Smartphone Selection Using MOORA and MOOSRA
Mehmet Hakan ÖzdemirMany electronic devices have become an indispensable part of our daily life thanks to the rapidly developing technology. Smartphones are the best example for this and choosing the right smartphone is becoming more and more important. In this study, first, eight criteria that are important in the smartphone selection were determined through literature search. These criteria are weight, rear camera resolution, battery capacity, RAM capacity, internal storage capacity, screen size, price and thickness. Then, university students were asked to rank these eight criteria in order of importance, and the criteria weights required for analysis were calculated from these rankings. Afterwards, seven smart phone models from different brands have been determined by taking into consideration the price range students can afford, and data for these eight criteria have been obtained from the Internet. Finally, a smartphone was selected among the seven smartphone models by using the calculated criteria weights in MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) and MOOSRA (Multi-Objective Optimization on the basis of Simple Ratio Analysis) methods and the results were interpreted.
MOORA ve MOOSRA Yöntemleriyle Akıllı Telefon Seçimi
Mehmet Hakan ÖzdemirBirçok elektronik alet, hızla gelişen teknoloji sayesinde günlük hayatımızın vazgeçilmez bir parçası haline gelmiştir. Akıllı telefonlar buna en güzel örnektir ve doğru akıllı telefon seçimi bu yüzden gitgide önem kazanmaktadır. Bu çalışmada öncelikle literatür taraması yapılarak akıllı telefon seçiminde önemli olan sekiz kriter belirlenmiştir. Bu kriterler, ağırlık, arka kamera çözünürlüğü, batarya kapasitesi, RAM kapasitesi, dahili depolama kapasitesi, ekran boyutu, fiyat ve kalınlıktır. Daha sonra üniversite öğrencilerinden bu sekiz kriteri önem sırasına göre sıralamaları istenmiştir ve bu sıralamalardan analiz için gerekli kriter ağırlıkları hesaplanmıştır. Sonra öğrencilerin alabileceği fiyat aralığı da göz önünde bulundurularak farklı markalardan yedi akıllı telefon modeli belirlenmiştir ve İnternet’ten bu modellerin belirlenen sekiz kritere ait verileri elde edilmiştir. Son olarak hesaplanan kriter ağırlıkları kullanılarak yedi akıllı telefon modeli arasından MOORA (MultiObjective Optimization on the basis of Ratio Analysis) ve MOOSRA (Multi-Objective Optimization on the basis of Simple Ratio Analysis) yöntemleri ile akıllı telefon seçimi yapılmıştır ve sonuçlar yorumlanmıştır.
Background
Smartphones have become an indispensable part of our lives with the development of technology. Mobile phones, which were previously used only for phoning and messaging purposes, now allow us to carry out our work from anywhere. According to the Digital 2020 report, there are 5,19 billion mobile phone users worldwide. According to this report, the rate of having any type of mobile phone is given to 90% among Internet users aged 16 to 64 years in our country. Statistics also show that 89% of Internet users between the ages of 16 and 64 in Turkey have a smartphone. This high rate clearly shows the importance of smartphone selection.
We have to make various decisions at every moment of daily life. Decision making is the process of choosing the best of the various alternatives where there are often many criteria. The term multi-criteria decision making (MCDM) refers to decision making in the presence of multiple conflicting criteria. Since the effects of the criteria differ from person to person when making a decision, each criterion affects the decision to a certain extent. There are various studies in which MCDM methods are applied to the selection of technological products. In this study, MOORA and MOOSRA methods were used for the smartphone selection.
Method
In MCDM models, the following three steps are followed: First, the relevant criteria and alternatives are determined, then the criteria weights are calculated and numerical values of the alternatives for the criteria are attached. Finally, these numerical values are processed and a ranking for each alternative is determined.
Students studying at the Turkish-German University in Istanbul were asked to rank the eight criteria, which were previously determined through literature search, in terms of importance in order to select a smartphone. These criteria are weight (g) (K1), rear camera resolution (MP) (K2), battery capacity (mAh) (K3), RAM capacity (GB) (K4), internal storage capacity (GB) (K5), screen size (inch) (K6), price (TL) (K7) and thickness (mm) (K8). For each student, the criteria weights were calculated from these rankings by using the rank-order centroid weight method and then the average was taken. The most important criterion for students in the selection of smart phones turned out to be the price. This is followed by battery capacity, RAM capacity, rear camera resolution, internal storage capacity, screen size, thickness and weight.
Seven smartphone models (A1, A2, A3, A4, A5, A6 and A7) from different brands have been determined by taking into consideration the price range students can afford, and data for these eight criteria have been obtained from the Internet. A smartphone was selected among the seven smartphone models by using the calculated criteria weights in MOORA and MOOSRA methods. For both methods, rear camera resolution, battery capacity, RAM capacity, internal storage capacity and screen size are the criteria to be maximized and weight, price and thickness are the criteria to be minimized.
Conclusion
In both methods, the A6 model is the best alternative. Although the price of the A6 model is relatively high compared to the price of other models, the high battery capacity and RAM capacity of this model as well as its high rear camera resolution put this model in the first place. As mentioned above, these three criteria follow the price criteria with the highest weight. In addition, both method gave the exactly the same rankings. MOORA and MOOSRA methods are mathematically not complex and very easy to apply. With these features, they are very advantageous compared to other MCDM methods. Rankings can be obtained by easily calculating yi * values with Microsoft Excel without the need for any other software package. Also, the calculation time is very short.
