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This paper explores emerging technologies in higher education libraries indexed in the Web of Science core collection and Scopus for the periods between 1994 and 2024 (January 18, 2024).

Data from Web of Science (WoS) and Scopus databases were collected and combined using RStudio software. Once this was completed using RStudio, the combined Scopus and Web of Science Excel file was uploaded into Biblioshiny, an interactive web interface. The data was then categorized to illustrate contributions from authors, journals, countries and academic institutions across the globe.

Results and findings related to publication growth trends, annual growth, core journals, impact and productivity of authors, most cited documents, collaborations, network mapping and country contributions on emerging technologies and higher education libraries are presented.

This topic requires further exploration as academic librarians are fast becoming integrated into the teaching and learning agenda of institutions globally.

Higher education libraries and library schools to promote the teaching identity of academic librarians by helping them improve their pedagogical and digital skills for online teaching.

Library and information science schools need to fast track the integration of emerging technologies into the curriculum. Higher education libraries should consider the training of staff in order to keep abreast of emerging technologies. Library management must frame their policies and strategies in order to promote the use of emerging technologies in higher education libraries.

The current study is novel in that it explores emerging technologies and higher education libraries using combined data from Scopus and Web of Science. The topic of emerging technologies and higher education libraries is still developing and therefore is in its infancy. The research is useful for researchers, library management and library schools in the higher education sector globally.

This paper aims to address three research questions (1) Who is the main stakeholder that shapes Airbnb experience, (2) Does Airbnb offers an authentic travel experience? and (3) What should be the future research trends in Airbnb?

This paper uses the systematic literature review (SLR) with a well-defined protocol, research strategy and methods to answer the research questions.

The review revealed that while Airbnb plays a significant role as the platform provider, the stakeholders influencing the experiences are multifaceted. Hosts, guests, local communities and even regulatory bodies all contribute to shaping the overall Airbnb Experience ecosystem. Hosts, in particular, have a crucial role in curating and delivering unique experiences, which significantly impacts the quality and authenticity of the offerings. On the question of whether Airbnb offers an authentic travel experience, the review uncovered mixed findings. For examples, some studies emphasized the potential for Airbnb to provide authentic and local experiences, allowing travelers to engage with the community and cultural aspects of a destination. However, other studies raised concerns about the commodification and standardization of experiences, leading to a potential loss of authenticity.

This paper is different from previous SLR where previous research systematically reviewed; motivations to use and choose Airbnb, institutionalization of Airbnb, stakeholders of Airbnb. This paper addresses authentic experience as a factor that influences activity participation.

This study analyses the literature on artificial intelligence (AI) and its implications for the agri-food sector. This research aims to identify the current research streams, main methodologies used, findings and results delivered, gaps and future research directions.

This study relies on 69 published contributions in the field of AI in the agri-food sector. It begins with a bibliographic coupling to map and identify the current research streams and proceeds with a systematic literature review to examine the main topics and examine the main contributions.

Six clusters were identified: (1) AI adoption and benefits, (2) AI for efficiency and productivity, (3) AI for logistics and supply chain management, (4) AI for supporting decision making process for firms and consumers, (5) AI for risk mitigation and (6) AI marketing aspects. Then, the authors propose an interpretive framework composed of three main dimensions: (1) the two sides of AI: the “hard” side concerns the technology development and application while the “soft” side regards stakeholders' acceptance of the latter; (2) level of analysis: firm and inter-firm; (3) the impact of AI on value chain activities in the agri-food sector.

This study provides interpretive insights into the extant literature on AI in the agri-food sector, paving the way for future research and inspiring practitioners of different AI approaches in a traditionally low-tech sector.