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Modeling Dynamic Relations Among Marketing and Performance Metrics (Paperback)
Loot Price: R2,199
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Modeling Dynamic Relations Among Marketing and Performance Metrics (Paperback)
Series: Foundations and Trends (R) in Marketing
Expected to ship within 10 - 15 working days
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Marketing and performance data often include measures repeated over
time. Time-series models are uniquely suited to capture the time
dependence of both a criterion variable and predictor variables,
and how they relate to each other over time. The objective of this
monograph is to give you a foundation in these models and to enable
you to apply them to your own research domain of interest. To this
end, the author discusses both the underlying perspectives and
differences between alternative models, and the practical issues
with testing, model choice, model estimation and interpretation
common in empirical research. This combination of marketing
phenomena and modeling philosophy sets this work apart from
previous treatments on the broader topic of econometics and time
series analysis in marketing. Time series models on marketing and
performance metrics come in different forms, and we distinguish
between 'traditional' time series models and the 'modern' time
series models. Modeling Dynamic Relations Among Marketing and
Performance Metrics first details the analysis steps,
interpretation and marketing insights from traditional time series
models. Starting with the univariate treatment of each separate
marketing time series in evolution/stationarity tests and ARIMA
models. Next, the author considers the over-time relation of
multivariate time series in transfer functions and intervention
analysis. The monograph then turns to multi-equation models, which
are the core workhorses of modern dynamic econometric and time
series models of the dynamic relations among marketing and
performance metrics. The concluding section discusses policy
analysis based on modern time series models and connect them to
other time series developments.
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