ijmatrix.shares {MCI}

Market shares in interaction matrix

Description

Calculating market shares in an interaction matrix based on the observations of the regarded variable.

Usage

ijmatrix.shares(rawmatrix, submarkets, suppliers, observations, 
varname_total = "freq_i_total", varname_shares = "p_ij_obs")

Arguments

rawmatrix

a data.frame containing the submarkets, suppliers and the observed data

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)

observations

the column with the regarded variable (e.g. frequencies, expenditures, turnovers)

varname_total

character value, name of the variable for the total absolute values of the i submarkets in the output (default: varname_total = "freq_i_total")

varname_shares

character value, name of the variable for the market shares p_{ij} in the output (default: varname_shares = "p_ij_obs")

Details

This function calculates the market shares of every j in every i (p_{ij}) based on an existing interaction matrix.

Value

The input interaction matrix which is a data.frame with a new column 'p_ij_obs' (or another stated name in the argument varname_shares) or, if used after ijmatrix.create, an update of the columns 'freq_i_total' and 'p_ij_obs' (or different stated names in the arguments varname_total and/or varname_shares).

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

Examples

data(grocery1)
# Loads the data

mymcidata <- ijmatrix.create (grocery1, "plz_submarket", "store_code")
# Creates an interaction matrix with market shares based on the frequencies 
# of visited grocery stores and saves results directly in a new dataset
mymcidata$freq_ij_corr <- var.correct(mymcidata$freq_ij_abs, 1)
# Corrects the frequency variable (no zero or negative values allowed)
mymcidata_shares <- ijmatrix.shares(mymcidata, "plz_submarket", "store_code", "freq_ij_corr")
# Calculates market shares based on the corrected frequencies
# and saves the results as a new dataset