ijmatrix.crosstab: Converting interaction matrix with market shares to...
In MCI: Multiplicative Competitive Interaction (MCI) Model

Description Usage Arguments Details Value Author(s) References See Also Examples

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

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

`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

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.

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

Thomas Wieland

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.

ijmatrix.create, ijmatrix.shares

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