Business to Business (B2B) sales forecast can be described as a decision-making process, which is based on past data (internal and external), formalized rules, subjective judgment, and tacit organizational knowledge. Its consequences are measured in profit and loss. The research focus of this paper is aimed to narrow the gap between planned and realized performance, introducing a novel model ba...

A method for forecasting the number of parts shipments is proposed for build-to-order products using pre-sales estimate information as a leading indicator. Since the target number of parts shipments changes irregularly and over a short lifecycle, it is difficult to forecast with conventional methods. The method uses Kalman filter to correct for the noise associated with the leading indicator an...

In order to reduce their stock, to avoid ruptures and to direct their marketing policies, textile companies must improve their supply chain management. This organization requires forecasting systems adapted to the uncertain environment of the textile field. Taking into account also delivery constraints, textile distribution need mean-term forecasting (one season) in order to launch new producti...

one of the basic assumptions of management accounting illustrate that costschanges has a significance relationship with increasing and decreasing in the levelof activity, recently after being raised of sticky costs issue by anderson and hiscolleagues this assumption was discussed. it means increases in costs by increasingthe more activity level of reduction in costs is exchange for the reductio...

Demand forecasting is one of the important activities in a supply chain which provides all the supply chain planning processes with market information crucial for efficient supply chain management. Its performance is measured by forecasting error, which is defined using the difference between forecast and actual sales. In this paper, we classify the forecasting error types based on the cases th...

We present methods to characterize market conditions from historical data, and we describe how this knowledge can be used to make strategic and tactical sales decisions. The methods are based on learning dominant market conditions, such as over-supply or scarcity, from historical data using computational methods to represent the price density function. We show how to use this knowledge, togethe...

© 2000, Elsevier Science Inc., 1040-6190/00/$–see front matter 3 to ensure observance by loads of their obligations will reduce required transaction analysis to that of marginal spot market transactions, to the great benefit of system security. Finally, the network will be in a position to plan for rational reinforcement and expansion on the basis of forecast growth of load within its boundarie...