Artificial Intelligence (Not) Replacing Coaches: A Thematic Literature Review DOI

A.Y. Ezhikov

Published: Dec. 12, 2024

Language: Английский

Artificial intelligence psychological anthropomorphism: scale development and validation DOI

Pengyi Shen,

Fengying Zhang,

Xiucheng Fan

et al.

Service Industries Journal, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 32

Published: June 17, 2024

This study explores the conceptualization, dimensional structure, and measurement of artificial intelligence (AI) psychological anthropomorphism in service scenarios. Data were collected using semi-structured in-depth interviews. A grounded theory research approach was employed to construct a structural model AI that included dimensions personality, empathy, mind. Exploratory confirmatory factor analyses subsequently conducted on questionnaire data through online surveys from which scale for developed. It consisted 16 items demonstrated good reliability validity. Moreover, equation modeling, strong nomological validity demonstrated. The results indicate its significantly positively predict trust identity threat. These findings enhance understanding conceptual meaning structure scenarios, as well provide psychometrically reliable valid tool use subsequent empirical research. Additionally, offer important insights developers, providers, regulatory agencies ameliorate design, formulate marketing strategies, refine governance policies.

Language: Английский

Citations

6

Customers’ metaverse service encounter perceptions: sentiment analysis and topic modeling DOI

S. Jerrin Issac Sam,

K. Mohamed Jasim,

M. Babu

et al.

Journal of Hospitality Marketing & Management, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23

Published: July 29, 2024

Using machine learning, we examined customers' opinions about the metaverse in hospitality industry (encompassing hotels, restaurant, gaming, virtual events, tours and travel). A total of 8,855 tweets were collected from Twitter (now called X), learning algorithms such as sentiment analysis topic modeling performed using Python libraries to capture important topics related applications. Nearly two thirds (60.9%) contained a mostly positive general toward use metaverse. Six emerged modeling: sightseeing, travel, business blockchain. Despite numerous studies on proper integration metaverse, VR AR, best our knowledge, this is one first conducted determine customer experience social media data.

Language: Английский

Citations

5

Exploring the Effect of Attachment on Technology Addiction to Generative AI Chatbots: A Structural Equation Modeling Analysis DOI

Yiting Huang,

Hanyun Huang

International Journal of Human-Computer Interaction, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 10

Published: Nov. 15, 2024

With the advancement of artificial intelligence technology, generative AI chatbots (GAIC) such as ChatGPT, are integrating into various aspects society and quietly changing people's lives. However, although there is a plethora research concerning social media usage addiction, discussions about remain far from adequate. Investigating use potential technology addiction to (TAGAIC) holds both theoretical practical significance. Drawing on attachment theory, this study aims investigate formative factors in TAGAIC. A structural equation model was used analyze data collected questionnaire survey 364 GAIC users. Results reveal that positively influenced by emotional but not functional attachment. Besides, perceived anthropomorphism empathy have positive effect attachment, while system quality information Limitations were discussed.

Language: Английский

Citations

4

The Impact of Perceived Experience on Customer Privacy Concerns During AI-Human Interaction: The Chain Mediating Effect of Hedonic Value and Trust DOI
Gang Li, T Wang, Miaomiao Yang

et al.

International Journal of Human-Computer Interaction, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 14

Published: Jan. 24, 2025

Language: Английский

Citations

0

Consumers' questions as nudges: Comparing the effect of linguistic cues on LLM chatbot and human responses DOI
Qian Wu, Han Zheng

Journal of Retailing and Consumer Services, Journal Year: 2025, Volume and Issue: 84, P. 104250 - 104250

Published: Feb. 4, 2025

Language: Английский

Citations

0

Promoting sustainable hospitality: examining the impact of voice assistant recommendations on customer engagement in pre-travel decision-making: moderating effects of use purpose and cultural orientation DOI Creative Commons
Han-Ling Jiang,

Lin-Hua Lu,

Tsunwai Wesley Yuen

et al.

Journal of Hospitality Marketing & Management, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 39

Published: March 26, 2025

Language: Английский

Citations

0

Artificial intelligence (AI) technology, its applications and the use of AI powered devices in hospitality service experience creation and delivery DOI
Doğan Gürsoy

International Journal of Hospitality Management, Journal Year: 2025, Volume and Issue: unknown, P. 104212 - 104212

Published: March 1, 2025

Language: Английский

Citations

0

Influencing Driving Safety by Matching AI Assistant's Verbal Emotions to Driver: A Randomized Controlled Trial on Performance, Attention, and Emotion DOI
Bo Huang,

Jian Lv,

Ligang Qiang

et al.

Computers in Human Behavior, Journal Year: 2025, Volume and Issue: unknown, P. 108667 - 108667

Published: April 1, 2025

Language: Английский

Citations

0

Artificial Intelligence Social Responsibility in the Consumer Market: Dimension Exploration and Scale Development DOI
Shen Peng-yi, Jinxiong Li, Demin Wan

et al.

International Journal of Consumer Studies, Journal Year: 2025, Volume and Issue: 49(3)

Published: April 21, 2025

ABSTRACT This study explored the conceptualization, dimensional structure, and measurement of artificial intelligence (AI) social responsibility in consumer market. Data were collected through semi‐structured in‐depth interviews with 32 respondents. A grounded theory research approach was employed to construct a structural model AI that included dimensions ethics, safety, applicability, credibility, reflexivity. Subsequently, an exploratory factor analysis conducted on 305 questionnaire data online survey as well confirmatory 325 data. The analyses led development scale consisting 18 items demonstrating good reliability validity. Moreover, using equation modeling, strong nomological validity demonstrated. results indicated its significantly predicted flow experience satisfaction. findings enhance understanding conceptual meaning structure market, provide psychometrically reliable valid tool for use future research. Furthermore, not only facilitate design implementation technologies, but they also offer crucial insights companies their stakeholders devise refine strategies other marketing tactics—thereby augmenting CSR 3.0 management practices.

Language: Английский

Citations

0

Facial emotional expressions and real-time viewership in cycling travel live streaming: A mixed-methods approach DOI Creative Commons
Mengfan Li, Mingming Cheng, Vanessa Quintal

et al.

Journal of Hospitality and Tourism Management, Journal Year: 2025, Volume and Issue: 63, P. 223 - 235

Published: May 13, 2025

Language: Английский

Citations

0