This paper proposes an approach that models and forecasts sales through a flexible parametric response function (multifunctional), allowing for differentiated behavioural assumptions of the response determinants to be specified, and uses neural network modelling as a re-specification tool for the response model in order to improve forecasting performance. An initial experiment on a sample of sales data demonstrates feasibility and gives comparative insights via alternative model specifications. Copyright © 2005 John Wiley & Sons, Ltd.
Demand forecasting is a crucial part of managing any supply chain network, since inaccurate forecast...
The most important indicator in business is the amount of sales. The magnitude of the level of sales...
Due to the strong competition that exists today, most manufacturing organizations are in a continuou...
Neural networks are a computing paradigm developed from the field of artificial intelligence and bra...
Neural networks are a computing paradigm developed from artificial intelligence and brain modelling’...
Artificial neural networks are now being extensively used in the area of marketing analysis as they ...
This study compares the performance of artificial neural networks and multiple linear regression as ...
Predicting business operations on the basis of previous events plays an important role in managing a...
Sales forecasting is an essential part of supply chain management. In retail business, accurate sale...
Econometric and predictive modeling techniques are two popular forecasting techniques. Both ofthese ...
Abstract. The paper focuses on the retail turnover prediction with artificial neural networks. The a...
So far studies estimating sales response functions on the basis of store-specific data either consid...
In this paper the authors proposed different Multilayer Perceptron Models (MLP) of artificial neural...
In this paper the authors proposed different Multilayer Perceptron Models (MLP) of artificial neural...
This paper develops an artificial neural network (ANN) model to forecast the optimum demand as a fun...
Demand forecasting is a crucial part of managing any supply chain network, since inaccurate forecast...
The most important indicator in business is the amount of sales. The magnitude of the level of sales...
Due to the strong competition that exists today, most manufacturing organizations are in a continuou...
Neural networks are a computing paradigm developed from the field of artificial intelligence and bra...
Neural networks are a computing paradigm developed from artificial intelligence and brain modelling’...
Artificial neural networks are now being extensively used in the area of marketing analysis as they ...
This study compares the performance of artificial neural networks and multiple linear regression as ...
Predicting business operations on the basis of previous events plays an important role in managing a...
Sales forecasting is an essential part of supply chain management. In retail business, accurate sale...
Econometric and predictive modeling techniques are two popular forecasting techniques. Both ofthese ...
Abstract. The paper focuses on the retail turnover prediction with artificial neural networks. The a...
So far studies estimating sales response functions on the basis of store-specific data either consid...
In this paper the authors proposed different Multilayer Perceptron Models (MLP) of artificial neural...
In this paper the authors proposed different Multilayer Perceptron Models (MLP) of artificial neural...
This paper develops an artificial neural network (ANN) model to forecast the optimum demand as a fun...
Demand forecasting is a crucial part of managing any supply chain network, since inaccurate forecast...
The most important indicator in business is the amount of sales. The magnitude of the level of sales...
Due to the strong competition that exists today, most manufacturing organizations are in a continuou...