Diagnosis-related groups (DRGs) are gaining prominence in healthcare systems worldwide to standardize potential payments to hospitals. This study, conducted across public hospitals, investigates the impact of DRG implementation on human resource allocation and management practices. The research findings reveal significant changes in job roles and skill requirements based on a mixed-methods approach involving 70 healthcare professionals across various roles. 50% of respondents reported changes in daily responsibilities, and 42% noted the creation of new roles in their organizations. Significant challenges include inadequate training (46%), and coding complexity (38%). Factor analysis revealed a complex relationship between DRG familiarity, job satisfaction, and staff morale. The study also found a moderate negative correlation between the impact on morale and years of service in the current hospital, suggesting that longer-tenured staff may require additional support in adapting to DRG systems. This study addresses a knowledge gap in the human resource aspects of DRG implementation. It provides healthcare administrators and policymakers with evidence to inform strategies for effective DRG adoption and workforce management in public hospitals.

Introduction: With the adoption of the rural rehabilitation strategy in recent years, China’s rural tourist industry has entered a golden age of growth. Due to the lack of management and decision-support systems, many rural tourist attractions in China experience a “tourist overload” problem during minor holidays or Golden Week, an extended vacation of seven or more consecutive days in mainland China formed by transferring holidays during a specific holiday period. This poses a severe challenge to tourist attractions and relevant management departments. Objective: This study aims to summarize the elements influencing passenger flow by examining the features of rural tourist attractions outside China’s largest cities. Additionally, the study will investigate the variations in the flow of tourists. Method: Grey Model (1,1) is a first-order, single-variable differential equation model used for forecasting trends in data with exponential growth or decline, particularly when dealing with small and incomplete datasets. Four prediction algorithms—the conventional GM(1,1) model, residual time series GM(1,1) model, single-element input BP neural network model, and multi-element input BP network model—were used to anticipate and assess the passenger flow of scenic sites. Result: The multi-input BP neural network model and residual time series GM(1,1) model have significantly higher prediction accuracy than the conventional GM(1,1) model and unit-input BP neural network model. A multi-input BP neural network model and the residual time series GM(1,1) model were used in tandem to develop a short-term passenger flow warning model for rural tourism in China’s outskirts. Conclusion: This model can guide tourists to staggered trips and alleviate the problem of uneven allocation of tourism resources.

The "chain length system" is a breakthrough attempt made to adapt to the needs of industrial management under the new development pattern of dual circulation and its industrial policy form. The cultivation of cross-border e-commerce talents in vocational colleges has received much attention. Currently, there are still many problems in the construction and teaching mode of cross-border e-commerce courses in vocational colleges, which are highlighted as the disconnection between course offerings and industry needs, low practical value of course content, low professional literacy of graduates, and inability of graduates to handle practical work. Therefore, it is crucial to construct and innovate a golden course for the development of cross-border e-commerce careers in the new era, focus on strengthening and supplementing the cross-border e-commerce talent chain, and open up the "last mile" of the cross-border e-commerce talent chain, so as to  improve the specifications and quality of talent cultivation. Starting from the pain points and difficulties of industry enterprise demand, curriculum teaching patterns, characteristics, and main contradictions as breakthrough points, we will carry out the construction of golden courses, using "task driven", "module teaching", "project teaching", "project incubation", "achievement recognition", and "point exchange" throughout the entire teaching process, in order to enhance the core competitiveness of cross-border e-commerce talents and serve the chain leader system in the Guangdong Hong Kong Macao Greater Bay Area.

This study aims to explore the connotation of “Guanxi” within contemporary Chinese marketing channels and to construct and verify a global management model. The objective is to examine how instrumental and emotional dimensions of Guanxi influence enterprise operations and management processes. A hybrid research methodology combining qualitative and quantitative approaches was employed. In-depth interviews with 30 dealer executives provided qualitative insights, while a large-scale survey with 305 valid responses facilitated quantitative analysis. SPSS22.0 and LISREL8.8 were utilized for data analysis, including reliability, validity, hypothesis testing, and structural equation modeling (SEM). The findings reveal that Guanxi is multi-dimensional, comprising both instrumental and emotional components. Instrumental Guanxi includes factors such as status, prestige, credibility, and decision-making power, while emotional Guanxi encompasses trust, emotional connection, and mutual respect. Both dimensions significantly affect professionalism, shared values, contact frequency, and popularity within marketing channels. Hypothesis testing confirmed the significant relationships between these variables, except for the non-significant impact of popularity on instrumental Guanxi. The mediating effects of flexibility and supervision on the relationship between Guanxi and corporate performance were also significant, highlighting the mechanisms through which Guanxi influences organizational outcomes. Moderating effects of perceived internal incentive fairness and digital collaboration capabilities further amplify these relationships. Finaly, the study underscores the dual importance of strategic utility and emotional resonance in Guanxi, providing a robust model for understanding its impact on business management. These insights are valuable for both researchers and practitioners aiming to leverage Guanxi in enhancing organizational performance and relational strategies.

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.