Conditions When Market Share Models Are Useful for Forecasting: Further Empirical Results

The increased availability of data and access to computers has meant that econometric methods are readily available to model and forecast market share. However, controversy exists over their usefulness. For example R. Brodie and C.A. de Kluyver's (International Journal of Forecasting, 1987, 3,...

Full description

Saved in:
Bibliographic Details
Main Authors: Bonfrer, Andre, Brodie, R.J.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 1994
Subjects:
Online Access:https://ink.library.smu.edu.sg/lkcsb_research/2299
https://doi.org/10.1016/0169-2070(94)90007-8
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.lkcsb_research-3298
record_format dspace
spelling sg-smu-ink.lkcsb_research-32982010-09-23T12:30:04Z Conditions When Market Share Models Are Useful for Forecasting: Further Empirical Results Bonfrer, Andre Brodie, R.J. The increased availability of data and access to computers has meant that econometric methods are readily available to model and forecast market share. However, controversy exists over their usefulness. For example R. Brodie and C.A. de Kluyver's (International Journal of Forecasting, 1987, 3, 423–437) review of empirical studies revealed that the predictive accuracy of causal market share models was not consistently better than that of a naive model. In contrast, V. Kumar and T.B. Heath (International Journal of Forecasting, 1990, 6, 163–174) found that causal models consistently outperformed the naive model when using aggregated weekly scanner data which allowed for more observations. This paper reports the results of a replication and extension study which confirms Kumar and Heath's findings. However, the increased accuracy from using the causal model is diminished considerably when the more realistic situation of forecasting competitive action is included. The paper concludes by outlining a research agenda aimed at further clarifying the conditions when market share models are useful for forecasting. 1994-01-01T08:00:00Z text https://ink.library.smu.edu.sg/lkcsb_research/2299 info:doi/10.1016/0169-2070(94)90007-8 https://doi.org/10.1016/0169-2070(94)90007-8 Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Business
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Business
spellingShingle Business
Bonfrer, Andre
Brodie, R.J.
Conditions When Market Share Models Are Useful for Forecasting: Further Empirical Results
description The increased availability of data and access to computers has meant that econometric methods are readily available to model and forecast market share. However, controversy exists over their usefulness. For example R. Brodie and C.A. de Kluyver's (International Journal of Forecasting, 1987, 3, 423–437) review of empirical studies revealed that the predictive accuracy of causal market share models was not consistently better than that of a naive model. In contrast, V. Kumar and T.B. Heath (International Journal of Forecasting, 1990, 6, 163–174) found that causal models consistently outperformed the naive model when using aggregated weekly scanner data which allowed for more observations. This paper reports the results of a replication and extension study which confirms Kumar and Heath's findings. However, the increased accuracy from using the causal model is diminished considerably when the more realistic situation of forecasting competitive action is included. The paper concludes by outlining a research agenda aimed at further clarifying the conditions when market share models are useful for forecasting.
format text
author Bonfrer, Andre
Brodie, R.J.
author_facet Bonfrer, Andre
Brodie, R.J.
author_sort Bonfrer, Andre
title Conditions When Market Share Models Are Useful for Forecasting: Further Empirical Results
title_short Conditions When Market Share Models Are Useful for Forecasting: Further Empirical Results
title_full Conditions When Market Share Models Are Useful for Forecasting: Further Empirical Results
title_fullStr Conditions When Market Share Models Are Useful for Forecasting: Further Empirical Results
title_full_unstemmed Conditions When Market Share Models Are Useful for Forecasting: Further Empirical Results
title_sort conditions when market share models are useful for forecasting: further empirical results
publisher Institutional Knowledge at Singapore Management University
publishDate 1994
url https://ink.library.smu.edu.sg/lkcsb_research/2299
https://doi.org/10.1016/0169-2070(94)90007-8
_version_ 1770570201562087424