The effect of university mergers on the Shanghai ranking

Docampo, Domingo; Egret, D.; Cram, L. E.

doi:10.1007/s11192-015-1587-5

Cited by 40 publications

(26 citation statements)

References 22 publications

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“…more central funding allocated to UoAs that are likely to generate better performance in the impact case studies). Docampo et al, 2015 for a discussion of mergers of HEIs to bring about a shift in the rankings), as larger institutes tend to perform better in generating non-academic impact and can better diversify the different priorities of research. Hence, if the marginal expected return of a given UoA (return here is the QR funding) is higher than for the others, then economic theory would suggest that more resources should be allocated to the former UoA compared to the others.…”

Section: Some Potential Implications For the Heismentioning

confidence: 99%

“…Furthermore, the design of the funding distribution may encourage more joint submissions to the next REF to benefit from economies of scale (see e.g. Docampo et al, 2015 for a discussion of mergers of HEIs to bring about a shift in the rankings), as larger institutes tend to perform better in generating non-academic impact and can better diversify the different priorities of research.…”

Section: Some Potential Implications For the Heismentioning

confidence: 99%

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Evaluating the potential effect of the increased importance of the impact component in the Research Excellence Framework of the UK

Pinar

Ünlü

2019

British Educational Res J

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The UK's Research Excellence Framework (REF) is a system that is intended to evaluate the quality of the research produced by higher education institutes (HEIs) in the UK in three areas: quality of research outputs; impact of this research beyond academia; and research environment. For the next REF, the funding bodies have reviewed the importance of the three assessment elements and decided to increase the weight of 'impact' to 25% (from 20% in REF2014) and decrease the weight of 'outputs' to 60% (from 65% in REF2014). This article first examines the relevance of some factors for the quality of impact submissions in REF2014 and finds that larger submissions and institutes with higher external research income received better impact scores in the REF. The article then examines the units of assessment (UoAs) and HEIs that benefitted from the inclusion of the impact agenda as part of REF2014 by examining the distribution of the quality-related research (QR) funding in the 2017-2018 period and finds that the QR funding gap among different UoAs tends to decrease but the gap among HEIs in most of the UoAs increased. With the increased importance of the impact agenda as a criterion for funding bodies, it is expected that research income will be concentrated in fewer universities in the future, with the increased importance of non-academic impact. This article also discusses some of the gaming strategies and long-term investment priorities that HEIs may engage in based on the new submission rules of the next REF.Notes: The QR funding (15-20-65) and QR funding (15-25-60) columns give total QR funding received by HEIs based on the 15%, 20% and 65% weights and the 15%, 25% and 60% weights given to the environment, impact and output, respectively. Total gains/losses are the differences between QR funding (15-20-65) and QR funding (15-25-60) columns.Effect of the impact component in the REF 153

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Section: Some Potential Implications For the Heismentioning

confidence: 99%

Section: Some Potential Implications For the Heismentioning

confidence: 99%

Evaluating the potential effect of the increased importance of the impact component in the Research Excellence Framework of the UK

Pinar

Ünlü

2019

British Educational Res J

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“…Reputation is important for teaching as universities with the best reputations can attract the best students (both nationally and internationally); reputation is also important for research as institutions with the best reputations can attract the best staff and research funding (Engwall, ). Universities are therefore competing for reputation as part of their strategy, and may see a merger, by increasing size and visibility, as an effective means of building reputation both nationally and internationally (Skodvin, ; Harman and Harman, ; Tirronenen and Nokkala, ; Aula and Tienari, ; Goedegebuure, ; Docampo et al , ; Tienari et al , ). Thus poor performance (denoted by low ranking) would lead to merger, in this instance. International competitiveness: With increasing globalization, merging in higher education has been seen as a specific strategy for improving competitive advantage in a global market for research, staff and students (Harman and Harman, ; Yang, ; Pinheiro et al , ; Zeeman and Benneworth, ).…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamics of Inefficiency and Merger in English Higher Education From 1996/97 to 2008/9: A Comparison of Pre‐Merging, Post‐Merging and Non‐Merging Universities Using Bayesian Methods

Johnes

Tsionas

2018

The Manchester School

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This paper investigates inefficiency/merger dynamics in the English higher education sector from 1996–97 to 2008–9. Merging can lead to greater efficiency, and this is the motivation for encouraging merger in the English higher education sector in a period of austerity. But inefficiency can also contribute towards the decision to merge, meaning that the relationship is two‐way. Although there is literature on the effects of merging in higher education, the dynamics are typically not modelled. This paper examines the differences in efficiency between pre‐merging, post‐merging and non‐merging universities, and explores the evolution of the effects over time following the merger. We develop a dynamic model of inefficiency and merger the estimation of which relies on Bayesian techniques organized around the use of Markov chain Monte Carlo. We find that typically merger delivers efficiency gains in the first instance, but these plateau soon after merger. Moreover, there is a wide dispersion around mean efficiency and there is a substantial group of mergers where the probability of efficiency improvement is relatively low. The policy implication is that merging universities is not a universal solution to improving their efficiency.

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“…There are several different world university rankings available (e.g., CWTS Leiden Ranking, The Times Higher Education World University Rankings, QS World University Rankings, and Academic Ranking of World Universities -ARWU), which are all based upon different input data. However, each ranking attributes more or less significance to bibliometric indicators, such as the number of publications produced in a given university, the quality (citation impact) of scientific publications, or the number of articles published in top journals (see, for example, Docampo et al 2015;Frenken et al 2017;Piro and Sivertsen 2016;Shehatta and Mahmood 2016). Naturally, the methodologies of how university rankings are produced differ from each other; thus, university rankings are different in terms of top university rankings (Abramo and D'Angelo 2015;Lin et al 2013).…”

Section: Location Of Excellent Organisations As a Factor Influencing mentioning

confidence: 99%

Factors Influencing Cities’ Publishing Efficiency

Csomós

2018

Journal of Data and Information Science

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Purpose Recently, a vast number of scientific publications have been produced in cities in emerging countries. It has long been observed that the publication output of Beijing has exceeded that of any other city in the world, including such leading centres of science as Boston, New York, London, Paris, and Tokyo. Researchers have suggested that, instead of focusing on cities’ total publication output, the quality of the output in terms of the number of highly cited papers should be examined. However, in the period from 2014 to 2016, Beijing produced as many highly cited papers as Boston, London, or New York. In this paper, another method is proposed to measure cities’ publishing performance by focusing on cities’ publishing efficiency (i.e., the ratio of highly cited articles to all articles produced in that city). Design/methodology/approach First, 554 cities are ranked based on their publishing efficiency, then some general factors influencing cities’ publishing efficiency are revealed. The general factors examined in this paper are as follows: the linguistic environment of cities, cities’ economic development level, the location of excellent organisations, cities’ international collaboration patterns, and their scientific field profile. Furthermore, the paper examines the fundamental differences between the general factors influencing the publishing efficiency of the top 100 most efficient cities and the bottom 100 least efficient cities. Findings Based on the research results, the conclusion can be drawn that a city’s publishing efficiency will be high if meets the following general conditions: it is in a country in the Anglosphere–Core; it is in a high-income country; it is home to top-ranked universities and/or world-renowned research institutions; researchers affiliated with that city most intensely collaborate with researchers affiliated with cities in the United States, Germany, England, France, Canada, Australia, and Italy; and the most productive scientific disciplines of highly cited articles are published in high-impact multidisciplinary journals, disciplines in health sciences (especially general internal medicine and oncology), and disciplines in natural sciences (especially physics, astronomy, and astrophysics). Research limitations It is always problematic to demarcate the boundaries of cities (e.g., New York City vs. Greater New York), and regarding this issue there is no consensus among researchers. The Web of Science presents the name of cities in the addresses reported by the authors of publications. In this paper cities correspond to the spatial units between the country/state level and the institution level as indicated in the Web of Science. Furthermore, it is necessary to highlight that the Web of Science is biased towards English-language journals and journals published in the field of biomedicine. These facts may influence the outcome of the research. Practical implications Publishing efficiency, as an indicator, shows how successful a city is at the production of science. Naturally, cities have limited opportunities to compete for components of the science establishment (e.g., universities, hospitals). However, cities can compete to attract innovation-oriented companies, high tech firms, and R&D facilities of multinational companies by for example establishing science parks. The positive effect of this process on the city’s performance in science can be observed in the example of Beijing, which publishing efficiency has been increased rapidly. Originality/value Previous scientometric studies have examined cities’ publication output in terms of the number of papers, or the number of highly cited papers, which are largely size dependent indicators; however this paper attempts to present a more quality-based approach.

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The effect of university mergers on the Shanghai ranking

Cited by 40 publications

References 22 publications

Evaluating the potential effect of the increased importance of the impact component in the Research Excellence Framework of the UK

Evaluating the potential effect of the increased importance of the impact component in the Research Excellence Framework of the UK

Dynamics of Inefficiency and Merger in English Higher Education From 1996/97 to 2008/9: A Comparison of Pre‐Merging, Post‐Merging and Non‐Merging Universities Using Bayesian Methods

Factors Influencing Cities’ Publishing Efficiency

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