coupling Human-Computer Interface Lensing Artificial Emotional Intelligence

Advances in computational intelligence and robotics book series, Год журнала: 2024, Номер unknown, С. 233 - 250

Опубликована: Июнь 30, 2024

The advancement of human-computer interfaces in Industry 5.0 has been crucial enhancing productivity and efficiency various domains. As the industry transitions towards 5.0, there is a growing demand for more advanced that incorporate artificial emotional intelligence capabilities. Artificial enables computers to mimic human emotions, allowing intuitive personalized interactions. integration into potential revolutionize decision making 5.0. By incorporating recognition response capabilities, can become intuitive, human-like, collaborative. This chapter highlights significance transforming interfaces, proposing an approach seamless integration, outlining applications future research focuses on addressing challenges exploring new frontiers further enhance intelligence-based interfaces.

Язык: Английский

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Examining How the Large Language Models Impact the Conceptual Design with Human Designers: A Comparative Case Study

International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 17

Опубликована: Июль 1, 2024

Advances in artificial intelligence have led to breakthroughs large language models (LLMs), like ChatGPT, opening up exciting possibilities for conceptual design. However, it's essential gain an in-depth understanding of how LLMs impact design output, process, and human designers' perception. To this end, we chose ChatGPT as example conducted the investigation with 30 participants divided into Human-LLMs groups human-human groups. The results indicated that there was no significant difference between their outputs, but incorporation shortened completion time fewer steps less allocated late stages Despite being perceived efficient trusted, can still be viewed potential collaborators, humans holding leadership. These findings offer HCI community a thorough comprehension influence creativity-related practices, providing valuable insights designing future interactions LLMs.

Язык: Английский

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Can interaction with generative artificial intelligence enhance learning autonomy? A longitudinal study from comparative perspectives of virtual companionship and knowledge acquisition preferences

Journal of Computer Assisted Learning, Год журнала: 2024, Номер 40(5), С. 2369 - 2384

Опубликована: Июнь 30, 2024

Abstract Background With the development of artificial intelligence (AI) technology, generative AI has been widely used in field education and represents a groundbreaking shift overcoming constraints time space within educational activities. However, previous literature not paid enough attention to AI‐involved teaching patterns, it is necessary evaluate effects this learning pattern. Objective s Based on social presence theory community inquiry model, main purpose study whether how interaction frequency with chatbots (IFC) affects people's autonomy (LA) under two preferences: knowledge acquisition virtual companionship, (SP) plays mediating role. Methods The 1‐year longitudinal was designed be conducted from May 2022 2023 included three rounds surveys 1155 undergraduate students their use robots for learning. Results Conclusions For learners preferring no direct correlation found between IFC LA. SP acted as factor, enhancing LA through increased chatbot interactions. This suggests that while interactions may directly influence LA, resulting can foster it. Conversely, favouring acquisition, higher negatively impacted both Despite this, strong sense consistently correlated positively indicating could offset some negative frequent use.

Язык: Английский

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The Roles of Social Perception and AI Anxiety in Individuals’ Attitudes Toward ChatGPT in Education

International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 18

Опубликована: Июнь 21, 2024

Язык: Английский

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Unlocking Digital Potential: Technological Capability as a Key Moderator-Mediator in Migrant Workers' Use of JMO Mobile

Data & Metadata, Год журнала: 2025, Номер 4, С. 727 - 727

Опубликована: Март 28, 2025

This study aims to examine the factors influencing technology adoption (TA) among Indonesian migrant workers, particularly in use of JMO Mobile application. The research integrates technological capability (TC) as both a moderating and mediating variable within TAM provide more comprehensive understanding behavior. Specifically, investigates impact Perceived Ease Use (PEOU), Benefits (PB), organizational support on TC TA. employs quantitative approach using survey method, collecting data from workers who PLS-SEM is applied analyze links variables. findings reveal that PEOU, PB, significantly influence Furthermore, serves moderator, strengthening link between PEOU TA, well PB Additionally, functions mediator indicating its critical role facilitating process. These have practical implications for improving engagement workers. By enhancing user-friendly features, providing clear benefits, offering through training programs, applications like can better meet workers' needs. contributes theoretical expansion by incorporating key factor adoption. originality this lies focus group has received limited attention TA studies, integration variable.

Язык: Английский

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Using ChatGPT for academic support: Managing cognitive load and enhancing learning efficiency – A phenomenological approach

Social Sciences & Humanities Open, Год журнала: 2025, Номер 11, С. 101301 - 101301

Опубликована: Янв. 1, 2025

Язык: Английский

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Unlocking EFL learners’ insights into ChatGPT use for L2 writing: The impacts of usage frequency and gender variations

Current Psychology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 7, 2025

Abstract The emergence of ChatGPT as a powerful chatbot has revolutionized global education in general and language learning particular since it can offer opportunities for students teachers. Against this backdrop, study aimed to explore whether gender usage frequency affect English learners’ perceptions use second (L2) writing beyond the classroom. In accordance with Technology Acceptance Model (Davis, 1989), research was conducted at major departments state university Türkiye. Employing fully integrated mixed methods approach adopting sequential explanatory design , present recruited 874 Turkish undergraduate students. Quantitative data were collected through Demographic Information Form Perception Scale, whereas qualitative gathered semi-structured interviews. Exploratory confirmatory factor analyses performed assess reliability validity scale. Descriptive inferential statistics run quantitative analysis, while analyzed using thematic analysis. results revealed that many participants used writing, though rarely, held positive tool. Gender-based variations detected terms but not overall perceptions; furthermore, there significant correlation between perceptions. Based on integration both sources, contradictory, expanded, confirmed outcomes emerged, explicit implications suggested regarding L2 outside

Язык: Английский

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