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This chapter explores the multifaceted relationship between quantum computing (QC) and sustainability, with a focus on the Quadratic Unconstrained Binary Optimisation (QUBO) framework. The manuscript delves into the theoretical underpinnings of QUBO and its formulation as a quantum annealing problem, identifying the quantum principles that facilitate the resolution of such optimisation challenges. It offers a critical analysis of the suitability of QUBO for unconstrained problems and its efficacy in consistently locating the global minimum – a pivotal concern in optimisation tasks. Further, this study provides a nuanced discussion on the intersection of QC and sustainability. It delineates the types of optimisation problems within sustainability initiatives that are amenable to formulation as QUBO problems, while also highlighting sustainability challenges that elude the QUBO framework. It argues for the integration of quantum solutions into business operations, highlighting the potential for QC to play a transformative role in achieving sustainability objectives. The critique of the current hype surrounding QC provides a balanced viewpoint, ensuring a grounded approach to the adoption of quantum technologies in tackling pressing global issues.

This study examined the role of artificial intelligence (AI) tools in facilitating the accessibility and usability of electronic resources (e-resources) in academic libraries.

This study employed a quantitative descriptive survey to collect data from library users. The population targeted was sampled using a purposive sampling technique. A total of 427 (58%) participated in this study.

Most respondents preferred electronic journals (e-journals) among the e-resources stored in academic libraries. Chatbots were identified as preferred AI tools for accessing and enhancing the usability of these resources. Strategies mentioned included the potential for integrating AI tools across various e-resources. However, among the challenges reported was the inability to integrate AI tools with the existing library management systems. Improving e-resource discovery and access can significantly enhance the effectiveness of AI tools in academic libraries.

Originality in the context of AI applications in academic libraries refers to the unique approaches, innovative tools and creative solutions that enhance the accessibility and usability of electronic resources. By focusing on unique solutions that enhance the accessibility and usability of e-resources, these libraries can better serve their diverse user populations and adapt to the evolving landscape of information needs.

The purpose of this study is to provide a holistic understanding of the factors that either promote or hinder the adoption of artificial intelligence (AI) in supply chain management (SCM) and operations management (OM). By segmenting the AI lifecycle and examining the interactions between critical success factors and critical failure factors, this study aims to offer predictive insights that can help in proactively managing these factors, ultimately reducing the risk of failure, and facilitating a smoother transition into AI-enabled SCM and OM.

This study develops a knowledge graph model of the AI lifecycle, divided into pre-development, deployment and post-development stages. The methodology combines a comprehensive literature review for ontology extraction and expert surveys to establish relationships among ontologies. Using exploratory factor analysis, composite reliability and average variance extracted ensures the validity of constructed dimensions. Pearson correlation analysis is applied to quantify the strength and significance of relationships between entities, providing metrics for labeling the edges in the resource description framework.

This study identifies 11 dimensions critical for AI integration in SCM and OM: (1) setting clear goals and standards; (2) ensuring accountable AI with leadership-driven strategies; (3) activating leadership to bridge expertise gaps; (4) gaining a competitive edge through expert partnerships and advanced IT infrastructure; (5) improving data quality through customer demand; (6) overcoming AI resistance via awareness of benefits; (7) linking domain knowledge to infrastructure robustness; (8) enhancing stakeholder engagement through effective communication; (9) strengthening AI robustness and change management via training and governance; (10) using key performance indicators-driven reviews for AI performance management; (11) ensuring AI accountability and copyright integrity through governance.

This study enhances decision-making by developing a knowledge graph model that segments the AI lifecycle into pre-development, deployment and post-development stages, introducing a novel approach in SCM and OM research. By incorporating a predictive element that uses knowledge graphs to anticipate outcomes from interactions between ontologies. These insights assist practitioners in making informed decisions about AI use, improving the overall quality of decisions in managing AI integration and ensuring a smoother transition into AI-enabled SCM and OM.

Global warming and climate change are significant barriers to food production due to rising temperatures and extreme weather events. Thus, some households have taken to producing organic food on their rooftop gardens to mitigate the aforementioned challenges, which could improve the green environment and reduce carbon dioxide emissions. Given the emergence of this trend, this study aims to predict organic food production intention and behaviour within urban rooftop home gardens using an integrated model of the value-belief-norm (VBN) theory and theory of planned behaviour (TPB).

Study data were collected from 352 households in two major Bangladeshi cities and analysed through SEM-PLS for model assessment and prediction.

Resultantly, biospheric and egoistic values led to an improved ecological worldview (EP). The EP, awareness of consequences (ACs) and social norms (SNs) predicted personal norms (PNs). In addition, PNs and SNs forecasted the intention to produce organic food in urban-area rooftop gardens. Strong intentions could promote and predict the adoption of organic food production in rooftop gardens. Based on the study outcomes, PN partially mediated the relationship between SN and the intention to produce organic food. Furthermore, the value–behaviour nexus performed serial mediation through beliefs, norms and intentions.

In this vein, the VBN framework provided a comprehensive guideline to encourage the intention and behaviour of organic food production in urban-area rooftops. Education and public policies potentially leveraged public beliefs and norms to engage in climate-friendly activities.

Cultivating organic herbs and vegetables on rooftop reduces dependency on industrially produced food and fertilised crops, making it a sustainable food choice and climate-mitigating activity. Thus, this study focuses on rooftop organic food production as a lens to examine pro-environmental intentions and behaviours. In addition, past studies have not emphasised the mediating roles of environmental beliefs, PN and intentions between the value–pro-environmental behaviour nexus. Such paths could be interesting to observe and add value to the VBN model. This study investigated the mediating roles of environmental beliefs, PN and intentions between the value–pro-environmental behaviour nexus and the role of PN between SN and pro-environmental behavioural intention with VBN farmwork.

This review paper examines the germaneness of libraries in sustaining information technology services, rethinking towards implementing futuristic strategies and the significant sustainability factors related to information technology (IT) services, identifying gaps in the existing studies and suggesting future areas of research work.

The study adopted a systematic literature review (SLR), in which 81 articles were identified and utilised for the paper. The inclusion and exclusion research design was used for the study.

The role of libraries in sustaining information technology services is increasingly crucial as they evolve into dynamic IT hubs, addressing the growing digital needs of users. This transformation involves integrating advanced technologies like cloud computing, artificial intelligence (AI), Internet of Things (IoT) and machine learning to enhance access and usability of information. Libraries support academic research and education by offering extensive digital archives and research databases, thereby fostering innovation and learning. They also play a vital role in community engagement by providing digital literacy programs and IT training, thus bridging the digital divide. Embracing sustainable IT practices and adapting to technological advancements ensure that libraries remain relevant and effective. However, these initiatives require significant investment in infrastructure and continuous staff training. The results highlight the complexity of maintaining sustainable library IT services and support an active, cooperative, and user-centred strategy.

Despite the importance of libraries in providing IT services, there is a lack of research on the germaneness of libraries in sustaining IT services (DSpace, 2022). The number of research publications on these topics has grown since the late 1990s and is increasing. However, contrary to the vast number of research publications, there are few literature reviews on libraries’ sustainability and information technology. Moreover, little is known about the germaneness of libraries in sustaining IT services.

Libraries’ roles in sustaining IT services and implementing futuristic strategies underscore their evolving importance in contemporary society. Libraries are not just centres of learning but are integral to community development, technological advancement and social inclusion. Rethinking and innovating their approach to IT services, libraries continue to serve as vital hubs of development and engagement, significantly benefiting communities worldwide. Furthermore, by addressing a significant research issue, creating creative solutions, stressing teamwork and supporting an all-encompassing strategy for maintaining library IT services. It is a stimulant for more study and cooperative initiatives to achieve sustainable library and information science development.

Libraries, both public and academic, have expanded their roles to become crucial hubs of innovation and business support. To cater to the emerging needs of the patrons, including entrepreneurs, libraries must digitally transform to innovate their business support services. This research aims to empirically validate the factors influencing the adoption of generative AI technologies (or switching intentions), particularly ChatGPT, among librarians providing business support services. The study explores the multifaceted factors that shape librarians’ decisions to adopt these technologies or consider alternative solutions.

The research study employed purposive or convenience sampling to select librarians actively supporting businesses and with some experience in generative AI technologies. After pilot testing the questionnaire, it was refined and administered via Google Forms, utilizing a Likert scale for responses. Informed consent was obtained from participants, with strict privacy protocols in place. Data analysis was conducted using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4 software, adhering to rigorous quality assurance protocols.

The research empirically validated key factors influencing the adoption or switching intentions toward generative AI technologies, particularly ChatGPT, among librarians supporting entrepreneurs. Identified factors encompass social influence, domain expertise, familiarity with technology, system quality, training and support, interaction convenience, anthropomorphism, perceptions of usefulness, ease of use and enjoyment. These perceptions influence librarians’ emotional responses to technology and affect their decisions regarding adoption or considering alternative options. Notably, demographic variables – age, gender, years of experience in business support and education level – do not significantly influence switching intentions, underscoring inclusivity in innovation.

The study offers practical implications for various stakeholders, including librarians, patrons, technology providers and policymakers. Librarians can benefit from fostering interdisciplinary collaborations and co-creation initiatives to strengthen social networks, enhance domain expertise, evaluate technology quality and customize training support. Technology providers have the opportunity to improve user experience by enhancing interaction convenience and anthropomorphism. Policymakers can support innovation within library settings through funding initiatives and changes in employment conditions. These recommendations aim to enable the seamless integration of generative AI technologies in libraries while fostering stakeholder collaboration to drive innovation and address evolving user needs.

This research enriches AI technology adoption theories within library contexts by providing empirical evidence and insights into the multifaceted dynamics influencing adoption decisions among librarians. It enhances existing theories by specifically focusing on generative AI adoption and its implications for library business support services. Despite the growing interest in AI technologies within library settings, empirical research on the factors influencing librarian decisions regarding generative AI adoption has been lacking. By addressing this gap, the study contributes to the fields of library and information sciences, entrepreneurship, technology management and innovation management, offering specificity and depth to our understanding of user decision-making processes.

This paper is the genesis for robots and robotic technology and their introduction to the Caribbean Academic library community. This paper aims to explore the specific areas that this technology can improve as well as their adaptability and dynamic yet multifaceted nature it possesses.

A thorough assessment of literature was done of all developed libraries that are employing the services of robots and robotic technology in their daily operations. Additionally, a meticulous analysis was done of all Caribbean Libraries that have explored, are currently exploring or actively explored the implementation of robots and robotic technology for effective use in their libraries.

Seamless functionality as well as the reduction of mundane repetitive tasks by library staff is at the fore. Efficacy and heightened levels of accuracy are also found to be a great factor for implementation as well as speed of retrieval and offsite storage are further benefits to the implementation of robots and robotic technology.

This research primarily assessed material on robotics and robotic technology that offers unprecedented efficacy and accuracy in the processing of information and tasks assigned as well as smooth location and retrieval of library material resulting in reduction in wait time for all library users.

To the best of the author’s knowledge, this paper is the first of its kind and is intended to trigger a “light bulb” in the minds of decision-makers and managers of Library spaces as to the potential robots and robotic technology has on fostering greater levels of efficacy in certain key areas of libraries and help improve user services while adding to the theoretical body of knowledge available in the field on this fast rising area.

The purpose of this paper is to provide answers regarding the factors that motivate or discourage the quadruple helix (QH) stakeholders and the wider public in citizen science (CS) activities. The research reveals a current overview of the perceptions, attitudes, concerns and motivation with regard to development of CS ecosystem in four countries: Greece, Lithuania, the Netherlands and Spain.

The researchers deploy a mixed methodology, entailing an in-depth literature review and a large-scale quantitative survey (approximately 2,000 citizens) targeting QH stakeholders and general public from the local national ecosystems. The results contain both descriptive statistics and statistical analysis per country. After the comprehensive overview of drivers and barriers regarding the participation in CS activities in general, the focus is narrowed down on the engagement motivation of different QH stakeholders and the differences in enabling/hindering factors at the local ecosystems.

Depending on the country and the pre-existing level of CS maturity, the results provide a complicated network of factors that unlock or block participation in CS activities. These factors include, to name a few, political maturity, civic engagement, technological infrastructures, economic growth, culture of stakeholder collaboration, psychological stimulus and surplus of resources. The implications of the findings necessitate the alignment of the envisioned CS ecosystem with the local dynamics in each country.

The quantitative nature of the survey method, limited sample size and only four countries context are noted as limitations of the study and offer future research potential for longitudinal settings and mixed-methods studies.

The results contribute to the wider literature on CS that focuses on perspectives, possibilities and differences in local contexts with respect to the public engagement by developing CS ecosystem. At the same time, its added value lies in the overall practical proposition, and how the latter can effectively and efficiently attract and retain different stakeholder groups and citizens, under a collaborative approach.

This study aims to examine the nature and extent of political dynamics (power struggles and contestations) among internal and external school stakeholders in the school evaluation processes and their influence on the objectivity and consistency of evaluations.

This study used a purposive sampling method to examine seven secondary schools in Dodoma Region, which were key in piloting the School Quality Assurance (SQA) policy implementation in 2018. The selected schools were government boarding institutions with long histories, managed by School Management Teams and Governing Boards that influenced school decision-making. These schools had regular SQA visits and produced School Self-Evaluation and Whole-School Evaluation reports, which served as the primary data sources. Data were analysed using a method that involved sorting, coding, identifying patterns and applying theory to interpret the findings. The analysis focused on discrepancies and power dynamics in school evaluations, particularly how internal and external evaluators’ roles were represented in the reports. Ethical considerations were ensured through confidentiality, pseudonymizing participants and obtaining clearance from relevant authorities. This study’s reliability and trustworthiness were enhanced through consistent data collection protocols, a transparent coding framework and triangulation of sources. This research offers insights into the politics of SQA policy implementation, highlighting tensions and power dynamics in school evaluations and revealing gaps between policy and practice.

This study identifies the SQA policy discourses that were tools and sites of power struggles and contestations among internal and external evaluators in all six quality domains. These political dynamics impacted the objectivity and consistency of evaluation outcomes due to subjectivity among evaluators. Internal evaluation had a positive image by offering higher quality indicators than external evaluation in most case study schools.

Policy documents provide a high-level overview, often missing the nuanced realities of school implementation. While updated periodically, they may not reflect current practices or challenges. These documents typically present an idealized vision of education, which might not align with actual outcomes. Analysing them alone can overlook the perspectives of teachers, students, parents and other stakeholders directly impacted by the policies. Informal practices and adaptations in response to policy directives may not be documented, and the interpretation of such documents can vary widely, leading to subjective analysis. In addition, policy documents lack empirical data on the effectiveness and impact of the policies.

This study highlights the need for clear and consistent evaluation criteria to reduce discrepancies between internal and external evaluators. It also underscores the importance of training and support for school-based evaluators to ensure reliable assessments. Moreover, this study calls for addressing political dynamics influencing evaluation objectivity, ensuring that evaluations genuinely reflect school performance. Finally, the findings advocate for involving all stakeholders in the evaluation process to enhance transparency and accountability.

This study has important social implications. It reveals how political dynamics can affect the fairness and transparency of school evaluations, potentially impacting stakeholders’ trust in the education system. This study highlights the need for equitable and unbiased evaluation practices to ensure that all schools are fairly assessed and supported. This can lead to better educational outcomes, as schools receive appropriate feedback and resources. Moreover, involving community members in the evaluation process can foster greater accountability and community engagement in educational development.

This study provides original value by addressing the intersection of political dynamics and educational evaluation. It uniquely examines how power struggles and political influences affect the objectivity and consistency of quality assurance practices. By highlighting discrepancies between internal and external evaluators, this study offers fresh insights into the challenges of implementing educational policies. This research contributes to the broader discourse on educational reform by advocating for more transparent and equitable evaluation processes, thereby enhancing policy effectiveness and educational outcomes.

This paper aims to design the digital transformation model for university libraries based on the Delphi method using the Iranian public university libraries as the study case.

A qualitative approach and the Delphi method were used to conduct the current research. In total, 15 experts in the field of digital transformation of libraries were selected through targeted and snowball sampling. They were asked to complete and finalize items identified from previous research to design a digital transformation model for public university libraries in Iran during successive Delphi rounds. The Delphi method was completed after the third round, upon reaching a favorable consensus.

The findings obtained from the research led to the presentation of the model in 7 main dimensions, 25 concepts and 139 components. Meanwhile, the concept of “data-centered” and changing the concept of “optimal reorganization of library resources” to the concept of “acquisitions and optimal reorganization of library resources” are among the new achievements of this research. In addition, the components of “promoting data-oriented thinking in the decision-making of library managers,” “encouraging employees to use and analyze data” and “planning to increase the digital literacy of librarians” were added to the concept of “data-oriented”; the components of “having knowledge of digital collection and its rules for the correct identification and evaluation of resources,” “familiarity with digital metadata standards and data transfer standards” and “familiarity with open access platforms” were added to the concept of “librarian knowledge competencies”; and the components of “planning, coordination,” “monitoring and evaluating the progress of library digital transformation projects” and “collaboration and networking with other academic library managers” in the concept of “library manager’s management skills”; the components of “identification of new digital formats and resources,” “creation, preparation and accessibility of game scientific content and free in the library,” “updating the resource organization policy with new organization concepts and rules” and “updating the library collection development policy based on the information needs of users” were added to the concept of “acquisitions and optimal reorganization of library resources” and “Web 2.0 technologies” component were added to the concept of “use of digital technologies in the library.”

This study is limited to Iranian public university libraries, and the findings may not be directly transferable to other contexts. In addition, the Delphi method, while effective for expert consensus, relies on subjective opinions and may not fully capture the complexities of digital transformation. Future research could explore the implementation challenges of the proposed model and its long-term impact on library services and user satisfaction. Despite these limitations, the study offers a valuable foundation for digital transformation initiatives in Iranian university libraries and can inform policy decisions and resource allocation.

The proposed digital transformation model offers practical guidance for Iranian university libraries. By implementing the model, libraries can enhance their services through data-driven decision-making, improved resource management and the adoption of new technologies. Librarians can develop the necessary digital competencies to effectively manage digital collections and engage with users. In addition, the model emphasizes the importance of collaboration among library managers, fostering knowledge sharing and best practices. Ultimately, the practical application of this model can lead to more efficient, user-centered and innovative library services.

The proposed digital transformation model for Iranian university libraries holds significant social implications. By enhancing access to information and resources, it can democratize knowledge and foster innovation. Increased digital literacy among librarians will equip them to better serve diverse user communities. However, equitable access to digital services must be ensured to prevent the widening of the digital divide. The model’s focus on data-driven decision-making can improve resource allocation and user satisfaction. By promoting collaboration and knowledge sharing, libraries can become more central to their communities and contribute to regional development. Ultimately, the success of this model depends on addressing potential challenges such as privacy concerns, digital security and the need for ongoing training and support.

The proposed model, with its 7 main dimensions, 25 concepts and 139 components, provides a roadmap for enhancing library services, resource management and decision-making. By emphasizing data-centered approaches, promoting digital literacy among librarians and integrating Web 2.0 technologies, libraries can adapt to the evolving needs of users. Collaboration and networking with other academic library managers can foster knowledge exchange and collective problem-solving. By implementing the proposed model, libraries can adapt to changing user needs, enhance services and contribute to the academic community’s success. However, implementing this model requires addressing challenges related to equity, privacy and accessibility, ensuring that all users benefit from the digital transformation. Overall, this research serves as a valuable resource for university library managers, guiding them toward effective digital adaptation and improved user experiences.