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...

Judgmental adjustments to statistically generated forecasts have become a standard practice in demand forecasting, especially at a stock keeping units level. However, due to the subjective nature of judgmental interventions this approach cannot guarantee optimal use of available information and...

Demand forecasting is a crucial aspect of the planning process in supply-chain companies. The most common approach to forecasting demand in these companies involves the use of a simple univariate statistical method to produce a forecast and the subsequent judgmental adjustment of this by the...

A study of short-term forecasting in UK supply chain companies has revealed that some companies make limited use of the facilities that are available in the statistical forecasting software that they have purchased. Despite their costs, the software packages are often used for little more than...

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...

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...

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...

Forecasting at the Stock Keeping Unit (SKU) disaggregate level in order to support operations management has proved a very difficult task. The levels of accuracy achieved have major consequences for companies at all levels in the supply chain; errors at each stage are amplified resulting in poor...

An avalanche of articles has described the testing of a time series for the presence of unit roots. However, economic model builders have disagreed on the value of testing and how best to operationalise the tests. Sometimes the characterization of the series is an end in itself. More often, unit...

The comparative accuracy of feedforward neural networks (NN) when applied to time series forecasting problems remains uncertain. This is because most studies suffer from either of two defects - they choose the NN from a wide range of alternatives in order to present the forecast accuracy results...