Academic lectures:A Unified Framework for Large-Scale Supply Chain Network design
发布时间: 2014-01-07 访问次数: 28

Report Title: A Unified Framework for Large-Scale Supply Chain Network design
Reporter(Institution): Prof. JENNIFER S. SHANG(University of Pittsburgh, USA)
Time:,18th December, 2013
Location: B-201, Building of Economics & Management, Jiulonghu Campus
Abstract: Supply chain network design affects a firm’s cost and customer satisfaction, two significant factors which drive profitability and business success. In this research, we propose a distribution network that focuses on total transportation cost minimization and customer service improvement. Specifically, we address four supply chain management issues: (i) determine the optimal number of distribution centers (DCs) the case firm needs to employ, (2) identify where the company should locate these DCs, (3) assign each retailer to a suitable DC, and (4) minimize the total transportation costs and reach the target service level.
Traditional distribution network models aim to minimize distribution costs by using a few predefined alternative locations. Unlike traditional models, in this research we know neither the number of DCs needed nor the candidate locations. The entire U.S. map provides a near-infinite number of potential warehouse locations for us to explore. By incorporating key information into the distribution system (e.g. zip codes, fuel price, and TL/LTL freight structures, customer locations and demands) and by converting mileage to carrier time in transit, we are able to comprehensively examine and compare all cities in the United States.
After solving the optimization model, we conduct a computational study and perform sensitivity analysis to determine the impact of changes in system parameters on the optimality of the model. The proposed supply chain network has substantially reduced the expenditure of the SC department and enhanced service levels through continuous supply and reduced stockouts. In conclusion, a good distribution system can enhance the effectiveness and efficiency of operations and marketing efforts.
Brief introduction of Reporter: Jennifer Shang is a professor of Supply Chain Management and Area Director of Business Analytics and Operations at the Joseph M. Katz Graduate School of Business, University of Pittsburgh. She received her PhD in operations management from the University of Texas at Austin; MBA from University of Iowa; and BBA from National Taiwan University.
Professor Shang’s current research emphasizes six areas: (1) The planning, scheduling and control of systems in supply chain and service organizations. She develops theoretical and heuristic approaches to improve the productivity and quality of business decision and process and to address corporate social responsibility; (2) Pricing and Revenue Management. She works on pricing, product bundling, e-commerce, and online market structure; (3) Business Analytics. She explores large data sizes and noise, and predicts rare events; (4) Healthcare management. She addresses inefficiencies and excessive cost issues in the US healthcare system. She also examines hospital overcrowding and develops coordination mechanisms for various departments within the hospital. (5) Multi-criteria decision making–¾an inter-discipline focus on operations, marketing, finance and MIS interactions. She applies Data Envelopment Analysis (DEA) technique to measure the relative efficiency of operating units with similar goals and objectives. Analytic Network Process (ANP) and other Multi-Criteria Decision Making (MCDM) tools are employed to make decisions under complicated business environment; (6) Design and evaluate integrated business systems. Given the importance of technology, Dr. Shang emphasizes the innovative use of information technology in the value chain management.  Of special interest are the manufacturing and service operations, Enterprise Resource Planning (ERP), and the e-business management.
Dr. Shang has published more than 50 papers in top journals such as Management Science, Marketing Science, Information Systems Research, Journal of Marketing, and European Journal of Operational Research, as well as a management science book in China, entitled “Management Science: A Spreadsheet Modeling Approach”.