The United States, Mexico, and Canada (USMCA) seek to promote fair wages and adequate working conditions, especially in Mexico, by strengthening labor rights and freedom of association. The objective of this research is to determine the factors that influence salary levels in the Mexican Automotive Industry (MAI), through a causality analysis in the Granger sense, to generate a panorama that allows a decision-making process in the Mexican salary policy. With data from the National Institute of Statistics and Geography, the Bank of Mexico and Statista, autoregressive vector models were estimated to determine causalities in the Granger sense. It was proven that minimum wage, employed personnel, production, total sales, and exports are some causes of remuneration in the sector, with the minimum wage being the most significant. The above suggests that the salary increase involves several actors, such as the government (minimum wage), the organization (production, sales and exports) and the market (employed personnel), therefore, the design of appropriate labor policies will contribute to the dignification of salaries inside the MAI.

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 paper demonstrates the importance of subnational data on housing to be systematically reported and added to country typologies. We asked which national and local level characteristics of housing regimes can serve as benchmarks for reasonable country groupings. The aim of this paper is to (1) develop a methodological tool enabling the comparison of conditions for housing policy implementation on national and subnational levels and (2) identify the group of countries where conditions for housing policy implementation on national and subnational levels tend to be comparable. This country classification can be used as a practical instrument for comparative analyses and policy learning. As a conceptual framework, we used the international comparative Housing research 2.0 launched by Hoekstra in 2020. For our analysis, we selected 15 basic factors that were tested in 24 European countries. We have identified three key factors having an impact on housing policy implementation: decentralisation level in housing, local budget housing expenditure and the information on which governance level has core competencies within housing. The numeric database has been run through a k-means cluster analysis. Five distinct types of countries with similarities in conditions for housing policy implementation on national and subnational level have been identified and described.

The number of accidents at level railway crossings, especially crossings without gate barriers/attendants, is still very high due to technical problems, driving culture, and human error. The aim of this research is to provide road maps application based on ergonomic visual displays design that can increase awareness level for drivers before crossing railway crossings. The double awareness driving (DAD) map information system was built based on the waterfall method, which has 4 steps: defining requirements, system and software design, unit testing, and implementation. User needs to include origin-destination location, geolocation, distance & travel time, directions, crossing information, and crossing notifications. The DAD map application was tested using a usability test to determine the ease of using the application used the System Usability Scale (SUS) questionnaire and an Electroencephalogram (EEG) test to determine the increase in concentration in drivers before and immediately crossing a railway crossing. Periodically, the application provides information on the driving zone being passed; green zone for driving distances > 500 m to the crossing, the yellow zone for distances 500m to 100m, and the red zone for distances < 100 m. The DAD map also provides information on the position and speed of the nearest train that will cross the railway crossing. The usability test for 10 respondents giving SUS score = 97.5 (satisfaction category) with a time-based efficiency value = 0.29 goals/s, error rate = 0%, and a success rate of 93.33%. The cognitive ergonomic testing via Electroencephalogram (EEG) produced a focus level of 21.66%. Based on the results of DAD map testing can be implemented to improve the safety of level railroad crossings in an effort to reduce the number of driving accidents.

The research aims to explore the degree of acceptance of digital work culture among the youth in the Emirati society within the study sample. Additionally, it aims to reveal the relationship between “gender” and “educational status” as sociodemographic factors among the youth in the study sample and their level of acceptance of digital work culture. Furthermore, the study aims to identify prospective trends in digital work culture among young individuals in Emirati society. Due to the nature of the descriptive research, it employed the “sample social survey” approach. The field study primarily utilized a quantitative tool for data collection, namely the “digital questionnaire.” This questionnaire was administered to a purposefully chosen random sample comprising young individuals actively seeking employment opportunities (unemployed individuals) or those new to the labor market. The participants fell within the age group of 15 to 35 years, totaling 184 individuals. Care was taken to ensure that this sample was representative of all youth categories in Emirati society, considering demographic factors such as gender, place of residence, and educational status. The research findings indicate that an overwhelming majority of young individuals in the study sample (97.8%) have no obstacles to accepting job opportunities that necessitate digital and technological skills. Moreover, the study uncovered a direct and statistically significant relation between “gender” and the “level of acceptance of digital work culture,” favoring females. This implies that females are more inclined to accept digital job opportunities compared to males. Additionally, the results highlighted a positive and statistically significant relation between both “educational status” and the “level of acceptance of digital work culture.” In other words, individuals with higher levels of education demonstrate a greater interest in digital job opportunities. Utilizing Step-wise Regression, the study also made predictions about the spread of “future digital work culture” in the United Arab Emirates based on the variable of “education.”