Using Market-Level Data to Understand Promotion Effects in a Nonlinear Model

Christen, Markus; Gupta, Kirti; Porter, Justin; Staelin, Richard; Wittink, Dick R.

doi:10.2307/3151895

Cited by 99 publications

(58 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…La incorporación de equipos escáner en los establecimientos minoristas, a partir de la dé-cada de los ochenta, ha permitido incrementar sustancialmente el número de investigaciones en este campo, así como la posibilidad de comprender mejor el comportamiento del consumidor que acude a dichos establecimientos (Christen et al 1997).…”

Section: Introductionunclassified

Untitled

2010

ADR

View full text Add to dashboard Cite

En esta investigación los autores analizan los diferentes tipos de promoción utilizados tanto por Marcas de Fabricante como por Marcas de Distribución y los efectos producidos en el largo plazo en las ventas en una y otra categoría. El análisis pone el foco en la actividad promocional realizada por las principales marcas de bebidas energéticas que operan en el mercado nacional. El estudio, realizado a partir de datos escáner a nivel de tienda en una serie histórica que abarca 7 años, contempla la casi totalidad de la historia de la categoría. En este sub-segmento concreto de bebidas se han producido crecimientos importantes en ventas en los últimos años, y las marcas puestas a punto por la distribución han logrado hacerse con más de la mitad de la cuota de mercado en los canales híper y súper, superando en volumen a la marca líder a partir del año 2004. Sin embargo el estudio muestra que el efecto en el largo plazo de las promociones en la categoría analizada es menos intenso en las Marcas de Distribución que en las Marcas de Fabricante, y que no todas las técnicas promocionales analizadas tienen el mismo efecto, siendo displays y folletos las que tienen un impacto mayor en las ventas.

show abstract

Section: Introductionunclassified

Untitled

2010

ADR

View full text Add to dashboard Cite

show abstract

“…jointly for all stores and chains. Christen et al (1997) demonstrate that there are substantial differences between the parameter estimates of a (nonlinear) model applied to linearly aggregated (summed) data and the corresponding estimates of the model applied to the original store data. The biases in the estimated effects from marketlevel data due to heterogeneity in the marketing activities across stores over which aggregation takes place can be very large.…”

Section: Evolutionary Model Buildingmentioning

confidence: 99%

“…This assumes homogeneous parameters across stores belonging to different chains because of confidentiality agreements between ACNielsen and cooperating retailers. Its use also reflects a belief that aggregation of data over stores would create systematic prob- SCAN*PRO-model with chain-specific parameters (Foekens/Leeflang/Wittink, 1994) SCAN*PRO-model specified at different levels of aggregation (Foekens/Leeflang/Wittink, 1994, Christen et al, 1997 Varying parameter SCAN*PRO model (Foekens/Leeflang/Wittink, 1999) lems. The appropriateness of this homogeneity assumption and aggregation issues was examined in Foekens /Leeflang/Wittink (1994) by estimating (1) and related expressions at: (i) the store level, (ii) the chain level, and (iii) the market level.…”

Section: Evolutionary Model Buildingmentioning

confidence: 99%

“…Multipliers are strongly biased upward in a nonlinear model applied to linearly aggregated (market-level) data; the magnitude of the bias depends upon the proportion of stores promoting the item (Christen et al (1997)). …”

Section: Findings: How Sales Promotions Workmentioning

confidence: 99%

“…• SCAN*PRO-model specified at different levels of aggregation (Foekens, Leeflang, Wittink, (1994), Christen et al, (1997)…”

Section: Evolutionary Model Buildingmentioning

confidence: 99%

See 2 more Smart Citations

How Promotions Work: SCAN*PRO-Based Evolutionary Model Building

Heerde

Leeflang

Wittink

2002

Schmalenbach Bus Rev

Self Cite

View full text Add to dashboard Cite

We provide a rationale for evolutionary model building. The basic idea is that to enhance user acceptance it is important that one begins with a relatively simple model. Simplicity is desired so that managers understand models. As a manager uses the model and builds up experience with this decision aid, she will realize its shortcomings. The model will then be expanded and will lead to the increase of complexity.Evolutionary model building also stimulates the generalization of marketing knowledge. We illustrate this by discussing different extensions of the SCAN*PRO model. The purpose of published model extensions is to increase the knowledge about "how promotions work" and to provide support for more complex decisions. We summarize the generated knowledge about how promotions work, based on this process. JEL-Classification: M31.

show abstract

Empirical analysis of competitive interaction in food product categories

Putsis

1999

Agribusiness

View full text Add to dashboard Cite

This article provides an overview of recent research on estimating competitive interaction in food product categories. In particular, the focus of this review is on research using scanner data conducted at the disaggregate (e.g., store, chain or local market) level, including empirical studies of vertical (i.e., within‐channel) conduct. Studies addressing the competitive interaction on price, as well as non‐price variables (e.g., in‐store display and feature advertising) are considered. The author first describes the methodologies available for measuring the competitive interaction between firms and then briefly summarizes recent empirical developments. Given the complexity of the interactions that take place in practice, it is argued that much of the richness of actual competitive behavior is lost in aggregate analysis. Competitive interaction is the result of a complex set of variables and influences—demand side factors, market and industry structure, firm “personality,” and category characteristics all interact in a complex fashion to determine strategic behavior of retailers and manufacturers. [Econ‐Lit citations: L110, L130, L660] © 1999 John Wiley & Sons, Inc.

show abstract

Using Market-Level Data to Understand Promotion Effects in a Nonlinear Model

Cited by 99 publications

References 0 publications

Untitled

Untitled

How Promotions Work: SCAN*PRO-Based Evolutionary Model Building

Empirical analysis of competitive interaction in food product categories

Contact Info

Product

Resources

About