Exploring the adoption of the metaverse and chat generative pre-trained transformer: A single-valued neutrosophic Dombi Bonferroni-based method for the selection of software development strategies


Önden A., Kara K., Önden İ., Yalçın G. C., Simic V., Pamucar D.

Engineering Applications of Artificial Intelligence, vol.133, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 133
  • Publication Date: 2024
  • Doi Number: 10.1016/j.engappai.2024.108378
  • Journal Name: Engineering Applications of Artificial Intelligence
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Keywords: Alternative ranking order method accounting for two-step normalization, Metaverse, Natural language processing, Single-valued neutrosophic sets, Virtual reality
  • Istanbul University Affiliated: Yes

Abstract

The contemporary era has witnessed remarkable developments that seek to transform and reshape traditional software development methodologies. Notably, artificial intelligence (AI) supported software development as well as software development in virtual reality environments have gained considerable prominence. This article introduces software development strategies to examine how software developers and companies respond to this transformation. Also, an advanced decision model is developed using the alternative ranking order method accounting for two-step normalization (AROMAN) method and further analyzed with the single-valued neutrosophic set-based AROMAN technique. The single-valued neutrosophic weighted Dombi Bonferroni operator is employed in the analysis process. This research offers two case studies investigating the preferences of developers and managers in software development strategies. The first case study examines the preferences of developers, while the second focuses on the preferences of managers. In both case studies, three fundamental software development methods are presented. These include the “traditional developers approach”, “AI-supported developers approach”, and “mixed reality and AI-supported developers approach”. These methods are ranked based on expert opinions concerning 10 criteria that influence the software development process. In both case studies, “output quality” is identified as the most influential criterion. From the perspective of software development methods, in both case studies, the “mixed reality and AI-supported developers approach” is identified as the most effective. Recommendations are provided for developers and managers. The findings also have significant implications for guiding developers and managers in making informed decisions and optimizing software development practices to align with the evolving AI and virtual reality landscape.