There are several methods in the literature to find the fuzzy optimal solution of fully fuzzy linear programming (FFLP) problems. However, in all these methods, it is assumed that the product of two trapezoidal (triangular) fuzzy numbers will also be a trapezoidal (triangular) fuzzy number. Fan et al. (“Generalized fuzzy linear programming for decision making under uncertainty: Feasibility of fuzzy solutions and solving approach”, Information Sciences, Vol. 241, pp. 12–27, 2013) proposed a method for finding the fuzzy optimal solution of FFLP problems without considering this assumption. In this paper, it is shown that the method proposed by Fan et al. (2013) suffer from errors and to overcome these errors, a new method (named as Mehar method) is proposed for solving FFLP problems by modifying the method proposed by Fan et al. (2013) . To illustrate the proposed method, some numerical problems are solved.

In many cases, the expected efficiency advantages of public-private partnership (PPP) projects as a specific form of infrastructure provision did not materialize ex post. From a Public Choice perspective, one simple explanation for many of the problems surrounded by the governance of PPPs is that the public decision-makers being involved in the process of initiating and implementing PPP projects (namely, politicians and public bureaucrats) in many situations make low- cost decisions in the sense of Kirchgässner (1948–2017). That is, their decisions may have a high impact on the wealth of the jurisdiction in which the PPP is located (most notably, on the welfare of citizen-taxpayers in this jurisdiction) but, at the same time, these decisions often only have a low impact on the private welfare of the individual decision-makers in politics and bureaucracy. The latter, for example, in many settings often have a low economic incentive to monitor/control what the private-sector partners are doing (or not doing) within a PPP arrangement. The purpose of this paper is to draw greater attention to the problems created by low-cost decisions for the governance of PPPs. Moreover, the paper discusses potential remedies arising from the viewpoint of Public Choice and Constitutional Political Economy.

Malaria is a mosquito-borne infectious disease that affects humans and poses a severe public health problem. Nigeria has the highest number of global cases. Geospatial technology has been widely used to study the risks and factors associated with malaria hazards. The present study is conducted in Ibadan, Oyo State, Nigeria. The objective of this study is to map out areas that are at high risk of the prevalence of malaria by considering a good number of factors as criteria that determine the spread of malaria within Ibadan using open-source and Landsat remote sensing data and further analysis in GIS-based multi-criteria evaluation (MCE). This study considered factors like climate, environmental, socio-economic, and proximity to health centers as criteria for mapping malaria risk. The MCE used a weighted overlay of the factors to produce an element at-risk map, a malaria hazard map, and a vulnerability map. These maps were overlaid to produce the final malaria risk map, which showed that 72% of Ibadan has a risk of malaria prevalence. Identification and delineation of risk areas in Ibadan would help policymakers and decision-makers mitigate the hazards and improve the health status of the state.

This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.

Carbonated soft drinks (CSDs) have long been a mainstay of the beverage business but changing consumer tastes and rising health awareness have necessitated a thorough study of the variables impacting consumer choices. This study intends to explore the complex web of customer preferences, purchasing behaviour, and perceptions related to carbonated soft drinks. This research analyses how numerous variables, including gender, affect these preferences and choices via careful examination. The purpose of thepresent research is to determine the perception of consumer influencing customer choice preferences for the consumption of carbonated soft drinks, influence of gender and the role of advertisement in finalizing the choice. It would be helpful to do further research to better understand how these highlighted variables affect purchasing choices, especially gender-based variances. The important influence of gender on consumer behaviour has been acknowledged. For this study, a structured questionnaire was distributed through online social media to individuals of 12–45 years of age from the period of April–May 2023. For analysis of the data collected, SPSS 22.0 was used. The study has confirmed that consumption of Coca-Cola is higher than any other soft drink in almost the entire country. The factors like youthfulness, tradition, status symbol and level of carbonation have different influences on the buying behavior of male and female consumers.