Purpose: The purpose of this paper is to understand the nomological network of associations between collective mindfulness and big data analytics in fostering resilient humanitarian relief supply chains.Design/methodology/approach: The authors conceptualize a research model grounded in literature and test the hypotheses using survey data collected from informants at humanitarian aid organizations in Africa and Europe.Findings: The findings demonstrate that organizational mindfulness is key to enabling resilient humanitarian relief supply chains, as opposed to just big data analytics.Originality/value: This is the first study to examine organizational mindfulness and big data analytics in the context of humanitarian relief supply chains.

Alongside the revolutionary benefits of AI, it can cause numerous problems across the system development process. AI ecosytem players have recently started to interrogate the ethical biases implicit in AI-enabled applications and agents. The contestable nature of ethics and the complexity of AI-enabled applications has led to incoherent literature around AI ethical biases. The numerous conceptions of AI ethics and a multiplicity of ethical biases has compounded matters for researchers, practitioners, and policy makers. The current study proposes a conceptual framework to organize AI ethical biases. A narrative literature review was conducted to identify and group the biases into data biases, method biases and implementation biases. The CRISP-DM framework was used to classify the ethical biases. The emerging conceptual framework has four clusters that represents: System development phases, scope of ethical bias, exemplars, and possible solutions. The study extends the existing AI ethical frameworks and provides a unified communication artefact for practitioners.

This research abstract provides a comprehensive overview of exploring the requirements and applications of the next generation Internet of Things (IoT). The study which used thorough literature review as methodology, involved a systematic search of relevant academic databases, such as Scopus, IEEE Xplore, and ACM Digital Library, using keywords such as “Internet of Things,” “next-generation IoT,” “IoT requirements,” and “IoT applications.” The search was limited to peer-reviewed journal articles, conference proceedings, and book chapters published within the last ten years to ensure the inclusion of the most recent and relevant information. It focused on identifying the key requirements for the next generation of Internet of Things (IoT) technologies, evaluating the current state of IoT applications and identify areas of improvement for future generations, investigating the potential impact of next-generation IoT on various industries and sectors. Other objectives of the study are: analysing the data security and privacy challenges that may arise with the implementation of next-generation IoT technologies, examining the potential environmental impact of next-generation IoT devices and propose sustainable solutions, investigating the use of artificial intelligence and machine learning algorithms for enhancing the capabilities of IoT applications and the future perspectives of internet of things. Additionally, the research delves into the diverse range of applications that can benefit from the next generation IoT. These applications span across industries such as healthcare, agriculture, transportation, and smart cities. The IoT enables improved efficiency, automation of processes, and better decision-making in various sectors. The findings highlight the need for holistic approaches to address the requirements and challenges of the next generation IoT. By focusing on interoperability, standardization, security, and data management, researchers and industry professionals can ensure the continued success and advancements of the IoT.

This study aims to explore and understand the literature on digital transformation (DT) research that will lead to developing a conceptual and thematic structure of DT management. The research approach employed a hybrid approach of bibliometric analysis and a structured review of DT management research studies from 2017 to 2023. Although systematic reviews and bibliometric analysis are distinct methods, they complement one another in research by enabling the synthesis and analysis of existing literature. Scopus and Web of Science (WoS) were selected as the bibliographic databases for this study since they are generally accepted as the most comprehensive data sources for various purposes. Findings revealed 186 publications during these periods, with the top three publications being the Journal of Business Research, Business Horizons and California Business Review. Top-ranking researchers hailed from Germany, Japan and Spain. Keywords that appeared were innovation, digital transformation, artificial intelligence and DT. In the management area, there are fewer studies conceptualising DT management that led to this study forming a conceptual framework using a qualitative, interpretative and thematic analysis approach. These findings are relevant for understanding the phenomenon of DT and DT management. The study contributes to the emerging body of knowledge in management and DT.

Although there is a growing body of literature on the impact of COVID-19 pandemic, limited evidence exists on the impact of the pandemic on informal female-owned enterprises, and especially those that are located in urban informal settlements. Based on a quantitative survey of 448 vendors selected through stratified random sampling, this study employed a descriptive design to examine the dynamics of women-led informal food vending enterprises across four informal settlements in Nairobi, with particular emphasis on the adverse impacts of the COVID-19 pandemic and the vendors’ coping strategies. Our findings show that women food vendors face numerous challenges which intensified during the pandemic, leading to increased business operation costs, spoilage of perishable products, and oscillating daily sales and profits due to unpredictable market forces. The vendors adopted various strategies to cushion their enterprises and households, including price and stock adjustments; the implementation of hygiene measures; increased use of mobile phones for transactions; reliance on credit, loans, savings, and social networks; temporary business closures; and the relocation of household members to rural areas. These results underscore the critical need for context-specific strategies to support and foster the resilience and sustainability of informal economies during future global pandemics. This is particularly urgent given that very few vendors received some form of institutional support, in addition to having limited access to business loans and training opportunities.