RESEARCH OBJECTIVE: The aim of the study was to comprehensively assess the level of adaptation of modern logistics technologies and evaluate the significance of key digitalization, market, and process trends, as well as to identify the determinants influencing their implementation in companies of various sizes and business profiles, operating in domestic and international supply chains.
THE RESEARCH PROBLEM AND METHODS: The research problem concerned the identification of digital technologies and trends that exert a dominant influence on the logistics transformation of enterprises, as well as the examination of how their significance varies across different organizational characteristics. A quantitative survey (N = 121) was administered, comprising 18 items, 11 of which were evaluated using a Likert scale. The collected data were subjected to descriptive statistical procedures and ranking analysis. The research employed methodologies characteristic of management and quality sciences, as well as political science and administration, which allowed for a multifaceted view of digital transformation processes.
THE PROCESS OF ARGUMENTATION: The argumentation was grounded in comparing the level of logistics technology adaptation with the perception of market and operational trends. The literature on the heterogeneous pace of digital transformation was incorporated and confronted with empirical results, which revealed relationships among analytical, process-oriented, and robotic solutions.
RESEARCH RESULTS: The results indicated that the highest level of adaptation is associated with cloud technologies and Big Data analytics, whereas robotization and blockchain remain at an early stage of implementation. The most influential determinants of development include shifts in consumer behavior, pressure to enhance efficiency, and the necessity to design new processes.
CONCLUSIONS, INNOVATIONS, AND RECOMMENDATIONS: It was found that digital transformation is driven mainly by demand-related and process-oriented factors, while its effectiveness depends on data integration, technological competence development, and efficient acquisition of financial resources. Priority is recommended for investments in analytical technologies and digital competencies, with a cautious approach to robotic and blockchain solutions due to persistent implementation barriers.
Digital transformation ; Logistics 4.0 ; Smart logistics technologies ; Supply chain management ; Big Data analytics
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