The paper shows that due to the features of SKU (stock-keeping unit) demand data wellknown error measures previously used to analyse the accuracy of adjustments are generally not advisable for the task. In particular, percentage errors are affected by outliers and biases arising from a large...

Forecasts of demand are crucial to drive supply chains and enterprise resource planning systems. Usually, well-known univariate methods that work automatically such as exponential smoothing are employed to accomplish such forecasts. The traditional Supply Chain relies on a decentralised system...

This paper proposes a methodology for examining the effect of demand uncertainty and forecast error on lot sizing methods, unit costs and customer service levels in MRP type manufacturing systems. A number of cost structures were considered which depend on the expected time between orders. A...

Successful ICT policy analyses and implementation rely on a sufficient knowledge of how and why consumers adopt new technologies. For instance, analysts of the digital divide may need to quantify the factors that are perceived to drive this ICT usage gap. This paper focuses on understanding the...

Aggregate models of innovation diffusion do not capitalise on valuable consumer adoption dynamics that emerge from consumer surveys. This is despite other modelling strategies which suggest that such dynamics may be very important to the process of diffusion. We present a segmental Gompertz...

There has been strong empirical evidence that demand variability increases as one moves up the supply chain (from the retailer to the raw materials supplier), a phenomenon called bullwhip effect. This paper examines the bullwhip effect and in particular one of its main causes, demand...