A state space model for exponential smoothing with group seasonality

We present an approach to improve forecast accuracy by simultaneously forecasting a group of products that exhibit similar seasonal demand patterns. Better seasonality estimates can be made by using information on all products in a group, and using these improved estimates when forecasting at the individual product level. This approach is called the group seasonal indices (GSI) approach, and is a generalization of the classical Holt-Winters procedure. This article describes an underlying state space model for this method and presents simulation results that show when it yields more accurate forecasts than Holt-Winters.Common seasonality; demand forecasting; exponential smoothing; Holt-Winters; state space model.

A value network development model and implications for innovation and production network management

In managing their value network, firms have to balance current and future value concerns and own and network partners' concerns. Firms generate immediate value through manufacturing and selling the current generation of products together with other firms in their production network. Firms generate future value by developing a new product generation with other firms and research institutes in their innovation network. Product innovation and production often take place simultaneously and recurrently. We take the discernible production and innovation activities to occur in co-evolving layers of the same network. We formulate a biplex value network development model that lays out the temporal pattern of production and innovation activities in the value network. We introduce terminology to pinpoint temporal interactions between the innovation and production activities. We study several exemplary complications in the cross-table of inter- and intragenerational interactions versus interactions within and across network layers

A value network development model and implications for innovation and production network management

In managing their value network, firms have to balance current and future value concerns and own and network partners' concerns. Firms generate immediate value through manufacturing and selling the current generation of products together with other firms in their production network. Firms generate future value by developing a new product generation with other firms and research institutes in their innovation network. Product innovation and production often take place simultaneously and recurrently. We take the discernible production and innovation activities to occur in co-evolving layers of the same network. We formulate a biplex value network development model that lays out the temporal pattern of production and innovation activities in the value network. We introduce terminology to pinpoint temporal interactions between the innovation and production activities. We study several exemplary complications in the cross-table of inter- and intragenerational interactions versus interactions within and across network layers

Dynamics and equilibria under incremental horizontal differentiation on the Salop circle

We study product differentiation on a Salop circle when firms relocate incrementally due to bounded rationality. We prove that, under common assumptions on demand, firms relocate only when two or more firms target the same niche. In any other case, there is no incentive for any firm to relocate incrementally. We prove that all distributions in which firms are sufficiently far apart in product space are unstable Nash equilibria. We prove, in particular, that the classical equidistant distribution is an unstable Nash equilibrium that cannot emerge from another distribution. However, we show that if each firm is engaged in head-on rivalry with one other competitor, the industry converges to an ’equidistantesque’ equilibrium of clusters of rivals