In the world of e-commerce, understanding the behaviour of customers is significant to solving a complex issue. Integrating graph theory with fuzzy sets and their various extensions can create an innovative approach to analysing user behaviour in e-commerce applications. This novel method will provide an overall and complete understanding of the specific relationships between consumers, products and transactions that can enable us to uncover hidden patterns, predict user preferences and optimize e-commerce platforms for enhanced user experiences and successive business. Extensions like Intuitionistic fuzzy sets will cater to situations when decisions are made under ambiguous conditions. This becomes increasingly applicable to e-commerce scenarios where consumer behaviour can be influenced by specific factors. When Graph theory is employed in the process, these sets can uncover valuable insights into the consumer's decision-making. Furthermore, Pythagorean fuzzy sets extend the Intuitionistic paradigm by providing an additional layer of precision. By distinguishing between the membership and non-membership functions, it affords a more granular view of e-commerce user behaviour. This can be particularly useful in deducing patterns within customer product reviews or purchase histories, paving the way for personalized marketing strategies. Similarly, Picture fuzzy sets facilitate the incorporation of neutral decisions within data analysis. Utilizing this extension within graph theory helps identify such potential opportunities for re-engagement. Adding to the pantheon of extensions are Hesitant fuzzy sets. In a world where users may have multiple opinions, these sets capture multiple values corresponding to the same element. In addition, there are many other extensions such as Shadowed sets, Q-rung orthopair sets, Neutrosophic sets, Plithogenic sets, Hypersoft sets that are used context of graph theory for analysing collective user behaviour in E-commerce applications. As a result, this nuanced tool allows for the expression of hesitations and reservations, crucial factors often overlooked in traditional e-commerce user behaviour analysis.To further enrich the analysis of collective user behaviour in e-commerce applications, a powerful mathematical construct called "Super Hyper Graphs" can be integrated into the fusion of fuzzy sets and graph theory. Super Hyper Graphs are an extension of traditional hypergraphs and can efficiently capture higher-order relationships and dependencies among multiple entities in a network. It has the ability to represent complex interactions between users, products, and transactions, allowing for a more comprehensive analysis of user behaviour patterns and preferences.In conclusion, the interplay of fuzzy sets and their extensions with graph theory including the integration of Super Hyper Graphs, has empowered e-commerce with a fresh analytical perspective. By adopting the uncertainty, ambiguity and variability intrinsic to collective user behaviour, these mathematical tools help map complex behavioural patterns ushering in a new era of consumer-centric e-commerce strategies. This special issue aims to dive deeper into the amalgamation of fuzzy sets along with their extensions and graph theory for the purpose of specifically targeting the sphere of e-commerce.

Potential topics include but are not limited to the following:

• Need for Fuzzy graph theory for decision-making analysis in business
• Exploring the effectiveness of Intuitionistic fuzzy sets in e-commerce user behaviour analysis.
• Application of Pythagorean fuzzy sets in precision marketing within e-commerce.
• Dynamic Super Hyper Graph Modelling for Real-time User Behaviour Analysis
• Integrating Picture fuzzy sets for analysing user indecision and improving re-engagement strategies.
• Hesitant fuzzy sets and the capture of multi-preference behaviour in e-commerce scenarios.
• Incorporating Neutrosophic sets in e-commerce models to deal with data inconsistencies.
• Emerging advances in fuzzy graph theory for the future business markets
• Utilization of Hypersoft sets for multi-attribute decision-making in e-commerce applications.
• Innovations in fuzzy graph theory for advertising and marketing in e-commerce
• Challenges and solutions in implementing fuzzy set-based models in e-commerce.
• Fuzzy graph theory for recommender systems in e-commerce
• Predictive modelling of user behaviour using fuzzy sets and graph theory in e-commerce.
• The influence of fuzzy set-based models on e-commerce strategies and outcomes.
• Future trends and prospects of fuzzy sets and their extensions in e-commerce.

Important Dates

• Paper Submission Due: 08.02.2024
• Notification of Review Results: 10.05.2024
  
• Revised Manuscript Due: 09.07.2024
  
• Final Decision: 15.09.2024

Guest Editors:

• Prof. Jia-Bao Liu (Lead Guest Editor) , Anhui Jianzhu University, Hefei, P.R. Chin (Email: liujiabao@ieee.org and liujiabao@ahjzu.edu.cn )
• Prof. Dr. Muhammad Javaid, University of Management and Technology, Lahore, Pakistan Pakistan (Email: muhammad.javaid@umt.edu.pk  )
• Dr. Mohammad Reza Farahani, Iran University of Science and Technology, Tehran, Iran (Email: mrfarahani88@gmail.com )