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This paper will identify and further explore the ideals versus realities of learning poverty and the consequential effects on our moral obligations and responsibilities. The wealthy nations are now under further pressure to recognise and realise their moral obligations to enabling social justice in the context of access, and distribution, of vaccines for the poorer nations. Learning poverty has always been a feature of our global economic, and institutional order, and has become an increasingly important factor in achieving justice.

The study focusses on a human rights approach to learning poverty and the ideals versus the realities of what we are beginning to see in the times of a global pandemic. The major challenges to justice is inherent to the recognition that wealthy nations continue to have a pivotal role in the reduction of poverty. The identified major challenges in the context of learning poverty are: “nation states and the global pandemic”, “international interactions and learning poverty” and “global institutions and learning inequalities”. In particular, the authors explore the concept of ideals versus realities through three “challenges”, which continues to challenge any semblance of justice in the current global vaccine distribution. Nation states and borders, international interactions and global institutions remain barriers in overcoming what is becoming a reality of learning poverty.

This paper seeks to look beyond the economics of vaccine trade and seek a way to accept a moral claim of justice for all. The authors consider how wealthy nations are active participants in the emergence of learning poverty for many nations.

By exploring the ideals versus realities of learning poverty, and human rights, the authors highlight some of the challenges, and wealthy nations moral obligations, through the emergence of a new dimensional indicator of poverty, learning poverty.

This study investigated the impact of entrepreneurship education on the international entrepreneurship intention of the university students while considering the mediating roles of entrepreneurship alertness, proactive personality, innovative behaviour and the moderating role of global mindset in this relationship.

The research employs a survey methodology, utilising a structured questionnaire for data collection. The study specifically concentrates on students enrolled at Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development (AAMUSTED) in Ghana, drawing its sample from six academic programmes within the university. Data analysis is conducted using structural equation modeling (SEM).

The findings of this research revealed that entrepreneurship education exerts a positive influence on the international entrepreneurial intention. Furthermore, entrepreneurship alertness acts as a mediator in the relationship between entrepreneurship education and innovative behaviour. Similarly, a proactive personality serves as a mediating factor between entrepreneurship education and innovative behaviour. Moreover, innovative behaviour operates as a mediator in the relationship between entrepreneurship education and international entrepreneurship intention. Additionally, a global mindset plays a crucial moderating role in the connection between entrepreneurship education and international entrepreneurship intention.

This study makes a significant contribution to the field by shedding light on the mediating roles of proactive personality, entrepreneurial alertness, innovative behaviour and global mindset moderating the relationship between entrepreneurship education and international entrepreneurship intention. These insights offer fresh perspectives on the complex dynamics at play in the realm of entrepreneurship education and its impact on students' intentions for the international entrepreneurship.

Due to changing consumer thinking patterns and market dynamics, the quick service restaurant (QSR) industry has changed dramatically in the past few years. Considering this, this study aims to examine the influence of perceived brand globalness and perceived brand localness on consumer word of mouth through brand attitude by considering consumer ethnocentrism and perceived brand origin as moderators.

This study obtained 750 responses from Turkish consumers through a survey and analyzed the data using the maximum-likelihood estimation technique with structural equation modeling.

This study discovered that perceived brand globalness and perceived brand localness are critical components that drive brand attitude, influencing consumers' WOM toward global and local QSR brands. Similarly, perceived brand globalness and perceived brand localness are important brand attributes influencing consumer WOM. Importantly, this study found the significant effects of perceived brand origin on brand attitude mainly toward perceived local brands compared to global QSR brands. Although this study did not uncover the influence of consumer ethnocentrism as expected. However, these insights may assist global and local managers to rethink their strategies toward Turkish consumer settings.

This study was conducted exclusively in Turkey. However, additional studies in other countries, such as the comparative Asian versus European consumers' perspectives, may be considered to generalize the findings.

This study provides recommendations to global and local managers to support them in designing and executing several brand positioning strategies in the QSR industry.

This novel study contributes to the accessibility diagnostic theory and signaling theory by examining consumers' perceptions of local and global brands.

This study aims to explore whether globalization and technology are harmful to health using a global panel data set of 52 countries over the period 1990–2019.

The study focused on four continents: Africa, the Americas, Asia/Oceania and Europe. The authors used four advanced econometric methodologies, which include the standard panel fixed effect (FE), Arellano–Bover/Blundell–Bond dynamic panel, Hausman–Taylor specification and two-stage least squares (FE-2SLS)/Lewbel-2SLS approaches.

The empirical evidence highlights the significance of globalization and technology in promoting global health. The findings suggest that globalization has various impacts on global health indicators and that technology is useful in tracking, monitoring and promoting global health. In addition, the empirical evidence indicates that a truly health-centred process of globalization and technological innovation can only be realized by ensuring that the interests of countries and vulnerable populations to health risks are adequately considered in international decision-making regarding global economic integration.

The authors suggest that achieving the aspiration of global health will entail the use of globalization and information technology to extend human activities and provide equal access to global health.

Renewable energy infrastructure is an important asset class in the context of reducing global carbon emissions going forward. This includes solar power, wind farms, hydro, battery storage and hydrogen. This paper examines the risk-adjusted performance and diversification benefits of listed renewable energy infrastructure globally over Q1:2009–Q4:2022 to examine the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio. The performance of renewable energy infrastructure is compared with the other major infrastructure sectors and other major asset classes. The strategic investment implications for institutional investors and renewable energy infrastructure in their portfolios going forward are also highlighted. This includes identifying effective pathways for renewable energy infrastructure exposure by institutional investors.

Using quarterly total returns, the risk-adjusted performance and portfolio diversification benefits of global listed renewable energy infrastructure over Q1:2009–Q4:2022 is assessed. Asset allocation diagrams are used to assess the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio.

Listed renewable energy infrastructure was seen to underperform the other infrastructure sectors and other major asset classes over 2009–2022. While delivering portfolio diversification benefits, no renewable energy infrastructure was seen in the optimal infrastructure portfolio or mixed-asset portfolio. More impressive performance characteristics were seen by nonlisted infrastructure funds over this period. Practical reasons for these results are provided as well as effective pathways going forward are identified for the fuller inclusion of renewable energy infrastructure in institutional investor portfolios.

Institutional investors have an important role in supporting reduced global carbon emissions via their investment mandates and asset allocations. Renewable energy infrastructure will be a key asset to assist in the delivery of this important agenda for a greener economy and addressing global warming. Based on this performance analysis, effective pathways are identified for institutional investors of different size assets under management (AUM) to access renewable energy infrastructure. This will see institutional investors embracing critical investment issues as well as environmental and social issues in their investment strategies going forward.

This paper is the first published empirical research analysis on the performance of renewable energy infrastructure at a global level. This research enables empirically validated, more informed and practical decision-making by institutional investors in the renewable energy infrastructure space. The ultimate aim of this paper is to articulate the potential strategic role of renewable energy infrastructure as an important infrastructure sector in the institutional real asset investment space and to identify effective pathways to achieve this renewable energy infrastructure exposure, as institutional investors focus on the strategic issues in reducing global carbon emissions in the context of increased global warming.

This study develops a model and algorithm to solve the decentralized resource-constrained multi-project scheduling problem (DRCMPSP) and provides a suitable priority rule (PR) for coordinating global resource conflicts among multiple projects.

This study addresses the DRCMPSP, which respects the information privacy requirements of project agents; that is, there is no single manager centrally in charge of generating multi-project scheduling. Accordingly, a three-stage model was proposed for the decentralized management of multiple projects. To solve this model, a three-stage solution approach with a repeated negotiation mechanism was proposed.

The experimental results obtained using the Multi-Project Scheduling Problem LIBrary confirm that our approach outperforms existing methods, regardless of the average utilization factor (AUF). Comparative analysis revealed that delaying activities in the lower project makespan produces a lower average project delay. Furthermore, the new PR LMS performed better in problem subsets with AUF < 1 and large-scale subsets with AUF > 1.

A solution approach with a repeated-negotiation mechanism suitable for the DRCMPSP and a new PR for coordinating global resource allocation are proposed.

The purpose of this paper is to provide a comprehensive framework that identifies thematic clusters and their interconnections within Global Talent Management (GTM), global careers and talent management (TM).

In this paper, this study conducted a co-citation analysis using bibliographic data to unveil the intellectual connections and relationships among thematic articles related to GTM sourced from the Web of Science.

This review highlights three key research themes: experiences working abroad, TM approaches and the complex nature of GTM as a living system.

The main limitation of this research is the sample itself. Content analysis based on the co-citation method resulted in some more recent releases being omitted.

The practical implications of the paper include providing a structured framework for understanding the complexities of GTM.

Research into the academic literature in this area is divided into various clusters, empirically demonstrating how GTM and global mobility are intertwined, revealing the need for us to more thoroughly comprehend the social ramifications of GTM practices and activities and the need to further analyse the influencing social aspects in a GTM strategy, like diversity, increased mobility and virtual reality.

The analysis revealed the emergence of three distinct thematic groups: (1) global work experiences, (2) TM approaches and (3) GTM.

Companies target globally mobile workers and face the war for talent, while individuals are more reluctant to engage in global mobility. This scenario led us to propose a model to understand the individuals' decision process to engage in global mobility.

Building on the self-determination theory, the theory of planned behavior and the literature on decisions for global mobility, the authors propose mechanisms through which psychological variables and assignments' factual and perceived contextual aspects (directly or indirectly) explain the decision to engage or not in global mobility.

This study offers a conceptual model with the authors' novel propositions to explain individuals' decision to engage in global mobility.

The model provides a more comprehensive explanation of the individuals' decision-making process to engage in global mobility than previous models and potentially yields more effective organizational practices to attract both well-established and emerging phenomena of globally mobile workers.

This study aims to identify and prioritize the key practices and strategies for effective global sourcing and supply chain management (SCM).

The study uses a combination of Pareto analysis and multi-objective optimization based on ratio analysis research methodology to analyze and establish the relationships among the identified key practices and strategies. Pareto analysis enables organization to prioritize organizational efforts and resources by focusing on the most critical factors.

The study shows that the “eco-friendly sourcing strategy”, “lean manufacturing” and “tool cost analysis” are the top critical practices and strategy variables for global sourcing and SCM, whereas the “risk management”, “procurement strategy” and “leverage digital solutions” are the critical practices and strategy variables.

The findings of this research can also assist organizations in making informed decisions to optimize their global sourcing and supply chain operations.

By using these methods, this research paper gives valuable insights into the critical practices and strategies that can enhance efficiency, mitigate risks and drive success in global sourcing and SCM. The subjects and elements this study identified will serve as a framework and suggestions for further theoretical investigation and real-world implementations.

Single-shot multi-category clothing recognition and retrieval play a crucial role in online searching and offline settlement scenarios. Existing clothing recognition methods based on RGBD clothing images often suffer from high-dimensional feature representations, leading to compromised performance and efficiency.

To address this issue, this paper proposes a novel method called Manifold Embedded Discriminative Feature Selection (MEDFS) to select global and local features, thereby reducing the dimensionality of the feature representation and improving performance. Specifically, by combining three global features and three local features, a low-dimensional embedding is constructed to capture the correlations between features and categories. The MEDFS method designs an optimization framework utilizing manifold mapping and sparse regularization to achieve feature selection. The optimization objective is solved using an alternating iterative strategy, ensuring convergence.

Empirical studies conducted on a publicly available RGBD clothing image dataset demonstrate that the proposed MEDFS method achieves highly competitive clothing classification performance while maintaining efficiency in clothing recognition and retrieval.

This paper introduces a novel approach for multi-category clothing recognition and retrieval, incorporating the selection of global and local features. The proposed method holds potential for practical applications in real-world clothing scenarios.