Exploring the Structural Topology of a Representative Sample of Retail Supply Chains and Their Evolution using a Data Visualization Approach

Visualizing supply network topology using financial data

2016 Seed Grant

This project will allow students to gain a better understanding of the inter-relationships in supply networks. Undergraduate students who have taken BITM3741 (Supply Chain Management) will be mapping out supply network structures using the FACTSET database. The students will be given clear guidelines as to how to collect the historical data as well as how it should be organized. Once the data is arranged, it can then be imported into a digital visualization software package (such as Gephi (https://gephi.org/), for further analysis and metric calculation.

Orenstein, Penina, “Visualizing supply network topology using financial data” (2016). Digital Humanities. 12.
http://scholarship.shu.edu/dh/12

Exploring the Structural Topology of a Representative Sample of Retail Supply Chains and Their Evolution using a Data Visualization Approach

2017 Faculty Fellow

This project, led by Supply Chain professor, Dr Penina Orenstein is part of an award winning ongoing initiative at Seton Hall University and represents a faculty driven student collaborative research project. It is built on an innovative concept which harnesses the power of financial supply chain vendor data (FACTSET www.factset.com) with network visualization software (Gephi – www.gephi.org). The result of this approach is the creation of a visual map of a company’s supply chain. This map can then be used to identify the supply chain’s structure, explore its evolution, and understand how structure impacts performance using key financial metrics. This will provide insight into customer behavior and preferences as well as how key supply chains select and build their supplier base. In addition, a data-driven understanding of modern supply chain networks is critical in today’s world in order to continue to build and enhance the supply chains of the future. The project will support research into the creation of models, analyses, and algorithms that will bridge data with decisions related to the design, planning, and operation of a supply chain network. Specifically, the advances will be connected to modeling, and the use of customized methods, analytical and computational, required for the relevant applications. The research will generate a body of knowledge which will help explain how modern supply chains develop, evolve and change as a result of modern societal demands.

Orenstein, Penina, “Exploring the Structural Topology of a Representative Sample of Retail Supply Chains and Their Evolution using a Data Visualization Approach” (2017). Digital Humanities. 15.
http://scholarship.shu.edu/dh/15