Evaluating university performance using reference point based composite indicators

Gibari, Samira El; Gómez, Trinidad; Ruiz, Francisco

doi:10.1016/j.joi.2018.10.003

Cited by 32 publications

(17 citation statements)

References 31 publications

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“…Within this family, the reference point method [38] was adapted by [39] to develop synthetic sustainability indicators dealing with different compensation degrees between the criteria. Lately, this methodology has been used in a variety of domains such as sustainability, university performance, regional social progress and to measure the ease of doing business [12,[40][41][42]. Among the main advantages of this type of MCDM distance based methodologies, we should mention its ease of implementation and ease of use, as the decision maker can establish a desired number of reference levels.…”

Section: Composite Innovation Indices: a Literature Reviewmentioning

confidence: 99%

A Multi-Criteria Reference Point Based Approach for Assessing Regional Innovation Performance in Spain

2020

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The evaluation of regional innovation performance through composite innovation indices can serve as a valuable tool for policy-making. While discussion on the best methodology to construct composite innovation indices continues, we are interested in deepening the use of reference levels and the aggregation issue. So far, additive aggregation methods are, largely, the most widespread aggregation rule, thus allowing for full compensability among single indicators. In this paper, we present an integrated assessment methodology to evaluate regional innovation performance using the Multi-Reference Point based Weak and Strong Composite Indicator (MRP-WSCI) approach, which allows defining reference levels and different degrees of compensability. As an example of application to the Regional Innovation Scoreboard, the proposed technique is developed to measure the innovation performance of Spain’s regions taking into account Spanish and European reference levels. The main features of the proposed approach are: (i) absolute or relative reference levels could be previously defined by the decision maker; (ii) by establishing the reference levels, the resulting composite innovation index is an easy-to-interpret measure; and (iii) the non-compensatory strong composite indicator provides an additional layer of information for policy-making (iv) a visualization tool called Light-Diagram is proposed to track the specific strengths and weaknesses of the regions’ innovation performance.

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Section: Composite Innovation Indices: a Literature Reviewmentioning

confidence: 99%

A Multi-Criteria Reference Point Based Approach for Assessing Regional Innovation Performance in Spain

2020

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“…This method was introduced in psychology by Likert and is currently widely used [43][44][45]. Following El Gibari et al [46], the weights for the ith indicator are extracted by (i) calculating the arithmetic mean of the judgments mw i ; (ii) computing the adjusted weights defined as aw i = 1.5 (mw i −1) to be applied in a multiplicative environment, where the ratio between two consecutive elements of the Likert-type scale is constant and equal to 1.5; and (iii) rescaling the adjusted weights so that they sum up to 1.…”

Section: Methodsmentioning

confidence: 99%

To Weight or Not to Weight, That Is the Question: The Design of a Composite Indicator of Landscape Fragmentation

et al. 2021

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Composite indicators (CIs), i.e., combinations of many indicators in a unique synthetizing measure, are useful for disentangling multisector phenomena. Prominent questions concern indicators’ weighting, which implies time-consuming activities and should be properly justified. Landscape fragmentation (LF), the subdivision of habitats in smaller and more isolated patches, has been studied through the composite index of landscape fragmentation (CILF). It was originally proposed by us as an unweighted combination of three LF indicators for the study of the phenomenon in Sardinia, Italy. In this paper, we aim at presenting a weighted release of the CILF and at developing the Hamletian question of whether weighting is worthwhile or not. We focus on the sensitivity of the composite to different algorithms combining three weighting patterns (equalization, extraction by principal component analysis, and expert judgment) and three indicators aggregation rules (weighted average mean, weighted geometric mean, and weighted generalized geometric mean). The exercise provides the reader with meaningful results. Higher sensitivity values signal that the effort of weighting leads to more informative composites. Otherwise, high robustness does not mean that weighting was not worthwhile. Weighting per se can be beneficial for more acceptable and viable decisional processes.

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“…A felsőoktatás egyre jelentősebb szerepet vállal az egyes nemzetek gazdasági növekedésében és társadalmi fejlődésében (OECD, 2015). A felsőoktatási intézmények a tudástermelés-és megosztás, valamint az innovációs potenciál szempontjából egyre inkább előtérbe kerülő szereplők (El Gibari et al, 2018). Tevékenységüket és teljesítményüket, mint ahogy más iparágakat és áltálában véve emberi tevékenységet, folyamatosan mérik és monitorozzák.…”

Section: Bevezetésunclassified

A QS-rangsor előrejelezhetősége a Scopus és a SciVal adatai alapján a hazai intézmények tükrében • The Predictability of QS Ranking Based on Scopus and SciVal Data through the Lens of Hungarian Institutions

Dobos¹,

Sasvári²,

Urbanovics³

2021

Ma.Tud.

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A felsőoktatási rendszerek és a felsőoktatási intézmények értékelésének nemzetközileg elismert módja a nemzetközi egyetemminősítő rangsorok használata. Ezek közül az egyik legismertebb a QS-rangsor, ami hat indikátor mentén minősíti az intézményeket. Jelen tanulmányunk két célt fogalmazott meg. Először azt vizsgáljuk meg, hogy a QS-rangsor és a Scopus/SciVal-adatbázisból nyerhető változókból TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) rangsoroló eljárással nyert egyetemi rangsorok hogyan viszonyulnak egymáshoz. Az eredmény nagy fokú egyezést mutat. A második célunk az volt, hogy ezen a QS egyetemi listán szereplő magyar egyetemeket megvizsgáljuk a régi és új rangsorok szerint. Egy egyetem kivételével a magyar egyetemek rangsora is nagy fokú stabilitást mutatott.

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Evaluating university performance using reference point based composite indicators

Cited by 32 publications

References 31 publications

A Multi-Criteria Reference Point Based Approach for Assessing Regional Innovation Performance in Spain

A Multi-Criteria Reference Point Based Approach for Assessing Regional Innovation Performance in Spain

To Weight or Not to Weight, That Is the Question: The Design of a Composite Indicator of Landscape Fragmentation

A QS-rangsor előrejelezhetősége a Scopus és a SciVal adatai alapján a hazai intézmények tükrében • The Predictability of QS Ranking Based on Scopus and SciVal Data through the Lens of Hungarian Institutions

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