This study explores the intricate relationship between family functioning, emotional bonding, parent-child contact, and academic success among students through a serial mediation analysis. The research, conducted on a sample of 200 participants, sheds light on the indirect pathways through which family dynamics influence academic achievements, emphasizing the significance of emotional connections and parent-child interactions. The findings affirm the positive association between family functioning and academic achievement, in alignment with prior research. Additionally, the study identifies parent-child bonds and contact as partial mediators in this relationship, reinforcing previous findings. A noteworthy discovery is the full complementary sequential mediation effect, revealing that family functioning’s influence on academic success becomes substantial when emotional bonds foster increased parent-child contact. In conclusion, this research underscores the importance of emotional bonds and parent-child contact as sequential mediators, emphasizing their role in translating family dynamics into academic achievements among students. While providing valuable insights, the study acknowledges limitations such as sample size, potential sampling bias, self-reported measures, and a cross-sectional design. Addressing these limitations and expanding the scope of outcomes in future research will contribute to a more comprehensive understanding of the complex dynamics within family and educational institutions relationships and their profound impacts on students’ academic success.

This study delves into the role of pig farming in advancing Sustainable Development Goal (SDG) 8—Decent work and economic growth in Buffalo City, Eastern Cape. The absence of meaningful employment opportunities and genuine economic progress has remained a significant economic obstacle in South Africa for an extended period. Through a mixed-method approach, the study examines the transformative impact of pig farming as an economic avenue in achieving SDG 8. Through interviews and questionnaires with employed individuals engaged in pig farming in Buffalo City, the study further examines pig farming’s vital role as a source of decent work and economic growth. The study reveals inadequate government support and empowerment for pig farming in Buffalo City despite pig farming’s resilience and potential in mitigating socio-economic vulnerabilities and supporting community’s livelihoods. To enhance pig farming initiatives, this study recommends government’s prioritization of an enabling environment and empowerment measures for the thriving of pig farming in Buffalo City. By facilitating supportive policies and infrastructures, the government can empower locals in Buffalo City to leverage pig farming’s potential in achieving SDG 8.

The existing ample literature studied the factors for adopting computer-assisted audit techniques (CAATs) by internal and external auditors, frequently ignoring their impact on the quality of audits and companies’ efficiency. This study delivers new evidence on the kinds of CAATs utilized by internal auditors, examines their adoption impact on corporate sustainability, and studies the moderating impact of company characteristics. This study used data from internal auditors in Ethiopia gathered using a survey, and the study hypotheses were tested using the partial least squares-structural equation modeling (PLS-SEM) technique. The study found a moderate utilization of CAATs by internal auditors in executing their activities. The result also revealed a highly positive impact of internal auditors’ CAAT utilization on fraud discovery in the acquisition process. The study found that the intensity of this relationship is impacted by the companies’ characteristics of management commitment. However, the size and type of the company are not impacting it. This study finding complements prior studies and helps practitioners make decisions that can improve CAAT utilization in internal audit functions for a high level of companies’ sustainability.

The economic complexity approach presents a shift from quantitative to qualitative measures of economic performance, while economic complexity refers to the accumulation of know-how. Economic complexity is considered a predictor of economic growth and research evidences a positive relationship between economic complexity and economic growth. In the EU countries, economic convergence is observed. Hence the question of economic complexity convergence arises, too. The paper aims to analyze the convergence of 27 EU countries considering their economic complexity from 1999 to 2021 computing the beta convergence. Using the Barro-type regressions, the econometric estimations focus on four indices of economic complexity—the economic complexity index published by Harvard’s Growth Lab, and economic complexity indices on research, trade, and technology published by the Observatory of Economic Complexity. The absolute beta convergence is observed in the EU except for the economic complexity index referring to trade. When including the dummy referring to the location of EU countries in the West or East of the EU considering their wealth, the conditional beta convergence is observed except for the trade-economic complexity index, again. When altering the condition of location by the GDP per capita and other controls, the conditional beta convergence of economic complexity in the EU is observed when estimating both fixed-effect models and dynamic panel data models based on the system generalized method of moments (GMM) estimator.

Optimizing Storage Location Assignment (SLA) is essential for improving warehouse operations, reducing operational costs, travel distances and picking times. The effectiveness of the optimization process should be evaluated. This study introduces a novel, generalized objective function tailored to optimize SLA through integration with a Genetic Algorithm. The method incorporates key parameters such as item order frequency, storage grouping, and proximity of items frequently ordered together. Using simulation tools, this research models a picker-to-part system in a warehouse environment characterized by complex storage constraints, varying item demands and family-grouping criteria. The study explores four scenarios with distinct parameter weightings to analyze their impact on SLA. Contrary to other research that focuses on frequency-based assignment, this article presents a novel framework for designing SLA using key parameters. The study proves that it is advantageous to deviate from a frequency-based assignment, as considering other key parameters to determine the layout can lead to more favorable operations. The findings reveal that adjusting the parameter weightings enables effective SLA customization based on warehouse operational characteristics. Scenario-based analyses demonstrated significant reductions in travel distances during order picking tasks, particularly in scenarios prioritizing ordered-together proximity and group storage. Visual layouts and picking route evaluations highlighted the benefits of balancing frequency-based arrangements with grouping strategies. The study validates the utility of a tailored generalized objective function for SLA optimization. Scenario-based evaluations underscore the importance of fine-tuning SLA strategies to align with specific operational demands, paving the way for more efficient order picking and overall warehouse management.

With the declaration of the Sustainable Development Goals (SDGs), the importance of localisation principles and, consequently, the local-level institutions in implementing development policies came to the forefront. India adopted a thematic approach by condensing the seventeen goals into nine themes, to be worked upon by the local administrative units, furthering that each Village Panchayat (constitutionally known as Grama Panchayats) should select a theme in a plan year and strive towards attaining it. For the South Indian state of Kerala, with its good trajectory of decentralised governance, this localisation process of SDGs was rather smooth. In this article, we discuss the case of the best-performing Grama Panchayat (GP) in Kerala, which has identified ‘Village with Self-Sufficient Infrastructure’ as the development theme. Through qualitative research methodology, we examine how the Panchayat included projects specific to this theme in the development plans and how the implementation helped produce effects on multidimensional aspects of SDGs using the SDG Impact Assessment Tool. The case studies of different infrastructure-based projects endorse that with proper planning and implementation of such projects, the lowest tier of administration can significantly contribute to the improvement of development goals. We have delineated full fund utilisation through convergence schemes, community participation, and strong monitoring mechanisms as the factors leading the selected Panchayat to be the champion of the cause. The accomplishment exhibited by the Panchayat by integrating SDGs into the Village Development Plan through the projects on the theme of self-sufficient infrastructure can be well emulated by other local bodies across the world.