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This paper explores who among the AACSB categorization of academics conducts the scholarship of teaching and learning (SoTL) research within business schools and how AACSB-accredited business schools capture SoTL research as part of their portfolio of intellectual contributions.

This study adopts a qualitative-method research design by collecting primary data through surveys, semi-structured interviews and secondary data in policy documents focused on AACSB-accredited business schools in Canada and the United States.

The findings establish that scholarly and practice academics who possess rigorously acquired research skills due to their terminal degrees are most likely to conduct SoTL research. The results also reveal an even split among respondents regarding whether their AACSB-accredited business school captures SoTL with their journal ranking frameworks.

Based on the findings, two recommendations are offered to foster more SoTL research at AACSB-accredited schools. First, higher education leaders (e.g. business school deans) can further inculcate a culture of SoTL research at the department and institutional levels by creating communities of practice (CoPs). Second, AACSB-accredited business schools could adopt more inclusive journal ranking frameworks to capture better and incentivize SoTL research.

This is the first known study to explore how AACSB Standards 3 and 8 are implemented and operationalized regarding SoTL research. Understanding how these standards are adopted and implemented could help institutional leaders, standard setters and administrators better facilitate SoTL research.

This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.

The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.

Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.

The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.

The purpose of this article is to theoretically outline and empirically test two contribution-based indicators: (1) the scholars' annual contribution-based measurement and (2) the annual contribution modified h-index, computing six criteria: total number of papers, computed SCImago Journal Rank values, total number of authors, total number of citations of a scholar’s work, number of years since paper publication and number of annual paper citations.

Despite widespread scholarly agreement about the relevance of research production in evaluation and recruitment processes, the proposed mechanisms for gauging publication output are still rather elementary, consequently obscuring each individual scholar’s contributions. This study utilised the Technique for Order of Preference by Similarity to Ideal Solution method, and the authors built two indicators to value author's contribution.

To test both indicators, this study focussed on the most productive scholars in communication during a specific time period (2017–2020), ranking their annual research contribution and testing it against standard productivity measures (i.e. number of papers and h-index).

This article contributes to current scientometric studies by addressing some of the limitations of aggregate-level measurements of research production, providing a much-needed understanding of scholarly productivity based on scholars' actual contribution to research.

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.

This article explores whether six broad categories of activities undertaken by Canadian business scholars’ academics: publications record, citations record, teaching load, administrative load, consulting activities, and knowledge spillovers transfer, are complementary, substitute, or independent, as well as the conditions under which complementarities, substitution and independence among these activities are likely to occur.

A multivariate probit model is estimated to take into account that business scholars have to consider simultaneously whether or not to undertake many different academic activities. Metrics from Google Scholar of scholars from 35 Canadian business schools, augmented by a survey data on factors explaining the productivity and impact performances of these faculty members, are used to explain the heterogeneities between the determinants of these activities.

Overall, the results reveal that there are complementarities between publications and citations, publications and knowledge spillovers transfer, citations and consulting, and between consulting and knowledge spillovers transfer. The results also suggest that there are substitution effects between publications and teaching, publications and administrative load, citations and teaching load, and teaching load and administrative load. Moreover, results show that public and private funding, business schools’ reputation, scholar’s relational resources, and business school size are among the most influential variables on the scholar’s portfolio of activities.

This study considers simultaneously the scholar’s whole portfolio of activities. Moreover, the determinants considered in this study to explain scholars’ engagement in different activities reconcile two conflicting perspectives: (1) the traditional self-managed approach of academics, and (2) the outcomes-focused approach of university management.

This study aims to explore the evidence-based usage patterns of higher education commission (HEC) subscribed e-journal databases in the university digital library used by the scholarly community and the academics’ online searching behaviour at a higher education institution in Pakistan.

The study used an explanatory sequential mixed methods approach. Raw transaction log data were collected for quantitative analysis, and the interview technique was used for qualitative data collection and thematic analysis.

Log analysis revealed that HEC subscribed databases were used significantly, and among those, scholarly databases covering various subjects were more frequently used than subject-specific society-based databases. Furthermore, the users frequently accessed the needed e-journal articles through search engines like Google and Google Scholar, considering them sources of free material instead of the HEC subscribed databases.

It provides practical implications for examining the evidence-based use patterns of e-journal databases. It suggests the need for improving the access management of HEC databases, keeping in view the usage statistics and the demands of the scholars. The study may also help create market venues for the publishers of scholarly databases by offering attractive and economical packages for researchers of various disciplines in developing and underdeveloped countries. The study results also guide the information professionals to arrange orientation and information literacy programs to improve the searching behaviour of their less frequent users and enhance the utilization of these subscribed databases.

The study is part of a PhD project and, to the best of the authors’ knowledge, is the first such work in the context of a developing country like Pakistan.

The purpose of this case study was to complement existing weeding and retention criteria beyond the most used methods in academic libraries and to consider citation counts in the identification of important scholarly works.

Using a small sample of items chosen for withdrawal from a small liberal arts college library, this case study looks at the use of Google Scholar citation counts as a metric for identification of notable monographs in the social sciences and mathematics.

Google Scholar citation counts are a quick indicator of classic, foundational or discursive monographs in a particular field and should be given more consideration in weeding and retention analysis decisions that impact scholarly collections. Higher citation counts can be an indicator of higher circulation counts.

The authors found little indication in the literature that Google Scholar citation counts are being used as a metric for identification of notable works or for retention of monographs in academic libraries.

The purpose of this study is to provide a comprehensive bibliometric analysis of publications in the Journal of Public Procurement (JoPP) from 2001 to 2021. The study provides insights into trends in publications, prominent publication themes, influential authors, institutions and countries that have prominently been associated with the journal’s journey.

The study used a bibliometric and content analysis approach using the VOSviewer software to develop insights into the trends, structures and patterns in publications in the journal. Data for the study was extracted from the Scopus and Google Scholar databases.

The study established that there has been consistent growth in the number of papers published by the journal within the last two decades. Yearly average publication by the journal stood at 14 papers between 2002 and 2009, with the annual average rising to approximately 18 papers between 2010 and 2021. The trend in publication has been established and identified the influential citations and contributors to the journal. The study has also clustered out the thematic structures in journal’s publications. The prominent and emerging research issues in the public procurement environment needing immediate research attention have been highlighted.

The study is a one-journal bibliometric analysis and subsequently ignores publications on public procurement from other journals.

The findings of this study highlight to the research community the contributions of JoPP to the public procurement discourse and present important avenues for future research agenda.

To the best of the authors’ knowledge, this study is the first bibliometric study for the JoPP, providing detailed bibliometric indexes of the 21-year period of the journal’s publications. The study comprehensively analyses the contributions in the JoPP to assess the trend and scope in publications in the field of public procurement and draws attention to emerging concerns and critical issues of neglect requiring research attention in the journal.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

The purpose of this study is to address the lack of a proper database or finding system for scholars of Islamic economics (IE), as well as the dearth of literature on bibliographic search and trend analyses of scholars in this field. This study aims to adopt a bibliometric review of the bibliography of experts in IE and scholars in disciplines allied to IE.

This study adopts a bibliometric review of the bibliography of experts in IE and scholars in disciplines allied to IE. The researchers collected data on scholars’ profiles and scholarly works and analyzed them to identify trends and patterns.

This study presents two main themes: the profiles of the scholars in IE and allied disciplines, and their scholarly works. The findings on the scholars’ profiles reveal that most scholars are contemporaries born between the 1940s and 1990s, concentrated in Malaysia and affiliated with the International Islamic University Malaysia. Regarding their scholarly works, the majority of their efforts resulted in 11,736 materials in the form of books, articles and conference papers spread across 13 sub-areas in IE.

This study fills the gap in literature by providing a database and finding system for scholars in IE and conducting a bibliographic search and trend analysis of scholars in this field. The findings shed light on the profiles of scholars and their scholarly works, which can guide future research in this area.