Biography
Heng Chen is an Assistant Professor in Supply Chain Management in the College of Business at the University of Nebraska-Lincoln.
His primary research interest is in the application of stochastic methods and data analytics for efficient, sustainable, and equitable operations in the public sectors, specializing in applications such as transportation and agriculture. His approach to these problems considers multiple stakeholders, including those who are often underrepresented. His overarching objective is to address equity issues, particularly for small stakeholders, and to examine the influence of public policies and government interventions in these sectors. Additionally, He incorporates uncertainty and the learning effects resulting from such uncertainties into his research models. His work has been published in several journals, including Production and Operations Management and Transportation Science. He has won several awards, including a best dissertation award and an outstanding paper award.
Undergraduate Courses
Operations and Supply Chain Management (SCMA 331) - Analytical management techniques for: ascertaining demand for the organization's goods and services; justifying and acquiring the necessary resources; and planning and controlling the transformation of resources into goods and services. Application in both large and small organizations, private and public enterprise, service, and manufacturing organizations.
Global Sourcing and Distribution (SCMA 439) - Sourcing strategies, concepts and tools in the context of integrated supply chains. Specific issues include make or buy decisions, supplier evaluation and selection, total cost of ownership, contracts and legal terms, negotiation, and purchasing ethics. Discussion of supply chains in the context of international trade. Purchasing options, to include benefits and risks in outsourcing. Information technology for control and coordination in international supply chains.
Teaching Interests
- Supply Chain Management
- Transportation and Logistics
- Stochastic models