Intellectual capital is one of the most crucial determinants of long-term economic development. The countries compete for highly skilled labor and talented youth. State regulatory interventions aim to, on the one hand, facilitate the retention of foreign high-productivity intellectual capital in the host country, transforming ‘educational’ and ‘scientific’ migrants into residents, and on the other hand, prevent the outflow of their own qualified workforce. The paper aims to outline the role of the nation’s higher education system in the influx and outflow of labor resources. A two-stage approach is applied: 1) maximum likelihood—to cluster the EU countries and the potential candidates to become members of EU countries based on the integrated competitiveness of their higher education systems, considering quantitative, qualitative, and internationalization aspects; 2) logit and probit models—to estimate the likelihood of net migration flow surpassing baseline cluster levels and the probability of migration intensity changes for each cluster. Empirical findings allow the identification of four country clusters. Forecasts indicate the highest likelihood of increased net migration flow in the second cluster (66.7%) and a significant likelihood in the third cluster (23.4%). However, the likelihood of such an increase is statistically insignificant for countries in the first and fourth clusters. The conclusions emphasize the need for regulatory interventions that enhance higher education quality, ensure equal access for migrants, foster population literacy, and facilitate lifelong learning. Such measures are imperative to safeguard the nation’s intellectual potential and deter labor emigration.

Mecula Haroano Laa is a local wisdom that includes beliefs, norms, and practices passed down from generation to generation in the context of agricultural resource preservation and community cultural identity formation. The author is interested in investigating the practices of the Mecula Haroano Laa tradition, which is unique to North Buton Regency and has unique specifications and characteristics. This research uses a qualitative approach. The data collection techniques used in this study are in-depth interviews and participatory observations. The results of this study demonstrate that Mecula Haroano Laa in North Buton society is more than just an agricultural custom; it is also an attempt to strengthen social solidarity among community members. This practice reflects the spirit of solidarity, gotong royong together, and respect for the environment. The North Buton community is actively involved in implementing Mecula Haroano Laa as a form of participation in developing sustainable agriculture. This research contributes to understanding the importance of local wisdom in building social cohesion in communities. Research implications include sustainable planning and efforts to empower communities in developing farms in North Buton Regency. Natural resource management policies may incorporate. Mecula Haroano Laa’s effective and sustainable resource management techniques to promote wise use, environmental conservation, economic resilience, and dependency reduction.

The mining industry significantly impacts the three pillars of sustainable development: the economy, the environment, and society. Therefore, it is essential to incorporate sustainability principles into operational practices. Organizations can accomplish this through knowledge management activities and diverse knowledge resources. A study of 300 employees from two of the largest mining corporations in South Kalimantan, Indonesia, found that four out of five elements of knowledge management—green knowledge acquisition, green knowledge storage, green knowledge application, and green knowledge creation—have a direct impact on the sustainability of businesses. The calculation was determined using Structural Equation Modelling (SEM). However, the study also found that the influence of collectivist cultural norms inhibits the direct effect of green knowledge sharing on corporate sustainable development. The finding suggests that companies operating in collectivist cultures may need to take additional measures to encourage knowledge sharing, such as rewarding employees for sharing their expertise on green initiatives, supportive organizational culture, clear expectations, and opportunities for social interaction.

Purpose: This study empirically investigates the effect of big data analytics (BDA) on project success (PS). Additionally, in this study, the investigation includes an examination of how intellectual capital (IC) and (KS) act as mediators in the correlation between BDA and KS. Lastly, a connection between entrepreneurial leadership (EL) and BDA is also explored. Design/Methodology- Using a sample of 422 senior-level employees from the IT sector in Peru. The partial least squares structural equation modeling technique tested the hypothesized relationships. Findings- According to the findings, the relationship between BDA and PS is mediated by structural capital (SC) and relational capital (RC), and BDA demonstrates a positive and noteworthy correlation with PS. Furthermore, EL is positively associated with BDA in a significant manner. Practical implications- The finding of this study reinforce the corporate experience of BDA and suggest how senior levels of the IT sector can promote SC, RC, and EL. Originality/Value- This study is one of the first to consider big data analytics as an important antecedent of project success. With little or no research on the interrelationship of big data analytics, intellectual capital and knowledge sharing the study contributes by investigating the mediating role of intellectual capital and knowledge sharing on the relationship between big data analytics and project success.

Purpose: Drawing on the Resource Based View (RBV) and Dynamic Capabilities Theory (DCT), the study seeks to investigate the impact of Big Data Analytics (BDA) on Project Success (PS) through Knowledge Sharing (KS) and Innovation Performance (IPF). Design/Methodology: Survey data were collected from 422 senior-level employees in IT companies, and the proposed relationships were assessed using the SMART-PLS 4 Structural Equation Modeling tool. Findings: The results show a positive and significant indirect effect of big data analytics on project success through knowledge sharing. IPF significantly mediated the relationship between BDA and PS in IT companies. Originality/Value: This study is one of the first to consider big data analytics as an essential antecedent of project success. With little or no research on the interrelationship of big data analytics, knowledge sharing, innovation performance, and organizational performance, the study investigates the mediating role of knowledge sharing and innovation performance on the relationship between BDA and PS. Implications: This study, grounded in RBV and DCT, investigates BDA’s influence on PS through KS and IPF. Implications encompass BDA’s strategic role, KS and IPF mediation, and practical and research-based insights. Findings guide BDA integration, collaborative cultures, and sustained success.