An intelligent assessment of factors affecting new generations in the era of the internet and new media using intuitionistic hesitant fuzzy sugeno-weber aggregation operators.

The network of millions of linked devices that exchange resources is known as the Internet. The rapid expansion of digital connectivity necessitates an assessment and understanding of its multifaceted impact on younger generations. There are many benefits and drawbacks to using the Internet, including issues with human health, education and learning habits, communication and relationships, and privacy and security. Almost every area of life involves some degree of uncertainty and fuzziness. The best method for practically reducing ambiguity when determining the best option from fuzzy and uncertain data is multi-attribute decision-making (MADM). The research aims to develop a comprehensive decision framework for examining Internet effects on youth generations through fundamental behavioral and social elements. So, in this regard, the Intuitionistic Hesitant Fuzzy set (IHFS) is an effective and flexible tool for the investigation of uncertain information. The Sugeno-Weber operational (SWO) rules are a more generalized and flexible approach than other existing triangular norms (TN) and triangular conorm (TCN). Using SWOs and IHFS information, we construct the intuitionistic hesitant fuzzy Sugeno-Weber weighted averaging (IHFSWWA) and intuitionistic hesitant fuzzy Sugeno-Weber weighted geometric (IHFSWWG) operators. Also, we investigate some fundamental axioms of aggregation operators (AOs), like monotonicity, boundedness, and idempotency. We construct the MADM algorithm based on the developed theory, and some solve real-life numerical examples for assessment of factors affecting the new generations given the internet. To validate the effectiveness and practical applicability, a comparison analysis was conducted between the proposed IHFSWWA and IHFSWWG approaches with existing AOs. The conclusion is discussed in the last section.