The presence of a crisis has consistently been an inherent aspect of the Supply Chain, mostly as a result of the substantial number of stakeholders involved and the intricate dynamics of their relationships. The objective of this study is to assess the potential of Big Data as a tool for planning risk management in Supply Chain crises. Specifically, it focuses on using computational analysis and modeling to quantitatively analyze financial risks. The “Web of Science—Elsevier” database was employed to fulfill the aims of this work by identifying relevant papers for the investigation. The data were inputted into VOS viewer, a software application used to construct and visualize bibliometric networks for subsequent research. Data processing indicates a significant rise in the quantity of publications and citations related to the topic over the past five years. Moreover, the study encompasses a wide variety of crisis types, with the COVID-19 pandemic being the most significant. Nevertheless, the cooperation among institutions is evidently limited. This has limited the theoretical progress of the field and may have contributed to the ambiguity in understanding the research issue.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

This study investigates the integration of Yao ethnic cultural history into sustainable jewelry design and its implications for human resource planning, organizational management, and employee engagement techniques within creative sectors. The research emphasizes new approaches to improving employee well-being, work happiness, and organizational commitment by integrating cultural authenticity with circular economy concepts. The study specifically aims to (1) use Yao cultural elements to strengthen the organization’s identity and boost employee pride, (2) evaluate how consumers respond to circular economy ideas and how these ideas impact employee motivation and performance, and (3) explore how sustainability efforts based on culture affect consumer behavior and the morale of the workforce. We used a mixed-methods approach, combining qualitative interviews with fifteen experts in design, sustainability, and cultural heritage with a quantitative survey of 240 participants. Research indicates that using Yao motifs—such as traditional needlework and nature-inspired designs—enhances market attractiveness and promotes more employee alignment with business ideals, hence improving satisfaction and performance. The increasing customer acceptance of recycled and upcycled items enhances employees’ sense of purpose and engagement. These findings highlight the importance of incorporating sustainable HR practices, including culturally oriented training and open ethical principles, to enhance labor relations and foster equity. Utilizing cultural heritage in design innovation serves as a strategic instrument to enhance human capital and promote long-term organizational sustainability.

The global shortage of nurses has resulted in the demand for their services across different jurisdictions causing migration from developing to developed regions. This study aimed to review the literature on drivers of nurses’ migration intentions from source countries and offer future research directions. A search strategy was applied to ScienceDirect, Web of Science, and Scopus academic databases to find literature. The search was limited to peer-reviewed, empirical studies published in English from 2013–2023 resulting in 841 papers. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to conduct a systematic review of 35 studies after thorough inclusion and exclusion criteria. In addition, the VOSviewer software was utilized to map network visualization of keywords, geographic and author cooperation for bibliometric understanding. The findings revealed various socio-economic, organizational, and national factors driving nurses’ migration intentions. However, limited studies have been conducted on family income, organizational culture, leadership style, infrastructure development, social benefits, emergency service delivery, specialized training, and bilateral agreements as potential drivers for informing nurses’ migration intentions. Moreover, a few studies were examined from a theoretical perspective, mainly the push and pull theory of migration. This paper contributes to the health human resources literature and shows the need for future studies to consider the gaps identified in the management and policy direction of nurse labor migration.

This study was conducted to examine the roles of interconnected stakeholders based on power and interests in Ecotourism Management Policy for Dalegan Beach, Gresik Regency, Indonesia using a qualitative method. Data were collected through observation, in-depth interviews, and focus group discussions with stakeholders. Furthermore, the identification of stakeholders interest in ecotourism development was based on the strengths, important positions, and influence of stakeholders categorized into several groups. The results showed that there were three categories of stakeholders, namely Main, Supporting, and Key. In the Village Government, Dalegan Beach Tourism Manager acted as a key player and the local community had the main role. Additionally, East Java Province Maritime and Fisheries Service, Gresik Regency Tourism and Creative Economy Office, Culture, Youth and Sports Office, Gresik Regency Public Works and Spatial Planning Service, and Commanditaire Vennotschaap Mahera (CV Mahera), the landowner, were recognized for lacking direct inclusion in policy matters. Different influences were reported on the legal decisions of the government to offer insights to policymakers in tourism governance. Subsequent study could examine the conflicts of interest among stakeholders.

The low economic growth of Gorontalo province and the smallest PDRB ADHK in Indonesia are the reasons why this research needs to be carried out to look at the influence of the number of poor people, human development index and unemployment on economic growth in the districts/cities of Gorontolo Province, as a result, there is a mismatch between empirical and theoretical, this research was conducted to fill the information gap on how the three variables influence economic growth, This research was conducted to determine the effect of the number of poor people, the human development index. and unemployment on economic growth, research population data on the number of poor people, HDI, Unemployment, Economic growth, the sampling technique of this research is non-probability sampling, where the full sampling method is applied, Gorontalo Province with six regencies/cities is sampled in this research, with data taken in 2012–2021, the data analysis technique uses panel data regression, with three-panel data model estimates namely CEM, FEM, REM and model selection techniques, Chow test, Hausmant Test and Lagrange multiplie equipped with classical assumption tests and T hypothesis tests and F, the research Finding show that the number of poor people in the Regency/City of Gorontalo Province does not have a significant effect on economic growth in Gorontalo Province. Rice, which is the staple food for the people of Gorontalo, apart from rice, the high level of cigarette consumption among the people of Gorontalo, apparently also has an impact. large impact on the increase in the number of poor people, the human development index in the Regency/City of Gorontalo Province has a significant influence on the economic growth of Gorontalo Province where every increase that occurs in the HDI results in an increase in economic growth in Gorontalo Province, thirdly, the open unemployment rate in the Regency/City of Gorontalo Province does not have a significant effect on the economic growth of Gorontalo Province, conclusion of this research is only HDI affects economic growth in Gorontalo.