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This study aims to explore the capabilities, limitations and potential of ChatGPT applicable to online reference services in academic libraries.

This study used the method of qualitative content analytics to assess the general capabilities of ChatGPT applicable in academic libraries. Two experienced academic librarians had face-to-face interactions with ChatGPT by asking ten most common questions often asked by faculty and students at the Georgia Southern University Libraries (https://library.georgiasouthern.edu/). To examine the ChatGPT’s applicability and capability, they also compared the ChatGPT with a popular online chat reference tool called LibChat, which is now widely used in academic libraries in 91 countries worldwide.

It was found that as an artificial intelligence (AI)-powered real-time chatbot ChatGPT could effectively provide faculty and students with general guidance on locating the needed information resources and services in academic libraries, though its responses might not be accurate or truthful all the time. Embedded into the LibAnswers system of the Springshare’s products (www.springshare.com/libanswers/), LibChat serves as a real-time online chat tool used by academic libraries for reference services, but it is only available during the regular librarians' duty hours. This technical limitation does not meet the dynamic needs of faculty, students, staff, and local community users. Only well-optimized AI-driven chat products like ChatGPT could provide 24/7 online services to support uninterrupted academic library services in the future.

This study only examined the general capability and potential of ChatGPT3.5 in specific subject areas. Additional studies are needed to further explore how the latest capabilities of ChatGPT4.0 or newer version, such as its text-to-image, text-to-speech, text-to-text, text-to-video and Web search, could impact future reference services of academic libraries. ChatGPT’s primary optimization and upgrades in the future may also change and impact this study's findings. The comparison between ChatGPT and LibChat presents a significant breakthrough of the generative AI technology in academic libraries. This comparative study encourages more academic experts, faculty, librarians and scholars to track the advance of generative AI applications, including ChatGPT, adopted in academic learning environments. In addition, the ChatGPT's complete capability and potential enhanced and integrated in the future may go beyond what this study evaluated.

This study examined the strengths and weaknesses of ChatGPT applicable to reference services of academic libraries. Through a comparison between ChatGPT and LibChat, this study suggests that optimized AI online chatbots still have a long way to go to meet the dynamic needs of faculty and students in the ever-changing academic learning environments. To contribute to the existing research literature focusing on the rise of generative AI tools such as ChatGPT, this study provides a valuable reference for the applicability of generative AI applications in academic libraries to promote more library creation and innovation in the coming years of the 21st century.

The purpose of this paper is to provide details of biomimetic and neuromorphic sensor research and developments and discuss their applications in robotics.

Following a short introduction, this first provides examples of recent biomimetic gripping and sensing skin research and developments. It then considers neuromorphic vision sensing technology and its potential robotic applications. Finally, brief conclusions are drawn.

Biomimetics aims to exploit mechanisms, structures and signal processing techniques which occur in the natural world. Biomimetic sensors and control techniques can impart robots with a range of enhanced capabilities such as learning, gripping and multidimensional tactile sensing. Neuromorphic vision sensors offer several key operation benefits over conventional frame-based imaging techniques. Robotic applications are still largely at the research stage but uses are anticipated in enhanced safety systems in autonomous vehicles and in robotic gripping.

This illustrates how tactile and imaging sensors based on biological principles can contribute to imparting robots with enhanced capabilities.

The paper aims to analyze the potential of artificial intelligence (AI) in enhancing marketing capabilities for Indian fast-moving consumer goods (FMCG) firms, with appropriate emphasis on dynamic capabilities (DC). By integrating AI into their operations, companies can enhance diverse marketing practices, leading to improved efficiency and effectiveness. In addition, the study offers valuable insights and guidance for effectively implementing AI in marketing strategies.

In-depth interviews of 26 seasoned professionals from various positions in the Indian FMCG sector were conducted for the study. A systematic approach of coding that includes open, axial and selective coding was made to recognize the themes that represent AI-enabled marketing practices. This approach ensured that the themes were precisely identified and comprehensively analyzed. Interviews followed by a rigorous coding process provide valuable insights into the practical implementation of AI-enabled marketing practices for the Indian FMCG industry.

The study’s results underscore the importance of AI in enhancing marketing practices for FMCG firms, particularly in four critical areas: personalization, consumer engagement, marketing automation and strategic goals. By adopting AI in these areas, Indian FMCG firms can significantly enhance their marketing capabilities, increasing efficiency, effectiveness and gaining a competitive advantage.

The study uses qualitative data analysis to explain how DC through AI technologies can enhance digital marketing practices for Indian FMCG organizations. Furthermore, the study provides valuable insights into how AI technologies can improve marketing capabilities and emphasizes the importance of DC. The study also proposes a framework for AI-enabled Marketing 4.0 that can guide FMCG firms seeking to leverage AI technologies to enhance their marketing practices.

This study outlines the potential for enhancing marketing practices by adapting AI in the Marketing 4.0 environment for Indian FMCG companies, highlighting the importance of DC in achieving this goal.

Digital technology's integration into education has transformed learning frameworks, necessitating the exploration of factors influencing students’ engagement in digital informal settings. This study, grounded in self-determination theory (SDT), proposes a model comprising artificial intelligence (AI) competence, chatbot usage, perceived autonomy (PA), digital informal learning (DIL) and students’ engagement.

The study collected survey data from 409 participants at Saudi Arabian universities, ultimately using 387 valid responses for analysis. This dataset was subjected to a thorough examination to confirm the validity of our proposed model. To decipher the complex interactions within our model, we utilized partial least squares structural equation modeling (PLS-SEM). The study adopted a disjoint two-stage method to formulate a reflective-formative higher-order construct (HOC).

The study's findings showed that cognitive learning (CL), metacognitive learning (MCL) and social and motivational learning (SML) are the essential components of DIL. Significantly, the study determined that AI competence, chatbot usage, PA and DIL markedly affect students’ engagement. Moreover, the R² value of 0.592 for student engagement indicates the model's robustness in explaining 59.2% of the variance, highlighting its effectiveness in identifying key drivers of student engagement in DIL contexts.

This research enhances understanding by detailing the intricate relationships among AI competence, chatbot usage, and students’ engagement in informal digital learning. It extends SDT to emphasize intrinsic motivations and AI capabilities, introducing reflective-formative HOCs for comprehending educational intricacies. It provides practical strategies for enhancing AI abilities and chatbot use in education, promoting personalized, engaging and autonomous digital learning spaces, thereby advancing educational theory and practice.

Key core technology is the most important weapon of the country, and breaking through the “strangled” problem is one of the real problems that China’s emerging industries and enterprises must solve. Accurately identifying the “strangled” problem will help China accelerate the realization of high-level scientific and technological self-reliance and win the battle against key core technologies.

Combined with the characteristics of key core technologies, the key core technology evaluation system was constructed from four dimensions: technology innovation, technology radiation, technology economy and technology safety. We adopt the entropy TOPSIS method to evaluate the patents, and the patents with the top 5% scores are identified as key core technology patents. Then, this study identifies key core technology “strangled” problems in three dimensions: technology value advantage, competitive advantage and quantitative advantage.

Taking the patent data of the global new generation information technology industry from 2011 to 2023 as a sample, 178 moderately “strangled” technologies and 49 severely “strangled” technologies are selected. The study results are consistent with the current situation of the new generation information technology industry’s development, and verify the feasibility and reliability of the key core technology “strangled” problem identification model.

This study uses patent data to identify key core technologies and “Strangled” in the new generation information technology industry. It can provide a reference for relevant national departments and agencies, as well as universities and enterprises.

This paper follows the call for more future-oriented practices within organisations, particularly in relation to how they respond to growing concerns about Earth’s sustainability and life on the Planet. This study aims to explore how the data produced by major scientific projects in the Space sector can support future-oriented accountability practices by enabling both a projection and an imagination of a more or less distant future, thereby feeding into accountability practices.

We rely upon a multiple interpretative case study analysis and interview-based data from three main organisations in the Earth observation (EO) value chain: an International Space Company, a Research Centre of Energy Transition and a European Private Equity Firm.

We find that future-oriented accountability practices can be fed by a creative assemblage of scientific data provided by Space sector’s programmes with different sources of knowledge and information. These data are embedded into a broader accountability system, connecting different actors through a “value chain”: from the data providers, gathering data from Space, to the primary users, working on data modelling and analysis, to the end users, such as local authorities, public and private organisations. The predictive data and expertise exchanged throughout the value chain feed into future-oriented accountability efforts across different time-space contexts, as a projected and imagined, more or less distant, future informs the actions and accounts in the present.

This research extends the literature on the time dimension of accountability. We show how a creative assemblage of scientific data with different sources of knowledge and information –such as those provided by Space sector’s programmes and EO data – enable organisations to both project the present into (a more or less distant) future and imagine this future differently while taking responsibility, and accounting for, what could be done and desired in response to it. We also contribute to the limited literature on accountability in the Space sector by examining the intricate accountability dynamics underpinning the relationships among the different actors in the EO data value chain.

This study explores job search dynamics among employed individuals. We focus on factors related to employees initiating their job searches and changing its intensity.

We conducted a qualitative study with 41 employed job seekers using semi-structured interviews.

Our analysis reveals six catalysts that initiate employee job searches and nine modulators that influence fluctuations in job search effort. We highlight the significant roles of social actors, resource dynamics, and personal, professional, and environmental factors in shaping employees’ job searches.

The diverse sample strengthens theory building but may not represent all employed job seekers. Future research would benefit from longitudinal designs.

This study underscores the influence of social actors on employee job search processes. Our findings offer valuable insights for policymakers and employers seeking to support employed job seekers and proactively manage voluntary turnover.

This research advances our understanding of employee job search beyond its traditional role in voluntary turnover. By integrating Conservation of Resources (COR) theory, we provide a framework for understanding employee job search initiation and modulation.

The study aims to review how the use of technology enhances the authentic tourist experience. Technology and digitalization have enhanced tourist experiences. However, critiques comment on its ability to over-commercialize activity and lack of authenticity. Thus, there is a need to synthesize knowledge of technology usage to increase authentic tourist experience.

The study carries out a bibliometric review of the studies focusing on the use of technology in enhancing tourist experiences. Two hundred journal articles, published between 1997 and 2023 were retrieved from the Web of Science (WoS) database to carry out descriptive and network analysis using the Gephi, VOSviewer and Science of Science (Sci2) software. The components of authentic tourism experience are identified from the literature through a content analysis.

The findings of the study are broadly classified into two: first, the most frequently used keywords in the study include tourist experience and satisfaction, co-creation, virtual reality, smart tourism, technology, authenticity and heritage tourism. Second, the five major themes studied in the topic include virtual reality and tourist experience; media, tourist experience and encounters; technology, smart tourism and tourist experience; digital transformation, social media and tourist experience; and virtual reality and tourist experience which are still relevant in the literature because of the presence of study gaps.

The findings are used to develop a conceptual framework for the role of technology in enhancing authenticity in tourism typologies where authenticity is critical.

The paper aims to explore the sided challenges facing the accounting profession in an advanced digitalised future where humans and robots will collaborate in working teams.

Employing a qualitative approach, the paper conducts a reflexive thematic analysis to identify challenges and associated socio-ethical risks of digitalisation; it then introduces an ethical decision-making model aimed at addressing these challenges.

Key professional accountants’ (PAs) sided challenges refer to autonomy, privacy, balance of power, security, human dignity, non-maleficence and justice, each of them possessing multifaceted dimensions that are interconnected dynamically to create a complex web of socio-ethical risks.

The ethical decision-making pathways corresponding to each detected challenges provide a useful reference and guideline for PAs in the digitalised future of the profession.

Using an anthropocentric perspective, the research addresses the sided challenges of accounting profession’s accelerated digitalisation; it contributes to fostering accountability and legitimacy of the accounting profession which serves the public interest.

By innovatively intertwining ethical positions with decision-making pathways, the paper offers a potential solution to address digitalisation’s sided challenges that might interfere with practitioners’ professional judgement and identity.

To enhance the understanding of the antecedents of students' career adaptability, this study employs the crossover model to explore the potential transfer of career adaptability from headteachers to students and the underlying mechanisms involved.

This study examined the proposed moderated mediation model using matched survey data collected from 37 headteachers and 1,598 students in Chinese higher vocational colleges.

Headteachers’ career adaptability is positively related to students’ career adaptability via students’ psychological capital. An increased frequency of headteacher–student interactions strengthened the indirect relationship between headteachers' career adaptability and students' career adaptability.

The findings suggest that, under certain conditions, headteachers’ career adaptability could be transferred to students via students’ psychological capital.