This study examines the effectiveness of Kazakhstan’s grant funding system in supporting research institutions and universities, focusing on the relationship between funding levels, expert evaluations, and research outputs. We analyzed 317 projects awarded grants in 2021, using parametric methods to assess publication outcomes in Scopus and Web of Science databases. Descriptive statistics for 1606 grants awarded between 2021 and 2023 provide additional insights into the broader funding landscape. The results highlight key correlations between funding, evaluation scores, and journal publication percentiles, with a notable negative correlation observed between international and national expert evaluations in specific scientific fields. A productivity analysis at the organizational level was conducted using non-parametric methods to evaluate institutional efficiency in converting funding into research output. Data were manually collected from the National Center of Science and Technology Evaluation and supplemented with publication data from Scopus and Web of Science, using unique grant numbers and principal investigators’ profiles. This comprehensive analysis contributes to the development of an analytical framework for improving research funding policies in Kazakhstan.

Performance Management is a major concern to various stakeholders in Education System, it is considered to be key driver to improve school effectiveness and learning quality. However, the complexity of education Systems, has made it challenging to apply an effective PM model. This study paper introduces a maturity model with six dimensions, fifteen Capability Areas and forty-two Best-Practices to assess education systems’ organizational capacity for performance management. It provides deep insights into their structural and functional characteristics and serves as a framework for decision-makers to identify and implement missing practices while enhancing existing ones. The maturity model was developed following the Design Science Research methodology to ensure both rigor and relevance. A bottom-up approach guided its design, integrating insights from extensive literature reviews and lessons learned from benchmark countries. The evaluation process employed a qualitative approach, using focus groups with a carefully selected cohort of academics, experts, and practitioners. The Moroccan case study serves as part of the “Reflection and Learning” phase, providing an initial test for the model and paving the way for further empirical research. Future studies will aim to test, refine, and extend the model, facilitating its application across diverse educational contexts.

Land use as for human-circumstance interaction is as we all know changed the global land surface sharply and continuously. Farmland abandonment is the phenomenon of going extreme of marginal of land use, which exert positive and negative impacts on our living circumstances. In order to map the extent of farmland abandonment of Zhejiang Province, we try to use the geo-big data analysis platform to perform the massive data preprocessing and map the extent of farmland abandonment of the study area based on multi-source land use and land cover data. Then we execute landscape pattern analysis using landscape pattern analysis software and spatial auto-correlation (Moran's I) analysis based on ArcGIS and Fragstats software. We found that the area of farmland is about 16.32% on account of all land use types, which is 1.89104 km2. While the whole area of FA is 1.72 × 108 m2, and the farmland abandonment ratio is 1.65%. AF's area is about 1.95 × 109 m2, and the continuous cultivation ratio is 18.69%. The landscape fragmentation, landscape aggregation and landscape diversity of FA, AF and FL are different. At the same time, the spatial auto-correlation of FA and AF are dominant high congregation and low discrete. At last, we compared our calculated results with the existed research results which demonstrate our research does scientific convincible. We also make futural prospects prediction and show the research deficiency as well as bring out some policy implications based on our research, which means build proper land use management regulation and decrease the farmland abandonment on account of the premise of suitable land use policies.

This study aims to investigate the relationship between internal and information integration within the supply chain (SCI-INTI and SCI-INFI), supply chain management (SCM) practices, and port operational performance (POP) in Oman’s container ports. Additionally, it explores the mediating role of SCM practices in the relationship between SCI-INTI, SCI-INFI, and POP in Oman. To meet the study’s objectives, a quantitative cross-sectional survey method was used. A total of 377 questionnaires were distributed to managers responsible for supply chain operations in the main departments at Sohar and Salalah ports, yielding 331 usable responses, with a response rate of 88 percent. The data collected were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that both internal and information integration within the supply chain have positive and statistically significant effects on the operational performance of Oman’s container ports (POP). Specifically, Supply Chain Integration with Internal Integration (SCI-INTI) significantly impacts POP (β = 0.249, t = 5.039, p < 0.001), and Supply Chain Integration with Information Integration (SCI-INFI) also significantly affects POP (β = 0.259, t = 4.966, p < 0.001). Additionally, SCI-INTI positively influences Supply Chain Management Practices (SCMP) (β = 0.381, t = 7.674, p < 0.001), as does SCI-INFI (β = 0.484, t = 9.878, p < 0.001). Furthermore, SCMP positively and significantly influences the operational performance of Oman’s container ports (β = 0.424, t = 7.643, p < 0.001). These findings contribute to the literature by emphasizing the significance of internal and information integration within the supply chain and SCM practices as strategic internal resources and capabilities that enhance operational performance in container ports. Understanding these elements enables decision-makers and policymakers within government port authorities and port operating companies to optimize internal resources and capabilities to improve port operational performance.

Social and environmental issues gain more importance for society that stimulates companies to adopt and integrate more sustainability practices into their business activities. This study is embedded in almost uncovered in the literature context of Russian business that undergoes its ESG transformation in conditions of unprecedented sanctions and hostile institutional environment. The study aims to reveal the role of internal stakeholders (top managers, line managers, and employees) in successful implementation of a company’s ESG practices along various dimensions. Using the primary data from 29 large Russian companies the fsQCA method is applied to identify various configurations of contingencies that stimulate their ESG performance. The analysis results in identification of two alternative core conditions for high ESG performance in Russian companies: high top management commitment to sustainability and low employees’ commitment to sustainability or the employees’ awareness about sustainability. At the end, the study results in two generic profiles composed of top management commitment, line management support, and employees’ awareness, behavior, and commitment towards ESG performance. The results show two different approaches towards ESG transformation that may bring a company to the comparably similar desired outcome. The study has a potential for generalization on a wider scope of emerging market contexts.

The augmentation of firm performance via customer concentration is particularly indispensable for organizational evolution. Both trade credit financing and financing constraints play pivotal roles in the nexus between customer concentration and performance. This research constructs a moderated mediation model to rigorously investigate the impact of customer concentration on firm performance, positing trade credit financing as the mediating variable and financing constraints as the moderating variable. The relevant hypotheses are evaluated empirically using panel data compiled from listed manufacturing firms in China over the period 2013–2020, yielding 8 firm-year observations. The empirical outcomes denote that customer concentration exerts a positive influence on firm performance, albeit having a negative impact on trade credit financing. Trade credit financing serves as a partial mediator in the relationship between customer concentration and manufacturing firm performance. Financing constraints are found to positively moderate the mediating role of trade credit financing in the relationship between customer concentration and firm performance. This research broadens the understanding of the implications of customer relationships on trade credit financing and performance, thereby enriching the knowledge base for managing a firm’s financing channels more effectively.