The construction industry's increasing complexity and dynamic project environments engender advanced risk management strategies. AI-based risk management tools, reliant on complex mathematical models, often impose specialised coding requirements, leading to challenges in accessibility and implementation. In this vein, Generative Artificial Intelligence (GenAI) emerges as a potentially transformative solution, leveraging adaptive algorithms capable of real-time data analysis to enhance predictive accuracy and decisionmaking efficacy within Construction Risk Management (CRM). However, integrating GenAI into CRM introduces significant challenges, including concerns around data security, privacy, regulatory compliance, and a skills gap. Our research seeks to address these issues by presenting a systematic bibliometric analysis that explores evolving trends, key research contributions, and critical methodological approaches related to GenAI in CRM. Thus far, our investigation has analysed 23 selected research articles from an initial corpus of 212 papers, spanning the period from 2014 to 2024. Early insights delineate a marked escalation in research activity from 2020 onwards, a surge likely engendered by 2 recent advancements in AI technologies and their applicability to construction management. We categorise GenAI's potential benefits into technical, operational, technological, and integration-related advantages, encompassing improvements in risk identification, predictive capabilities, scheduling, and cybersecurity. Simultaneously, we identify significant risks, particularly related to data governance, social acceptance, and the operational impacts of AI-driven decisions. These preliminary findings underscore the imperative for systematic governance frameworks and proactive stakeholder engagement to optimise GenAI's benefits whilst mitigating its latent risks.

Agricultural cooperatives (co-ops) are increasingly recognised for their capacity to enhance resilience in the face of crises such as climate change, economic disruptions, and pandemics. This study investigates how governance structures and adaptive project management strategies contribute to effective crisis management in coops. Initial findings reveal that regulatory compliance acts as both a constraint and an enabler, while economic volatility drives the need for costly technological investments. External stakeholder influence provides essential resources but imposes governance to align internal and external priorities. Social capital, manifesting as community trust and collaboration, supports crisis response but can be weakened under financial stress. Hybrid governance frameworks emerge as vital, balancing member engagement with professional oversight to maintain organisational stability. We propose the Crisis Resilience in Agricultural Cooperatives conceptual framework, which links external pressures, internal dynamics, and resource availability to resilience outcomes. This research highlights the importance of strategic governance, adaptive project management, and effective social networks in fostering coop resilience and provides guidance for policymakers and practitioners.

Industry 5.0 (I5.0) is increasingly emerging as a prominent paradigm across the global business landscape, with three distinctive core values: human-centricity, sustainability, and resilience. This shift introduces notable changes in multiple aspects and requires academics and practitioners to reexamine the concept of supply chain management. Whilst previous research has identified the potential of I5.0 in enhancing supply chain performance (SCP), there has been insufficient attention paid to the understanding of the nature and implications of human-AI interactions. More specifically, there is a lack of thorough discussion on the mechanism how I5.0 can improve SCP. This exploratory study therefore aims to develop theoretical insights through empirical examination of the relationships between I5.0 and SCP in the manufacturing industry, with supply chain integration (SCI) as a mediator. Adopting a dynamic capabilities perspective, we argue that overcoming the challenges associated with implementing I5.0 may motivate companies to integrate their supply chains and enhance their SCP. Partial least squares structural equation modelling (PLS-SEM) is applied to test the hypotheses using survey data from 230 industry professionals, followed by a fuzzy analytic hierarchy process (FAHP) to quantify and prioritise the impacts of I5.0 challenges on SCP indicators. The results indicate that I5.0 has a direct positive impact on both SCI and SCP. Furthermore, SCI plays a significant role in mediating the relationship between I5.0 and SCP. This research contributes to the body of knowledge by empirically validating the relationships between I5.0, SCI, and SCP in a solitary and holistic model, thereby bridging the gaps in the literature between these distinct research streams.