Muhayy Ud Din Zafar

T.C. BAHÇEŞEHİR UNIVERSITY GRADUATE SCHOOL OF SOCIAL SCIENCES DEVELOPMENT OF A TURKISH UNIVERSITIES RANKING MODEL FOR GLOBAL ASPIRANTS AN AHP & WASPAS BASED APPROACH MASTERS OF MARKETING FACULTY OF ECONOMICS Mehmet YILDIZ- İSTANBUL, 2021 T.C. BAHÇEŞEHİR UNIVERSITY GRADUATE SCHOOL OF SOCIAL SCIENCES DEVELOPMENT OF A TURKISH UNIVERSITIES RANKING MODEL FOR GLOBAL ASPIRANTS AN AHP & WASPAS BASED APPROACH MASTERS OF MARKETING FACULTY OF ECONOMICS Mehmet YILDIZ- Asst. Prof. Orceun TUREGUN İSTANBUL, 2021 T.C. BAHÇEŞEHİR UNIVERSITY GRADUATE SCHOOL OF SOCIAL SCIENCES FACULTY OF ECONOMICS Name of the project: Development of a Turkısh Unıversıtıes Rankıng Model for Global Aspırants: An AHP & WASPAS Based Approach Name/Last Name of the Student: Mehmet YILDIZ Date of Thesis Defense: dd/mm/yyyy I hereby state that the capstone project prepared by Your Name (Title Format) has been completed under my supervision. I accept this work as a “Capstone Project”. dd/mm/yyyy Advisor’s Name (Asst. Prof. ...) I hereby state that I have examined this capstone project by Your Name (Title Format) which is accepted by his supervisor. This work is acceptable as a capstone project and the student is eligible to take the capstone project examination. dd/mm/yyyy Assoc. Prof. Dr. Adem Karahoca Head of the Department of Software Engineering We hereby state that we have held the capstone examination of Your Name (Title Format) and agree that the student has satisfied all requirements. THE EXAMINATION COMMITTEE Committee Member Signature 1. Your Advisor’s Name ……………………….. 2. ………………………….. ……………………….. 3. ………………………….. ……………………….. Academic Honesty Pledge I promise, on penalty of failure of SE4997 (or 4998), not to collaborate with anyone, not to seek or accept any outside help, and not to give any help to others. I understand that all resources in print or on the web must be explicitly cited. In keeping with Bahçeşehir University’s ideals, I pledge that this work is my own and that I have neither given nor received inappropriate assistance in preparing it. Name Date ii Signature ABSTRACT DEVELOPMENT OF TURKISH UNIVERSITIES RANKING MODEL FOR GLOBAL ASPIRANTS: AN AHP & WASPAS BASED APPROACH Student Name Faculty of Engineering Department of Software Engineering Advisor: Dr.Professor’s Name JANUARY, 2021, 35 pages Most of the countries around the world offer enough opportunities to complete higher secondary (college) and basic professional education to their people. Students tend to explore specialization in professional education after graduation. Turkish universities are new destination to most of the under developed and developing countries due to their affordable tuition fees, living expenses and in returning quality education opportunities. This research has been done in perspective of international students and has used unconventional parameters of university ranking systems, which are generally looked by global aspirants. An AHP and WASPAS based algorithm was used to quantify aggregated score to help students pick one of the universities among Bahcesehir, Istanbul Bilgi, Işık, Özyeğin, Altinbas, Beykent and İstanbul Okan university. Weightage of all comparing parameters was decided based on literature reviews and a neutral student’s perspective. Bahcesehir university stood out based on aggregated score of all individual parameters, showing its rich cross cultural community and ease of induction support to international students. Key Words: Ranking, faculty, exchange programs, citations. iii ÖZET BİTİRME PROJESİNİN ADI (BÜYÜK HARFLERLE) Öğrencinin Adı (Başlık Formatında) Mühendislik Fakültesi Yazılım Mühendisliği Bölümü Tez Danışmanı: Danışmanın İsmi (Başlık Formatında) AY (BÜYÜK HARFLERLE), Yıl,sayfa sayısı(ör. 45 sayfa) Projenin Türkçe Özeti. All paragraphs in this section follow the format “Normal”. Make sure that the format selected is “Normal”. You can check it from the menu Format>Styles and Formatting that will be opened on the right-hand side of this document. Anahtar Kelimeler: Proje ile ilgili anahtar kelimeler virgül ile ayrilmiş olarak buraya yazılır. iv TABLE OF CONTENTS Academic Honesty Pledge ..................................................................................................... ii ABSTRACT..........................................................................................................................iii ÖZET .................................................................................................................................... iv TABLE OF CONTENTS....................................................................................................... v LIST OF TABLES ............................................................................................................... vii LIST OF FIGURES ............................................................................................................viii LIST OF ABBREVIATIONS ............................................................................................... ix 1. INTRODUCTION ............................................................................................................. 1 2. LITERATURE REVIEW .................................................................................................. 2 2.1. Academic Ranking of World Universities (ARWU) ............................................. 2 2.2. Times Higher Education ........................................................................................ 2 2.3. Webometrics .......................................................................................................... 3 2.4. QS World University Rankings by Quacquarelli Symonds................................... 4 2.5. Review of Conventional Ranking Systems ........................................................... 4 2.6. Review of AHP & WASPAS Approach ................................................................ 6 3. DATA AND METHOD..................................................................................................... 8 3.1. Aim ........................................................................................................................ 8 3.2. Analytical Hierarchy Process (AHP) Method ....................................................... 9 3.3. Weighted Aggregated Sum Product Assessment (WASPAS) Method ............... 10 4. THE AHP METHOD....................................................................................................... 12 4.1. Selection of Experts ............................................................................................. 12 4.2. Development of Selection Criteria ...................................................................... 12 4.3. Development of a Pair Wise Comparison Matrix [C] ......................................... 12 4.4. Normalized Pair Wise Comparison Matrix [C]N ................................................. 14 4.5. Criteria Weightages [W] ...................................................................................... 14 4.6. Consistency Analysis ........................................................................................... 15 4.7. AHP Calculations for Respective Criteria Scores ............................................... 16 5. THE WASPAS METHOD .............................................................................................. 17 5.1. Int’l Students Admission Pre-Requisites ............................................................. 17 5.2. Number of Schools and Faculties ........................................................................ 18 v 5.3. Top Cited Researchers / Openness Rank Value .................................................. 19 5.4. Research and Publications Index / Excellenc Rank Value .................................. 19 5.5. Average Tuition Fees ........................................................................................... 20 5.6. Accommodation Expenses ................................................................................... 20 5.7. International Students Exchange Programs ......................................................... 21 5.8. International Ranking of University .................................................................... 21 5.9. National Ranking of University ........................................................................ 22 5.10. Total Strength of Teaching Faculty ................................................................... 22 5.11. PhD Faculty Percentage ..................................................................................... 23 5.12. Total Number of Enrolled Students ................................................................... 23 5.13. Number of International Students ...................................................................... 24 5.14. Student Teacher Ratio ........................................................................................ 24 5.15. Number of University Campuses ....................................................................... 25 5.16. Aggregated Performance Scores after WASPAS Calculations ......................... 25 6. RESULTS AND CONCLUSIONS ................................................................................. 30 APPENDIX A – AHP CALCULATIONS .......................................................................... 31 APPENDIX B – WASPAS CALCULATIONS .................................................................. 33 REFERENCES .................................................................................................................... 35 vi LIST OF TABLES Table 1 - Importance Scale Table ............................................................................ 13 Table 2 - AHP Criteria Weightages ......................................................................... 14 Table 3 - AHP Calculations for Respective Criteria Scores .................................... 16 Table 4 - WASPAS Evaluation for Admission Pre-Reqs ........................................ 18 Table 5 - WASPAS Evaluation for No of Schools and Faculties ............................ 18 Table 6 - WASPAS Evaluation for Openness Rank ................................................ 19 Table 7 - WASPAS Evaluation for Excellence Rank .............................................. 19 Table 8 - WASPAS Evaluation for Tuition Expenses ............................................. 20 Table 9 - WASPAS Evaluation for Accommodation Expenses .............................. 20 Table 10 - WASPAS Evaluation for International Students Exchange Programs ... 21 Table 11 - WASPAS Evaluation for International Ranking of Universities ........... 21 Table 12 - WASPAS Evaluation for National Ranking of Universities .................. 22 Table 13 - WASPAS Evaluation for Total Strength of Teaching Faculty ............... 22 Table 14 - WASPAS Evaluation for Percentage of PhD Faculty ............................ 23 Table 15 - WASPAS Evaluation for Total Strength of Students ............................. 23 Table 16 - WASPAS Evaluation for Percentage of International Students ............. 24 Table 17 - WASPAS Evaluation for Student - Faculty Ratio .................................. 24 Table 18 - WASPAS Evaluation for Number of Campuses .................................... 25 Table 19 - Segregation of WASPAS criteria ........................................................... 26 Table 20 - Normalized Criteria Value Matrix .......................................................... 27 Table 21 - Criteria Weights ...................................................................................... 27 Table 22 - Comparison of Results: AHP & WASPAS ............................................ 30 vii LIST OF FIGURES Figure 1 - Times Higher Education Ranking Criteria ................................................ 3 Figure 2 - Webometrics Ranking Matrix ................................................................... 3 Figure 3 - QS World University Ranking System ..................................................... 4 Figure 4 - Option Alternatives for Selection of a University ..................................... 8 Figure 5 - Development of Selection Criteria by Experts ........................................ 12 Figure 6 – Pair Wise Comparison Matrix based on Experts Weightages ................ 13 Figure 7 - Pair Wise Comparison Matrix Based on Importance Scale [C] .............. 13 Figure 8 - Normalized Pair Wise Comparison Matrix ............................................. 14 Figure 9 - Weighted Sum Matrix and λ ................................................................... 15 Figure 10 - Consistency Validation ......................................................................... 15 Figure 11 - Selection of Performance Indicators and Allocation of Weightages .... 17 Figure 12 - WASPAS Criteria Matrix with Values ................................................. 26 Figure 13 - Weighted Sum Model & Ranks ............................................................ 28 Figure 14 - Weighted Product Model & Ranks ....................................................... 29 Figure 15 - WASPAS Model Performance Scores and Ranks ................................ 29 viii LIST OF ABBREVIATIONS AHP Analytical Hierarchy Process WSM Weighted Sum Model WPM Weighted Product Model WASPAS Weight Aggregated Sum and Product Aggregated Sum ix 1. INTRODUCTION With increase in competition in every race of life, ranking systems had been showing increase in popularity and importance. Had it been pessenger airlines or cargo servives at one hand, and consumer electronics and FMCGs on the other, independent ranking systems have proved their significance from both consumers and producers perspective. Like industry, academia has also got affected positively with various ranking systems and criteria. This has made universities to work more for develop more research and industrial collaborations. Universities aroun the world are being ranked by multiple independent and unbiased international agencies, every year based on specific set of performance indicators. These performance indicators are assessed through open data available at university resource pages or is submitted by universities to few of the most credible ranking agencies. These ranking system not only help students around the globe, to pick their destination for quality education in their preffered field but also help universities to analyse their own performance. There is a boom of research, publications and industrial patents by universities since ranking systems has gotten significant popularity. Countries’ own higher education councils are striving to develop more comprehensive and locally triggered model of ranking system. National ranking systems of higher education councils are taken more credible because of the fact that government councils are in the reach of most accurate facts, that are to be compared while ranking establishment. Keeping in view the above mentioned facts, the current research was aimed to develop a non-conventional model of turkish universities, which would be based on parameters that are widely considered by international students while applying to any destination outside their country of residence. An AHP and WASPAS based models has been developed to predict more accurate score indicators under consideration. Weightage of all compared parameters was decided based on literature reviews and a neutral student’s perspective. Scores against eached weighted parameter has been calculated through credible resources. 1 2. LITERATURE REVIEW A brief overview of existing ranking systems and criteria is necessary to proceed for selection of indicators for current ranking model. Major ranking systems include but not limited to the following:  Academic Ranking of World Universities (ARWU)  Times Higher Education  Webometrics (Web Ranking of Universities)  QS World University Rankings by Quacquarelli Symonds  UniRank (4icu.org) This list is also an example for inserting bullets. Make sure that all bulleted lists in your document obey the format of the above list. 2.1. Academic Ranking of World Universities (ARWU) ARWU is widely know as Shanghai rankings; started in 2009 to initially rank pure sciences subjects and subsequently increasing the scope to almost all major pure, social and applied sciences subjects and respective institutions. The system is more consistently developing in terms of criteria as it is based on subject specialists feedbacks with continuous increase in speacialists database. Main indicators include the quantification of major award winning graduates and faculty, most cited research publications and overall performance of institute as per its size. The aggregate of respective KPIs would determine overall score of performance (Liu & Cheng, 2005). 2.2. Times Higher Education Times higher education university rankings system is a detailed and comprehensive ranking model based on multiple performance indicators, both research and development based factors. The major indicators and respective weightage is as under (as available on www.timeshighereducation.com):  Teaching 30%  Research 30%  Citations 30%  International Outlook 7.5% 2  Industry Income 2.5% The sub-division of each major indicator has been shown in figure – 1; data against each indicator is sought by respective universities or obtained through open sources. Figure 1 - Times Higher Education Ranking Criteria 2.3. Webometrics Webometrics is a ranking system that focus on published research quality of each university, promoting open accessibility of research knowledge generated by the universities. The performance indicators are mainly consisting of following (as available on webometrics.info, 2021):  Presence: Size of university’s own web domain and contents 5%  Visibility: Web content with connected external networks 50%  Openness: Research citations from top 210 authors 10%  Excellence: Number of most cited research papers 35% Figure 2 - Webometrics Ranking Matrix 3 2.4. QS World University Rankings by Quacquarelli Symonds QS world ranking system undertake a consistent workframe based on six components assessment matrix that delivers a credible performance measure. This system has also included employers feeback about university’s graduates which eventually speaks about the quality of education and industrial research being given to their graduates. The major indicators and respective weightage to each performance indicator in QS ranking system is as under (as available on www.topuniversities.com):  Academic Reputation 40%  Employer Reputation 10%  Faculty / Student Ratio 20%  Citations per Faculty 20%  International Faculty Ratio 5%  International Student Ratio 5% Figure 3 - QS World University Ranking System 2.5. Review of Conventional Ranking Systems Rebeka et al (2010) proposed an AHP based model that was comprised of nonconventional indicators including socio-environment factors. The modified model, apart from resulting into university's ranking, also suggested strengths, weaknesses and opportunities for the institute under consideration. Rad et al (2011) worked out to identify course based ranking and clustering of universities in Iran. They emphasized the subject wise clustering of universties and employed AHP based algorithms to classify the universities. Heike et al (2013) critically reviewed the international ranking systems of 4 universities and observed that they project specific global geographies as hub for ideal higher education systems. They indicated that these ranking systems have resulted into establishing knowledg based economies. They iterated that a subject specific ranking criteria would have resulted into entirely different prospects of higher education quality index. Benoit (2015) emphasized the necessaity of considering respectives country's higher education system while allocating certain numbers for a ranking parameter by international ranking systems. He described the role of higher education system in developing the shape of university's research and industrial potential. Elyase et al (2015) discovered an innovative dimesion to rank universities with respect to their social impact factor. Aspirants are generally inclined towards entrepreneuership and innovation while chosing a specific university. The authors observed that ranking index of turkish universities by The Scientific And Technological Research Council of Turkey (TUBITAK) has multiple dimensions but is still inadequate in respect of social and behavioral parameters of ranking criteria. The author suggested that social and behavioral parameters should be included as constant indicators for evaluation in a university ranking system. Cinzia et al (2015) proposed that the conventional university ranking systems not only have educational importance but also have significant contributions towards policy making and media strategy. By analyzing main criticisms on ranking system, the author consluded the importance of investment in open data management regarding university's key performance indicators. Bü şra Alma et al. (2016) observed the variance of ranking methodology in current ranking systems around the globe, resulting in fluctuation of a university's ranking in different ranking systems. They emphasized to develop a national ranking system for turkish higher education institutes and proposed a ranking criteria that is based on main parameters of research, academic staff, teaching quality, students, international orientation of university and overall grading of institute. These main parameters were sub-divided into multiple indicators that resulted into a comprehensive ranking model. Vladimir Ivančević et al. (2018)worked to search open data regarding performance indicators of serbian national higher education varasities. They developed a ranking matrix based on open data available with serbian ministry of education, science and technology 5 development and at respective universities. While citing international ranking systems, they compared their own findings with international standings of local universities. 2.6. Review of AHP & WASPAS Approach There are multiple algorithms that help to solve multi-criteria decision making (MCDM) problems. Out of those algorithms, Analytic Hierarchy Process (AHP) is the most common one being used by researchers and industrialists. The basics of this process include but not limited to develop an analytical hierarchy based on experts’ opinion. The selection of experts require a qualification criteria to have an authentic and desireable results. The experts develop their opinion based matrix of some performance criteria which is further analyzed pair wise, with all the alternative options available. There is then concluded a priority vector; the steps for derivation of which has been different at different researchers. Saaty (1980) gave the idea of using an eigenvector method to derive the priority vector. But the successors always had been criticising this method for having a low consistency and irregular prioritization results. In addition to him, following other researchers also gave alternatie methodologies to derive a priority vector for AHP analysis: 1. ATW Chu et al (1979) proposed a Weighted least-squares method (WLSM) 2. Crawford (1987) developed a Logarithmic Least Squares Method (LLSM) 3. Saaty et al (1984) again proposed a Least Squares Method (LSM) to adress the inconsistency and prioritization issues 4. RE Jensen (1984) developed a Chi-square method (CSM) 5. Cogger et al (1985) introduced a Gradient Eigenweight Method (GEM) along with another Least Distance Method (LDM) 6. Islei et al (1988) proposed a Geometric Least Squares Method (GLSM) In addition to above the efforts kep evolving to make the AHP process more and more consistent and reliable for multi-criteria decision making (MCDM) problems. İn addition to above techniques, Bryson (1995) introduced Goal Programming Method (GPM) and a few years later, again along with Joseph (1999) developed another technique of Logarithmic Goal Programming Approach (LGPA). However, despite availability of these much processes for derivation of priority vector through Analytical Hierarchy Process, the comparative analysis of all these methodologies has not concluded the most viable solution. 6 Multi criteria decision making processes are opted in a case where the available options, also called alternatives, are there in a finite numbers. The major useage of these methods are normally seen in project assessments, selection of various equipment and plants. Before the introduction of Weighted Aggregated Sum Product Assessment (WASPAS) Method, Weighted Sum Model (WSM) and Weighted Product Model (WPM) were mostly used as a part of Multi criteria decision making processes. This innovative idea of integrating both Weighted Sum Model (WSM) and Weighted Product Model (WPM) to conclude a more reliable decision making algorithm of WASPAS was presented by Zavadskas et al. (2012). He worked to measure the accuracies of both parent models and based on those he advocated to integrate both methods into WASPAS as the later one was concluding with increased accuracy. Jawad et al (2021) has lately worked to carry out a new development while extending weighted aggregated sum product assessment (WASPAS) method to a new approach called uncertain probabilistic linguistic - WASPAS (UPL-WASPAS) for recognition as an innovative methodology based on the proposed aggregation operators. 7 3. DATA AND METHOD Since 2015-16, Turkey has been witnessing a spike in arrival of international students there, for persuance of their professional studies. Current estimated figure of international students in Turkey is around 650,000 which is a testimonial of country’s recognition as an arising destination of students around the globe. Before initiating the process of application, prospected students try to compare certain parameters that may help them chosing a credible place, where they can persue their education with peace and confidence of quality. 3.1. Aim This research aims to provide a logical and comprehensive assessment criteria to put certain universities in order of preference, keeping it in perspective of an international student. To make it easier for prospected aspirants, the performance idicators chosen were, more detailed and a blend of research, ease of processing, industrial linkage and cross cultural values. The universities, that are to be analyzed are as follows: 1. Bahcesehir University 2. İstanbul Bilgi University 3. Işık University 4. Özyeğin University 5. Altinbas University 6. Beykent University 7. İstanbul Okan University BAHCESEH İR OAKN BILGI OPTION ALTERNATIVES BAEYKENT ISIK ALTINBAS OZEYGIN Figure 4 - Option Alternatives for Selection of a University 8 To achieve the goals of this research, the selection of performance and comparison indicators were selected keeping in view to perform two discrete algorithms, i.e: 1. Analytical Hierarchy Process (AHP) 2. Weight Aggregated Sum and Product Aggregated Sum (WASPAS) The detailed selection parameters and their respective justifications are being delineated in the following sub-sections. 3.2. Analytical Hierarchy Process (AHP) Method For development of an analytical hierarchy process model, the selection parameters were classified into 5 main criteria, all of which were further sub-divided in to multiple sub-criterias. The goal was to pick one university out of seven (7), mentioned in preceding section. All these seven universities were taken as “a set of alternatives”. Goal: Selection of a University as an International Student Criteria 1: Ease of Process Criteria 2: Size of University Sub-Criteria: No of Faculties, Teaching Strength, Total Students, Student / Teacher Ratio, Number of Campuses Criteria 3: Research Quality Sub-Criteria: Top Cited Researchers, Research & Publication Index, International Ranking of University, National Ranking of University, PhD Faculty Criteria 4: Finances Sub-Criteria: Tuition Fees, Accommodation Expenses Criteria 5: Cross Cultural Values Sub-Criteria: International Students Exchange Programs, Strength of International Students Alternatives: Bahcesehir University, İstanbul Bilgi University, Işık University, Özyeğin University, Altinbas University, Beykent University, İstanbul Okan University The algorithm to carry out a consistent AHP based assessment had the following steps: 1. Selection of Experts: The current research is aimed to identify the best university for prospected international students. That needs to be inquired either 9 from international education consultants or from prospected students who plan to undertake their education out of their country. A panel of 15 different respondents, comprising of both education consultants and prospected students, were taken as experts for this purpose. 2. Development of Selection Criteria: Experst were initially asked to give their opinions about the preferred set of criteria which they look while selecting a university abroad. After developing a set of 5 main and 15 sub-criterias (15 in total), all those respondents were asked to give relative importance of these criterias by assigning a weighted score to each one of 15 criterias, and thus by making a total sum of 100. 3. Development of Pair Wise Comparison Matrix: Based on expert’s relative importance given to each criteria, a 15 x 15 order pair wise comparison matrix was developed, relative to an importance scale mentioned therein. 4. Normalized Pair Wise Comparison Matrix: A normalized pair wise comparison matrix of 15 x 15 order was generated by dividing each entry of a column of pair wise comparison matrix by respective column sum. 5. Criteria Weights: Adding each row entry got us a row sum which is equal to respective criteria weight. 6. Consistency Analysis: Consistency analysis was done by acquiring consistency index and getting it divided by random index for a 15 numbers of criteria set as given by JOSÉ et al (2005) consıstency ın the analytıc hıerarchy process: a new approach. 7. Calculation and Findings: Scores for various criteria and their weights were calculated as per respective standings of all alternatives (universities). The method and results have been mentioned in respective sections. 3.3. Weighted Aggregated Sum Product Assessment (WASPAS) Method İn order to develop a Weighted Aggregated Sum Product Assessment (WASPAS) model, a panel of 15 different respondents, comprising of both education consultants and prospected students, were the selection parameters were asked to give their opinions about the preferred set of criteria which they look while selecting a university abroad. Their response was classified into 15 points of assessment. The respective weightage of each 10 parameter was picked through AHP process. All those parameters were segregated on the basis of beneficial and non-beneficial criterias. WASPAS is a combination of two parallel procedures; Weighted Sum Model (WSM) and Weighted Product Model (WPM). The algorithm to carry out an accurate WASPAS based assessment had the following steps: 1. Development of Criteria Matrix: Based on expert’s opinions regarding selection parameters while chosing a university abroad, a criteria matrix was developed, and respective values were assigned to each university for its given criteria based on open sources’ information as placed in Appendix B. 2. Segregation of Criteria & Min / Max Values: All the criterias were segregated based on their attribute of being beneficial or cost criteria. The cost criteria was termed as non-beneficial one. Beneficial criteria was one whose higher value is desired while the non-beneficial one is that criteria whose lower value is generally desired. Highest row entry values were marked as Vmax against beneficial criteria rows while lowest values in rows against nonbeneficial criteria were marked as Vmin. 3. Normalized Matrix: A normalized criteria matrix was obtained by deviding each row entry with their respective Vmax or Vmin. Following formulas were used for this purpose: For Beneficial Criteria: Value / Vmax For Non-Beneficial Criteria: Vmin / Value 4. Criteria Weights: Criteria weights were kept same as obtained through AHP. 5. Weighted Sum Model (WSM): Weighted Sum Model is obtained by multiplying each Row Entry by respective Weight (obtained from AHP) and Adding each Row's all Entries, we'll get a Performance Value of Each Criteria. 6. Weighted Product Model (WPM): Weighted Product Model is obtained by raising each Row Entry to an Exponent of respective Weight (obtained from AHP); and then Mulitplying each Row's all Entries, we'll get a Performance Value of each Criteria. 7. WASPAS: WASPAS = [λ*(WSM)]+[(1-λ)*(WPM)] where λ was taken as 0.5 11 4. THE AHP METHOD The analytical hierarchy process for selection of a university among given seven options was complex as the choice of selection parameters had to be made in perspective of an international student. The perspective of students around the world varies from country to country of their origin. The process involved the following steps in detail: 4.1. Selection of Experts The current research is aimed to identify the best university for prospected international students. That needs to be inquired either from international education consultants or from prospected students who plan to undertake their education out of their country. A panel of 15 different respondents, comprising of both education consultants and prospected students, were taken as experts for this purpose. 4.2. Development of Selection Criteria Experst were initially asked to give their opinions about the preferred set of criteria which they look while selecting a university abroad. After developing a set of 15 criterias, all those respondents were asked to give relative importance of these criterias by assigning a weighted score to each one of 15 criterias, and thus by making a total sum of 100. Figure 5 - Development of Selection Criteria by Experts 4.3. Development of a Pair Wise Comparison Matrix [C] Based on expert’s relative importance given to each criteria, a 15 x 15 order pair wise comparison matrix was developed, relative to an importance scale mentioned therein. 12 Figure 6 – Pair Wise Comparison Matrix based on Experts Weightages The importance scale to replace relative pair wise comparison matrix’s values is as: Table 1 - Importance Scale Table Importance Scale Score Importance Value Reciprocal Score Reciprocal Value - Scores less than 1.0 will get a value, reciprocal of their conjugate cell; All the values in pair wise comparison matrix made through expert’s weightages were replaced as per above mentioned importance scale. Thus the pair wise comparison matrix, then obtained was: Figure 7 - Pair Wise Comparison Matrix Based on Importance Scale [C] 13 4.4. Normalized Pair Wise Comparison Matrix [C]N A normalized pair wise comparison matrix of 15 x 15 order was generated by dividing each entry of a column of pair wise comparison matrix by respective column sum. Figure 8 - Normalized Pair Wise Comparison Matrix 4.5. Criteria Weightages [W] Adding each row entry got us a row sum which is equal to respective criteria weightages. That turned out to be as follows: Table 2 - AHP Criteria Weightages C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 Ease of Processing Number of Schools & Faculties Top Citations Research & Publications Tuition Fees Accommodation Charges Students Exchange Programs Int'l Ranking of University National Ranking of University Total Strength of Teaching Faculty PhD Faculty Total Number of Students Number of International Students Student Teacher Ratio Number of Campuses Total 14 - 4.6. Consistency Analysis Consistency analysis was done by acquiring consistency index (CI) and getting it divided by random index (RI) for a 15 numbers of criteria set as given by JOSÉ et al (2005) consıstency ın the analytıc hıerarchy process: a new approach. The algorithm to carry out a consistency analysis had the following steps: 1. Calculating Weighted Sum Value Matrix [WSM]: Multiplying criteria weightages [W] to respective columns of pair wise comparison matrix [C] gave us Weighted Sum Value Matrix [WSM]. [WSM] = [C] x [W] 2. Calculation of λ: Again adding rows to get a weighted sum of each row and the dividing each row sum value with respective criteria weightages got us to row wise value of λ. Figure 9 - Weighted Sum Matrix and λ 3. Consistency ratio: Consistency index (CI) was calculated by CI = (λmax – n) / n – 1 Random index (RI) for n = 15 was given 1.5831 by JOSÉ et al (2005). A ratio of CI with respect to RI gave us Consistency Ratio (CR) which was found less than 0.1. Figure 10 - Consistency Validation 15 4.7. AHP Calculations for Respective Criteria Scores The respective data to allocate equivalent score against weightages have been picked up from most credible open sources in the following order of preferences: 1. University’s website 2. Credible ranking system’s websites as listed in Chapter 2 3. Open sources’ cited data published at online research databases The detailed comparison of each parameter against all universities with the source of respective data being mentioned is given in chapter 5; while calculation formulas are being placed in appendix 1. The calculated weightage scores against each parameter are as under: Table 3 - AHP Calculations for Respective Criteria Scores Code Criteria Weight Bahcesehir Bilgi Isik Ozyegin Altinbas Beykent Okan C1 Ease of Processing Number of Schools & Faculties Top Citations Research & Publications Tuition Fees Accommodation Charges Int’l Exchange Programs Int'l Ranking of University National Ranking of University Total Strength of Teaching Faculty PhD Faculty Total Number of Students Number of Int’l Students Student Teacher Ratio Number of Campuses 0.0327 0.02725 0.0218 0.01635 0.01635 0.0218 0.02725 0.01635 0.0200 0.0188 0.02 0.0129 0.0129 0.0141 0.0141 0.0141 0.0327 0.0310 0.0301 0.0295 0.0309 0.0303 0.0299 0.0297 0.0200 0.0189 0.01909 0.0175 0.01898 0.01558 0.01823 0.01749 0.0327 0.01362 0.0289 0.02335 0.02335 0.02069 0.0327 0.0272 0.0327 0.01284 0.0299 0.0327 0.0299 0.0214 0.0310 0.0128 0.1835 0.1835 0.1468 0.1101 0.1835 0.1101 0.0367 0.1468 0.0105 0.00859 0.00905 0.00728 0.00802 0.00659 - 0.00726 0.0327 0.025 0.028 0.0177 0.0224 0.0130 0.0198 0.01737 0.0105 0.0056 0.0105 0.00224 0.00508 0.0028 0.00745 0.00869 0.1835 0.12877 0.09446 0.05403 0.1085 0.09175 0.09175 0.09175 0.0963 0.06537 0.04255 0.02239 0.02240 0.03260 0.0963 0.08301 0.0963 0.0154 0.00725 0.00039 0.00453 0.03659 0.00298 0.00693 0.0327 0.0113 0.03234 0.01309 0.02973 0.01123 0.01015 0.01373 0.1835 0.1835 0.09175 0.06116 0.03058 0.09175 0.12233 0.03058 Total 1.000 0.751 0.613 0.421 0.547 0.520 0.548 0.524 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 16 5. THE WASPAS METHOD The selected performance indicators and ranking criteria has been chosen after detailed literature review and keeping in view the perspective of an international student while travelling abroad for his studies. İn order to develop a Weighted Aggregated Sum Product Assessment (WASPAS) model, a panel of 15 different respondents, comprising of both education consultants and prospected students, were the selection parameters were asked to give their opinions about the preferred set of criteria which they look while selecting a university abroad. Figure 11 - Selection of Performance Indicators and Allocation of Weightages The respective weightage of each parameter was picked through AHP process. All those parameters were segregated on the basis of beneficial and non-beneficial criterias. The respective data to allocate equivalent score against weightages have been picked up from most credible open sources in the following order of preferences: 1. University’s website 2. Credible ranking system’s websites as listed in Chapter 2 3. Open sources’ cited data published at online research databases İn the following sections, the detailed comparison of each parameter against all universities is being detailed, with the source of respective data being mentioned therein. 5.1. Int’l Students Admission Pre-Requisites It is the measure of ease of application and visa processing at each university. In addition, following assumptions were made to estimate the weighted score against this parameter:  Requirement of IELTS/TOEFL: -1 17  Turkish Proficiency Requirement: -1  Requirement of GRE: -1  Req of Recommendations: -1  If App Fee > 100 US $: -1  If Processing Time > 02 Months: -1 Table 4 - WASPAS Evaluation for Admission Pre-Reqs Sr University Value Source 1 Bahçeşehir University 5 bau.edu.tr /content / 9146-admission-offoreign-students-living-abroad-and-in-turkey 2 İstanbul Bilgi University 4 bilgi.edu.tr/en/international/internationaladmissions/admission-requirements/ 3 Işık University 3 isikun.edu.tr/ 4 Özyeğin University 3 https://www.ozyegin.edu.tr/en/studentservices/application-admission/ 5 Altınbaş University 4 international.altinbas.edu.tr/en/page/entryrequirements 6 Beykent University 5 beykent.edu.tr/en/international/internationalstudents/ 7 İstanbul Okan University 3 okan.edu.tr/en/international/page/7362/ language-requirements/ 5.2. Number of Schools and Faculties University with highest faculties has been awarded with full marks; while the rest being given marks relative to highest. Table 5 - WASPAS Evaluation for No of Schools and Faculties Sr University Value Source 1 Bahçeşehir University 16 int.bau.edu.tr/about-bau/bau-in-numbers/ 2 İstanbul Bilgi University 17 bilgi.edu.tr/en/ 3 Işık University 11 isikun.edu.tr/international 4 Özyeğin University 11 ozyegin.edu.tr/en/about-us 5 Altınbaş University 12 international.altinbas.edu.tr/en/page/altinbasin-numbers 6 Beykent University 12 beykent.edu.tr/en/academic/ 18 İstanbul Okan University 7 12 okan.edu.tr/en/ 5.3. Top Cited Researchers / Openness Rank Value Number of citations from Top 210 authors are being evaluated; lower rank will project higher score against weightage. A total of 30,000 universities around the globe has been evaluated. Table 6 - WASPAS Evaluation for Openness Rank Sr University Value Source 1 Bahçeşehir University 1,494 http://webometrics.info/en/Europe/Turkey 2 İstanbul Bilgi University 2,360 http://webometrics.info/en/Europe/Turkey 3 Işık University 2,878 http://webometrics.info/en/Europe/Turkey 4 Özyeğin University 1,652 http://webometrics.info/en/Europe/Turkey 5 Altınbaş University 2,186 http://webometrics.info/en/Europe/Turkey 6 Beykent University 2,533 http://webometrics.info/en/Europe/Turkey 7 İstanbul Okan University 2,662 http://webometrics.info/en/Europe/Turkey 5.4. Research and Publications Index / Excellenc Rank Value Number of papers published amongst the top 10% most cited journals in each one of the 26 disciplines of the full database. Lower rank gives higher score value and a total of 30,000 universities around the globe has been evaluated. Table 7 - WASPAS Evaluation for Excellence Rank Sr University Value Source 1 Bahçeşehir University 1,579 http://webometrics.info/en/Europe/Turkey 2 İstanbul Bilgi University 1,354 http://webometrics.info/en/Europe/Turkey 3 Işık University 3,726 http://webometrics.info/en/Europe/Turkey 4 Özyeğin University 1,519 http://webometrics.info/en/Europe/Turkey 19 5 Altınbaş University 6,626 http://webometrics.info/en/Europe/Turkey 6 Beykent University 2,643 http://webometrics.info/en/Europe/Turkey 7 İstanbul Okan University 3,753 http://webometrics.info/en/Europe/Turkey 5.5. Average Tuition Fees Graduate (Masters) programs only; higher fees will have less score. University with lowest fees has been awarded full marks; while the rest being given marks relative to it. Value represents an average of total graduate program fee in US $. Table 8 - WASPAS Evaluation for Tuition Expenses Sr University Value Source 1 Bahçeşehir University 12,000 2 İstanbul Bilgi University 5,650 bilgi.edu.tr/media/uploads/2019/11/14/ yl_fiyat_listesi_2019_20x30_eng.pdf 3 Işık University 7,000 isikun.edu.tr/web/-- 4 Özyeğin University 7,000 ozyegin.edu.tr/en/mba/tuition-feesscholarships 5 Altınbaş University 7,900 international.altinbas.edu.tr/en/page/tuitionand-fees 6 Beykent University 5,000 unipage.net/en/9867/beykent_university 7 İstanbul Okan University 6,000 studyinturkey.dreamapply.com/en_GB/ institutions/institution/362-okan-university int.bau.edu.tr/admission/tuition-fees/ 5.6. Accommodation Expenses Low accommodation expenses will project higher score against weightage. Value represents an average of monthly accommodation expense of single dormitory in US $. Table 9 - WASPAS Evaluation for Accommodation Expenses Sr University Value Source 1 Bahçeşehir University 700 int.bau.edu.tr/faq/ 2 İstanbul Bilgi University 300 rocapply.com/study-in-turkey/turkeyuniversities/ 3 Işık University 275 isikun.edu.tr/international/student-life 20 4 Özyeğin University 300 ozyegin.edu.tr/en/dormitories/housing-fees 5 Altınbaş University 420 international.altinbas.edu.tr/en/page/ accommodation 6 Beykent University 290 beykent.edu.tr/en/student/life-atbeykent/accommodation/ 7 İstanbul Okan University 700 apply.studyinturkey.com/en_GB/institutions/ institution/362-okan-university 5.7. International Students Exchange Programs University with most exchange programs has been awarded with full marks; while the rest being given marks relative to highest. Table 10 - WASPAS Evaluation for International Students Exchange Programs Sr University Value Source 1 Bahçeşehir University 5 international.bahcesehir.edu.tr/exchange/ 2 İstanbul Bilgi University 4 bilgi.edu.tr/en/in 3 Işık University 3 isikun.edu.tr/international/programs-andinternational-cooperation 4 Özyeğin University 5 ozyegin.edu.tr/en/international-cooperationexchange-programs/partner-institutions 5 Altınbaş University 3 altinbas.edu.tr/en/internationalization/intern ational-academic-cooperation/bilateralagreements 6 Beykent University 1 only Erasmus+ 7 İstanbul Okan University 4 okan.edu.tr/en/uluslararasiprogramlar/page/ 5160/bilateral-exchange-agreements/ 5.8. International Ranking of University Lower ranking number corresponds to higher score. Table 11 - WASPAS Evaluation for International Ranking of Universities Sr University Value Source 1 Bahçeşehir University 2509 https://www.4icu.org/reviews/4539.htm 2 İstanbul Bilgi University 1901 https://www.4icu.org/reviews/4569.htm 3 Işık University 4229 https://www.4icu.org/reviews/4568.htm 21 4 Özyeğin University 3259 https://cwur.org/2020-21.php 5 Altınbaş University 5127 https://www.4icu.org/reviews/14699.htm 6 Beykent University 3660 https://www.4icu.org/reviews/4542.htm 7 İstanbul Okan University 4255 https://www.4icu.org/reviews/10111.htm 5.9. National Ranking of University Lower ranking number corresponds to higher score. Table 12 - WASPAS Evaluation for National Ranking of Universities Sr University Value Source 1 Bahçeşehir University 37 https://www.4icu.org/reviews/4539.htm 2 İstanbul Bilgi University 25 https://www.4icu.org/reviews/4569.htm 3 Işık University 80 https://www.4icu.org/reviews/4568.htm 4 Özyeğin University 55 https://cwur.org/2020-21.php 5 Altınbaş University 105 https://www.4icu.org/reviews/14699.htm 6 Beykent University 69 https://www.4icu.org/reviews/4542.htm 7 İstanbul Okan University 82 https://www.4icu.org/reviews/10111.htm 5.10. Total Strength of Teaching Faculty University with highest number of faculty has been awarded with full marks; while the rest being given marks relative to highest. Table 13 - WASPAS Evaluation for Total Strength of Teaching Faculty Sr University Value Source 1 Bahçeşehir University 456 topuniversities.com/universities/bahcesehiruniversity 2 İstanbul Bilgi University 845 topuniversities.com/universities/istanbul-bilgiuniversitesi 3 Işık University 180 topuniversities.com/universities/isikuniversitesi 22 4 Özyeğin University 409 topuniversities.com/universities/ozyeginuniversity 5 Altınbaş University 225 timeshighereducation.com/world-universityrankings/altinbas-university 6 Beykent University 600 timeshighereducation.com/world-universityrankings/beykent-university 7 İstanbul Okan University 700 https://www.4icu.org/reviews/10111.htm 5.11. PhD Faculty Percentage Higher percentage of PhD faculty has been awarded more weightage scores. Table 14 - WASPAS Evaluation for Percentage of PhD Faculty Sr University Value Source 1 Bahçeşehir University 320 topuniversities.com/universities/bahcesehiruniversity 2 İstanbul Bilgi University 435 topuniversities.com/universities/istanbul-bilgiuniversitesi 3 Işık University 53 4 Özyeğin University 242 topuniversities.com/universities/ozyeginuniversity 5 Altınbaş University 113 Estimated figure – 50% 6 Beykent University 300 Estimated figure – 50% 7 İstanbul Okan University 350 Estimated figure – 50% topuniversities.com/universities/isikuniversitesi 5.12. Total Number of Enrolled Students University with highest number of students has been awarded with full marks; while the rest being given marks relative to highest. Table 15 - WASPAS Evaluation for Total Strength of Students Sr University Value Source 1 Bahçeşehir University 19688 topuniversities.com/universities/bahcesehiruniversity 2 İstanbul Bilgi University 12816 topuniversities.com/universities/istanbul-bilgiuniversitesi 3 Işık University 6744 topuniversities.com/universities/isikuniversitesi 23 4 Özyeğin University 6747 topuniversities.com/universities/ozyeginuniversity 5 Altınbaş University 9820 international.altinbas.edu.tr/en/page/altinbasin-numbers 6 Beykent University 29000 apply.beykent.edu.tr/en_GB/institutions/ institution/1-beykent-univesity 7 İstanbul Okan University 25000 https://www.4icu.org/reviews/10111.htm 5.13. Number of International Students Higher percentage of international students has been awarded more weightage scores. Table 16 - WASPAS Evaluation for Percentage of International Students Sr University Value 1 Bahçeşehir University 3160 2 İstanbul Bilgi University 965 3 Işık University 28 4 Özyeğin University 318 5 Altınbaş University 3732 6 Beykent University 900 7 İstanbul Okan University 1800 Source topuniversities.com/universities/bahcesehiruniversity topuniversities.com/universities/istanbul-bilgiuniversitesi topuniversities.com/universities/isikuniversitesi topuniversities.com/universities/ozyeginuniversity international.altinbas.edu.tr/en/page/altinbasin-numbers apply.beykent.edu.tr/en_GB/institutions/ institution/1-beykent-univesity Estimated figure 5.14. Student Teacher Ratio Lower student – teacher ratio will project higher score against weightage. Table 17 - WASPAS Evaluation for Student - Faculty Ratio Sr University Value Source 1 Bahçeşehir University 43 topuniversities.com/universities/bahcesehiruniversity 2 İstanbul Bilgi University 15 topuniversities.com/universities/istanbul-bilgiuniversitesi 3 Işık University 37 topuniversities.com/universities/isikuniversitesi 24 4 Özyeğin University 16 topuniversities.com/universities/ozyeginuniversity 5 Altınbaş University 44 international.altinbas.edu.tr/en/page/altinbasin-numbers 6 Beykent University 48 apply.beykent.edu.tr/en_GB/institutions/ institution/1-beykent-univesity 7 İstanbul Okan University 36 Estimated figure 5.15. Number of University Campuses Higher number of campuses will project higher score against weightage. Table 18 - WASPAS Evaluation for Number of Campuses Sr University Value Source 1 Bahçeşehir University 6 int.bau.edu.tr/about-bau/bau-in-numbers/ 2 İstanbul Bilgi University 3 bilgi.edu.tr/en/ 3 Işık University 2 isikun.edu.tr/international 4 Özyeğin University 1 ozyegin.edu.tr/en/about-us 5 Altınbaş University 3 international.altinbas.edu.tr/en/page/altinbasin-numbers 6 Beykent University 4 beykent.edu.tr/en/academic/ 7 İstanbul Okan University 1 okan.edu.tr/en/ 5.16. Aggregated Performance Scores after WASPAS Calculations WASPAS is a combination of two parallel procedures; Weighted Sum Model (WSM) and Weighted Product Model (WPM). The algorithm to carry out an accurate WASPAS based assessment had the following steps: 1. Development of Criteria Matrix: Based on expert’s opinions regarding selection parameters while chosing a university abroad, a criteria matrix was developed, and respective values were assigned to each university for its given criteria based on open sources’ information as placed in Appendix B. 25 WASPAS Criteria and Respective Values Code C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 Criteria Bahcesehir Bilgi Isik Ozyegin Altinbas Beykent Okan 5 16 4 17 3 11 1,494 1,579 12,-,-,688 3,160 43 6 2,360 1,354 5,-,-,- 2,878 3,726 7,-,-,- 3 11 1,652 1,519 7,-,-,- 4 12 2,186 6,626 7,-,-,820 3,732 44 3 5 12 2,533 2,643 5,-,-,- 3 12 2,662 3,753 6,-,-,000 1,800 36 1 Ease of Processing (Relative Value) Number of Schools & Faculties (Nos) Top Citations Rank (No) Research & Publications Rank (No) Tuition Fees (USD / Program) Accommodation Charges (USD / Month) Students Exchange Programs (No) Int'l Ranking of University (No) National Ranking of University (No) Total Strength of Teaching Faculty (No) PhD Faculty (No) Total Number of Students (No) Number of International Students (No) Student Teacher Ratio (Value) Number of Campuses (No) Figure 12 - WASPAS Criteria Matrix with Values 2. Segregation of Criteria & Min / Max Values: All the criterias were segregated based on their attribute of being beneficial or cost criteria. The cost criteria was termed as non-beneficial one. Beneficial criteria was one whose higher value is desired while the non-beneficial one is that criteria whose lower value is generally desired. Highest row entry values were marked as Vmax against beneficial criteria rows while lowest values in rows against nonbeneficial criteria were marked as Vmin. Table 19 - Segregation of WASPAS criteria Code Criteria B /NB Ref Value Vmax Vmin C1 Ease of Processing (Relative Value) B 6 5 C2 Number of Schools & Faculties (Nos) B - 17 C3 Top Citations Rank (No) NB 30,000 1,494 Research & Publications Rank (No) NB 30,000 1,354 Tuition Fees (USD / Program) NB - 5,000 Accommodation Charges (USD / Month) NB - B - C4 C5 C6 275 C7 Students Exchange Programs (No) C8 Int'l Ranking of University (No) NB 13,800 1,901 C9 National Ranking of University (No) NB 200 25 C10 Total Strength of Teaching Faculty (No) B - 845 C11 PhD Faculty (No) B - 435 C12 Total Number of Students (No) B - 29,000 C13 Number of International Students (No) B - 3,732 C14 Student Teacher Ratio (Value) NB - C15 Number of Campuses (No) B - 26 5 15 6 3. Normalized Matrix: A normalized criteria matrix was obtained by deviding each row entry with their respective Vmax or Vmin. Following formulas were used for this purpose: For Beneficial Criteria: Value / Vmax For Non-Beneficial Criteria: Vmin / Value Table 20 - Normalized Criteria Value Matrix Code Criteria Bahcesehir Bilgi Isik Ozyegin Altinbas Beykent Okan 1 0.8 0.6 0.6 0.8 1 0.6 0.941 1 0.647 0.647 0.706 0.706 0.706 1 0.633 0.519 0.904 0.683 0.590 0.561 C1 Ease of Processing C2 Number of Faculties C3 Top Citations Rank C4 Research & Publications 0.858 1 0.363 0.891 0.204 0.512 0.361 C5 Tuition Fees 0.417 0.885 0.714 0.714 0.633 1 0.833 C6 Accommodation Charges 0.393 0.917 1 0.917 0.655 0.948 0.393 C7 Students Exchange Programs 1 0.8 0.6 1 0.6 0.2 0.8 C8 Int'l Ranking of University 0.758 1 0.450 0.583 0.371 0.519 0.447 0.676 1 0.313 0.455 0.238 0.362 0.305 0.540 1 0.213 0.484 0.266 0.710 0.828 C9 C10 National Ranking of University Strength of Teaching Faculty C11 PhD Faculty 0.736 1 0.122 0.556 0.260 0.690 0.805 C12 Total Number of Students 0.679 0.442 0.233 0.233 0.339 1 0.862 C13 Number of Intl Students 0.847 0.259 0.008 0.085 1 0.241 0.482 C14 Student Teacher Ratio 0.349 1 0.405 0.938 0.341 0.313 0.417 C15 Number of Campuses 1 0.5 0.333 0.167 0.5 0.667 0.167 4. Criteria Weights: Criteria weights were kept same as obtained through AHP. Table 21 - Criteria Weights Code Weight Criteria 1 C1 Ease of Processing (Relative Value) 0.0327 C2 Number of Schools & Faculties (Nos) 0.0200 C3 Top Citations Rank (No) 0.0327 C4 Research & Publications Rank (No) 0.0200 C5 Tuition Fees (USD / Program) 0.0327 C6 Accommodation Charges (USD / Month) 0.0327 C7 Students Exchange Programs (No) 0.1835 C8 Int'l Ranking of University (No) 0.0105 C9 National Ranking of University (No) 0.0327 C10 Total Strength of Teaching Faculty (No) 0.0105 27 C11 PhD Faculty (No) 0.1835 C12 Total Number of Students (No) 0.0963 C13 Number of International Students (No) 0.0963 C14 Student Teacher Ratio (Value) 0.0327 C15 Number of Campuses (No) 0.1835 5. Weighted Sum Model (WSM): Weighted Sum Model is obtained by multiplying each Row Entry by respective Weight (obtained from AHP) and Adding each Row's all Entries, we'll get a Performance Value of Each Criteria. Weighted Sum Model & Performance Score Code C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 Criteria Ease of Processing (Relative Value) Number of Schools & Faculties (Nos) Top Citations Rank (No) Research & Publications Rank (No) Tuition Fees (USD / Program) Accommodation Charges (USD / Month) Students Exchange Programs (No) Int'l Ranking of University (No) National Ranking of University (No) Total Strength of Teaching Faculty (No) PhD Faculty (No) Total Number of Students (No) Number of International Students (No) Student Teacher Ratio (Value) Number of Campuses (No) Performance Score Rank Bahcesehir Bilgi Isik Ozyegin Altinbas Beykent Okan - - - - - - - - - - - - - - Figure 13 - Weighted Sum Model & Ranks 6. Weighted Product Model (WPM): Weighted Product Model is obtained by raising each Row Entry to an Exponent of respective Weight (obtained from AHP); and then Mulitplying each Row's all Entries, we'll get a Performance Value of each Criteria. 28 Weighted Product Model & Performance Score Code C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 Criteria Ease of Processing (Relative Value) Number of Schools & Faculties (Nos) Top Citations Rank (No) Research & Publications Rank (No) Tuition Fees (USD / Program) Accommodation Charges (USD / Month) Students Exchange Programs (No) Int'l Ranking of University (No) National Ranking of University (No) Total Strength of Teaching Faculty (No) PhD Faculty (No) Total Number of Students (No) Number of International Students (No) Student Teacher Ratio (Value) Number of Campuses (No) Performance Score Rank Bahcesehir Bilgi Isik Ozyegin Altinbas Beykent Okan - - - - - - - - - - - - - - Figure 14 - Weighted Product Model & Ranks 7. WASPAS: WASPAS = [λ*(WSM)]+[(1-λ)*(WPM)] where λ was taken as 0.5. The overall aggregated scores after calculation of each criteria’s weighatge against all universities are being detailed in the following figure: WASPAS Model Code C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 Criteria Ease of Processing (Relative Value) Number of Schools & Faculties (Nos) Top Citations Rank (No) Research & Publications Rank (No) Tuition Fees (USD / Program) Accommodation Charges (USD / Month) Students Exchange Programs (No) Int'l Ranking of University (No) National Ranking of University (No) Total Strength of Teaching Faculty (No) PhD Faculty (No) Total Number of Students (No) Number of International Students (No) Student Teacher Ratio (Value) Number of Campuses (No) Performance Score Rank Bahcesehir Bilgi Isik Ozyegin Altinbas Beykent Okan - - - - - - - - - - - - - - Figure 15 - WASPAS Model Performance Scores and Ranks 29 6. RESULTS AND CONCLUSIONS The Bahcesehir university stood out at top amongst its competitors due to strong structure of international students exchange programs, doctrate faculty, strength of enrolled students and most number of campuses. The results of both AHP and WASPAS methods turned out to be in well synchronization for top two universities i.e. for Bahcesehir and Bilgi University. The slight deviation for the ranks of remaining universities is because of the fact that they are very close in terms of performance indicators. A high weighted indicator in AHP would have turned into a lower one duing Weighted Sum or Product Model. The agreement of results with minor variation in lower ranked universities, increases the reliabilty and validates both of the methods adopted for this research. The overall comparison of aggregate scores in each reserach method and individual standing of respective universities has been delineated in the following table. Table 22 - Comparison of Results: AHP & WASPAS AHP Sr. WASPAS University Aggregate Standing Aggregate Standing 1 Bahcesehir 0.751 1 7.799 1 2 Bilgi 0.613 2 7.668 2 3 Isik 0.421 7 7.046 7 4 Ozyegin 0.547 4 7.363 6 5 Altinbas 0.520 6 7.397 5 6 Beykent 0.548 3 7.470 4 7 Okan 0.524 5 7.487 3 The above mentioned results declare the authenticity of the data gathered through open sources and reaffirms the research methodology used in this project. 30 APPENDIX A – AHP CALCULATIONS 31 32 APPENDIX B – WASPAS CALCULATIONS 33 34 REFERENCES A.T.W. Chu, R.E. Kalaba, K. Spingarn, (1979) A comparison of two methods for determining the weights of belonging to fuzzy sets, J. Optim. Theory Appl. 27 - T.L. Saaty (1980), The Analytic Hierarchy Process, McGraw-Hill, New York. T.L. Saaty, L.G. Vargas, (1984) Inconsistency and rank preservation, J. Math. Psychol- R.E. 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Jawad Ali, Zia, Tabasam (2021) WASPAS-based decision making methodology with unknown weight information under uncertain evaluations. 36 Web References https://int.bau.edu.tr. https://www.bilgi.edu.tr/en/ https://www.isikun.edu.tr/international https://www.ozyegin.edu.tr/en https://international.altinbas.edu.tr/en/ https://www.beykent.edu.tr/en https://www.okan.edu.tr http://en.wikipedia.org/wiki/Analytic_Hierarchy_Process http://webometrics.info/en/Europe/Turkey https://www.rocapply.com/study-in-turkey/turkey-universities/ https://www.unipage.net/en/ https://studyinturkey.dreamapply.com/ https://www.4icu.org/ https://cwur.org/2020-21.php https://www.timeshighereducation.com/world-university-rankings/ https://www.topuniversities.com/universities/ 37