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This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.

The outcomes of public research institutions (PRIs), also known as research and development (R&D) institutions, in developing countries, including Indonesia, are still dubious. This study aims to measure the efficiency of R&D institutions using the case of the Indonesian Institute of Sciences, with and without an assessment of the role of scientific publication.

A panel data envelopment analysis (DEA) model is used to estimate the research efficiency of Indonesian R&D institutions during the period 2016–2019 based on the relationship between intellectual property (IP), research budgets and number of active researchers. The Tobit model is subsequently applied to analyze the factors that affect efficiency.

The DEA analysis shows an average efficiency value of 0.361, implying that 42% of the decision-making units (DMUs) have above-average efficiency scores. When scientific publication is added as an output variable, the efficiency increases to an average of 0.545, resulting in 53% of the DMUs with above-average efficiency.

The main implication is that scientific publications can increase the output of R&D institutions in Indonesia. This study recommends strengthening the research group establishment led by research professors along with setting acceptable high output targets. Researcher competence must be improved together with support for research collaboration among the different fields of science. Scientific publications should be considered part of IP measurement along with the type of mandate of each PRI.

This study offers a method of evaluation of research efficiency that can be applied to institutions outside Indonesia, thus furthering the dialogue on science and technology policy management.

This paper contributes to the literature by using a new and comprehensive method to measure research output – that of IP measurement, including new scientific publication. The implications provide action points for the governments to support R&D institutions and for research practitioners to augment research output.

This paper aims to identify the strengths of the universities based on the research area which are prioritized by the Government of Indonesia in the National Medium Term Development Plan 2015–2019, in the research areas of food and agriculture; energy, new and renewable energy; health and medicine; transportation; telecommunication, information and communication; defense and security technologies and advanced materials.

The mapping of the research strength in Indonesian universities is performed by using data of the university research output in the Information System for Research and Community Service, Ministry of Research, Technology and Higher Education and categorized into seven categories, i.e. accredited national journals, international journals indexed by Scopus or others, Intellectual Property ownership, textbooks, prototypes and an appropriate technology. Based on the data obtained from Information System for Research and Community Service, there are 904 universities in Indonesia conducting research activities and generating 14,188 research outputs.

This paper analyzes 3 of the 9 National Research Priorities, namely, food, energy and health and medicine. The data show that there are 904 universities in Indonesia conducting research activities and producing 14,188 research results. The research strength index based on National Research Priorities shows that three universities have the highest cluster strength index. Gadjah Mada with an index value of 4.95 is the highest index in the food cluster. In the energy cluster of the Institut Teknologi Bandung with the highest index value of 0.63. Meanwhile, the Universitas Indonesia reached 2.06 as the highest index value in the health and medicine cluster.

Measurement of the strength of the study was conducted using data from research results from universities in 2016 which were recorded in the Information System for Research and Community Service. The University’s R&D strength is calculated from seven categories of research results: accredited national journals, international journals indexed by Scopus or others, intellectual property rights, textbooks, prototypes and appropriate technology products.

This study aims to measure the global research landscape of the National Institute of Pharmaceutical Education and Research (NIPER) of India on a set of quantitative and qualitative metrics in terms of research output toward exploring research trends and give an overview of collaborative practices by researchers of NIPERs.

The present study has selected the Scopus database as a tool to retrieve potential publications of studied NIPERs during the last 12 years (2010–2021). NIPER-Mohali, NIPER-Hyderabad, NIPER-Ahmedabad, NIPER-Guwahati and NIPER-Kolkata have been selected for the study. The study has adopted a comprehensive search strategy to extract 3,926 publications data. VOS viewer 1.6.17, BibExcel and Microsoft Excel were used for data analysis and visualization.

The global scientific research output of NIPERs accrued 3,926 publications with an average of 327 publications per year. The retrieved publications fetched a total of 67,772 citations with an average citation impact of 17.26. There observed a steady growth of publications from 168 to 509 registered with an average growth rate of 18.44%. The mean relative growth rate and doubling time of research output are 0.26 and 2.94. The authorship patterns explore collaborative trends as most of the publications were published by multiple authors (99.39%). NIPERs have expanded their outreach to collaborate with the USA, Malaysia, Saudi Arabia, Australia and the UK to collaborate on research and regulatory reforms exhibits in the USA as a major contributor.

The present study is the first effort to evaluate the global research productivity of NIPERs and assess the current research trends on a set of quantitative and qualitative metrics to provide some insights into the complex dynamics of research productivity. The study’s outcome may help to identify the current research progress of NIPERs at the global level.

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.

This research aimed to examine the impact of input, process, output, productivity and outcome variables on university research performance and the indicators that represent them in order to improve academic quality and contribute to government policy.

The quantitative approach was used through a survey method that obtained samples using questionnaires from 150 leaders of research institutions and continued analysis using the structural equation modeling-partial least square (SEM-PLS) to test the developed model.

Except for the relationship between process and productivity variables, all variable relationships had a positive and significant effect. Furthermore, the input, process, output, productivity and outcome variables each include seven, twelve, four and ten indicators.

This study has several ramifications because it provides a clear policy input and advances science. As a prelude to developing research performance assessment tools that take into account variances in a tertiary institution, this research aids in the implementation of national policies for assessing research performance in postsecondary institutions.

To improve the accuracy of the information acquired, we conducted a survey among the heads of research units at various higher-ranking Indonesian universities, taking into consideration their skill and experience in leading research organizations and conducting research. Other than that, our belief in the originality of our manuscript is strengthened by the way we applied systems theory to construct a performance evaluation model that examines each contribution made by each system aspect.

The overall aim of this research is to propose a research incentive framework for academic staff members at the South African universities of technology (UoTs).

An exploratory case study methodology was applied, while a questionnaire was used to (1) identify the factors that stimulated staff members' research activities; (2) assess what was considered an appropriate way of measuring research productivity and (3) identify appropriate research awards, recognition and rewards. Working from the self-determination theory (SDT), the results of the data analysis were used to develop a framework for ensuring crowding-in of research incentives into intrinsic motivation. This framework is anchored on the three main components (competence, autonomy and social relatedness) of the cognitive evaluation theory (CET) that provides guidelines for the design of a research incentive system.

Intrinsically motivated researchers tend to conduct research for their inherent satisfaction because it meets their basic individual psychological need for competence. Existing research incentives and productivity systems fail to provide intrinsic motivation for researchers. Recommendation for a framework for designing research incentive systems is centred on the researchers themselves. This approach contributes to a research environment that provides space for autonomy, creativity, flexibility and innovation and consequently a successful research output that is hinged on the ability to keep researchers intrinsically motivated.

A conceptual framework is proposed specifically for technically focused UoT suggesting that crowding-in the motivation of researcher incentives results in improved intrinsic-based motivation. The autonomy of researchers in particular is regarded as the most important driver of such motivation, with the availability of resources, collegiality and research skills and development ranking as the most important aspects specifically driving intrinsic motivation. The framework not only provides a tool for institutions of higher education focused on developing the technical skills, but also offers management at any type of university challenged with low research outputs and a poor research ethos with an alternative method to improve both the quantity and quality of research outputs.

Genetics, a discipline of biology, is one of the most recent and rapidly advancing disciplines in science. This study aims to present a bibliometric analysis of the genetics research output of Iranian authors, map the intellectual structure of these studies and investigate the development path of this literature and the interrelationships among the main topics.

This study searched the Web of Science database for documentation of Iranian-published genetics research published up to 2020. Further, this study used HistCite software to profile and analyze the most cited articles and references and to draw their historiographies.

A database search revealed 21,329 documents that created the study population. The highest cited publications based on the Global Citation Score (GCS) and Local Citation Score (LCS) achieved scores of 602 and 47, respectively. The publication growth rate study demonstrated consistent expansion over time. The scientific maps based on LCS and GCS had five and four clusters, respectively. Furthermore, journal articles emerged as the predominant type of publication.

The significance of this study is in its contribution to understanding the genetics research position in Iran, informing policymakers and researchers, helping scientific collaboration and its impact on public attitudes and quality of life. The results of the present study, with benefits for various groups of communities, such as policymakers, academic groups and public society, can bridge the gap between theoretical research and practical implications.

The results of this study, by helping future advancement in health care, medical genetics and disease prevention, may have a direct and indirect positive influence on the quality of life. Furthermore, it may lead to more informed discussions on health care and biotechnology as well as influencing public attitudes and perceptions.

Ultimately, this study concludes that despite the proliferation of publications in terms of quantity and complexity, especially in areas such as disease diagnosis, prevention and treatment, there remains a need for more attention to other facets of genetics such as biology and biotechnology. Iranian publications are most related to population genetics, human genetics, molecular genetics, medical genetics, genomics, developmental genetics and evolutionary genetics out of 10 branches of genetics. This study reveals patterns in scientific outputs and authorship collaborations and plays an alternative and innovative role in revealing Iranian research trends in genetics.

The purpose of this study is to examine the research efficiency of the research universities in Türkiye and to identify potential areas for improvement and to examine the factors affecting efficiency.

For this purpose, data envelopment analysis was conducted with the output-oriented Banker, Charnes and Cooper (BCC) model with five-year article and citation counts data of 23 universities which were obtained from the Web of Science Core Collection.

The findings of the study show that only eight research universities are efficient. There are areas of development for universities to be effective. In addition, the findings of the regression analysis conducted to reveal the determinants of efficiency revealed significant results.

Research universities in Türkiye should allocate their resources in a way to increase research performance. Policies should be developed to increase the number of publications and, more importantly, the quality of publications.

Potential areas for improvement were identified for the universities to become efficient. The results revealed that both publication quality and productivity need to be improved, but there is more room for improvement in publication quality. Regression analysis with the determinants of efficiency scores shows that the development level of the region where the universities are located has a positive effect on the research efficiency of universities. In addition, it is concluded that smaller universities have better efficiency scores.

There has been a recently growing interest by architects in practice-based research and the impact of research. At the same time, several post-graduate architecture programmes with practice-led research agendas were founded. This shift towards architectural design research is analysed using the notions of “process-driven research”, “output-driven research” and “impact”. The study aims to investigate and unveil the link between graduate programmes and graduates with a research interest and to test the tripartite model of “process-driven research”, “output-driven research” and “impact” in the context of small architectural practices.

The study uses a qualitative and exploratory research approach that includes 11 in-depth interviews conducted in 2020, during the first nationwide COVID-19 lockdown in the United Kingdom (UK) selected interviews were architects representing (1) members or alumni of practice-related graduate architecture programmes in London and (2) founders of London-based small architectural practices within the last decade.

While focussing on the London context, the paper offers transferable insights for the key potentials of practice-led design research in small architectural practices and the actions that might improve research practice.

This paper addresses a lack of studies on how design research differs between diverse types and sizes of architectural firms, why emerging small architectural practices increasingly engage with research and how this shapes their practice. This knowledge is important to fully understanding architectural design research and its strengths or weaknesses.