Calculating market areas/local market shares using the probabilistic market area model by Huff
huff.shares(huffdataset, origins, locations, attrac, dist, gamma = 1, lambda = -2,
atype = "pow", dtype = "pow", gamma2 = NULL, lambda2 = NULL, check_df = TRUE)an interaction matrix which is a data.frame containing the origins, locations and the explanatory variables (attraction, transport costs)
the column in the interaction matrix huffdataset containing the origins (e.g. ZIP codes)
the column in the interaction matrix huffdataset containing the locations (e.g. store codes)
the column in the interaction matrix huffdataset containing the attraction variable (e.g. sales area)
the column in the interaction matrix huffdataset containing the transport costs (e.g. travelling time or street distance)
a single numeric value of \(\gamma\) for the exponential weighting of the attraction variable (default: 1)
a single numeric value of \(\lambda\) for the (exponential) weighting of distance (transport costs, default: -2)
Type of attraction weighting function: atype = "pow" (power function), atype = "exp" (exponential function) or atype = "logistic" (default: atype = "pow")
Type of distance weighting function: dtype = "pow" (power function), dtype = "exp" (exponential function) or dtype = "logistic" (default: dtype = "pow")
if atype = "logistic" a second \(\gamma\) parameter is needed
if dtype = "logistic" a second \(\lambda\) parameter is needed
logical argument that indicates if the given dataset is checked for correct input, only for internal use, should not be deselected (default: TRUE)
Returns the input interaction matrix including the calculated shares (p_ij) as data.frame.
This function computes the market shares from a given interaction matrix and given weighting parameters. The result matrix can be processed by the function shares.total() to calculate the total values (e.g. annual sales) and shares.
Huff, D. L. (1962): “Determination of Intra-Urban Retail Trade Areas”. Los Angeles : University of California.
Huff, D. L. (1963): “A Probabilistic Analysis of Shopping Center Trade Areas”. In: Land Economics, 39, 1, p. 81-90.
Huff, D. L. (1964): “Defining and Estimating a Trading Area”. In: Journal of Marketing, 28, 4, p. 34-38.
Loeffler, G. (1998): “Market areas - a methodological reflection on their boundaries”. In: GeoJournal, 45, 4, p. 265-272.
Wieland, T. (2015): “Nahversorgung im Kontext raumoekonomischer Entwicklungen im Lebensmitteleinzelhandel - Konzeption und Durchfuehrung einer GIS-gestuetzten Analyse der Strukturen des Lebensmitteleinzelhandels und der Nahversorgung in Freiburg im Breisgau”. Projektbericht. Goettingen : GOEDOC, Dokumenten- und Publikationsserver der Georg-August-Universitaet Goettingen. http://webdoc.sub.gwdg.de/pub/mon/2015/5-wieland.pdf
# NOT RUN {
data(Freiburg1)
data(Freiburg2)
# Loads the data
huff.shares (Freiburg1, "district", "store", "salesarea", "distance")
# Standard weighting (power function with gamma=1 and lambda=-2)
# }
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