decisionMatrix: Creates the decision matrix

In avilesd/productConfig: Tools to analyze behavioral patterns from Product Configurators

Description

The decision matrix is the basic object for analyzing data from product configurators (pC). The decision matrix is basically a representation of the interaction of one user with a product configurator through each step. Each columns stands for one attribute of the pC, i.e. for one specific product setting. Each row represents different configurations of a product. The rounds vary between users, since they are generated each time the user interacts with the pC. See Details for more info.

Usage

decisionMatrix(dataset, userid = NULL, attr = NULL, rounds = NULL,
  cost_ids = NULL)

Arguments

dataset	a data.frame with the user generated data from a product configurator. See Details of decisionMatrix for more information about which data should included in this argument.
userid	an integer vector indicating for which user the output of this function should be calculated. This functions is vectorised in this argument, i.e. you may enter more userIDs simultaneously.
attr	attribute IDs, vector of integer numbers corresponding to the attributes (columns) you desire to use.
rounds	integer vector, text option or a list of integer vectors. Which steps of the configuration process should be shown? Defaults are first and last step. Text options are all, first, last. Alternatively, a vector of arbitrarily chosen rounds can be entered as well.
cost_ids	argument used to convert selected cost attributes into benefit attributes. Integer vector. Cost type attributes have the characteristic, that a lower value means the user is better off than with a higher value. E.g. price is often considered a cost type attribute. Should be equal to attr input or a subset of it.

Details

dataset We assume the input data.frame has following columns usid = User IDs, round = integers indicating which round the user is in (0-index works best for 'round'), atid = integer column for referring the attribute ID (1 indexed), selected = numeric value of the attribute for a specific, given round, selectable = amount of options the user can chose at a given round, with the current configuration. This is a necessary parameter.

userid is a necessary parameter, without it you'll get a warning. Default is NULL.

attr Default calculates with all attributes. Attributes are automatically read from provided table, it is important you always provide the complete dataset so that the package functions properly. Moreover the attributes will not be sorted. Output columns are returned in the ordered they were inputed.

rounds If you need to compute different rounds for each user you enter, this argument accepts a list of integer vectors indicating which rounds should be used for each user. The function does not read names, it works in the order the list was given.

cost_ids If attr and cost_ids differ, the functions will first compute the entire decision matrix using the cost_ids and only in the end will it 'subset' the result to the desired attr.

Default assumes all your attributes are of benefit type, that is a higher value in the attribute means the user is better of than with a lower value. If one or more of the attributes in your data is of cost type, e.g. price, so that lower is better then you should identify this attributes as such, providing their ID, they'll be converted to benefit type (higher amount is better).

General: Through the matrix you can observe the value of each attribute at any given moment or round. The number of columns of the matrix will always be the same for all users. The number of rows depends on how much clicks or rounds the user made in the product configurator. At the very least, you will always get 'round 0' meaning the initial, default configuration and 'round 1' the last or final configuration, this is assuming the user just clicked once or not at all.

Value

A decision matrix for selected users with rows.length = length(rounds) and column.length = length(attr). Colnames = attrIDs and rownames = chosen rounds.

References

ProductConfig Github page: https://github.com/avilesd/productConfig

Examples

#Not Runnable yet
decisionMatrix(camera2_config_data, 11) # Necessary arguments dataset and userid
decisionMatrix(my_data, userid = 11:15, attr = c(1,3,5))
decisionMatrix(another_data, userid = c(80,90,100,110), rounds = c(1,2,3,7,8,9))

decisionMatrix(data2, 2:200, rounds = "all")
decisionMatrix(data2, 120, rounds = "first", cost_ids = 1)
decisionMatrix(data1, userid = 5, attr = c(1,4), rounds = "all", cost_ids="c(1,2)") #All possible parameters are in use here.

avilesd/productConfig documentation built on May 11, 2019, 4:08 p.m.