Asymmetric advertising impact

Julien Schmitt; Ganaël Bascoul; Shuba Srinivasan

Asymmetric advertising impact

Julien Schmitt, Ganaël Bascoul, Shuba Srinivasan

Marketing & Strategy

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Companies under pressure from stakeholders to meet profit expectations are often tempted to cut advertising expenses, particularly in times of economic difficulties. However, firms may not fully grasp the actual impact of such drastic cuts. Indeed, the general assumption is that advertising effects are symmetric: the numerical sales impact of budget increase or decrease would be the same in absolute value. Our paper addresses this gap by developing a new model based on multivariate time-series analysis (VAR models) to capture these asymmetric dynamic
relationships. Our results show that advertising models are improved by allowing the capture of these asymmetric patterns.

Original language	English
Title of host publication	Proceedings of the 39th European Marketing Academy Conference (EMAC)
Publication status	Published - 2010
Event	39th European Marketing Academy Conference (EMAC) - Copenhagen, Denmark Duration: 1 Jun 2010 → 4 Jun 2010

Conference

Conference	39th European Marketing Academy Conference (EMAC)
Country/Territory	Denmark
City	Copenhagen
Period	1/06/10 → 4/06/10

Bibliographical note

CD ROM

Keywords

advertising
asymmetry
time-series
Vector Auto-Regressive models

Access to Document

Asymmetric Advertising ResponseAccepted author manuscript, 66.3 KB

Cite this

@inproceedings{9886e0369a89443b97ae48e5e2311407,

title = "Asymmetric advertising impact",

abstract = "Companies under pressure from stakeholders to meet profit expectations are often tempted to cut advertising expenses, particularly in times of economic difficulties. However, firms may not fully grasp the actual impact of such drastic cuts. Indeed, the general assumption is that advertising effects are symmetric: the numerical sales impact of budget increase or decrease would be the same in absolute value. Our paper addresses this gap by developing a new model based on multivariate time-series analysis (VAR models) to capture these asymmetric dynamicrelationships. Our results show that advertising models are improved by allowing the capture of these asymmetric patterns.",

keywords = "advertising, asymmetry, time-series, Vector Auto-Regressive models",

author = "Julien Schmitt and Gana{\"e}l Bascoul and Shuba Srinivasan",

note = "CD ROM; 39th European Marketing Academy Conference (EMAC) ; Conference date: 01-06-2010 Through 04-06-2010",

year = "2010",

language = "English",

booktitle = "Proceedings of the 39th European Marketing Academy Conference (EMAC)",

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TY - GEN

T1 - Asymmetric advertising impact

AU - Schmitt, Julien

AU - Bascoul, Ganaël

AU - Srinivasan, Shuba

N1 - CD ROM

PY - 2010

Y1 - 2010

N2 - Companies under pressure from stakeholders to meet profit expectations are often tempted to cut advertising expenses, particularly in times of economic difficulties. However, firms may not fully grasp the actual impact of such drastic cuts. Indeed, the general assumption is that advertising effects are symmetric: the numerical sales impact of budget increase or decrease would be the same in absolute value. Our paper addresses this gap by developing a new model based on multivariate time-series analysis (VAR models) to capture these asymmetric dynamicrelationships. Our results show that advertising models are improved by allowing the capture of these asymmetric patterns.

AB - Companies under pressure from stakeholders to meet profit expectations are often tempted to cut advertising expenses, particularly in times of economic difficulties. However, firms may not fully grasp the actual impact of such drastic cuts. Indeed, the general assumption is that advertising effects are symmetric: the numerical sales impact of budget increase or decrease would be the same in absolute value. Our paper addresses this gap by developing a new model based on multivariate time-series analysis (VAR models) to capture these asymmetric dynamicrelationships. Our results show that advertising models are improved by allowing the capture of these asymmetric patterns.

KW - advertising

KW - asymmetry

KW - time-series

KW - Vector Auto-Regressive models

M3 - Conference publication

BT - Proceedings of the 39th European Marketing Academy Conference (EMAC)

T2 - 39th European Marketing Academy Conference (EMAC)

Y2 - 1 June 2010 through 4 June 2010

ER -

Asymmetric advertising impact

Abstract

Conference

Bibliographical note

Keywords

Access to Document

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Cite this