Evaluation of the quality and quantity of research results in higher education

Bucur, Amelia; Kifor, Claudiu Vasile; Marginean, Silvia

doi:10.1007/s11135-016-0452-9

Cited by 6 publications

(4 citation statements)

References 31 publications

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“…Research, as a way of knowing, interpreting and transforming reality, cannot ignore the constant demands of an increasingly unstable, complex and diverse business world; hence, for some researchers [77], the two traditional research approaches (qualitative and quantitative) fall short in the resolution of problems and situations that require new perspectives. In this context, the application of mixed methods approaches is important, which allows us to exploit the strengths of both approaches to achieve more complete understandings of business and social problems [78][79][80][81].…”

Section: Mixed Methods Approachmentioning

confidence: 99%

Human Resource Management Contributions to Knowledge Sharing for a Sustainability-Oriented Performance: A Mixed Methods Approach

2019

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This research examines how internal and external Human Resource Management (HRM) contributes to Knowledge Sharing (KS) in order to reach Sustainability-Oriented Performance. This paper uses a mixed methods approach to report on the main antecedents of KS for Sustainability-Oriented Performance. There are many antecedents of KS both inside and outside organizations that are as yet unidentified. This research applies two complex statistical techniques, namely, structural equation modeling (SEM) (Study 1) and fuzzy-set Qualitative Comparative Analysis (fsQCA) (Study 2). First, SEM is used to determine the antecedents of KS for Sustainability-Oriented Performance: Affective Commitment (AC) (an internal dimension of HRM) and a collaboration-oriented Human Resource Management system (CHRMS) (an external dimension of HRM). Second, three multi-group SEMs are used to determine whether a manager’s characteristics (age and gender) and firm size moderate the relationship between KS and its antecedents. Finally, an fsQCA is conducted to identify alternative configurations that lead either to KS or to its absence. The sample comprises data from an online survey of 367 certified innovative Portuguese small and medium enterprises (SMEs). The SEM results show that a collaboration-oriented HRM system always has a positive effect on KS for Sustainability-Oriented Performance. In addition, if the manager is a young man working in a small firm, their AC positively affects KS. There are alternative configurations that lead to the presence or absence of KS. There is, therefore, empirical evidence for the moderating effects of the manager’s age and gender, and firm size. Our study offers improved new HRM configurations and results when compared to the sole use of traditional quantitative statistical methods. The results are consistent and conclusive.

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Section: Mixed Methods Approachmentioning

confidence: 99%

Human Resource Management Contributions to Knowledge Sharing for a Sustainability-Oriented Performance: A Mixed Methods Approach

2019

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“…Different studies have searched for this "best" set of quality indicators, although most of the times with a sectorial focus. In fact, it is possible to find in the literature the proposal of indicators for teaching and learning (Lieber, 2019;SQELT, 2020), research (Bucur et al, 2018;Bruni et al, 2020;Biscaia et al, 2020) or relation with society (Biscaia et al, 2020;Bruckmann et al, 2019). It is, however, harder to find studies reporting a set of indicators addressing the three processes in conjunction and with a link to the design of an effective and efficient QMS.…”

Section: Quality Indicatorsmentioning

confidence: 99%

“…Different studies have searched for this “best” set of quality indicators, although most of the times with a sectorial focus. In fact, it is possible to find in the literature the proposal of indicators for teaching and learning (Lieber, 2019; SQELT, 2020), research (Bucur et al. , 2018; Bruni et al.…”

Section: Literature Reviewmentioning

confidence: 99%

SMART-QUAL: a dashboard for quality measurement in higher education institutions

Adot

Akhmedova

Alvelos

et al. 2022

IJQRM

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PurposeThe paper aims to define a dashboard of indicators to assess the quality performance of higher education institutions (HEI). The instrument is termed SMART-QUAL.Design/methodology/approachTwo sources were used in order to explore potential indicators. In the first step, information disclosed in official websites or institutional documentation of 36 selected HEIs was analyzed. This first step also included in depth structured high managers’ interviews. A total of 223 indicators emerged. In a second step, recent specialized literature was revised searching for indicators, capturing additional 302 indicators.FindingsEach one of the 525 total indicators was classified according to some attributes and distributed into 94 intermediate groups. These groups feed a debugging, prioritization and selection process, which ended up in the SMART-QUAL instrument: a set of 56 key performance indicators, which are grouped in 15 standards, and, in turn, classified into the 3 HEI missions. A basic model and an extended model are also proposed.Originality/valueThe paper provides a useful measure of quality performance of HEIs, showing a holistic view to monitor HEI quality from three fundamental missions. This instrument might assist HEI managers for both assessing and benchmarking purposes. The paper ends with recommendations for university managers and public administration authorities.

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“…Naturally, the selection of the most adequate performance indicators seems to be a significant challenge worldwide (Coomes, Moore, Paterson, Breau, Ross, & Roulet, 2013;Sahel, 2011;Schreiber, Malesios, & Psarakis, 2012;Wildgaard, Schneider, & Larsen, 2014). The most critical factors are deemed to be the following ones: whether the quality or quantity should be considered to be more important (Bucur, Kifor, & Mărginean, 2018, Kallio, Kallio, & Grossi, 2017, how much importance should be given to the impact factor (Brito & Rodríguez-Navarro, 2019;McKiernan, Schimanski, Nieves, Matthias, Niles, & Alperin, 2019;Zhang, Rousseau, & Sivertsen, 2017), which of the indexing databases (e.g., Web of Science, Scopus and Google Scholar) should be used as the basic source during the evaluation process (Martín-Martín, Orduna-Malea, Thelwall, & Delgado López-Cózar, 2018;Mikki, 2010;Vieira & Gomes, 2019), and which of the counting methods (e.g., integer, fractional, and first author counting) should be employed (Egghe, Rousseau, & Van Hooydonk, 2000;Gauffriau, Larsen, Maye, Roulin-Perriard, A., & Von Ins, 2007;Gauffriau, 2017;Van Hooydonk, 1997).…”

Section: Introductionmentioning

confidence: 99%

Introducing recalibrated academic performance indicators in the evaluation of individuals’ research performance: A case study from Eastern Europe

Csomós

2020

Journal of Informetrics

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Evaluation of the quality and quantity of research results in higher education

Cited by 6 publications

References 31 publications

Human Resource Management Contributions to Knowledge Sharing for a Sustainability-Oriented Performance: A Mixed Methods Approach

Human Resource Management Contributions to Knowledge Sharing for a Sustainability-Oriented Performance: A Mixed Methods Approach

SMART-QUAL: a dashboard for quality measurement in higher education institutions

Introducing recalibrated academic performance indicators in the evaluation of individuals’ research performance: A case study from Eastern Europe

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