The goal of this research project is to advance practical knowledge of designing supply contracts under emerging trends in industry because such knowledge is crucial for optimizing supply chain performance in the real world. Mass retailers are powerful "buyers" that manage buyer-driven channels with multiple - domestic or international - supply options. Other examples of powerful buyers include the government and the military. Although market power has been shifting to the buyer in various markets, only a limited amount of academic research has analyzed this shift in the power structure. Traditionally, the supplier (e.g., manufacturer) has been more powerful, and, hence, the previous research emphasizes supplier-driven contracts in which the supplier acts as the channel leader. Taking into account the recent trend in power shifting explicitly, this research attempts to provide a comparison of optimal supply contract designs under different types of uncertainty due to volatile nature of market conditions.

The outcomes are expected to provide insights about the individual and joint impacts of power structure and information asymmetry on supply chain performance, the value of information for contract design under different supply chain channel structures, and the impact of supply uncertainty on contract design under different supply chain channel structures. By providing insightful results that address the efficiency of buyer-driven channels, if successful, this research is expected to i) improve the efficiency of decision making and contract negotiations, ii) impact the way contracts are developed both in buyer- and supplier-driven channels with an emphasis on supply chain performance, and iii) lead to quantifiable benefits for partnering companies in terms of cost efficiency in contractual settings, ultimately benefiting customers, shareholders, and the economy. An accompanying goal is to contribute to the education of a new generation of supply chain engineers through the PI's research, education, and industry collaboration activities focusing on contemporary trends in industrial engineering and supply chain management.

Project Start
Project End
Budget Start
2011-09-01
Budget End
2014-08-31
Support Year
Fiscal Year
2011
Total Cost
$280,000
Indirect Cost
Name
Texas Engineering Experiment Station
Department
Type
DUNS #
City
College Station
State
TX
Country
United States
Zip Code
77845