Optimal customization of supply chains in dynamic environments

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Success in the 21st century requires harnessing supply chains, rather than individual firms, for sustainable competitive advantage. One of the primary problems of managing supply chains in the present market scenario is the constantly evolving business environment. On the other hand, advances in technology now enable managers to accurately track these changes, which can then be used for more focused decision-making.  In this research program our aim is to develop and analyze models that can improve the dynamic decision-making capability of Canadian firms and prepare them to compete effectively in the global marketplace. Specifically, we would like to develop integrated operations-marketing models that will help us understand how supply chains should: i) customize their decisions for diverse customer niches, ii) adapt their decisions dynamically (and in an agile fashion) over time, and iii) align the incentives of the chain partners, in order to maximize their profits. Our research program will comprise of four different models characterized by distinct product/market features to address a wide variety of business environments. In the first phase of the research program we would like to examine the optimal dynamic pricing and inventory control policy for innovative make-to-stock products (e.g., laptops, fashion garments), keeping in mind that the market characteristics (e.g., demand variability, price-elasticity) for these products change rapidly during their lifecycles. In the second phase we plan on exploring the optimal dynamic decision policy for durable products (e.g., appliances, automobiles). We are most interested in understanding how firms select an optimal dynamic pricing policy for such products, and how operational choices might affect the optimal policy. In the third phase we will study the optimal time-and-price based product differentiation for MTO/service segment (e.g., courier, delivery services) in a competitive framework, and address the related capacity management issues. The last phase of this research program will develop models to investigate the optimal incentive alignment policy for supply chain members in dynamic, decentralized environments.