Smog is a significant threat in Pakistan, having become a persistent issue in recent years. Excessive industrialization, increased reliance on fossil fuels, and increased automobile emissions have all led to epidemic levels of air pollution. Smog, or air pollution, can pose significant risks to humans and plants due to its harmful effects. Air pollution contributes to global health issues, including lung, breathing, and skin ailments. Pakistan, an undeveloped nation, is grappling with the detrimental effects of smog on various sectors such as health, ecology, transportation, and education. This study aims to employ multi-criteria decision-making (MCDM) methodologies to examine points of view on smog-related issues in Pakistan. The analysis specifically concentrates on the health, economic, social, and ecological consequences of smog and the solutions employed to mitigate its effects. By employing various approaches, such as the Method based on the Removal Effects of Criteria (MEREC) objective weighting technique to determine the weights of each criterion and select the essential criteria, pair-wise comparisons are performed in the Best–Worst Method (BWM) on the best and worst criteria selected through MEREC. We have created a designated consistency ratio for the BWM to assess the reliability of the comparisons. Entropy is an objective weighting technique used to calculate the weights of the best and worst criteria, and the TOPSIS technique is employed to determine the most suitable alternative from a collection of choices by evaluating their resemblance to an ideal answer.

One of the most important innovations brought by digitization is the cryptocurrency, also called virtual or digital currency, which has been discussed in recent years and in particular is a new platform for investors. Different types of cryptocurrencies such as Bitcoin, Ethereum, Binance Coin, and Tether do not depend on a central authority. Decision making is complicated by categorization and transmission of uncertainty, as well as verification of digital currency. The weighted average and weighted geometric aggregation operators are used in this article to define a multi‐attribute decision‐making approach. This work investigates the uniqueness of q‐rung orthopair fuzzy hypersoft sets (q‐ROFHSS), which respond to instabilities, uncertainty, ambiguity, and imprecise information. This research also covers some fundamental topics of q‐ROFHSS. The model offered here is the best option for learning about electronic currency. This study validates the complexity of decision‐making problems with different attributes and subattributes to obtain an optimal choice. We conclude that Bitcoin has a diverse set of applications and that crypto assets are well positioned to become an important asset class in decision making.

Agriculture remains the backbone of Pakistan’s economy, supporting a substantial segment of the rural population. Recently, agritourism has emerged as a viable avenue for economic diversification, offering new income streams in rural communities. This study explores stakeholder perceptions of sustainable development in agritourism and seeks to identify the key criteria and alternatives necessary for strategic decision-making in this sector. The fuzzy rough set approach is used for multi-criteria decision-making on the data collected from a questionnaire-based survey. Seven alternatives are analyzed for ten criteria. The analysis revealed that retail opportunities, agri-farm tours, farm stays, and on-site activities are the high-ranked alternatives for balancing sustainable agritourism's economic, environmental, and social impacts.

Consumption of renewable energy is on the rise because new technologies have made it cheaper and easier to meet the needs of a long-term energy source. In the present study, the idea of optimal usage of sustainable energy is discussed, taking into consideration the environmental and economic conditions that exist in Pakistan’s textile manufacturing industry. By taking into account the regional potential for the application of renewable energy resources, solar energy generators are taken into consideration, and a fully intuitionistic fuzzy (FIF) textile energy model is constructed. Using the FIF model to determine the optimal distribution of solar energy units resulted in a tolerable number of unused energy units. These units may be returned to the central power supply station, which would save both money and energy.