fowler_2026_pev_charger_purchase

12,304 rated or chosen profiles from 769 respondents, in up to 8 tasks of 2 profiles varying on 6 attributes.

One of 2 tables from the same source; this one is the purchase table. The others are listed under Related tables.

About this table

DescriptionDiscrete choice experiment with 769 Belgian drivers choosing between two hypothetical home electric-vehicle chargers that differ in smart-charging control, solar charging, two-way charging, peak-use management, annual bill reward and price, or keeping their current charger. 8 tasks each, choice with an opt-out.
ReferenceFowler, B., van Passel, S., & Lizin, S. (2026). From purchase to participation: Sequential choice experiments on PEV smart-charging [Manuscript submitted to Utilities Policy; replication data and code]. Mendeley Data.
LicenceCC BY 4.0
Source datahttps://doi.org/10.17632/pgrgnctxjf

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents769
Rows (one per respondent, task and profile)12,304
Tasks per respondent (most)8
Profiles per task2
Attributes6
Tasks with no profile chosen1,405

Design

Topicclimate energy environment
A profile representsproduct service
CountryBE
Language shownnl, fr, en
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choicePlease indicate your preference for a new electric car charger. You can choose between two hypothetical private residential chargers, or you can keep your current charger that has no advanced features. [choice, opt-out allowed]

Columns

attr_peak_managementattr_priceattr_rewardattr_smart_chargingattr_solar_chargingattr_two_way_chargingchoicecov_agecov_daily_drive_kmcov_drives_evcov_duration_seccov_educationcov_income_bandcov_languagecov_regioncov_womanidprofiletasktrial_version

The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("fowler_2026_pev_charger_purchase", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("fowler_2026_pev_charger_purchase", source="conj")

How to cite

@misc{https://doi.org/10.17632/pgrgnctxjf,
  doi = {10.17632/PGRGNCTXJF},
  url = {https://data.mendeley.com/datasets/pgrgnctxjf},
  author = {Fowler, Brian and van Passel, Steven and Lizin, Sebastien},
  keywords = {Discrete Choice Modeling},
  title = {Replication Data and Code for “From Purchase to Participation: Sequential Choice Experiments on PEV Smart-Charging”},
  publisher = {Mendeley Data},
  year = {2026}
}

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint_2 v1.4
Redivis dataset DOI10.57761/hk97-wv30
Manifest pin for this IRW versionv1.4
Metadata sourceirw_meta v44.0