ijmatrix.crosstab {MCI}R Documentation

Converting interaction matrix with market shares to crosstable

Description

This function converts a given interaction matrix with (local) market shares to a crosstable where the rows are the submarkets and the columns contain the market shares

Usage

ijmatrix.crosstab(mcidataset, submarkets, suppliers, shares)

Arguments

mcidataset

The interaction matrix containing the submarkets/origins, suppliers/locations and local market shares

submarkets

the column in the dataset containing the submarkets (e.g. ZIP codes)

suppliers

the column in the dataset containing the suppliers (e.g. store codes)

shares

the column in the dataset containing the local market shares

Details

In many cases the results of a market area analysis shall be visualized in a map, e.g. by pie charts or contour lines which belongs to the standard map types in Geographical Information Systems (GIS). An interaction matrix can not be processed directly in a GIS due to its linear character. This function converts an interaction matrix into a special kind of crosstable where the rows contain the origins i and the local market shares p_{ij} are represented by the columns. The submarkets/origins ID (rows) can be joined directly to the geodata (e.g. point shapefile) while the columns can be used for visualization.

Value

A data.frame containing i rows and j+1 columns (suppliers/locations and one column containing the submarkets/origins).

Author(s)

Thomas Wieland

References

Cooper, L. G./Nakanishi, M. (2010): “Market-Share Analysis: Evaluating competitive marketing effectiveness”. Boston, Dordrecht, London : Kluwer (first published 1988). E-book version from 2010: http://www.anderson.ucla.edu/faculty/lee.cooper/MCI_Book/BOOKI2010.pdf

Huff, D. L./McCallum, D. (2008): “Calibrating the Huff Model Using ArcGIS Business Analyst”. ESRI White Paper, September 2008. https://www.esri.com/library/whitepapers/pdfs/calibrating-huff-model.pdf

Wieland, T. (2015): “Raeumliches Einkaufsverhalten und Standortpolitik im Einzelhandel unter Beruecksichtigung von Agglomerationseffekten. Theoretische Erklaerungsansaetze, modellanalytische Zugaenge und eine empirisch-oekonometrische Marktgebietsanalyse anhand eines Fallbeispiels aus dem laendlichen Raum Ostwestfalens/Suedniedersachsens”. Geographische Handelsforschung, 23. 289 pages. Mannheim : MetaGIS.

See Also

ijmatrix.create, ijmatrix.shares

Examples

data(grocery2)
# Loads the data

grocery2_cross <- ijmatrix.crosstab(grocery2, "plz_submarket", "store_code", "p_ij_obs")
# Converts the market shares in the grocery2 dataset to a crosstable

[Package MCI version 1.3.3 Index]