Measurement Issues in Time-Series Research: Reliability and Validity Assessment in Modeling the Macroeconomic Effects of Advertising
Опубликовано на портале: 29-09-2003
Journal of Marketing Research (JMR).
1984.
Vol. 21.
No. 1.
P. 12-20.
Тематический раздел:
Methods for the analysis of time series have become widely known and are now applied
regularly by marketers and other social scientists. Time-series analysis has proved
useful in such areas as forecasting (e.g., Kapoor, Madhok, and Wu 1981; Moriarty
and Adams 1979), assessing the relationship between advertising and sales (e.g.,
Aaker, Carman, and Jacobson 1982; Jagpal and Hui 1980), examining market responses
to specified interventions (e.g., Franke and Didow 1981; Wichern and Jones 1977),
and testing hypothesized concomitancies in time-series designs (e.g., Hanssens 1980).
In contrast to cross-sectional research, time-series designs generally challenge
the researcher's ability to discover and analyze multiple-item, multiple-method data
required for reliability and validity assessment. Currently archived time-series
data generally include at best single-item measures infrequently available for a
restricted period of time. Increased attention to measurement issues in time-series
research should result in renewed emphasis on the design, measurement, and archiving
of multiple "focal local indicators" (Campbell 1976) of marketing phenomena. It also
should contribute to further research in the limitations of currently available time-series
statistical models and causality tests and to the development of promising alternative
procedures.
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