Purpose: This research aims to investigate the impact of technological challenges, including techno-overload, techno-complexity, and techno-insecurity, on employee job satisfaction within the banking sector of Saudi Arabia. Additionally, the study examines the mediating roles of supervisor support and job clarity in buffering the effects of technological challenges on job satisfaction. Method: The study employs a quantitative research design, utilizing an online questionnaire to collect data from banking employees in Saudi Arabia. The sample size of 135 participants was determined using the rule of thumb technique. Random sampling was utilized to ensure representativeness. Data analysis was conducted using Statistical Package for Social Sciences (SPSS) to explore the relationships between technological challenges, supervisor support, job clarity, and employee job satisfaction. Findings: The findings of the study reveal a significant negative impact of techno-overload, techno-complexity, and techno-insecurity on employee job satisfaction within the banking sector of Saudi Arabia. Moreover, supervisor support and job clarity were found to mediate these relationships, highlighting their importance in mitigating the adverse effects of technological challenges on job satisfaction. Originality/Significance: This research contributes to the existing body of knowledge by providing empirical evidence on the relationships between technological challenges, supervisor support, job clarity, and employee job satisfaction within the specific context of Saudi Arabian banks. The findings have significant implications for organizational leaders and managers in developing evidence-based strategies to manage technological challenges and promote employee well-being in the banking sector of Saudi Arabia.

The integration of new technologies and digitalisation causing significant changes in the skills demanded, leading to skills shortages and skills gaps in digital context. Undoubtedly, the employees’ digital skills and knowledge need to be aligned with the ongoing technological changes. This study obtains inputs from the employers from professional services sector regarding the demand for digital skills and the existence of gaps in digital skill among the employees. The impact of digital skills and willingness to pay for the micro-credential on the employability was investigate. 308 responses from the employers reside in Klang Valley, Johor and Penang collected via online survey. The five areas of digital skills adopted from Digital Competence 2.0, and the pair-sample t-test in SPSS was used to identify the present of skill gaps. Besides, PLS-SEM was used to test the hypotheses with regard to impacts of digital skills and micro credential on employability. The findings indicate that problem-solving and safety skills were ranked as highly demanded digital skills in the future. The skill gaps were found in all areas of digital skills except information and data literacy. The employers agreed that digital skills did affect their decision in hiring the graduate employees and they are willing to pay for micro-credentials to address the skills gaps. Yet, willingness to pay for micro-credentials did not affect the employability directly and indirectly. This study provides insights into the demand of digital skills and the digital skills gaps. Implications of the study from theoretical and practical perspectives are discussed.

The effects of aid dependency on preventing the achievement of sustainable development in Africa has not been given appropriate academic attention. Aid dependency in Africa is undoubtedly among the most factors that have promoted poverty and underdevelopment. Aid dependency which hindered the growth of local innovation, promoted divisions that has affected good governance for sustainable development. Aid dependency has promoted chronic poverty, mental laziness and unstable health and well-being. It has ignited unhealthy condition that has created a perpetual vicious cycle of poverty that prevents the achievement of sustainable development. The study found that planning diplomacy can serve as a solution to aid diplomacy and address its effects thus promoting the achievement of sustainable development. Planning diplomacy was found to have critical links with Africa’s communalism theory, thus making it an ideal approach to addressing the effects of aid dependency in Africa. Planning diplomacy was found to promote local and business in collective manner. It is through this collective approach that sustainable development can be achieved in Africa. Planning diplomacy was found a key for sustainable development because it makes good use of foreign aids, promotes local ownership thus strengthens sustainable economic growth and development that makes sustainable development achievable. Planning diplomacy was equally found a remedy to aid dependency because it enhances knowledge and skills transfer. Knowledge and skills transfer promotes sustainable development because it facilitates sharing of skills that brings innovation and technologies to local citizens in a collective manner. The study adopted a qualitative research methodology with the use of secondary data collected from existing literature published in the public domain. Collected data was analysed and interpreted through document analysis technique.   

The research issue at hand pertains to the intricate mechanisms of state regulation that govern the economy of Kazakhstan, particularly in the context of the international sanctions that have been instituted by the nations comprising the Eurasian Economic Union. In order to thoroughly investigate this complex subject matter, this scholarly paper employs a variety of sophisticated methodologies grounded in bibliometric analyses of the most recent 90 academic papers that focus on the various mechanisms of state regulation pertinent to the economic landscape of Kazakhstan. As a subsequent phase in this research endeavor, the modeling of higher-order moments is undertaken with the express aim of delineating the multifaceted ramifications that stem from a singular and isolated perturbation affecting one of the key variables encapsulated within the higher-order moments model. This detailed analytical approach facilitates an in-depth exploration of both the immediate outcomes and the subsequent values of the endogenous variables that are under scrutiny. The innovative aspect of this article’s findings lies in the comprehensive analysis dedicated to the state regulation of Kazakhstan’s economy, which is significantly influenced by the international sanctions that have been imposed by member countries of the Eurasian Economic Union. The outcomes of this research provide a methodical and scientifically rigorous framework for understanding the overarching system of state regulation, which is of paramount importance for cultivating sustainable development within the socio-economic dynamics that characterize the nation of Kazakhstan.

The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI's capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.