This paper uses existing studies to explore how Artificial Intelligence (AI) advancements enhance recruitment, retention, and the effective management of a diverse workforce in South Africa. The extensive literature review revealed key themes used to contextualize the study. This study uses a meta-narrative approach to literature to review, critique and express what the literature says about the role of AI in talent recruitment, retention and diversity mapping within South Africa. An unobtrusive research technique, documentary analysis, is used to analyze literature. The findings reveal that South Africa’s Human Resource Management (HRM) landscape, marked by a combination of approaches, provides an opportunity to cultivate alternative methods attuned to contextual conditions in the global South. Consequently, adopting AI in recruiting, retaining, and managing a diverse workforce demands a critical examination of the colonial/apartheid past, integrating contemporary realities to explore the potential infusion of contextually relevant AI innovations in managing South Africa’s workforce.

The objective of this study is to examine the impact of decentralization on disaster management in North Sumatra Province. Specifically, it will analyze the intergovernmental networks, local government resilience, leadership, and communication within disaster management agencies. The study used a hybrid research approach, integrating qualitative and quantitative methodologies to investigate the connections between these factors and their influence on disaster response and mitigation. The study encompassed 144 personnel from diverse government tiers in North Sumatra and performed a meta-analysis on the implementation of disaster management. Intergovernmental networks were discovered to enhance collaboration in disaster management by eliminating regulatory gaps and efficiently allocating logistics. Nevertheless, local governments have obstacles as a result of limited resources and inadequate expertise, notwithstanding the progress made in infrastructure technology. The F test results reveal that leadership and communication have a substantial impact on the performance of BPBD personnel. The meta-assessment classifies its impact as extraordinarily high, suggesting comprehensive evaluation and successful achievement of goals in disaster management planning. Efficient cooperation among relevant parties is essential in handling calamities in North Sumatra. The government, commercial sector, NGOs, universities, and society have unique responsibilities. To improve effectiveness, governments should encourage private sector involvement, while institutions can increase their research contributions.

Tangerang City is characterized by its dense residential, commercial, and industrial activities and strategic proximity to Jakarta. This study aims to evaluate the strategic planning and implementation of innovative city initiatives in Tangerang, Indonesia, focusing on integrating blockchain, Internet of Things (IoT) big data technologies and innovation in urban development. This study has employed explanatory survey data from a structured questionnaire distributed to a diverse Tangerang community sample, including users and non-users of the “Smart City Tangerang Live” application. The survey was conducted for 2-months March to April 2022, included 71 and the sample included individuals across 13 districts, utilizing cluster sampling to ensure representativeness. The findings reveal a positive community response towards the smart city initiatives, with significant Engagement and interaction with the “Tangerang Live” application. However, technology access and usage disparities among different community segments were noted. The study highlights the critical role of intelligent technologies in transforming urban infrastructure and services, improving the quality of life, and fostering sustainable urban development in Tangerang. The implications of this study are multifaceted. For urban planners and policymakers, the results underscore the importance of strategic planning in innovative city development, emphasizing the need for inclusive and accessible technological solutions. The study also suggests potential areas for improvement in community engagement and public awareness campaigns to promote the adoption and efficient use of smart technologies.

Cartography includes two major tasks: map making and map application, which is inextricably linked to artificial intelligence technology. The cartographic expert system experienced the intelligent expression of symbolism. After the spatial optimization decision of behaviorism intelligent expression, cartography faces the combination of deep learning under connectionism to improve the intelligent level of cartography. This paper discusses three problems about the proposition of “deep learning + cartography”. One is the consistency between the deep learning method and the map space problem solving strategy, based on gradient descent, local correlation, feature reduction and non-linear nature that answer the feasibility of the combination of “deep learning + cartography”; the second is to analyze the challenges faced by the combination of cartography from its unique disciplinary characteristics and technical environment, involving the non-standard organization of map data, professional requirements for sample establishment, the integration of geometric and geographical features, as well as the inherent spatial scale of the map; thirdly, the entry points and specific methods for integrating map making and map application into deep learning are discussed respectively.

The reference urban plan is an urban planning tool often used to orient the development of Chadian cities. However, expanding Chadian urban centers, such as Sarh, face challenges in implementing urban planning orientations of their urban plans within the set deadlines. The objective of this study is to identify the factors impeding the effective implementation of the reference urban plan for Sarh town. The methodology employed encompasses a literature review, individual interviews with urban planning experts, geographic information system (GIS) data, household surveys and statistical analysis. The results revealed that less than a quarter (19.72%) of the households surveyed were aware of the reference urban plan. The applied logistic regression model identified age, occupation and level of education as the main factors influencing public participation in the preparation of the reference urban plan. On average, 33.33% of the urban planning guidelines and 21.74% of the projected urban projects were implemented, with a difference of 1631.28 hectares (ha) between the projected plan and the actual plan for the town. Five factors were identified as contributing to the failure to implement the reference urban plan for Sarh town, including low funding, inadequate land management, a lack of political will, weak governance and poor communication. Consequently, participatory and inclusive planning approaches, effective financial mobilisation, strong governance, and the use of modern technologies such as GIS tools are recommended to enhance the implementation of urban planning tools.