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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 use of national and international rankings of universities is increasing rapidly. Dill and Soo (2005), who take a generally positive view of university league tables, review the performance of some leading examples of the genre. They conclude that “Our review of the five leading commercial university league tables from Australia, Canada, the UK, and the US suggests that the definitions of academic quality used in these tables are converging…It would be valuable to extend the analysis to league tables developed in Europe, Asia, and Latin America to see the extent to which a common construct of academic quality is becoming truly international” (Dill & Soo, 2005, pp. 525–526).

Prospective students and other stakeholders in the education system use global and national rankings as a measure of the quality of education offered by different higher educational institutions. The ranking of an Institution is seen as a measure of reputation and has a significant role in attracting students. But are students happy in the top-ranked institutions? Does a high rank translate into high student satisfaction? This study answers this question taking data from top educational institutions in India.

This study examines how the top-ranked higher education institutions in India fare on student satisfaction. Using the data on key performance indicators published by the National Institutional Ranking Framework (NIRF) and student satisfaction scores of these institutions reported by NAAC, the study explores a possible relationship between the ranking of an institution and its student satisfaction score.

The study finds no significant relationship between the ranking of an institution and its student satisfaction score. The only institutional performance dimension which has a positive correlation with student satisfaction is graduate outcome. The diversity dimension is seen to be negatively correlated with student satisfaction.

The importance of modifying the ranking frameworks to account for the real drivers of student satisfaction is highlighted. The items in the student satisfaction survey should be regularly updated to reflect the actual concerns of the students. This is very important given the fact that the number of Indian students going abroad for higher education recorded a six-year high in 2022 at 750,365.

With more than 50,000 institutions catering to over 40 million students, India has the largest higher education system in the world. Given the high level of competition among these institutions, ranking and accreditation have become important parameters used by students for selection of an institution. But do top-ranked higher education institutions have the most satisfied student community? The assumption is disproved using the most credible secondary data. This study is the first of its kind in the Indian context. It has huge implications for the most respected ranking frameworks.

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.

Traditionally, the pool from which the United States (US) drew its US-born science and engineering talent has been relatively homogeneous – consisting mostly of non-Hispanic white males. Because science and technology drive the economy worldwide, it is imperative that the US develop, nurture, and utilize the talent of all its citizens. Yet, efforts to diversify the US science talent pool often focus on non-Hispanic white females and much less often on African American males and, of course, African American women.