Optimizing Supply Chain Logistics in the Fashion Retail Industry Using Network Theory

Thesis Abstract

Efficient management of supply chain logistics remains a critical challenge within the highly dynamic and competitive fashion retail industry, where rapid inventory turnover and evolving consumer preferences demand agile and optimized logistical processes. Despite significant advances in supply chain management practices, many fashion retailers continue to encounter inefficiencies, leading to increased costs, delayed deliveries, and decreased customer satisfaction. This study aims to develop a comprehensive framework for optimizing supply chain logistics in fashion retail organizations through the application of network theory, thereby enhancing overall supply chain performance and resilience. The primary objectives are to 1) model the supply chain network of a representative fashion retail organization using network theory principles, 2) identify key nodes and relationships influencing logistical efficiency, 3) evaluate the current supply chain’s structural vulnerabilities and bottlenecks, and 4) propose targeted interventions to optimize network flow and reduce logistical costs. To achieve these objectives, a mixed-methods research design was adopted, combining quantitative network analysis with qualitative interviews for contextual understanding. The population comprised supply chain managers, logistics coordinators, and warehouse staff within a leading fashion retail chain operating in a metropolitan area with 150 stores and distribution centers. A purposive sampling technique was employed to select 30 key stakeholders, and a combination of structured questionnaires, company records, and system data was used for data collection. Quantitative data on shipment volumes, lead times, transportation routes, and cost matrices were collected and analyzed using social network analysis (SNA) tools such as Gephi and UCINET to map and measure network density, centrality, and betweenness. Network configuration properties were examined to identify critical nodes and pathways. Additionally, the study used regression analysis to explore the relationship between network structural metrics and logistical performance indicators, and thematic analysis was employed to interpret qualitative insights from interviews regarding operational challenges and strategic priorities. Model specification incorporated principles from the supply chain network theory and the dynamic capabilities framework to assess the impact of network modifications on logistical robustness and adaptability. Expected findings suggest that the current supply chain network displays suboptimal connectivity, with over-reliance on central nodes that create bottlenecks and increase vulnerability to disruptions. Key nodes such as regional distribution centers are anticipated to emerge as critical points whose optimization could significantly improve flow efficiency. The study anticipates revealing that targeted decentralization and diversification of transportation routes, guided by network analysis, can reduce lead times by up to 20% and logistics costs by approximately 15%. These improvements are expected to be achieved through reconfiguring supply chain networks to enhance redundancy and decentralization while maintaining service levels. This research contributes novel insights into the application of network theory within the context of fashion retail logistics, providing a theoretical and empirical basis for network-based optimization strategies. It extends existing supply chain management literature by demonstrating how network analytical techniques can identify structural vulnerabilities and inform strategic interventions tailored to the specific complexities of fashion retail logistics. Furthermore, the study develops a practical model that integrates network analysis with operational decision-making frameworks, facilitating data-driven logistics planning. The main conclusion underscores the importance of adopting a network-centric perspective to enhance logistical efficiency and resilience. It recommends that fashion retail organizations undertake comprehensive network audits using social network analysis tools regularly, implement decentralization strategies at critical nodes, and invest in flexible logistics infrastructure capable of rapid reconfiguration. Future research should explore the integration of real-time tracking with dynamic network modeling to further improve responsiveness and adaptability in fashion supply chains, especially under conditions of sudden market shifts or disruptions.