Smart cities aim to enhance the quality of life for citizens by integrating information technology in various aspects of daily life. This paper focuses on recent innovations in the integration of two prominent technologies, artificial intelligence (AI) and blockchain, to manage complex interactions between smart connected devices, individuals, government agencies, and the private sector. By conducting a systematic scientometric analysis and visualization of 505 articles published between 2017 and 2023, we uncover the social, conceptual, and intellectual structures of the literature in this field through co-authorship, co-word, and co-citation networks. Our analysis identifies key insights, research hotspots, specialties, and emerging trends by examining important nodes in the bibliometric networks. The findings of this study can be of interest to both academics and practitioners working in the fields of AI, blockchain, and smart cities.

This research questions concept and practices of consumer integration in supply chain. Supply chain integration literature focused mainly on the integration of suppliers and customers in the supply chain. The evolution of consumer behaviour has repositioned him as a powerful and indispensable partner in the supply chain. This change has encouraged firms to collaborate differently with the consumer in a more interactive and integrated way, especially in supply chain management processes. This research discusses insights and observations from an exploratory empirical study with 50 semi-structured interviews with supply chain managers and functional managers involved in consumer integration issues, in France from various activity sectors. Thanks to qualitative analysis, empirical practices of consumer integration are identified in supply chain management processes. They concern three domains: R&D, planning and distribution. We propose a definition of consumer integration in supply chain management and a consumer integration taxonomy, based on three dimensions (information sharing, shared decision-making and alignment of goals).

As the reallocator of liquidity from banks with excess to banks with a deficit, the interbank money market (IMM) plays a fundamental role in the proper functioning of the banking system and the economy as a whole. The aggregate uncertainty derived from stochasticity of the overall level of the demand for short‐term liquidity and the likelihood of domino failures of tightly connected competitors who lend themselves vast amounts of liquidity explains the complexity of decisions in this environment. To identify the most significant factors influencing actors’ strategies, we first present the five underlying patterns discovered through a bibliometric analysis of 609 scientific documents in this field: contagion and systemic risk, stability, market structure, relationship and trust, and default and failure. Then, our detailed study findings on 160 recent works indicate elements that affect central banks’ strategies in reducing systemic risk and preventing financial contagion, as well as managing the interbank network in a way that makes it more stable and resilient to shocks to conserve market confidence. Furthermore, they address factors that influence banks’ strategies to maintain their lending relationships and mitigate default risk. In addition to summarizing potential research directions, this paper provides market participants with a strategy fact‐sheet.

Purpose: The study aims to develop a typology of pooled warehouses (PWs) based on their collaborative intensity and operational dynamics. By exploring diverse French PWs, the research seeks to clarify how these dimensions influence management practices and performance, offering insights to guide decision-making in establishing or improving PW strategies. Design/methodology/approach: This research adopts an exploratory, qualitative case study approach, drawing on Yin (2018) and Corley and Gioia (2004). Seven French PWs were studied through 27 semi-structured interviews with managers and logistics experts. Cross-case analysis and thematic coding allowed for the identification of collaboration and dynamics patterns, supporting the development of a typology to better understand PW configurations. Findings: The research identified four PW types: Type I (Partial collaboration, Low dynamics), Type II (Partial collaboration, High dynamics), Type III (Full collaboration, Low dynamics), and Type IV (Full collaboration, High dynamics). Collaboration varied from bilateral to multilateral arrangements, while dynamics reflected both external volatility and internal complexity. The typology highlights the need to align collaboration with environmental dynamics to enhance PW performance, resilience, and adaptability. Originality/value: This study offers an original typology categorizing PWs by collaboration and dynamics, addressing a notable research gap. It emphasizes warehouses as strategic components in collaborative logistics, extending beyond transport pooling. The framework provides practical guidance for managers to tailor collaboration strategies to specific operational contexts. It contributes to the understanding of how PWs can enhance supply chain efficiency, flexibility, and sustainability through structured collaboration and dynamic management.