Information Sharing Between Partners in a Supply Chain
Knowledge and information are widely recognized as a potential competitive advantage in supply chain management. Several studies have shown that cooperation and information sharing can increase benefits, reduce cost, or both. On the other hand, firms may experience a negative reverse-impact, when a receiving partner uses the transferred information to manage its supply chain, resulting in an outcome that hurts the sharing partner. In general, every firm attempts to maintain the competitiveness of a monopoly, while at the same time tries to gain the additional benefit of interorganization cooperation. To balance these risks and benefits, firms need quantitative tools to assist in making decisions regarding information sharing. Such tools would be most valuable if they determine how much and what information should be shared as well as when, with whom, and under what conditions. This research explores these issues through a methodology based on game theory.
Agri-Food Supply Chain Management
Agri-food supply chains widely range from food safety and quality assurance to logistics and business modeling. In modern food retail and food service industries, safe and nutritional food in excellent quality with just-in-time delivery, is expected by customers, especially in developed countries. Developing countries such as Thailand, as food suppliers, have sought opportunities in cross border trade, to developed countries. To expand markets, there are needs in product and process improvement, in both food quality assurance and value creation. However, other important considerations including agriculture sustainability, energy efficiency, and welfare of workforce, should be considered together with cost reduction and profit maximization. This research studies assessment and effectiveness of current configurations and investigates balance and sustainable improvement of food supply chains in developing countries. This research is conducted and validated based on supply chain analysis, optimization, and simulation models.