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The present study aims to investigate levels of awareness and use of Web 2.0 tools by librarians in the university libraries of East Azerbaijan (EA) in Iran and to determine how librarians use these tools in everyday life.

A Web-based questionnaire was used to collect data from 38 per cent librarians in the university libraries of EA.

The research findings indicate that the librarians were more familiar with Web 2.0 tools such as wikis and blogs. While librarians widely use blogs and wikis, tools such as social bookmarking, social networks, RSS feeds, instant messaging and digital maps were less frequently used. Results obtained from present study indicated that librarians use Web 2.0 tools mostly to communicate with friends and family, to keep up-to-date, to collaborate with colleagues and for curiosity and fun. Also, librarians believe that Web 2.0 tools can be used mostly for sharing information about library resources. Internet filtering, lack of access to high-speed internet and lack of training were the major obstacles for Web 2.0 adoption by librarians.

This study is a useful source for implementing Web 2.0-based technology in libraries. Also, this study will help managers understand the librarians’ needs about Web 2.0 to improve their library services.

This study carries out a systematic literature review (SLR) on responsible management education (RME). A total of 174 publications listed on the Scopus database addressing RME, published between 2007 and 2022 (inclusive), have been analyzed.

The articles included in the study were searched based on relevant key terms in the title, abstract and author keywords associated with each publication. The analysis led to the identification of the most relevant sources, authors and publications that can be used to circumscribe RME. Selected studies were analyzed using the Bibliometrix R-tool.

This study shows how three interrelated levels of analysis—namely, conceptual, intellectual and social—allow researchers to further organize the data to produce rich content for the RME. The contribution of this study is twofold: first, our values-based approach helps overcome the axiological ambiguity of the principles for RME (PRME), which invoke the importance of incorporating “the values of global social responsibility” (Principle 2) but fail to define and operationalize these values. Second, the authors provide a rationale and guidance for implementing values-based RME in business schools.

This study offers a unique SLR on RME. It gives a clear picture of this field by talking about what has been done and what the future might hold for RME.

This study aims to investigate the everyday life information seeking behavior of transgender people in Pakistan.

A quantitative study, based on a survey design, was conducted to explore the everyday information needs of transgender people along with the types and frequency of using information sources. This study further explored the barriers to seeking everyday life information. Data were collected from 378 transgender people from Pakistan.

Music related information was the most important daily life information need and television appeared as one of the primary information sources frequently consulted by the transgender people. The respondents revealed a variety of challenges in accessing information including lack of education, lack of understanding about available information sources, biased treatment by the public and lack of technological skills. Furthermore, a statistically significant difference was found in everyday information needs and sources consulted on the basis of their age and education.

The findings provide a guideline to educate information providers, government agencies and other stakeholders about the information needs of this marginalized community in Pakistan. This study also suggests ways in which stakeholder may improve information systems and services to better assist transgender people.

The purpose of this paper is to review the extant research literature on omnichannel retailing and map the research trends in this field through a bibliometric analysis and network visualization exercise.

This paper employs bibliometric analysis techniques on research literature retrieved from the Scopus and Web of Science databases over the period 2013–2020 and assesses indicators such as research production and citation trends, top contributing authors, countries, journals and organizations through tools offered by the Scopus/Web of Science databases as well as Biblioshiny. A network visualization analysis of patterns such as keyword co-occurrences and co-authorship linkages between contributing countries has been investigated through the use of VOSviewer.

The bibliometric analysis indicates that research in this field is currently dominated by USA and China with Germany and UK also being key contributors. The analysis has indicated that the field of omnichannel retailing straddles multiple domains such as logistics, distribution, operations and consumer behavior, thereby offering significant future scope for research linking omnichannel retailing with these subject areas.

This study maps the structure of research done in the field of omnichannel retailing and outlines the key contributors in terms of authors, journals and organizations that can serve as an input for future research. The study also identifies possible avenues for future research in the knowledge domain of omnichannel retailing.

Significant interest in Integrated Management Systems (IMS), as a key area within ISO-related Management System Standards (MSS) literature, has been evident from both academia and industry over the past three decades. This study aims to map the evolution and current state of IMS research and propose possible directions for future studies.

A comprehensive content and bibliometric analysis of 846 documents from the Scopus database across the period 1995 to 2023 was conducted. This included performance analysis to track publication trends and identify key contributors, and content analysis to specify dominant research methodologies and the MSS most commonly integrated. Furthermore, science mapping techniques—such as co-authorship networks, keyword co-occurrence analysis, and bibliographic coupling—were utilized to outline the collaborative networks and the conceptual and intellectual structure of the field.

The study identifies three principal IMS research themes: the practical implementation of IMS, their role in promoting sustainability and social responsibility, and their impact on continuous performance improvement. It also highlights the field’s evolution and key research constituents—including influential works, prolific authors, leading academic institutions and countries, and top publishing journals. It further reveals that IMS research exhibits strong collaboration across authors and countries, and a rich methodological plurality, notably with a marked increase in empirical surveys in recent years. Additionally, it identifies the most frequently referenced MSS for integration, prominently featuring ISO 9001, ISO 14001, and ISO 45001/OHSAS 18001.

This study is original in its application of a dual analytical approach—bibliometric and content analysis—to provide a holistic overview of IMS research. It offers new insights into the integration of diverse MSS and proposes several promising paths for future research. Among the most prominent are standardizing IMS fundamental specifications, conducting more empirical research with advanced methods to evaluate the effects of MSS integration, providing practical support for organizations in IMS implementation through tailored methodologies and tools, and exploring the potential of Industry 4.0 and 5.0 technologies to advance IMS practices.

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.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.