Earnings disparities in South Africa, and specifically the Eastern Cape region are influenced by a complex interplay of historical, socio-economic, and demographic factors. Despite significant progress since the end of apartheid, persistent disparities in earnings continue to raise questions about the effectiveness of policies aimed at reducing inequality and promoting equitable social system. Individual-level dataset from the 2021 South African general household survey were subjected to exploratory analysis, while Heckman selection model was used to investigate the determinants of earnings disparities in the study area. The results showed that majority of the population are not working for a wage, commission or salary, which also pointed to the gravity of unemployment situation in the area of study. Most of the working population (both male and female) are lowest earners (R ≤ 10,000), and this also cuts across all age-group categories. Majority of working population have no formal education, are drop out, or have less than grade-12 certificate, and very few working populations with higher education status were found in the moderate and relatively high earnings categories. While many of the working population are engaged in the informal sector, those in the formal sector are in the lowest earners group. Compared to any other race, the Black African group constituted the majority of non-wage earners, and most in this group were found in the lowest earners group. Some of the working population who were beneficiaries of social grants and medical aids scheme were found in the lowest, low, and moderate earnings categories. The findings significantly isolated the earnings-effect of age, marital status, gender, race, education, geographic indicators, employment sector, and index of health conditions and disabilities. The study recommends interventions addressing racial, gender, and geographic wage gaps, while also emphasizing the importance of equitable access to education, health infrastructure, and skills development.

Floods have always been an unavoidable natural disaster globally. Due to that, many efforts have been taken in order to alleviate the effect, especially in protecting the victims from losing their lives as well as their belongings. This study focuses on ensuring a smooth allocation process for flood victims to the relief centres considering the nature of their location, near the river, inland, and coastal. The finding indicated that a few implications have been highlighted for disaster management, such as changes in flood victim allocation patterns, classification of prone areas based on three areas, identification of most disaster areas, and others. Thus, to enhance the efficiency of allocation and to avoid any bad incidents happening during the flood occurrence, the allocation of flood victims is proposed to be started at a more critical area like the river area and followed by other areas. The finding also indicated that the proposed allocation procedure yielded a slightly lower average travel distance than the existing practice. These findings could also provide valuable information for disaster management in implementing a more efficient allocation procedure during a disaster.

Objective: The influence of climate on forest stands cannot be ignored, but most of the previous forest stand growth models were constructed under the presumption of invariant climate and could not estimate the stand growth under climate change. The model was constructed to provide a theoretical basis for forest operators to take reasonable management measures for fir under the influence of climate. Methods: Based on the survey data of 638 cedar plantation plots in Hunan Province, the optimal base model was selected from four biologically significant alternative stand basal area models, and the significant climate factors without serious covariance were selected by multiple stepwise regression analysis. The optimal form of random effects was determined, and then a model with climatic effects was constructed for the cross-sectional growth of fir plantations. Results: Richards formula is the optimal form of the basic model of stand basal area growth. The coefficient of adjustment  was 0.8355; the average summer maximum temperature  and the water vapor loss  in Hargreaves climate affected the maximum and rate of fir stand stand growth respectively, and were negatively correlated with the stand growth. The adjusted coefficient of determination  of the fir stand area break model with climate effects was 0.8921, the root mean square error (RMSE) was 3.0792, and the mean relative error absolute value (MARE) was 9.9011; compared with the optimal base model,  improved by 6.77%, RMSE decreased by 19.04%, and MARE decreased by 15.95%. Conclusion: The construction of the stand cross-sectional area model with climate effects indicates that climate has a significant influence on stand growth, which supports the rationality of considering climate factors in the growth model, and it is important for the regional stand growth harvest and management of cedar while improving the accuracy and applicability of the model.

Leadership behavior is a critical component of effective management, significantly influencing organizational success. While extensive research has examined key success factors in road management, the specific role of leadership behaviors in road usage charging (RUC) management remains underexplored. This study addresses this gap by identifying and analyzing leadership behavior dimensions and their impact on management performance within the RUC context. Using a mixed-methods approach, focus group discussions with industry practitioners were conducted to define eight leadership behavior dimensions: Central-Level Leadership Guidance (LE1), Local-Level Leadership Guidance (LE2), Central-Level Leadership Commitment (LE3), Local-Level Leadership Commitment (LE4), Subordinate Understanding from Central-Level Leadership (LE5), Subordinate Understanding from Local-Level Leadership (LE6), Work Motivation (LE7), and Understanding Rights and Obligations (LE8). These dimensions were further validated through a quantitative survey distributed to 138 professionals involved in RUC management in Vietnam, with the data analyzed using structural equation modeling (SEM) and partial least squares (PLS) estimation. The findings revealed that LE3 (Central-Level Leadership Commitment) had the strongest direct impact on management performance (MP) and mediated the relationships between other leadership dimensions and management outcomes. This study contributes to the theoretical understanding of leadership in RUC management by highlighting the centrality of leadership commitment and offering practical insights for improving leadership practices to enhance organizational performance in infrastructure management.

China is currently at a critical juncture in implementing the rural revitalization strategy, with urbanization and tourism development as crucial components. This study investigates 41 counties (cities) in the Wuling Mountain area of central China, constructing an evaluation system for the coordinated development of these two sectors. The coupling coordination degree is calculated using a combination weighting method and the coupling coordination degree model. Spatio-temporal evolution characteristics are analyzed through spatial autocorrelation, while the geographic detector explores the driving factors of spatial variation. The findings reveal a significant increase in coupling coordination between urbanization and tourism, transitioning towards a coordinated phase. Spatially, urbanization and tourism exhibit positive correlations, with high-value clusters in the southeast and northwest and low-value clusters in the south. The geographical detector identifies industrial factors as the most critical drivers of spatial variation. This study offers novel insights into the dynamics of urbanization and tourism, contributing to the broader literature by providing practical implications for regional planning and sustainable development. The results are relevant to the Wuling Mountain area and serve as a reference for similar regions globally. However, the study has certain limitations, such as regional specificity and data availability, which should be considered in the context of this research.