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Artificial intelligence (AI) applications pose a potential threat to users' data security and privacy due to their high data-dependence nature. This paper aims to investigate an understudied issue in the literature, namely, how users perceive the threat of and decide to use a threatening AI application. In particular, it examines the influencing factors and the mechanisms that affect an individual’s behavioral intention to use facial recognition, a threatening AI.

The authors develop a research model with trust as the key mediating variable by integrating technology threat avoidance theory, the theory of planned behavior and contextual factors related to facial recognition. Then, it is tested through a sequential mixed-methods investigation, including a qualitative study (for model development) of online comments from various platforms and a quantitative study (for model validation) using field survey data.

Perceived threat (triggered by perceived susceptibility and severity) and perceived avoidability (promoted by perceived effectiveness, perceived cost and self-efficacy) have negative and positive relationships, respectively, with an individual’s attitude toward facial recognition applications; these relationships are partially mediated by trust. In addition, perceived avoidability is positively related to perceived behavioral control, which along with attitude and subjective norm is positively related to individuals' intentions to use facial recognition applications.

This paper is among the first to examine the factors that affect the acceptance of threatening AI applications and how. The research findings extend the current literature by providing rich and novel insights into the important roles of perceived threat, perceived avoidability, and trust in affecting an individual’s attitude and intention regarding using threatening AI applications.

This study aims to examine the influence of the derived attributes of embedded artificial intelligence-mobile smart speech recognition (AI-MSSR) technology, namely perceived usefulness, perceived ease of use (PEOU) and perceived enjoyment (PE) on consumer purchase intention (PI) through the chain relationships of attitudes to AI and consumer smart experience, with the moderating effect of consumer innovativeness and Generation (Gen) X and Gen Y in fashion retail.

The study employed a quantitative survey strategy, drawing a sample of 836 respondents from Sri Lanka and India representing Gen X and Gen Y. The data analysis was carried out using smart partial least squares structural equation modelling (PLS-SEM).

The findings show a positive relationship between the perceived attributes of MSSR and consumer PI via attitudes towards AI (AAI) and smart consumer experiences. In addition, consumer innovativeness and Generations X and Y have a moderating impact on the aforementioned relationship. The theoretical and managerial implications of the study are discussed with a note on the research limitations and further research directions.

To multiply the effects of embedded AI-MSSR and consumer PI in fashion retail marketing, managers can develop strategies that strengthen the links between awareness, knowledge of the derived attributes of embedded AI-MSSR and PI by encouraging innovative consumers, especially Gen Y consumers, to engage with embedded AI-MSSR.

This study advances the literature on embedded AI-MSSR and consumer PI in fashion retail marketing by providing an integrated view of the technology acceptance model (TAM), the diffusion of innovation (DOI) theory and the generational cohort perspective in predicting PI.

This study explored the different artificial intelligence (AI) applications used in academic libraries and the key factors and impediments related to their implementation.

The author applied quantitative research methods in the form of a questionnaire, using both open and closed questions. A total of 472 valid questionnaires were received from academic librarians.

The author sought responses from librarians who had implemented AI applications and those who had not, identifying the types of AI applications implemented, key factors relating to their implementation, and impediments to promoting AI. Gaps were identified between the level of support for AI applications and the negative effect of the impediments. Furthermore, the more extensive the individual and organizational knowledge activities performed by the librarians and libraries held, the more positive the attitude was librarians' attitude toward AI applications in their libraries. However, librarians recognized that AI applications are inevitable, but indicated that the difficulties of in execution have hampered the adoption of AI.

The sample data were collected in Taiwan; therefore, the data may only represent the views of Taiwanese academic librarians on AI applications. The results of this study may not apply to librarians worldwide; however, they may provide a useful reference.

The results revealed the top four AI applications that libraries would most likely implement in the near future. Therefore, AI application developers and suppliers can prioritize the promotion of these products for to academic libraries. This study revealed that funding and costs related to AI implementation were discovered to be key factors relating to implementing AI applications. Some impediments to the implementation of AI applications relate to technological problems. Several librarians suggested that managers should invest more resources at an early stage rather than reducing cutting back on human resources initially. Although worries regarding privacy and ethics were mentioned expressed by some respondents, most academic librarians did not regard these to be major concerns.

This study provides the perspectives of librarians who have implemented AI applications and of those who have not. In addition, it explores the advantages and disadvantages of AI applications, and the level of support for and impact of AI applications and promotions. This study also included a gap analysis. Moreover, individual and organizational knowledge activity scales were adopted to examine AI awareness and the perceptions of academic librarians.

The purpose of this paper is to explore the use of artificial intelligence (AI) in libraries, especially university libraries, which are faced with users from various countries who have different languages and cultures. Seamless M4T, which is being developed, has great potential for helping university librarians maximize library services by providing ease of communication.

Analyzing the possibility of developing Seamless M4T using natural language processing techniques and how to train language models to be smarter AI tools and can be used to break down language barriers between librarians and users.

The implementation of AI-based application Seamless M4T can help university librarians provide maximum service to users who are hampered by language and culture with advanced communication skills. Seamless M4T has an automatic speech recognition feature for dozens of languages, so it can translate speech-to-text, text-to-speech or both text and speech. To convert written words into verbal forms, this AI can also translate and transcribe text and speech in real-time without significant delays.

This paper emphasizes the use of AI in university libraries to improve services, especially in communication due to language differences between librarians and users. Advantages in using AI in libraries can support the collaboration and scholarly communication process.

The evolution from emerging technologies to smart libraries is thoroughly analyzed thematically and bibliometrically in this research study, spanning 2013 through 2022. Finding and analyzing the significant changes, patterns and trends in the subject as they are represented in academic papers is the goal of this research.

Using bibliometric methodologies, this study gathered and examined a large corpus of research papers, conference papers and related material from several academic databases.

Starting with Artificial Intelligence (AI), the Internet of Things (IoT), Big Data (BD), Augmentation Reality/Virtual Reality and Blockchain Technology (BT), the study discusses the advent of new technologies and their effects on libraries. Using bibliometric analysis, this study looks at the evolution of publications over time, the geographic distribution of research and the most active institutions and writers in the area. A thematic analysis is also carried out to pinpoint the critical areas of study and trends in emerging technologies and smart libraries. Some emerging themes are information retrieval, personalized recommendations, intelligent data analytics, connected library spaces, real-time information access, augmented reality/virtual reality applications in libraries and strategies, digital literacy and inclusivity.

This study offers a thorough overview of the research environment by combining bibliometric and thematic analysis, illustrating the development of theories and concepts during the last ten years. The results of this study helps in understanding the trends and future research directions in emerging technologies and smart libraries. This study is an excellent source of information for academics, practitioners and policymakers involved in developing and applying cutting-edge technology in library environments.

This paper aims to present a systematic literature review and bibliometric analysis of research papers published on chat generative pre-trained transformer (ChatGPT), an OpenAI-developed large-scale generative language model. The study’s objective is to provide a comprehensive assessment of the present status of research on ChatGPT and identify current trends and themes in the literature.

A total of 328 research article data was extracted from Scopus for bibliometric analysis, to investigate publishing trends, productive countries and keyword analysis around the topic and 34 relevant research publications were selected for an in-depth systematic literature review.

The findings indicate that ChatGPT research is still in its early stages, with the current emphasis on applications such as natural language processing and understanding, dialogue systems, speech processing and recognition, learning systems, chatbots and response generation. The USA is at the forefront of publishing on this topic and new keywords, e.g. “patient care”, “medical”, “higher education” and so on are emerging themes around the topic.

These findings underscore the importance of ongoing research and development to address these limitations and ensure that ChatGPT is used responsibly and ethically. While systematic review research on ChatGPT heralds exciting opportunities, it also demands a careful understanding of its nuances to harness its potential effectively.

Overall, this study provides a valuable resource for researchers and practitioners interested in ChatGPT at this early stage and helps to identify the grey areas around this topic.

This article aims to reveal the factors influencing the sustainable development of mobile e-commerce from both user and operational perspectives. It fills the gap in qualitative research on the sustainable development of artificial intelligence (AI) technology in mobile e-commerce based on the grounded theory. This study provides valuable insights and inspiration for sustainable development in this field and lays the theoretical foundation and research reference for future studies.

Based on the grounded theory (GT), interview method was used to conduct the study.

The impact of AI applications on mobile e-commerce is mainly reflected in three stages of the customer shopping process. They are pre-shopping, mid-shopping and after-shopping AI services and each of the three stages has its own separate dimensions that need attention. The study and its persistence aspects are discussed.

The results of this study can provide forward-looking suggestions and paths for the construction and optimization of future e-commerce platforms, contribute to the sustainable development of e-commerce and contribute to the sustainable and healthy growth of the social economy.

This study proposes sustainable development measures for the application of AI in mobile e-commerce, from operation to supervision, which is an important reference for promoting coordinated and rapid socio-economic development.

Employee engagement (EE) can result in multiple positive impacts not only on the individual and his/her team but also on the organisational and financial outcome of the business. If artificial intelligence (AI) can be used as a tool to facilitate EE, organisations will be more than satisfied to adopt it. The paper aims to study the penetration of AI for EE in corporate India.

Based on the information gathered through secondary research, a framework of questions was built and sent to some senior people in the area of AI and HR to check for its completeness. Respondents based on inclusion criteria were selected through random purposive sampling to be a part of the study. A total of 23 respondents participated in the study. Qualitative data analysis of the transcripts was conducted using MAXQDA 2022 (Verbi Software, Berlin, Germany), which is a qualitative data analysis software. Multiple readings were undertaken to identify the patterns and relationships in the data.

The participants described a variety of issues while using or planning to use AI for EE. Some of the issues mentioned were related to cost, challenges, mindsets and attitudes, demography of employees, comfort in the use of technology, size of the organisation, change management strategies, software vendors and vendor support. The most common responses were grouped into headings such as Organisation, Process, Employee and Software Choice Related aspects.

Lately, the overall work environment, work and personal life balance, and quality of life have become more desirable than earning a good salary. AI is becoming a part of various aspects of business but its role in HR is yet to be explored. AI’s capabilities to predict may result in more employee work satisfaction. The paper explores the possibility of using AI as a tool in every aspect of employee life cycle, thereby attempting to make HR processes more productive and enhance EE.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

The purpose of this study is to investigate artificial intelligence (AI) as enabler of future library services, with consideration to how prepared are librarians in African university libraries.

This study applied the interpretive content/document analysis of literature harvested from different databases of Scopus and Web of Science. AI could be used to perform daily routines in circulation, serial, reference and selective dissemination of information among others. It could also be applied to the provision of innovative services of recognition of library activities such as answering research quarries, cataloguing and classification of library materials and management of library system software of different databases within the library systems.

It could be deduced from the study that AI would continue to serve as a panacea to future library services irrespective of its geographical context. Due to the evolving nature of knowledge growth, AI having its roots in the field of engineering has been found useful to support future library services. The support accrued from library service delivery in the library profession has made librarians continue to interact with other intelligent machines that can demonstrate human behaviour even though they are not real human beings. The behaviour of machines and AI where human beings play a significant role has brought many renovations in the management of complex tasks of processing, communication, knowledge representation, decision making and suggestions, on potentials of diverse work operations.

The understanding that the present paper portrays in the context of future library services is that there is no way the AI could function without a human interaction perspective when drawing an analogy from computer science, information science and information systems fields of study.

The interest of users across their background would be strengthen if AI advances transformed the handling complex tasks of processing, communication, knowledge representation, decision-making and giving suggestions, among other things. The possibilities of diverse work operations from empirical evidence of studies consulted in recent times gave the authors the impetus to consider AI as the enabler of future library services.

The increasing demands from library patrons have prompted librarians to adapt their methods of delivering services. These emerging technologies have also brought about shifts in approaches to teaching and learning. Consequently, the recent surge in digital technology-driven service innovations has ushered in a fresh paradigm for education and research. In response to these changes, librarians are actively seeking novel and innovative technologies to enhance user experiences within their libraries. They serve as catalysts for introducing modern and advanced technologies, consistently adapting to contemporary tools that enhance their offerings.