Rural tourism plays a crucial role in rural development in Indonesia by providing employment opportunities, livelihood, infrastructure, cultural preservation, and environmental preservation. However, it is prone to external shocks such as natural disasters, public health events, and volatility in the national and global economy. This study measures the resilience of rural tourism to external shocks caused by the COVID-19 pandemic in 24 rural tourism destinations in Indonesia covering four years from 2019 to 2022. A synthetic composite index of the Adjusted Mazziotta-Pareto index (AMPI) is used to measure rural tourism resilience followed by clustering analysis to determine the typology of the resilience. The AMPI measure is also compared with the conventional Mazziotta-Pareto index (MPI) method. The resilience index is composed of capacity and performance components related to resilience. The results show that in the first year of COVID-19, most tourism villages in Indonesia were severely affected by the pandemic, yet they were able to recover afterward, as indicated by positive differences in the AMPI index before and after COVID-19. Thus, rural tourism villages in Indonesia have a strong capacity and performance to recover from pandemic shock. Lessons learned from this analysis can be applied to policies related to rural tourism resilience in developing countries.

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.

This study used quantitative methods to examine the correlation between adaptive learning technology and cognitive flexibility in kids receiving special education. The study included a cohort of 120 kids, ages 8–12, who were diagnosed with particular learning difficulties, ADHD, or autism spectrum disorder. Cognitive flexibility was evaluated using the Wisconsin Card Sorting Test (WCST), while the utilization of adaptive learning technologies was quantified using self–report questionnaires. The data was analyzed using several statistical methods, such as independent samples t-tests, regression, Pearson correlation coefficients, ANOVA, and ANCOVA. The findings revealed a noteworthy and favorable correlation between the utilization of adaptive technology and the scores of cognitive flexibilities. This correlation remained significant even after accounting for demographic characteristics. Moreover, it was shown that the diagnostic status had a moderating effect on the correlation between the utilization of adaptive technology and cognitive flexibility. The results emphasize the capacity of adaptive learning technologies to improve cognitive flexibility abilities in kids with special needs, offering significant knowledge for educators, legislators, and technology developers.

This study examines the relationship between macroeconomic determinants and education levels in eight selected African oil-exporting countries (AOECs) over the period 2000–2022. Drawing on human capital theory, the paper scrutinizes the impact of factors such as income inequality, health outcome, economic growth, human development, unemployment, education expenditure, institutional quality, and energy consumption on education levels. Employing robust estimation techniques such as fixed effects (FE), random effects (RE), pooled mean group (PMG) and cross-section autoregressive distributed lag model (CS-ARDL), the study unveils vital static and dynamic interactions among these determinants and education levels. Findings reveal notable positive and significant connections between education levels and some of the variables—human capital development, institutional quality, government expenditure on education, and energy consumption, while income inequality demonstrates a consistent negative relationship. Unexpectedly, health outcomes exhibit a negative impact on education levels, warranting further investigation. Furthermore, the analysis deepens understanding of long-run and short-run relationships, highlighting, for example, the contradictory impact of gross domestic product (GDP) and unemployment on education levels in AOECs. Finally, the study recommends targeted human development programs, enhanced public investment in education, institutional reforms for good governance, and sustainable energy infrastructure development.

Reusable bags have been introduced as an alternative to single-use plastic bags (SUPB). While beneficial, this alternative is economically and environmentally viable only if utilized multiple times. This study aims to identify the determinants influencing the use of reusable bags (RB) over single-use plastic bags (SUPB) within the framework of ecological impact reduction, employing the Theory of Planned Behavior (TPB). The focus is on understanding how attitudes (AT), subjective norms (SN), and perceived behavioral control (PBC) collectively guide consumers towards adopting reusable bags as a pro-environmental choice. The focus is on understanding how attitudes (AT), subjective norms (SN), and perceived behavioral control (PBC) collectively guide consumers towards the adoption of reusable bags as a pro-environmental choice. Data were collected through a survey administered to 814 consumers in Lahore, employing both regression analysis and Structural Equation Modeling (SEM) to assess the impact of AT, SN, and PBC on reusable bag consumption (RBC). The TPB framework underpins the hypothesis that these three psychological factors significantly influence the decision to use RBs. Both regression and SEM analyses demonstrated that AT, SN, and PBC positively affect RBC, with significant estimates indicating the strength of each predictor. Specifically, PBC emerged as the strongest predictor of RBC (PBC2, β = 0.533, p < 0.001), highlighting the paramount importance of control perceptions in influencing bag use. This was followed by AT (β = 0.211, p < 0.001) and SN (β = 0.173, p < 0.001), confirming the hypothesized positive relationships. The congruence of findings from both analytical approaches underlines the robustness of these techniques in validating the TPB within the context of sustainable consumer behaviors. The investigation corroborates the TPB’s applicability in predicting RBC, with a clear hierarchy of influence among the model’s constructs. PBC’s prominence underscores the necessity of enhancing consumers’ control over using RBs to foster sustainable consumption patterns. Practical implications include the development of policies and marketing strategies that target the identified determinants, especially emphasizing the critical role of PBC, to promote broader adoption of RBs and contribute to significant reductions in plastic waste.

The prospects of digital infrastructure in promoting rural economic growth and development are by and large immense. The paper found that rural development is considerably important for economic development and for achievement of sustainable livelihoods that increases people’s ability to achieve good health and wellbeing that enable the achievement of sustainable development. The paper found that digital imbalance and digital illiteracy in the rural areas hinder implementation of digital infrastructure to lead to rural economic growth. Digital infrastructure is the source of economic opportunities that enables local people in the rural areas to be more creative in achieving development success. It enables them to have a unique sense of place and fashioning of vibrant economic and financial opportunities that ensure the achievement of sustainable rural economic development. However, the paper found that the application of digital infrastructure to South Africa’s rural areas in the bid to promote rural economic growth has been hindered by factors like the digital divide, financial constraints, digital illiteracy and the failure to own a smart phone. These factors hinder digital infrastructure from leading to sustainable rural economic development and growth. The paper used secondary data gathered from existing literature. The use of qualitative research methodology and document and content analysis techniques became vital in the process of collecting and analyzing collected data.