THEORETICAL AND METHODOLOGICAL FOUNDATIONS AND BIBLIOMETRIC ANALYSIS OF LOGISTICS SUPPORT FOR ENTREPRENEURSHIP UNDER CONDITIONS OF UNCERTAINTY

Abstract

The article explores the theoretical and methodological foundations of the formation and transformation of logistical support for entrepreneurial activity operating under conditions of high environmental uncertainty, market volatility, and systemic disruption risks. The study scientifically substantiates the need to revise and delineate the conceptual and categorical framework in logistics theory. Specifically, the authors differentiate the categories of "logistics" as a domain of knowledge, "logistics management" as an operational process, and "logistical support" as a comprehensive managerial system. Logistical support is conceptualized not merely as a set of transportation and warehousing activities, but as an integrated system of managerial, organizational, resource, technological, infrastructural, and information-analytical conditions designed to sustain business viability and continuity.

To identify key global research trajectories and structural relationships within this domain, a bibliometric analysis was conducted using VOSviewer software based on a curated dataset of 195 terms indexed in Scopus. The co-occurrence network map, overlay temporal visualization, and field density map were constructed and analyzed. The findings reveal a paradigm shift in global research from traditional cost minimization toward supply chain resilience, risk mitigation, and continuity management.

The bibliometric mapping identified seven distinct semantic clusters, illuminating the multi-component nature of logistical support. These clusters connect supply chain resilience, risk assessment, and strategic planning with modern digital technologies, including artificial intelligence, machine learning, and ERP integration. Special attention is devoted to the concept of Triple-A capabilities (agility, adaptability, and alignment), emphasizing that modern adaptability relies heavily on data-driven decision-making and digital visibility. The study concludes that building an effective logistical support mechanism requires integrating internal dynamic capabilities with the broader infrastructural ecosystem, providing a foundation for sustainable entrepreneurial competitiveness in turbulent environments.