An investigation on trust in AI-enabled collaboration: Application of AI-Driven chatbot in accommodation-based sharing economy

Cheng, Xusen; Zhang, Xiaoping; Yang, Bo; Fu, Yaxin

doi:10.1016/j.elerap.2022.101164

Cited by 18 publications

(5 citation statements)

References 57 publications

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“…In using PLS-SEM, the extended value-belief-norm theory incorporating ESG as well as AI trust and benefits has substantially explained space tourist behaviors in relation to sustainability for the entire group. Specifically, the significant impact of value on beliefs, trust, and benefits implies that people with high value on sustainable space tourism are more likely to have strong beliefs in sustainable space tourism as well as trust in and benefits of AI with space tourism, extending prior literature (Cheng et al, 2022b; Frank, 2021; Landon et al, 2018). The positive influence of ESG on beliefs, trust, and benefits suggests that potential space tourists with high degrees of ESG have perceived better beliefs on sustainable space tourism as well as AI trust and benefits with space tourism, thereby expanding previous studies on ESG, sustainability, and AI (Bosone et al, 2022; Clementino & Perkins, 2021; Moon et al, 2022).…”

Section: Discussionsupporting

confidence: 57%

“…Factors such as familiarity, self-efficacy in robot usage, technological attachment, social influence, and a general trustful attitude toward technology were identified to impact the propensity to trust AI social robots (Chi et al, 2021). When considering the use of chatbots by accommodation providers, perceived system usability emerged as a key element influencing trust in AI, followed by perceived intelligence, perceived affinity, and perceived privacy breaches (Cheng et al, 2022b).…”

Section: Literature Reviewmentioning

confidence: 99%

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Effects of Value-Belief-Norm Theory, ESG, and AI on Space Tourist Behavior for Sustainability With Three Types of Space Tourism

Kim,

Hall,

Kwon

et al. 2023

Journal of Travel Research

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Since reusable launch vehicles have revolutionized access to space, space tourism has received enormous policy and research attention. However, such growth is occurring within a wider context of concerns over climate change, emissions, and space debris. Although the space industries have enormous environmental impacts, few studies have been undertaken on the sustainability of space tourism. Therefore, we aim to create and assess an extended value-beliefs-norms theory with environmental, social, and governance (ESG) factors, trust in artificial intelligence (AI), and the benefits of AI, in comparing three types of space tourism (Earth, suborbital, and orbital). To achieve the goals, multi-method analyses of 1,000 respondents were applied, including partial least squares-structural equation modeling, multi-group analysis, fuzzy-set Qualitative Comparative Analysis, and deep learning. Results revealed that the extended value-belief-norm model well explains space tourist behavior, ESG also has significant roles on the research model, and the three types have unique characteristics.

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Section: Discussionsupporting

confidence: 57%

Section: Literature Reviewmentioning

confidence: 99%

Effects of Value-Belief-Norm Theory, ESG, and AI on Space Tourist Behavior for Sustainability With Three Types of Space Tourism

Kim,

Hall,

Kwon

et al. 2023

Journal of Travel Research

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“…Misuse of personal data can result in fraud, identity theft, and other nasty things. Personal data security is essential to preserve user confidence and trust in e-commerce platforms (Cheng et al, 2023). According to the study by Sean Michael Kerner.…”

Section: Literature Reviewmentioning

confidence: 99%

Investigating Potential Applications of Machine Learning Techniques for Personal Data Protection in E-commerce

2023

IJCATR

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The increasing demand of e-commerce and online retail services in the past years has required development of strong security protocols able of protecting the privacy and safety of consumers. Machine learning has proven an essential tool in the analysis and reaction to cybersecurity threats, thus ensuring the security and privacy of users of online retail stores all over the globe. In this sense, machine learning protocols have proven essential in the prevention of cyberattacks like cross site scripting (XSS), in the identification of potential threats affecting the financial results and overall performance of a company, or the surveyance of the behavior of the individuals within an online community to identify excessively authoritative and potentially harmful members within different communities. The present paper analyzes the state-of-the-art advances in this field, providing an overview of the different methods that have proven their validity to develop machine learning-based models to ensure the security and privacy of users of online retail stores. The proposed machine learning methods use validation protocols such as NLP, SVM-based algorithms, neural networks, and text mining. Based on such analysis, the paper suggests potential approaches to a better implementation of machine learning in cybersecurity, enabling a faster and more effective response against the threat.

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“…Compared to traditional IT tools that are used to interrelate the service offered with the customer, chatbots are made up of functionalities that allow them to provide social and emotional understanding (Song et al, 2022). They show a high capacity to process requirements from various users and then suggest a collaboration process that responds to their needs (Cheng et al, 2022). In general, they join other user-oriented applications and fulfil the purpose of being easy and consistent means between organisations and clients (Nguyen et al, 2022), helping them to find information, provide feedback and even file complaints (Chen et al, 2022, Fan et al, 2022Liu et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Application of the Chatbot in University Education: A Bibliometric Analysis of Indexed Scientific Production in SCOPUS, 2013-2023

Chamorro-Atalaya,

Olivares-Zegarra,

Sobrino-Chunga

et al. 2023

IJLTER

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Universities today are employing tools based on artificial intelligence to improve the educational service in general. The chatbot represents an online communicative interaction tool which contributes to solving daily queries required by students, teachers or graduates. However, there are few bibliometric review studies on the chatbot that show in which areas there is a greater concentration or lack of scientific production at the university level. The objective of this article is to explore and describe the research trends regarding the application of the chatbot in university education through the bibliometric analysis of publications indexed to Scopus. The research is of an exploratory-descriptive level, developed under a quantitative approach. The study covered the scientific production between the years 2013 and 2023, identifying 210 manuscripts. It was identified that there is a growing trend in scientific production, particularly in scientific articles and conference papers. The most cited article was published in 2018 and has 162 citations. Therefore, it is concluded that there is a greater concentration in the scientific production of manuscripts focused on improving the university educational service, applying significantly to the improvement of academic performance, administrative management and university wellbeing. However, there is a gap that needs to be reduced in terms of the lack of scientific studies in which the chatbot is used as a tool to identify the satisfaction of university students. In addition, there is a lack of research on the use of a regulatory framework that regulates the application of the chatbot at the university level.

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An investigation on trust in AI-enabled collaboration: Application of AI-Driven chatbot in accommodation-based sharing economy

Cited by 18 publications

References 57 publications

Effects of Value-Belief-Norm Theory, ESG, and AI on Space Tourist Behavior for Sustainability With Three Types of Space Tourism

Effects of Value-Belief-Norm Theory, ESG, and AI on Space Tourist Behavior for Sustainability With Three Types of Space Tourism

Investigating Potential Applications of Machine Learning Techniques for Personal Data Protection in E-commerce

Application of the Chatbot in University Education: A Bibliometric Analysis of Indexed Scientific Production in SCOPUS, 2013-2023

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