TY  - JOUR
AB  - The marriage of new scanner‐type data sources and new computing and analysis methods is allowing a new approach to the development and use of models for decision support and product line management. Data‐driven modeling describes a process of model‐building wherein models are created that fit the dynamics of the data rather than assuming a priori relationships among brands and their marketing mix elements. Based on a combination of time‐series and econometric modeling methods, these models can significantly improve a modeler’s ability to capture marketplace structure and dynamics. Although more complex than their predecessors, the capabilities of these new data‐driven decision support models make them potentially very powerful tools, improving intuition and managerial understanding while suggesting improved decision alternatives. Develops such a model using detailed multiproduct retail data and demonstrates its capabilities.
VL  - 6
IS  - 2
SN  - 1061-0421
DO  - 10.1108/10610429710175664
UR  - https://doi.org/10.1108/10610429710175664
AU  - D’Souza Giles
AU  - Allaway Arthur
PY  - 1997
Y1  - 1997/01/01
TI  - A data‐driven modeling approach to product level decision support
T2  - Journal of Product & Brand Management
PB  - MCB UP Ltd
SP  - 130
EP  - 142
Y2  - 2024/04/19
ER  -