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This study aims to examine publications of supply chain management (SCM) researchers from across the world and maps the leadership role of authors and institutions based on how prolific they are in publishing and on network measures of centrality while accounting for the quality of the outlets that they publish in. It aims to inform stakeholders on who the leading SCM scholars are, their primary areas of SCM research, their publication profiles and the nature of their networks. It also identifies and informs on the leading SCM research institutions of the world and where leadership in specific areas of SCM research is emerging from.

Based on SCM papers appearing in a set of seven leading journals over the 15-year period of 2001-2015, publication scores and social network analysis measures of total degree centrality and Bonacich power centrality are used to identify the highest ranked agents in SCM research overall, as well as in some specific areas of SCM research. Social network analysis is also used to examine the nature and scope of the networks of the ranked agents and where leadership in SCM research is emerging from.

Authors and institutions from the USA and UK are found to dominate much of the rankings in SCM research both by publication score and social network analysis measures of centrality. In examining the networks of the very top authors and institutions of the world, their networks are found to be more inward-looking (country-centric) than outward-looking (globally dispersed). Further, researchers in Europe and Asia alike are found to exhibit significant continental inclinations in their network formations with researchers in Europe displaying greater propensity to collaborate with their European-based counterparts and researchers in Asia with their Asian-based counterparts. Also, from among the journals, Supply Chain Management: An International Journal is found to exhibit a far more expansive global reach than any of the other journals.

The journal set used in this study, though representative of high-quality SCM research outlets, is not exhaustive of all potential outlets that publish SCM research. Further, the measure of quality that this study assigns to the various publications is based solely on a publication score that accounts for the quality of the journals, as rated by Association of Business Schools that the papers appear in and nothing else.

By informing the community of stakeholders of SCM research about the top-ranked SCM authors, institutions and countries of the world, the nature of their networks, as well as what the primary areas of SCM research of the leading authors in the world are, this research provides stakeholders, including managers, researchers and students, information that is helpful to them not only because of the insights it provides but also for the gauging of potential for embedding themselves in specific networks, engaging in collaborative research with the leading agents or pursuing educational opportunities with them.

This research is the first of its kind to identify and rank the top SCM authors and institutions from across the world using a representative set of seven leading SCM and primary OM journals based on publication scores and social network measures of centrality. The research is also the first of its kind to identify and rank the top authors and institutions within specific areas of SCM research and to identify future research opportunities relating to aspects of collaboration and networking in research endeavors.

The purpose of this paper is to analyze author and methodological characteristics in top-tier publications in higher education. As the importance of research in the professoriate continues to grow and faculty face ratcheted-up expectations for prestige in their research, such data are important contextually and historically.

This descriptive study examines 587 articles within four top-tier higher education research journals from 2008 to 2012. Data were open coded and analyzed with a research team, resulting in an intercoder reliability of 0.96.

Results show most authors are assistant professors, overwhelmingly received PhD’s from very high research institutions (Carnegie classification), and currently work in similar institutions. Five degree-granting institutions accounted for 29.0 percent of publications in top-tier journals. Additionally, quantitative research accounted for 60.6 percent of published articles, with regression as the most commonly used analytic technique (34.7 percent).

This study examined only higher education faculty and institutions based in the USA as well as first authors.

These results are meant to provide baseline data for top-tier journals within higher education and might inform conversations about methodological acceptability, respectability of qualitative research, graduate education research requirements, journal editor trainings, and tenure and promotion criteria.

This paper provides an update to previous studies that examined publications in higher education within the last three decades. In addition, this study examines author characteristics, which previous studies have mostly excluded. This study offers empirical data to inform conversations about the state of research in top-tier publications within higher education.

The purpose of this paper is to develop and test a comprehensive model of personal and institutional input variables, composed of elements describing status‐based antecedents, job/organizational context antecedents, and individual level antecedents, which may contribute to the production of significant (top‐tier) research outputs in the management discipline.

The development and empirical examination of this model were done with two main goals in mind. First, the nature and degree to which certain factors lead to the production of top‐tier research productivity in the management discipline were explored. Second, it is hoped that information about these relationships could then be used by institutions and individuals so that they could better understand what it takes to adequately prepare faculty members to achieve increased productivity or, alternatively, to decide whether the goal of top‐tier research production is consistent with individual and institutional resources. As such, the results of this investigation should have interesting and potentially important implications for both academic status attainment and career success.

Hierarchical moderated regression analyses of 440 faculty records revealed that the status of current affiliation of the faculty member, editorial board membership, faculty rank, and the availability of doctoral students were related to top‐tier research productivity.

The findings from this study have important implications for the careers of management faculty at AACSB‐accredited business schools. Faculty at higher status institutions appear to enjoy a number of cumulative advantages due to increased social, human and cultural capital that support the production of top‐tier research. Additionally, faculty with doctoral student support and those with memberships on editorial boards seem to possess the resources and connections necessary to produce top‐tier research on a consistent basis. Future research should investigate institution‐specific inducements to research productivity (e.g. research support and remuneration) and the exact causal nature of the editorial board/productivity relationship.

Prior research has investigated status effects using broad categories as predictors, whereas this research uses interval values representing research‐based assessments of institution status rankings. Additionally, this research creates and tests a comprehensive causal model of research productivity antecedents.

In this paper, the authors use a new methodology, called paper affiliation index, to create finance journal ranking using expert judgment and research impact, both of which are based on secondary, objective measures, thus making it possible to produce lists every year without human manipulation at virtually no cost.

Bibliometrics. Python implementation.

A new ranking with 65 finance journals.

This procedure helps to reduce bias and to deal with known problems associated with current methodologies. The data used in the methodology comes from public sources; the procedure is therefore easily replicable. This methodology is not subject-dependent and thus can be transferred to other realms of knowledge. Once the bibliometric institutional data has been gathered, the procedure is not computationally costly: a Python implementation of the algorithm executes the whole computation in a few seconds. Results seem to correct the pernicious Matthew effect which is so evident in citation-based methods.

The institutional classification created includes all institutions that have contributed papers to the field of finance. The procedure helps to reduce bias and to deal with known problems associated with current methodologies. The data used in the methodology comes from public sources, the procedure is therefore easily replicable. The methodology is not subject-dependent and thus can be transferred to other realms of knowledge. Once the bibliometric institutional data has been gathered, the procedure is not computationally costly.

The performance analysis of top 50 management institutions of India is conducted to understand their efficiency in utilizing available resources. The importance of different indicators is investigated to identify most preferred strategies of top management institutions in the country in order to meet the expectations of all stakeholders. Artificial neural networks models are applied for pattern recognition and classification purpose using self-organized map algorithms. A huge reservoir of young generation is being trained every year to meet the demand of business in different sectors of economies. It becomes a matter of concern to know the performance of the management institutes to ensure the overall national progress, which can be done by enabling organizations to improve their efficiency and effectiveness, provided the right information and skills are served. Data envelopment analysis (DEA) and self-organizing maps are utilized together to take advantages of optimization and prediction capabilities inherent in each method, and they may be beneficial to assess institution’s competitive position and design their own strategies in order to improve. The paper aims to discuss these issues.

The DEA is used to understand the utilization of resources by institutions on the bases of efficiency scores. Due to a greater flexibility and adaptability, neural technique, i.e. self-organized map, which is an artificial intelligence-based technique, a popular unsupervised learning model with a capability to capture patterns from data sets, is used. In this study, various parameters like qualification of faculty, research output of faculty members, expenditure made for functioning of the institution, etc., are considered. These academic and operational indicators are investigated in relation to the rank score and the efficiency score of top management institutions, and different strategies as a combination of input as well as output indicators are identified.

In the analysis, three types of strategies are identified. At present, the focus on salary packages of graduates seems the most utilized strategy. It is also observed that the strategy of having good performance, in terms of consultancy, peer and employer perception, has the highest success rate (in terms of score used for ranking). Results obtained using both techniques shows that due to high deviation and less explored research publications and sponsored research project is an opportunity that institutions can work upon to have maximum output. But to maintain consistency in terms of the high rank score and efficiency score, management institutions need to focus on consultancy, peer and employer perception.

This research identifies the different parameters categorized into various inputs and outputs for the management institutions in India for the benchmarking. It studies the importance of identified parameters in terms of success (rank score and efficiency score). Further investigation of relationship between parameters and success is conducted. Different strategies as a combination of parameters are identified. The current choice of top management institutions is revealed in terms of their preference and effectiveness of strategy. This research also provides some insight about long-term and short-term strategies, which may be beneficial to education managers or decision makers.

It is one of the rare papers in terms of performance measurement through data envelopment method and identification of strategy using artificial intelligence. This paper utilized a hybrid methodology that integrates these two data analytic methods to capture an innovative performance and strategies prediction in education system.

The study aims to investigate returns on investment (ROI) from the academic library of India's top ten leading university libraries in terms of research publication. Librarians help academic researchers in a variety of ways. Some of these methods are collection oriented, whilst others are service oriented. The study investigates many factors responsible for the increased or decreased institutional ROI, performance and research out of the institution, such as total library budget, staff, library collection, service and facilities. The ROI % shows the institution's highest and lowest investment return in research publication.

The study is expiation about ROI from the academic library of India's top ten leading university libraries in terms of research publication. The study is based on primary and secondary data gathered from the Ministry of Education, Government of India and universities ranking in June 2020. The data were compiled from the ranking list regarding total library budgets, staff and research publications for 2017–2020. The research is limited to a ROI analysis of university libraries. The study should aid libraries in better understanding the idea of ROI in order to improve library services. The study then looked at various institutions' ROI from 2017 to 2020.

The study aims to investigate ROI from the academic library of India's top ten leading university libraries in terms of research publication. This study investigates many factors responsible for the increased or decreased institutional ROI, performance and research out of the institution, such as total library budget, staff, library collection, service and facilities. The study found that the overall highest research output is by the Indian Institute of Science and the lowest by Jamia Millia Islamia among the ten leading university libraries in India.

The ROI study displays the importance of libraries in terms of research publication of the institutions. This research can also support decision-making, library collection development and institutional library system analysis. The library can assist with publications, sponsorships, grants, finances and teaching enhancement research output. The last point justifies the library's increased importance in establishing an organisation's status and obtaining accreditation.

The purpose of this paper is to highlight the use of big data through patentometric insights for R&D decision-making.

This study assesses the inventive activity through ‘big data’ patents, registered by inventors worldwide, using WIPO Patentscope database. The objective is to use the insights from patentometrics for R&D decision-making. The data from WIPO PatentScope (https://patentscope.wipo.int/search/en/search.jsf) was searched for current patent scenario in area of ‘big data’. The data was further organized and cleaned using the Google ‘OpenRefine’. Data was pre-processed to remove all null values. Cleaned data was analyzed using programming language ‘R’, MS Excel (charts and Pivot tables) and free data visualization tool called ‘Tableau Public’, to get insights for R&D decision-making.

The key insights included trends (patents with years of publication), top technologies trending the current space, top organizations leading in these technologies and the top inventors who are publishing patents in these technologies through leading organizations were drawn. Details in Section 5 in the paper.

Global patent data is multi-lingual and spreads across a set of multiple databases. Domain experts may be required to assess, identify and extract the relevant information for analysis and visualization of multi-lingual distributed data sets. Government organizations generally have multi-dimensional goals that may be more toward societal benefits. On the other hand, the commercial companies are more focused on profit. Therefore, the performance management process has to be really effective because it is critical for getting value in the government sector.

Insights from patent analytics serve as the important input to R&D managers as well as policymakers to assess the global needs to plan the national orientation according to the global market. This will help further for R&D projects prioritization, planning, budget allocations, human capital planning and other gamut of R&D management and decision-making.

Facilitation for R&D institutions (government as well as private) to formulate the research strategy for the domains or research areas to delve into. R&D decisions will be completely data-driven making them more accurate, reliable, valid and informed. These insights are very relevant for policymakers as well to facilitate the need assessment to determine the National priorities, make improvements in meeting societal country-level challenges during the resource allocation at top and subsequently at all other levels.

Data analytics of global patents in “big data” till 2019 to get insights to facilitate R&D decision-making.

We examine the citations from four international business (IB) journals over 2000‐2004 to show the areas, the journals, and the institutions that impact IB research. The leading works that influence IB research are primarily management journals, scholarly books, and IB journals. IB research is published in non‐IB journals, as well and this has influenced the recent research in IB journals. U.S. and non‐U.S. academic institutions and non‐academic organizations are among the top 100 institutions that impact IB research, indicating that this research is a truly global endeavor. Finally, recent IB research is influenced more by recent published research than by past research. Scholarly books have become less influential, while the economics, finance, and marketing journals show no change in the influence on IB research over time.

What academic and managerial elements are particularly influential regarding performance? This study aims to address these questions as part of a broader longitudinal study. The current paper focusses on the results relating to performance management and measurement, and how the sectorial developments impacted on individuals and institutions.

An interpretive research methodology was used, which illustrates the institutional performance management and measurement system. The first part of the interpretive study was a single case study, focussing on one “old” research-intensive university. The second part included five institutions, three UK top-tier universities, focussing on top-level research and education, and two “new” universities with a greater teaching than research portfolio.

The current paper focusses on the results relating to performance management and measurement, and how higher education (HE) developments impacted on individuals and institutions, reflected in the notion of performance habitus. The qualitative element of the study sought to gain insight into which factors influence performance management and measurement and what changing effect these have on academic members of staff. The findings illustrate how academic values and managerial control practices create an academia-specific performance management approach, measured by particular key performance indicators that are used for the institution as a whole and then applied to units and individuals within institutions. With regard to institutional performance, more established and institutionalised performance management and measurement practices are relied upon. Both elements are addressed in this study, and the authors conclude that the interplay of human capital and institutional structure creates the most successful performance-related outcome.

The current study adds additional insights on how the changing HE context affects academic members and how the future of the UK HE sector is perceived. Insights can be derived for other HE sectors, as the contextual factors of international competition, tightening of resources and nature of the academic sector transcend national borders. Thus, practices illustrated in the current study are useful for institutions and academic managers of other HE sectors as well.

The purpose of this paper is to analyze the scientific collaboration of institutions and its impact on institutional research performance in terms of productivity and quality. The researchers examined the local and international collaborations that have a great impact on institutional performance.

Collaboration dependence measure was used to investigate the impact of an institution on external information. Based on this information, the authors used “index of gain in impact through collaboration” to find the impact of collaborated publications in institutional research performance. Bibliographic data between 1996 and 2010 retrieved from Scopus were used to conduct current study. The authors carried out the case study of top institutes of Pakistan in terms of publication count to elaborate the difference between high performing institutions and those who gain disproportionally in terms of perceived quality of their output because of local or international collaboration.

The results showed that the collaboration of developing countries institutes on international level had a great impact on institutional performance and they gain more benefit than local collaboration. Altogether, the scientific collaboration has a positive impact on institutional performance as measured by the cumulative source normalized impact per paper of their publications. The findings could also help researchers to find out appropriate collaboration partners.

This study has revealed some salient characteristics of collaboration in academic research. It becomes apparent that collaboration intensity is not uniform, but in general, the average quality of scientific production is the variable that most often correlates positively with the collaboration intensity of universities.