Prioritizing Strategic Goals in Higher Education Organizations by Using a SWOT–PROMETHEE/GAIA–GDSS Model

Živković, Živan; Nikolić, Djordje; Savic, Marija; Djordjević, Predrag; Mihajlović, Ivan

doi:10.1007/s10726-017-9533-y

Cited by 19 publications

(11 citation statements)

References 24 publications

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“…After the essential contribution was proposed [8], Macharis et al [10] further revisited their PROMETHEE GDSS and illustrated Gaia in greater detail for observing consensus and conflict within a group and its applications. Govindan et al [46] prioritized green suppliers in a food supply chain by PROMETHEE I and II, conducted a group compromise rank by minimizing the distance from the individual ranks through linear programming, and validated the result by robustness analysis.Živković et al [47] used PROMETHEE-GAIA analysis to prioritize strategic goals in higher education organizations, as Gaia is able to provide information about potential conflicts of interests among DMs. He and Xu [11] developed a consensus framework for three preference orderings for PROMETHEE II.…”

Section: Group Prometheementioning

confidence: 99%

Threshold-Enhanced PROMETHEE Group Decision Support under Uncertainties

Shih

2021

Mathematical Problems in Engineering

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As threshold determination is arduous when using PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluations) to make decisions, this study proposes a comprehensive PROMETHEE-based group decision support for covering the uncertainties of threshold determination, risk preferences, and the evaluation itself. To reduce the difficulty on threshold determination, it explicitly offers statistical aggregation of individuals’ indifference and preference thresholds so as to obtain benefits from multiple sources of knowledge and experience. Three typical combinations are characterized that reflect conservative, balanced, and aggressive group preferences. We also derive 6 properties to illustrate the effects of threshold changes on preference changes. Despite variances among the individual rankings of alternatives, the rank differences within the group decisions do converge by the illustrative example. A larger interval of a conservative group preference generates more diverse ranks versus the other two group preferences. Moreover, PROMETHEE III has a power on managing inaccurate measurement. The introduction of S-shaped functions has the benefit of fitting behavioral decision making under uncertainty. Integrating these approaches together for a decision support, our proposal is less affected by rank variance and coherent with traditional group PROMETHEE under differentiated decision power.

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Section: Group Prometheementioning

confidence: 99%

Threshold-Enhanced PROMETHEE Group Decision Support under Uncertainties

Shih

2021

Mathematical Problems in Engineering

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“…Based on the data collected through the questionnaire (Ahmad & Love, 2013), a relevant research base was created, which was completed at the Technical Faculty in Bor, University of Belgrade, Serbia, in 2017. The Technical Faculty in Bor (TFB) is part of the University of Belgrade (UB), which is, according to the Shanghai list, ranked among the top 500 universities in the world, which implies a high quality of teaching and scientific work (Zivkovic et al, 2017). The TFB teaches a group of technology and engineering sciences, and today it has four study programmes: Mining Engineering, Metallurgical Engineering, Chemical Engineering, and Engineering Management, with a total number of about 1400 students.…”

Section: Questionnairementioning

confidence: 99%

Model for Considering the Propensity of Students to Accept M-learning

Milošević

Rakić

Arsić

et al. 2020

Manage: J. Sustainable Bus. Manage, Solutions Emerging Econ.

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Research question: The aim of the study is to examine the inclination of engineering students in Serbia to adopt M-learning. Motivation: Mobile technologies provide new solutions in the current concept of learning. Students today have a new approach to learning since they live in the era of digital technology. The use of mobile technology in higher education came along with the technological enlightenment of professors and students, eradicating geographical boundaries and enabling cooperative learning. Idea: Mobile learning (M-learning) is unthinkable without the use of mobile devices and it plays an increasingly important role in the development of teaching methods in higher education. The research refers to the analysis and assessment of M-learning in higher education with the aim to identify problems and weaknesses related to the application of M-learning in order to set alternatives and criteria for the proposed model. Data: The survey was conducted through a questionnaire, and 341 correctly filled out questionnaires were collected. The obtained data were processed by the Visual Promethee software package. Tools: The research methodology was based on the Multi-criteria decision analysis (MCDA) method which was used in the form of PROMETHEE II/GAIA technique. In order to rank the student programmes from different study areas, groups of questions were used as criteria, and study programmes were used as alternatives. Findings: The acquired results indicated that M-learning was mostly used by the students of Engineering Management, since they frequently used mobile technology in certain required courses, as well as for obligatory business practice. It was also concluded that the study programme Metallurgical Engineering had the lowest performance concerning the implementation of M-learning among all other observed study programmes. Contribution: The conclusions of this study can add to the awareness-raising of the higher education institutions' interested parties and alert them to improve the quality of M-education by pointing out that there are differences in the adoption of M-learning depending on the type of engineering sciences.

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“…Higher education organizations are involved in a changing environment, and their position in global contexts increasingly depends on their ability to adapt to the environment, together with the continuous improvement of teaching and research activities [1]. In this context, external stakeholders require transparency and accountability and the main challenge for higher education institutions lies in rethinking their role in the higher education landscape to consider and improve their performance profiles, i.e., how good higher education institutions are at performing their activities [2].…”

Section: Introductionmentioning

confidence: 99%

“…The Equation (1) is applied in the majority of the voting methods based on score rules. Specificaly, the desirability of the criteria c defined in (1), where xc vs is the number of vsth places that the criteria c obtains from the students. This is applied when:…”

mentioning

confidence: 99%

A Multiple Criteria Decision Making Approach to Designing Teaching Plans in Higher Education Institutions

et al. 2020

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The involvement of competences in the teaching–learning planning process in Higher Education is essential for their success in the European Higher Education Area. This study presents a participatory multi-criteria model based on Voting Analytic Hierarchy Process (VAHP) analysis, focusing on the attainment of competences that permits consensus between lecturers and students in the design of teaching plans using two assessments: the assessment of competences by students and the lecturers’ assessment of the contribution of teaching strategies to the attainment of each competence. To validate the methodology, a survey was carried out to determine the preferences of 211 students on the competences of a quantitative subject in several business degrees and a survey of 11 lecturers to assess the contribution of the teaching strategies in the acquisition of each competence. The results show that practical lessons and group work should receive more importance in the teaching plans of the subject Financial Management according to the defined competences, the students’ preferences and the criterion of each lecturer for each teaching strategy. The results show the applicability of the participatory methodology proposed to formally agree on the design of teaching plans in higher education organizations between lecturers and students.

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Prioritizing Strategic Goals in Higher Education Organizations by Using a SWOT–PROMETHEE/GAIA–GDSS Model

Cited by 19 publications

References 24 publications

Threshold-Enhanced PROMETHEE Group Decision Support under Uncertainties

Threshold-Enhanced PROMETHEE Group Decision Support under Uncertainties

Model for Considering the Propensity of Students to Accept M-learning

A Multiple Criteria Decision Making Approach to Designing Teaching Plans in Higher Education Institutions

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