Low levels of financial literacy cause people to have lower savings rates, higher transaction costs, larger debts and the loans acquisition with higher interest rates, therefore it becomes relevant to analyze the determinants of financial literacy. The aim of this research is to identify whether there is an association between the financial literacy level and sociodemographic characteristics. The Mexican Petroleum Company (Pemex) employees is the population analyzed. Pemex is the state-owned oil and natural gas producer, transporter, refiner and marketer in Mexico. A non-probabilistic convenience sampling was performed and 404 responses were obtained. The analysis of data was carried out with the Bayesian method. The results show that there is an association between Pemex employees’ level of financial literacy and their level of education, income, age and type of retirement saving. No association was found between their level of financial literacy and gender, marital status and whether or not they have children.

Ignorance of laws and policies creates barriers to the social inclusion of persons with disabilities (PWDs), hindering their full participation in communal life and opportunities. The current study aims to analyze the social inclusion of PWDs in the context of ignorance of laws and policies and how it influences their overall social inclusion. To achieve the study objectives, data were collected from a sample of 488 PWDs, comprising 284 males and 204 females, in the selected six Union Councils (sub-administrative units) of District Malakand, Pakistan. Respondents were chosen through multistage stratified random sampling. In the univariate and multivariate level analyses, the chi-square test and Kendall’s Tau-b test statistics were used to test the relationship between ignorance of laws and policies and the social inclusion of PWDs. Gender and level of disability were used as control variables at the multivariate level. The results of Kendal Tb and chi-square significance values depicted a spurious relation among ignorance of laws and policies and social inclusion of PWDs while controlling respondent’s gender. The results highlighted that ignorance of laws and policies reduced social inclusion in male to a higher extent than female. Additionally, the social inclusion of PWDs with moderate disabilities is more significantly hampered by ignorance of laws and polices than those with severe disabilities.

The aim of this article is to investigate the impediments to creativity perceived by managers, the levels of creativity, its indicators, and personal characteristics conducive to creativity, as well as to elucidate the correlations among them. An experimental study was conducted involving 300 participants. Methods employed include surveying, testing, and mathematical statistical analysis. As the level of creativity increases, participants tend to assess their opportunities more favorably. The expression of creativity depends on the interconnection among the barriers to creativity, indicators of creativity, and personal qualities of creativity. A high level of creativity is manifested when there are fewer barriers and personal qualities such as Imagination and a propensity for Risk-taking. Conversely, the level of expression of creativity is low when there is an interconnection between Creativity and Complexity, Imagination, and creativity barriers such as lack of confidence and conformity to majority opinion.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.

This study scrutinizes the allocation of financial aid for climate change adaptation from OECD/DAC donors, focusing on its effectiveness in supporting developing countries. With growing concerns over climate risks, the emphasis on green development as a means of adaptation is increasing. The research explores whether climate adaptation finance is efficiently allocated and what factors influence OECD/DAC donor decisions. It examines bilateral official development assistance in the climate sector from 2010 to 2021, incorporating climate vulnerability and adaptation indices from the ND-GAIN Country Index and the IMF Climate Risk Index. A panel double hurdle model is used to analyze the factors influencing the financial allocations of 41,400 samples across 115 recipient countries from 30 donors, distinguishing between the decision to select a country and the determination of the aid amount. The study unveils four critical findings. Firstly, donors weigh a more comprehensive range of factors when deciding on aid amounts than when selecting recipient countries. Secondly, climate vulnerability is significantly relevant in the allocation stage, but climate aid distribution does not consistently match countries with high vulnerability. Thirdly, discerning the impact of socio-economic vulnerabilities on resource allocation, apart from climate vulnerability, is challenging. Lastly, donor countries’ economic and diplomatic interests play a significant role in climate development cooperation. As a policy implication, OECD/DAC donor countries should consider establishing differentiated allocation mechanisms in climate-oriented development cooperation to achieve the objectives of climate-resilient development.

Infrastructure development policies have been criticised for lacking a deliberate pro-gender and pro-informal sector orientation. Since African economies are dual enclaves, with the traditional and informal sectors female-dominated, failure to have gendered infrastructure development planning and investment exacerbates gender inequality. The paper examines the effect of the infrastructure development index, the size of the informal economy, and the level of economic development on gender inequality. The paper applies the panel autoregressive distributed lag method to data on the gender inequality index, infrastructure development index, GDP per capita, and size of the informal sector for the period 2005–2018. The sample consists of 44 African countries. The research established that the infrastructure development index, its sub-indices, GDP per capita, and the size of the informal sector are crucial dynamics that governments need to consider carefully when formulating development policies to reduce gender inequality. The research found that investment in infrastructure in general, transport infrastructure, and energy infrastructure reduces gender inequality. infrastructure development has gender inequality increasing effects in some countries and gender inequality reducing effects in others. The pattern suggests that at the continental level a Kuznets-type patten in the relationship between gender inequality and infrastructure development, gender inequality and size of informal sector, and gender inequality and GDP per capita exists. Some countries are in the region where changes in these covariates positively correlate with gender inequality, while others are in the region where further increases in the covariates reduce gender inequality.