dualValueMatrix.oneAttr: Returns a Value Matrix using two reference points (one...

Description Usage Arguments Details Value References Examples

Description

This function is a more basic function than dualValueMatrix. This function is based on the value function of the dual-reference point model (dual-rp) [1]. It first builds a desicion matrix for each user and then applys the drp-utility function over each value using smallerThanZero. The dual-rp value function first creates a gain-loss matrix based on the two reference points. It then outputs the value of each gain/loss based on the loss aversion (lambda) and the relative importance of the goal (delta).

Usage

1
2
3
dualValueMatrix.oneAttr(dataset, userid = NULL, attr = NULL,
  rounds = NULL, cost_ids = NULL, dual.refps = c(sq = NA, g = NA),
  lambda = 2.25, delta = 0.8, consumption_fun = NULL)

Arguments

dataset

data.frame with the user generated data from a product configurator. See decisionMatrix for specifications of the dataset.

userid

a vector of integers that gives the information of which users the matrix should be calculated. Vectorised.

attr

attributes ID, one integer corresponding to the attribute you desire to use; attr are assumed to be 1-indexed.

rounds

integer vector or text option. Which steps of the configuration process should be shown? Defaults are first and last step. Text options are all, first, last.

cost_ids

argument used to convert selected cost attributes into benefit attributes. Cost attribute means that weith a lower value, the user is better off than with a higher value (e.g. price). Default assumes all attributes are of benefit type (higher amount is better).

dual.refps

numeric vector - two numbers indicating the status-quo and the aspiration level(goal) for the given attributes. Status-quo should always be the first input. Contrary to dualValueMatrix, this function also allows for aspiration levels to be smaller than the status-quo (g < sq) [1].

lambda

numeric - parameter of loss aversion for the value function as given by [1]. Default value is 2.25 as in [2] and should be lambda > 1.

delta

numeric - expresses the relative importance of the aspiration level to other factors. Default is 0.8 and it should satisfy 0 < delta <1.

Details

This function does the same as dualValueMatrix but only for one attribute, for more details please see the mentioned function.

Note: When converting a cost attribute to a benefit attribute its two reference points change as well, enter the unconverted refps, the function transforms them automatically when it detects a cost_ids != NULL

Value

a list of value matrices with one attribute for each user.

References

[1] Golman, R., & Loewenstein, G. (2011). Explaining Nonconvex Preferences with Aspirational and Status Quo Reference Dependence. Mimeo, Carnegie Mellon University.

[2] Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and uncertainty, 5(4), 297-323.

Examples

1
2
3
4
5
6
7
dualValueMatrix.oneAttr(myData, 10, attr = 3, dual.refps = c(1, 3.5))
dualValueMatrix.oneAttr(myData, userid= 60, rounds= "all", attr = 1, dual.refps = c(1.5, 2.5)
dualValueMatrix.oneAttr(myData, 10, attr=4, dual.refps = c(0.17, -0.10), cost_ids = 4) # Note for cost_ids SQ > G

# Return an error, 1.Too many attributes or 2. none entered
dualValueMatrix.oneAttr(keyboard_data, 8:9 , attr = c(10,12,14,16), dual.refps = c(100, 150))
dualValueMatrix.oneAttr(data1, 2) # 2. No attribute entered

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