Global supply chains are currently undergoing significant transformation under the influence of marketing trends and rapid digitalization. The growing complexity of customer needs, combined with the expansion of e-commerce and the integration of Industry 4.0 technologies, requires new approaches to the design and coordination of supply chain strategies. This article explores the interrelation between supply chain management (SCM), contemporary marketing tendencies, and the implementation of advanced IT solutions. The main objective is to analyze how customer-oriented strategies and digital innovations - such as big data analytics, artificial intelligence, blockchain, and cloud platforms - contribute to the resilience, flexibility, and efficiency of supply chains. The methodological framework includes a literature review, comparative analysis of global companies, and case-based evaluation of IT adoption in logistics operations. Results demonstrate that marketing-driven SCM strategies, supported by digital technologies, improve demand forecasting accuracy, shorten delivery lead times, and enhance customer experience. Moreover, companies that align marketing insights with supply chain planning achieve superior competitive advantages by creating adaptive networks and developing sustainable partnerships. The article contributes to both theory and practice by emphasizing the necessity of integrating market dynamics with technological capabilities in modern SCM. Practical recommendations are provided for managers and policymakers to strengthen competitiveness in volatile markets through the synergy of marketing strategies and IT-enabled logistics.
Despite the growing adoption of Environmental, Social, and Governance (ESG) criteria in corporate strategy, a significant gap exists in understanding how consumer perceptions of ESG translate into the adoption of tangible green logistics services. This study investigates how ESG factors influence consumer willingness to pay for green logistics such as sustainable transport, optimized material flow and eco-friendly packaging in an emerging market context. Grounded in the Theory of Planned Behavior, the model examines the mediating roles of green brand image, green trust, and green purchase intention in shaping sustainable logistics consumption. A structured online survey was administered to 350 young consumers belong to Generation Z, and data were analyzed using PLS-SEM. Structural model results reveal that green marketing and CSR significantly enhance green purchase intention, while greenwashing undermines trust. All hypothesized relationships were statistically significant. This research provides a novel, validated model linking perceived ESG performance to consumer willingness to pay for green logistics. It offers practical insights for supply chain managers on leveraging transparent ESG practices to build brand trust and drive adoption of sustainable logistics solutions.
This study proposes a mathematical model for optimizing delivery routes in the urban distribution of Coca-Cola FEMSA to OXXO stores in Texcoco municipality, State of Mexico. Based on a theoretical framework grounded in linear programming using the Simplex method and graph theory, an algorithm was developed and implemented in LINDO software to minimize logistics costs, distance traveled, and fuel consumption. This approach, in turn, ensures a more sustainable route by achieving a reduction in polluting gas emissions. The results show a 12.3% reduction in distance, decreasing from 66.25 km to 58.1 km, and a 12.4% saving in fuel costs, from 686.28 to 600.96 Mexican pesos, for the route. The results demonstrated a significant contribution to the reduction of the carbon footprint, with a decrease of approximately 2.04 kg of CO2, achieving a more sustainable urban distribution and greater operational efficiency.
As sustainability becomes a strategic imperative in industrial operations, a comprehensive evaluation of material handling equipment's environmental, economic, and social impacts is essential. This study proposes a novel simulation-based framework to assess and compare the sustainability performance of forklifts and Automated Guided Vehicles (AGVs) in warehouse-to-assembly line operations. Leveraging the Triple Bottom Line (TBL) approach, we integrate technical, environmental (e.g., energy consumption, GHG emissions), economic (operational costs), and social (ergonomics) indicators into a unified evaluation model. Using Siemens Tecnomatix Plant Simulation, we model an automotive intralogistics scenario where components are transported from the warehouse to the assembly stations. Our results reveal that AGVs outperform forklifts in terms of energy efficiency (44% lower consumption) and scalability, but exhibit higher idle times (46.11%). In contrast, forklifts offer greater operational flexibility. The study presents a replicable methodology for dynamic sustainability assessment in intralogistics and provides actionable insights for technology selection, demonstrating how trade-offs between automation and social-centric systems influence sustainable outcomes in manufacturing environments.
This study examines how logistics digitalization in small and medium-sized enterprises (SMEs) engaged in e-commerce shapes customer satisfaction and business competitiveness through specific operational mechanisms. Using a structured narrative review, the research integrates conceptual findings into an analytical framework. The methodology consists of a bibliographic search (2020-2025), followed by a thematic synthesis of 69 abstracts selected after applying exclusion criteria. The analysis shows that digital logistics practices create value when they activate four mechanisms: visibility, synchronization, accuracy, and efficiency/automation. These mechanisms enhance customer satisfaction by improving transparency, reliability, personalization, and service speed, while strengthening competitiveness through cost reduction, scalability, and market differentiation. The findings also reveal that the effectiveness of these mechanisms depends on digital maturity, cultural adaptability, and absorptive capacity, as well as on broader institutional conditions. Limited investment, skill shortages, regulatory gaps, and infrastructural inequalities constrain SMEs' ability to fully scale digital tools, underscoring that technological adoption alone is insufficient without organizational readiness and institutional support. By articulating a framework of mechanism-based pathways linking digital practices to customer satisfaction and competitiveness, the study advances theoretical understanding beyond descriptive taxonomies and toward explanatory models of digital logistics. The study concludes by proposing a staged digital maturity model as a supporting tool to identify the current level of logistics capabilities of SMEs and to project scaling pathways toward higher levels of integration, automation, and analytical sophistication.
