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Identifying time trends in advertising expenditure components : a simple regression approach on data for 17 European countries in 1994 to 2007
Košmelj, Katarina (Avtor), Žabkar, Vesna (Avtor)

URLURL - Predstavitvena datoteka, za dostop obiščite http://mrvar.fdv.uni-lj.si/pub/mz/mz6.1/kosmelj.pdf Povezava se odpre v novem oknu

Izvleček
The study analyzes the components of advertising spending for a group of European countries with stable total advertising spending over the period 1994-2007. Three components of advertising spending were considered: Electronic, Print, and Online. Our main objective was to study how the components were restructured within the period under study and to find clusters of similar countries. A specific distance for time series, which is expressed as a linear combination of a standard distance measure and the weights, was to be used. The standard distance used for compositional data is the Aitchison distance, however it was found unsuitable due to zero and near zero values in the Online component. As a simple alternative a linear regression model on the components was used, followed by standard cluster analysis on the regression estimates. Results enable a deeper insight into the level of each component and into the structural changes in components for clusters of examined countries.

Jezik:Angleški jezik
Ključne besede:Evropa, oglas, stroški, statistične metode, časovne vrste, analiza
Vrsta gradiva:Delo ni kategorizirano (r6)
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:EF - Ekonomska fakulteta
Leto izida:2009
Št. strani:str. 173-185
Številčenje:Vol. 6, no. 2
UDK:659.1
ISSN pri članku:1854-0023
COBISS.SI-ID:18718182 Povezava se odpre v novem oknu
Število ogledov:640
Število prenosov:183
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
 
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Gradivo je del revije

Naslov:Metodološki zvezki
Skrajšan naslov:Metodol. zv.
Založnik:Fakulteta za družbene vede
ISSN:1854-0023
COBISS.SI-ID:215795712 Povezava se odpre v novem oknu

Sekundarni jezik

Jezik:Neznan jezik
Ključne besede:Europe, advertisement, costs, statistical methods, time series, analysis

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