Smartphone Addiction Assessment Using Pythagorean Fuzzy CRITIC-TOPSIS

Creative Commons License

Ertemel A. V., Menekse A., Camgöz Akdağ H.

Sustainability (Switzerland), vol.15, no.5, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 15 Issue: 5
  • Publication Date: 2023
  • Doi Number: 10.3390/su15053955
  • Journal Name: Sustainability (Switzerland)
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Aerospace Database, CAB Abstracts, Communication Abstracts, Food Science & Technology Abstracts, Geobase, INSPEC, Metadex, Veterinary Science Database, Directory of Open Access Journals, Civil Engineering Abstracts
  • Keywords: smartphone addiction, Pythagorean fuzzy, CRITIC, TOPSIS, MCDM
  • Istanbul Technical University Affiliated: Yes


Addiction to smartphones, particularly among adolescents, has reached alarming proportions, rivaling or perhaps exceeding internet addiction as the most widespread kind of dependence in modern culture. Evaluating the degree of problematic smartphone use habits by experts and identifying the vulnerable ones to steer to the right treatment program has become a critical issue. Since such a task may involve an abundance of criteria and candidates, as well as the inherent subjectivity of multiple decision experts participating in the process, the assessment of smartphone addiction can be framed as an uncertain multi-criteria decision-making (MCDM) problem. As an extension of intuitionistic fuzzy sets, Pythagorean fuzzy sets can be used to efficiently manage ambiguity and uncertainty during decision-making. This study provides an integrated fuzzy MCDM methodology based on Pythagorean fuzzy sets for evaluating the smartphone addiction level of adolescents. The Criteria Importance Through Inter-criteria Correlation (CRITIC) method is used to determine the importance levels of criteria in an objective manner, and smartphone addiction levels of the selected candidates are ranked using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach. A sensitivity analysis is conducted to examine the variations in candidate rankings caused by changes to the criteria and weights of the decision experts. Moreover, in the context of comparative analysis, the Evaluation based on Distance from Average Solution (EDAS) approach is used to validate the acquired findings.