The use of artificial intelligence (AI) is related to the dynamic development of digital skills. This article focuses on the impact of AI on the work of non-profit organizations that aim to help those around them. Based on 10 semi-structured interviews, it is presented here how it is possible to work with AI and in which areas it can be used—in social marketing, project management, routine bureaucracy. At the same time, workers and volunteers need to be educated in critical and logical thinking more than ever before. These days, AI is becoming more and more present in almost all the activities, bringing several benefits to those making use of it. On the one hand, by using AI in the day-to-day activities, the entities are able to substantially decrease their costs and have the advantage of being able to have, in most cases, a better and faster job done. On the other hand, those individuals that are more creative and more innovative in their line of work should not feel threatened by those situations in which organizations decide to use more AI technologies rather than human beings for the routine activities, since they will get the opportunity to perform tasks that truly require their intellectual capital and decision making abilities.

The objective of the research is twofold. The study examines the role of public finance in promoting sustainable development in SSA. Secondly, the study investigates the optimal level of public finance beyond which public finance crowds out investment and hinders sustainable development in SSA. The study adopts a battery of econometric techniques such as the traditional ordinary least square (OLS) estimation technique, Driscoll-Kraay covariance matrix estimator, and the dynamic panel threshold model. The study found that an increase in public debts lead to a decline in sustainable development. In contrast, the results show that increase in spending on health and education, and tax can engender sustainable development in SSA. Further, we uncover the optimal levels of public spending on health and education, and public debts that engenders sustainable development in SSA. One main implication of the findings is that governments across SSA needs to reduce public debts levels and increase public spending on health and education to within the threshold levels established in this study to aid sustainable development in SSA.

Despite many investigations concerning antecedents of organizational commitment in the workplace, very few studies so far have analyzed the direct or indirect impact of HR change leadership role on organizational commitment via HR attribution. Therefore, given the reciprocal principle of social exchange theory, attribution theory and signal theory, this study formulated hypotheses and a model to test the relationships between included variables by employing the mixed-method approach. In-depth interviews were initially conducted to develop questionnaires to collect quantitative data. Employing PLS-SEM to analyze the data collected from 1058 employees working in 24 sustainable enterprises in Vietnam, the findings show that the degree of adopting HR change leadership role was positive, directly affecting organizational commitment. Also, both well-being and performance HR attribution play partially mediated roles in the relationship. The findings suggest that the organizational commitment depends on not only how the degree of adopting HR change leadership role is executed, but also how employees perceive and interpret the underlying management intent of these practices. In a sustainable context, adopting HR change leadership role plays a critical role in shaping employees’ interpretations of sustainable HR practices and their subsequent attributions. Besides, employees’ belief on why are sustainable HRM practices implemented has an influence on the organizational commitment that in turn contributes to the overall sustainable performance.

Using a qualitative research methodology and explanatory approach to collect data, we assessed whether the Beijing Consensus diplomacy in Africa is a promoter or threat to Africa’s pathway to sustainable development. The collected data were analysed using document and content analysis techniques. Analysis of the data revealed that the Beijing Consensus diplomacy in Africa is a positive initiative that has created a win-win situation, promoting sustainable development. The Beijing Consensus is opposed to the Washington Consensus, which influenced a win-lose situation that has deepened poverty, making Africa unable to move towards achieving sustainable development. The study found that China’s resource-for-development approach has similarities with pre-colonial Africa’s barter trade approach, which Africans practised in the entire continent. The analysis showed that applying the Beijing Consensus diplomacy to Africa has led to economic growth and development. The results showed that China’s Belt Road Initiative has transformed Africa, changing the continent from poverty to economic productivity, as road infrastructure is associated with economic growth and development. Moreover, it was evident from the analysis that without an African continental foreign policy rooted in continental sovereignty with transparent terms and conditions, Africa’s current benefits from China’s investments would lead to poverty instead of sustainable development. A continental foreign policy would create an African Consensus, which would act on behalf of the entire continent. This African Consensus diplomacy would thus become a continental foreign policy defining Africa globally. However, as it stands, the Beijing Consensus diplomacy is a promoter of sustainable development, but this promotion would not last long without African Consensus diplomacy. The study recommends that Africa should establish a continental foreign policy with African Consensus diplomacy to enable the continent to have one standard foreign policy and goal when trading with China and any other external world.

Good health and well-being are embedded in the 3rd Goal amongst the UN Sustainable Development Goals. The primary objective of this research was to identify the most critical economic, social, and administrative barriers to implementing the Expanded Program on Immunization (EPI) in the Punjab Province of Pakistan. A sequential exploratory design and case study technique were used, employing both qualitative and quantitative methods. In the first stage, in-depth interviews with 50 key officials were conducted to identify the most critical barriers to the EPI program. A quantitative analysis was then performed based on the results obtained from qualitative analysis, and rank orders of barriers were received from the same health department experts. The results indicate that twenty-eight barriers can cause implementation problems for this program. Still, the ten barriers that gained the maximum hits are the most important barriers, which include Shortage of vaccinators, mismanagement of vaccines’ cold chain, biometric android application, ice-lined refrigerators, communication gap, inadequate legislation of EPI program, capacity building issues with EPI staff, Misconceptions about EPI program, lack of awareness of the parents and community, refusal cases and inadequate cooperation of lady health workers (LHWs). Coordinated efforts of the government and the public are highly recommended to address these barriers.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.