Demand modeling and forecasting is important for inventory management, retail assortment and revenue management applications. Current practice focuses on univariate demand forecasting, where models are built separately for each product. However, in many industries there is empirical evidence of correlated product demand. In addition, demand is usually observed in several periods during a sellin...

We analyze volume flexibility — the ability to produce above/below the installed capacity for a product — under endogenous pricing in a two-product setting. We discover that the value of volume flexibility is a function of demand correlation between products, an outcome which cannot be explained by classical risk-pooling arguments. Furthermore, while the value of product flexibility always decr...

Supply chain demand prediction plays a very important role for enterprises to realize sales and markets management target effectively, especially for fresh agricultural product enterprises. A new model for supply chain demand prediction for fresh agricultural product enterprises is presented based on improved BP neural network. First the advantages and disadvantages of BP neural network algorit...

We develop a theoretical model about how organizations cope with the bullwhip effect created by consumer demand uncertainty through product modularity and information sharing across the supply chain. Unpredictability of consumer demand is likely to accentuate inventory flows in the supply chain. Information sharing and product modularity can be used by organizations to mediate the impact of unc...

The hallmarks of today’s business environment are volatile demand, shorter product life cycles, and increasing global competition. Advances in information technology allow more and more information to be shared across entities so that the activities can be better coordinated throughout the entire supply chain. For different products and under different demand patterns, sharing information may h...

This paper provides evidence that a firm’s stock price movements affect its customer demand. I develop a model in which customers learn about a firm’s product quality partially from its stock price. This learning induces feedback from the price to customer demand. Furthermore, the firm manager adjusts product launch decisions in anticipation of these demand shifts. Consistent with the model’s i...

To expand sales, many manufacturers try to develop and sell product lines. Frequently, however, the operations of distributing a product line creates tension between manufacturers and retailers as they do not necessarily agree on which product versions included in the product line should be sold to consumers. To mitigate this tension, previous literature has shown that if a manufacturer (he) wa...

An optimisation-based control framework that simultaneously determines the optimal inventory and product pricing policies is developed for multi-product, multi-echelon supply chain networks. The optimisation problem aims at adjusting the available manufacturing resources, product distribution, inventories and prices for the entire supply chain network to satisfy demand while maximising network ...

The present study implements a generic methodology for describing and analyzing demand supply networks, that is, networks from a company’s suppliers to its customers. There can be many possible demand supply networks with different logistics costs for a product. Therefore, we introduce a Petri Net-based formalism, and a reachability analysis based algorithm that finds the optimum demand supply ...