A Two-Phased Multi-Criteria Decision-Making Approach for Selecting the Best Smartphone

Abstract

In the last 20 years, rapid and significant developments have occurred in communication and information technologies. In parallel with these developments, the importance of smartphones has increased. In addition, many smartphone manufacturers have launched and continue to launch a number of new models with many features. People who want to buy a new smartphone have difficulties selecting the best smartphone among the numerous models available on the technology markets. Therefore, smartphone selection has become a complex multi-criteria decision-making (MCDM) problem for people. Hence, decision-making processes will be facilitated by using MCDM methods, and these will provide the most appropriate decision. In this paper, the best smartphone among the 28 alternatives determined by the person who will buy them are selected by using three main criteria and 17 sub-criteria with the help of a two-phased MCDM approach. In the first phase, 28 smartphone alternatives are ranked using the analytic network process (ANP). In the second phase, a model that includes the best four alternatives of ANP is created. Afterwards, the best smartphone is selected using the generalised Choquet integral (GCI) method according to this model. Finally, the findings and the results are given. OPSOMMINGGedurende die afgelope twintig jaar het daar vinnige en noemenswaardige ontwikkeling in die kommunikasie en informasie tegnologie geskied. In parallel hiermee het die belangrikheid van slimtelefone toegeneem. Daarmee saam stel slimtelefoon-vervaardigers gereeld nuwe modelle met nuwe funksies vry. Dit is dus moeilik vir 'n potensiële kliënt om die beste seleksie uit die groot verskeidenheid tot hul beskikking te maak. Slimtelefoonseleksie is 'n ingewikkelde multi-kriteria besluitnemingsprobleem. Die besluitnemingsproses word dus gefasiliteer deur gebruik te maak van multi-kriteria besluitnemingsmetodes. Hierdie artikel bepaal die beste slimtelefoon vanuit agt-en-twintig alternatiewe deur gebruik te maak van drie hoof kriteria en sewentien subkriteria met die hulp van 'n twee-ledige multi-kriteria besluitnemingsbenadering. Eerstens word die agt-entwintig alternatiewe met behulp van die analitiese netwerk proses gerangskik en daaruit word 'n model, wat uit die vier beste alternatiewe bestaan, geskep. Laastens word die beste slimtelefoon gekies deur die veralgemeende Choquet integraal metode op die model toe te pas.

An Extended Intuitionistic Fuzzy Multi-Attributive Border Approximation Area Comparison Approach for Smartphone Selection Using Discrimination Measures

“…We have implemented the same numerical example applying the developed approach for comparing with the existing approaches. The above Smartphone selection problem is also solved by the ANP-Generalized Choquet integral method (Yildiz and Ergul, 2015), the fuzzy ELECTRE method (Belbag et al, 2016) and the Shapley discrimination measure VIKOR method (Mishra and Rani, 2019). Outcomes of the different approaches were obtained to certify the outcomes of the developed IF-MABAC method.…”

“…ii. The developed approach utilizes IFSs to develop the procedure, different from the methods in Yildiz and Ergul (2015) and Belbag et al (2016), wherein the FSs are implemented. iii.…”

“…iv. Multiple DEs have been selected in the developed method whose weights are given in terms of IFNs, while the methodology proposed in Yildiz and Ergul (2015), Belbag et al (2016) and Mishra and Rani (2019) did not incorporate the group decision making (GDM) procedure. v. Criteria weights in the developed IF-MABAC method are provided as IFNs, whereas in Belbag et al (2016) and Mishra and Rani (2019), the crisp weights are assumed, leaving no space to handle the uncertainty.…”

An Integrated Multi-Attribute Model for Evaluation of Sustainable Mobile Phone

“…The methods of analysis used in these studies varied. Among them, considerable works stand out the use of MCDM methods [18,[24][25][26][27][28][29][30][31][32][33][34]. However, the literature in which they consider sustainability criteria when choosing a mobile phone by consumers is much lower [6,15,17,[35][36][37][38][39] and none of them uses MCDM.…”

“…Büyüközkan and Güleryüz [26] integrated fuzzy theory to TOPSIS method in order to deal with uncertainty in a process of smart mobile phone selection. Application of analytical network process and generalized Choquet integral (GCI) byYildiz and Ergul [25], offered a mechanism for clients to rely on a selection strategy for their desirable mobile phones. In India, a group of experts modeled a structure for smartphone selection using hardware, economic and physical attributes and multi-criteria tools called valuation based on distance from average solution [43].…”