A Decision-Making Model Based on Topsis, Waspas, and Multimoora Methods for University Location Selection Problem
Bibliographic Data
| ID | 16910478 |
|---|---|
| Authors | Pınar MİÇ (0000-0002-9655-0319, Tarsus University, corresponding author), Z Figen Antmen (0000-0001-8475-1300, Cukurova University) |
| Year | 2021 |
| Volume | 11 |
| Issue | 3 |
| Publication date | 2021-07-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | SAGE Open (JOURNAL) |
| Journal identifiers | ISSN: 2158-2440 • E-ISSN: 2158-2440 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/21582440211040115 |
| OpenAlex | W3195860874 |
| Language | EN |
| Citations received | 1 |
| References cited | 81 |
With the growing population increase and following young population’s desire to study at the university, political authorities are supporting university and higher education investments, especially in the last 10 years. This situation has increased the number of universities considerably. Because a university will provide socioeconomic dynamism to both the development of the country and the region, choosing the right university location has become a significant problem nowadays. In line with this, this study is focused on supporting the new university location decision in a wide region in Turkey where currently the number of universities in the region is relatively low despite the high population density in the area. Alternative cities to be utilized in the study are determined particularly taking the demographic structure into consideration and various multicriteria decision-making (MCDM) techniques are applied. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Weighted Aggregated Sum Product Assessment (WASPAS), and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) are applied to a real case study. Related criteria and alternative locations are specified by consulting seven experts. Within the study, both the results of these methods are presented, and also sensitivity analyses are conducted to observe how sensitive the results are to the changes in the criteria weights. The results obtained are purposed to aid decision makers in this field
Economics · Ideal solution · Multiple-criteria decision analysis · Operations management · Operations research · Population · Preference · Sociology · Statistics · TOPSIS · Computer Science · Facility Location and Emergency Management · Mathematics · Multi-Criteria Decision Making · Optimization and Mathematical Programming · Artificial Intelligence
| Citations per year | 0.33 |
|---|---|
| Citation span | 2023 - 2023 (1) |
| Highly cited | No |