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This study aims to determine how the applications of blockchain technology (BT) can play a crucial role in managing financial flows in the humanitarian supply chain (HSC) and what benefits and challenges are associated with BT in a humanitarian setting.

The present study used a qualitative research approach, incorporating a systematic literature review and conducting semi-structured interviews with 12 experts in the fields of humanitarian operations, supply chain management, fintech and information technology.

The findings show that the humanitarian sector has the potential to reap significant benefits from BT, including secure data exchange, efficient SCM, streamlined donor financing, cost-effective financial transactions, smooth digital cash flow management and the facilitation of cash programs and crowdfunding. Despite the promising prospects, this study also illuminated various challenges associated with the application of BT in the HSC. Key challenges identified include scalability issues, high cost and resource requirements, lack of network reliability, data privacy, supply chain integration, knowledge and training gaps, regulatory frameworks and ethical considerations. Moreover, the study highlighted the importance of implementing mitigation strategies to address the challenges effectively.

The present study is confined to exploring the benefits, challenges and corresponding mitigation strategies. The research uses a semi-structured interview method as the primary research approach.

This study adds to the existing body of knowledge concerning BT and HSC by explaining the pivotal role of BT in improving the financial flow within HSC. Moreover, it addresses a notable research gap, as there is a scarcity of studies that holistically cover the expert perspectives on benefits, challenges and strategies related to blockchain applications for effective financial flows within humanitarian settings. Consequently, this study seeks to bridge this knowledge gap and provide valuable insights into this critical area.

This study aims to explore the potential benefits of integrating Artificial Intelligence (AI) with Social Emotional Learning (SEL) in educational settings.

A systematic review of emerging AI technologies such as virtual reality, chatbots, sentiment analysis tools, gamification and wearable devices is conducted to assess their applicability in enhancing SEL.

AI technologies present opportunities for personalized support, increased engagement, empathy development and promotion of well-being within SEL frameworks.

Future research should focus on addressing ethical concerns, fostering interdisciplinary collaborations, conducting longitudinal studies, promoting cultural sensitivity and developing robust ecosystems for AI in SEL.

This study contributes by outlining pathways for leveraging AI to create inclusive and supportive learning environments that nurture students' socio-emotional competencies, preparing them for success in a globally connected world.

Researchers looking for ways to change the insecure behaviour that results in phishing have considered multiple possible reasons for such behaviour. Therefore, the purpose of this paper is to understand the role of optimism bias (OB – defined as a cognitive bias), which characterises overly optimistic or unrealistic individuals, to ensure secure behaviour. Research that focused on issues such as personality traits, trust, attitude and Security, Education, Training and Awareness (SETA) was considered.

This study built on a recontextualized version of the theory of planned behaviour to evaluate the influence that optimism bias has on phishing susceptibility. To model the data, an analysis was performed on 226 survey responses from a South African financial services organisation using partial least squares (PLS) path modelling.

This study found that overly optimistic employees were inclined to behave insecurely, while factors such as attitude and trust significantly influenced the intention to behave securely.

Our contribution to practice seeks to enhance the effectiveness of SETA by identifying and addressing the optimism bias weakness to deliver a more successful training outcome.

Our study enriches the Information Systems literature by evaluating the effect of a cognitive bias on phishing susceptibility and offers a contextual explanation of the resultant behaviour.

This study explores the relationship between Tourism Systems and Smart Cities, aiming to identify what prevents public managers from including these systems in Smart City strategies. This separation neglects that increasing tourism attractiveness may also impact city resources, infrastructures and inhabitants.

To this end, we developed a critical literature review consulting three databases: Scopus, Web of Science and EBSCOhost. A total of 73 articles were selected and analyzed through thematic analysis.

Through this critical review, we develop a framework of barriers to integrating a tourism system in Smart City strategies composed of four main barrier themes and 11 barrier factors. Findings show the need for innovative research and public managers to go beyond considerations related to technological challenges and instead focus on other barriers hindering integration, such as the lack of participatory governance and knowledge of tourism systems' current and future impact.

This study offers a critical identification of barriers impeding the inclusion of tourism systems in Smart City strategies, providing a useful guideline for public managers aiming to follow an innovative approach to smart development where tourism can still be a tool to enhance the attractiveness of the territory while considering its current and future impact on the city.

The purpose of this paper was to extend the current knowledge on the impacts of activity-based workplaces (ABWs) on productivity in knowledge work. It offers more background information that is needed to properly evaluate ABWs’ suitability for different organisations. In the results section, ABWs are compared to the cellular and open-plan office types.

This study was conducted using a survey method with 5,841 respondents. The data were collected between 2015 and 2019 from 32 public-sector organisations.

The findings of this paper reveal that ABWs offer clear advantages over the other office types but requires careful design and well-implemented solutions. The superiority between ABWs and cellular offices also depends on workers’ profiles and needs and is not for everyone.

For practitioners, this paper offers valuable information to compare the three office types: ABW, cellular and open-plan. It also highlights the importance of careful planning and good implementation, which are both essential to making the ABW environment productive for employees. Finally, this paper clearly provides evidence that ABWs and open-plan offices differ in their facilities and productivity.

This paper included a unique and large sample with open variables, which are fairly rare in ABW-related papers. It also provides evidence that ABWs, when implemented correctly, seem to be an excellent option for some work profiles.

Companies are increasingly benefiting from artificial intelligence (AI) applications in various domains, but also facing its negative impacts. The challenge lies in the lack of clear governance mechanisms for AI. While documentation is a key governance tool, standard software engineering practices are inadequate for AI. Practitioners are unsure about how to document AI, raising questions about the effectiveness of current documentation guidelines. This review examines whether AI documentation guidelines meet regulatory and industry needs for AI applications and suggests directions for future research.

A structured literature review was conducted. In total, 38 papers from top journals and conferences in the fields of medicine and information systems as well as journals focused on fair, accountable and transparent AI were reviewed.

This literature review contributes to the literature by investigating the extent to which current documentation guidelines can meet the documentation requirements for AI applications from regulatory bodies and industry practitioners and by presenting avenues for future research. This paper finds contemporary documentation guidelines inadequate in meeting regulators’ and professionals’' expectations. This paper concludes with three recommended avenues for future research.

This paper benefits from the insights from comprehensive and up-to-date sources on the documentation of AI applications.

This paper demystifies the fluid workforce phenomenon increasingly discussed in the circles of organizational innovators and explores the characteristic aspects of the fluid workforce in the healthcare sector.

We analyze the concept and provide a generic review of definitions of a fluid workforce in relation to other similar concepts established in the academic and practitioner literature, contextualize the fluid workforce phenomenon in healthcare and distinguish relevant drivers and categories of fluid workers in this sector. We also discuss the implications of a fluid workforce for healthcare organizations, drawing on the health labor market and human resource management (HRM) practices frameworks.

The fluid workforce in healthcare is not new. Today’s main novelties are related to the wide diversity of types of fluid workforce that have emerged, the expanding scale of diffusion of the fluid workforce and the emergence of digital technologies to support HRM decisions. While a fluid workforce may provide solutions to address mismatches in the supply and demand of health workers, it can also worsen working conditions, increase dual practice and have implications for existing HRM practices.

We disentangle a novel term for the public sector, healthcare and HRM literature. We discern similarities and distinctions, presenting a framework for managing and analyzing this workforce at organizational and labor market levels in the healthcare sector. Acknowledging the challenges in estimating the existing fluid workforce labor market size, we offer practical methodologies to empirically estimate its prevalence within the healthcare industry and build an agenda for future research.

To enrich the research on the economic consequences of enterprise digital development from the perspective of capacity utilization.

Using a sample of listed firms from 2010 to 2020, this paper exploits text analysis of annual reports to construct a proxy for enterprise digital development.

Results show that enterprise digital development not only improves their own capacity utilization but also generates a positive spillover effect on the capacity utilization of peer firms and firms in the supply chain. Next, based on the incomplete information about market demand and potential competitors when making capacity-building decisions, the mechanism tests show that improving the accuracy of market forecasts and reducing investment surges are potential channels behind the baseline results. Cross-sectional tests show the baseline result is more pronounced when industries are highly homogeneous and when firms have access to less information.

This paper contributes to the research related to the economic consequences of digital development. With the development of the digital economy, the real effects of enterprise digital development have also triggered extensive interest and exploration. Existing studies mainly examine the impact on physical operations, such as specialization division of labor, innovation activities, business performance or total factor productivity (Huang, Yu, & Zhang, 2019; Yuan, Xiao, Geng, & Sheng, 2021; Wang, Kuang, & Shao, 2017; Li, Liu, & Shao, 2021; Zhao, Wang, & Li, 2021). These studies measure the economic benefits from the perspective of the supply (output) side but neglect the importance of the supply system to adapt to the actual market demand. In contrast, this paper focuses on capacity utilization, aimed at estimating the net economic effect of digital development by considering the supply-demand fit scenario. Thus, our findings enrich the relevant studies on the potential consequences of digital development.

The purpose of this paper is to examine the relationships among diversity, equity and inclusion (DEI), sport and the metaverse.

The authors overview the metaverse, sport applications and ways multilevel theory can help explain the influence of DEI.

Drawing from multilevel theory, the authors identify parallels between the sport metaverse and traditional sport as well as unique DEI opportunities in the sport metaverse.

The manuscript contributes to the nascent body of research regarding sport and the metaverse, with a specific focus on social issues and the importance of considering unique DEI opportunities.

This study investigates the individual and binary (i.e. combined) effects of institutional dimensions of open government data (which include instructional, structural and accessible rules) on scientific research innovation, as well as the mediating roles that researchers' perceived data usefulness and data capability play in between.

Based on a sample of 1,092 respondents, this study uses partial least squares structural equation modeling (PLS-SEM) and polynomial regression with response surface analysis to evaluate the direct and indirect effects of individual and binary institutional dimensions on scientific research innovation.

The findings demonstrate that instructional, structural and restricted access data have a positive effect on scientific research innovation in the individual effect. While the binary effect of institutional dimensions produces varying degrees of scientific research innovation. Furthermore, this study discovers that the perceived usefulness and data capability of researchers differ in the mediating effect of institutional dimensions on scientific research innovation.

Theoretically, this study contributes new knowledge on the causal links between data publication institutions and innovation. Practically, the research findings offer government data managers timely suggestions on how to build up institutions to foster greater data usage.