International whole sub-criteria. Keywords: ranking; multi criteria decision


International university rankings are an integral part of the higher education landscape. In the article, the authors conduct the analysis of capacities for Baqiyatallah university to meet the requirements claimed by the Iranian Ministry of Education which sets the aim to reach the first 10 lines of University in Iran. The aims of this study are to weight the performance evaluation indices based on multi-criteria decision making. we utilize the analytic hierarchy process (AHP) to weight to the criteria and in the next step, The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) applied for ranking the the end it was found that The results obtained with regard to the most important factors were the highest factor of the faculty members with the value of 0.402, the axis of publication and production with the value of 0.267, the Factor of capacity building with 0.174 and the axis of researcher project with value 0.156, respectively, weights 1 to 4 . In order to rank the sub-criteria, Smart TOPSIS software has been used. According to the results of this study, the criterion of innovation, discoveries, patents, and technology localization with 0.924 is another important factor the whole sub-criteria.

Keywords: ranking; multi criteria decision making; criteria; AHP; TOPSIS

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!

order now



Higher education as a public commodity is a public sector responsibility. In the past two decades, higher education has been considered as a focal point that ensures the progress of society in other areas. New developments, especially the advent of the knowledge economy, have led to quality improvement as a measure of access to higher education by society as a matter of priority in higher education policymaking. In this regard, quality policy tools have been developed to maintain and improve the quality of the higher education system. However, the quantitative development policy of higher education in Iran as a response to growing social demand provided Variety of fields in higher education But Iran’s higher education, with the current trend of quantitative growth, does not have an effective model for establishing and maintaining quality. Institutions play a critical role in national and global development. They support global development strategies by providing the highly qualified manpower and research necessary for further growth 1. Among the different levels of education, higher education is especially conducive to fostering high-tech talent, which is the key factor in increasing national quality and the main path to improving a nation’s competitiveness 2. International ranking systems usually depend on a certain set of indicators. Today, several large-scale university ranking programs exist. Most of them rely partly or wholly on bibliometric measures 3.rankings have a positive impact in that they contribute to public awareness about higher education and promote transparency of institutions 4.The exclusiveness of university rankings has led to a few attempts to go beyond the institutional level and to rank countries’ higher education systems. Simultaneously, there is a growing opinion which considers that it would be more relevant to develop benchmarking instruments in order to avoid the kind of unexpected effects which are necessarily associated with any ranking. The focus of this study is Identify and evaluate the most important criteria that lead to the promotion of the scientific rank of the Baqiyatallah University among Iranian universities.


Literature Review:

Since 1983, the journal of U.S. News and World Reports has been publishing “America’s Best Colleges” which reveals the assessment of American universities in terms of performance become global phenomenon triggered that start of ranking systems development and their proliferation all around the world 5. Altbach 6 states that nowadays higher education institutions and departments can develop a global mark without difficulty and ranking lists contribute this. Besides, academic institutions have the advantage of analyzing their education systems position among others, taking strategic decisions related to resource allocation and enhancing their positions in ranking lists. Academic Ranking of World Universities (ARWU) is known as one of the most popular international ranking systems which rank universities all over the world based on research performance. Alumni and staff winning Nobel Prizes and Fields Medals, highly cited researchers in 21 broad subject categories, articles published in Nature and Science and indexed in SCIE and/or SSCI and academic performance relative to institutional size are the indicators of the ranking framework. By weighting each indicator and aggregating a total score for research performance is achieved 7.The German studies by Büttner, Kraus, and Rincke (2003) and Helbig and Ulbricht (2010) analyze the influence of German university rankings on the number of enroll students and the sorting of students according to ability. They show that rankings also seem to influence the matriculation decision in Germany. However, both German studies cannot control for university fixed effects and, therefore, fail to disentangle the effect of the additional information provided by the rankings from the common knowledge regarding university attractiveness. Recent years, some organizations regularly release university rankings, such as QS World University Rankings, US News Top World University Rankings, Times Higher Education World University Rankings, Academic Ranking of World Universities (ARWU), etc. Within these rankings, the technology of Multi-Criteria Decision Making (MCDM) is one of the most popular methodologies to implement the ranking and evaluation of world universities 8.  Li et al. presented a two-dimensional approach by balancing “quantity” and “quality” to evaluate the research performance of universities in Mainland China, Hong Kong, and Taiwan 9. Shin (2011) states the primary goal of rankings is to provide information to their target customers, mainly students, parents, and higher education institutions while on the other hand quality assurance and accountability mechanisms focus on improving quality and financial accountability 10.


Research Methodology:


1.      Analysis hierarchy process (AHP):

Proposed by Saaty 11, the analytic hierarchy process (AHP) is a multiple-criteria decision-making method that is normally applied to overcome problems in uncertain conditions or to consider several evaluation criteria during the decision-making process. The MCDM model aims to provide a decision maker with a precise reference for decision making and to reduce the risk of making the wrong decision. Saaty proposes the decision makers preferences by formulating the Fundamental Scale. Criteria and sub-criteria can be numerous; comprising of both tangible and intangible factors which an individual considers during the decision making process. AHP seeks to capture this process by identifying a hierarchy of decision making in relation to a pre-speci?ed goal 12. For the decision problem modeling step, AHP has a strong potential in structuring the decision problem in the form of hierarchical structure. In its general form, the hierarchy structure takes a tree shape where the root represents the overall goal and the nodes that are descending from the goal represent the criteria. The criteria could be branching out into other clusters of evaluation criteria which can be found in the intermediate levels of the structure 13. The calculation steps of the AHP are presented as follows 11,14:

Step2: The pairwise contrasting of n criteria is summarized in an n-by-n pairwise assessment matrix. Let us define C={Cj | j=1,2,…,n}.as set of criteria.The n-by-n evaluation matrix, A, includes comparisons of the criteria from the set C. The matrix A is given:



In this context, based on the AHP hierarchy given in Fig 1, aij represents the numeric assessment of the pairwise comparison between criteria i and j. For example, if the criteria i has absolute importance over the criteria j, then aij = 9, and if conversely aji= . The entries of the matrix A follows the subsequent rules:


Next step in AHP process normalizes and obtains the respective weights of each matrix A by dividend column entries by corresponding column sums. The principal eigenvector W concurrent to the largest eigenvalue of matrix A precedence of the elements:

he final step in AHP requires conducting a consistency analysis as the eminence of AHP results is highly dependent on the congruity of the pairwise comparison judgment. The consistency analysis is accomplished in two steps. Initially, the consistency index (CI) is determined through                  

Where the R.I. represents the average consistency index (i.e., the random index). Saaty 15 computed the R.I. as the average consistency of square matrices coming from various orders n, which he filled with random entries. The average consistency values of these matrices are given

By Saaty and Vargas 16,If the C.R. < 0.1, then the estimate is accepted; otherwise, a new comparison matrix is solicited until C.R. < 0.1.   2.      The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS):   The AHP is a useful tool to solve complex problems, however, in several cases, it is necessary to be combined with other Multiple Criteria Decision Making (MCDM) methods. TOPSIS is a favorable MCDM method 17.The reasons for selecting TOPSIS can be summarized as follows 18:The fundamental principle of TOPSIS method is based on the proposed method satisfies the condition of being the closest to the positive ideal solution and also being the farthest from the negative ideal solution with multi-judges and multi-criteria. 19. In order to compare the alternatives and upgrade the final ranking the Euclidean distances between each alternative and both the ideal and the negative-ideal solutions are calculated first; then the closeness coefficient is calculated to measure the two distances respectively 20. TOPSIS process can be described as follows 21.   Step 1.Establish a decision-making matrix format to model the problem with the presentation of all alternatives and criteria. The matrix format D can be concisely expressed as:             Step 2. The importance of criteria (weights) is directly evaluated by pairwise comparisons using AHP scales (Table 1) from decision makers.   Step 3. The vector normalization technique is used for computing the element (rij) of the normalized decision matrix, which is given as: Step 4: The weighted normalized decision matrix can be calculated by multiplying each row (rij) of the normalized decision matrix with its associated attribute weight wj. The weighted normalized value  is calculated as below Step 5: The ideal solution (  is made of all the best performance scores and the negative-ideal solution (Ai) is made of all the worst performance scores at the measures in the weighted normalized decision matrix where i = 1, 2, . . . , N. The Mathematical expression is as follows: Step 6: The n-dimensional Euclidean distance can measure the distance of an alternative j to the ideal solution. Separation of each alternative from the positive ideal solution ( Similarly, separation from the negative ideal solution ( ) is then given by Step7: the ranking score ( ) is calculated as When  is close to 1, the alternative is regarded as ideal; and when  is close to 0, the alternative is regarded as non-ideal.