MCI (version 1.3.3)

shopping2: Distance matrix for the point-of-sale survey in Karlsruhe

Description

The dataset contains a distance matrix (OD matrix: Origins-Destinations matrix) including the street distance and the travel time from the customer origins to the shopping destinations, both stored in the dataset shopping1.

Usage

data("shopping2")

Format

A data frame with 3723 observations on the following 5 variables.

from

a factor containing the customer origin (place of residence) as internal code

to

a factor containing the shopping destination

d_km

a numeric vector containing the street distance from the origins to the destinations in km

d_time

a numeric vector containing the driving time from the origins to the destinations in km

route

a factor containing the interaction/route code between origins and destinations (from-to)

See Also

shopping1, shopping3, shopping4

Examples

# NOT RUN {
# Market area segmentation based on the POS survey in shopping1 #

data(shopping1)
# The survey dataset
data(shopping2)
# Dataset with distances and travel times

shopping1_adj <- shopping1[(shopping1$weekday != 3) & (shopping1$holiday != 1) 
& (shopping1$survey != "pretest"),]
# Removing every case from tuesday, holidays and the ones belonging to the pretest

ijmatrix_POS <- ijmatrix.create(shopping1_adj, "resid_code", "POS", "POS_expen")
# Creates an interaction matrix based on the observed frequencies (automatically)
# and the POS expenditures (Variable "POS_expen" separately stated)

ijmatrix_POS_data <- merge(ijmatrix_POS, shopping2, by.x="interaction", by.y="route", 
all.x = TRUE)
# Adding the distances and travel times

ijmatrix_POS_data_segm_visit <- shares.segm(ijmatrix_POS_data, "resid_code", "POS",
"d_time", "freq_ij_abs", 0,10,20,30)
# Segmentation by travel time using the number of customers/visitors
# Parameters: interaction matrix (data frame), columns with origins and destinations,
# variable to divide in classes, absolute frequencies/expenditures, class segments

ijmatrix_POS_data_segm_exp <- shares.segm(ijmatrix_POS_data, "resid_code", "POS",
"d_time", "freq_ij_abs_POS_expen", 0,10,20,30)
# Segmentation by travel time using the POS expenditures
# }