This dataset, china_cars_tbl_df, is a tibble containing stated choice observations from a conjoint survey conducted by Helveston et al. (2015). The survey includes 448 choice observations from Chinese car buyers and 384 from U.S. car buyers. The surveys were administered in 2012 across four major Chinese cities (Beijing, Shanghai, Shenzhen, and Chengdu), online in the U.S. via Amazon Mechanical Turk, and in person at the Pittsburgh Auto Show. Participants were asked to choose a vehicle from a set of three alternatives in 15 choice tasks.
Usage
data(china_cars_tbl_df)Format
A tibble with 20,160 observations and 20 variables:
- id
Participant ID (numeric)
- obsnum
Observation number (numeric)
- choice
Indicates if the option was chosen (1 = yes, 0 = no) (numeric)
- hev
Hybrid electric vehicle dummy variable (numeric)
- phev10
Plug-in hybrid vehicle with 10-mile range dummy (numeric)
- phev20
Plug-in hybrid vehicle with 20-mile range dummy (numeric)
- phev40
Plug-in hybrid vehicle with 40-mile range dummy (numeric)
- bev75
Battery electric vehicle with 75-mile range dummy (numeric)
- bev100
Battery electric vehicle with 100-mile range dummy (numeric)
- bev150
Battery electric vehicle with 150-mile range dummy (numeric)
- phevFastcharge
Fast charging availability for PHEV (numeric)
- bevFastcharge
Fast charging availability for BEV (numeric)
- price
Price of the vehicle (numeric)
- opCost
Operating cost (numeric)
- accelTime
Acceleration time (numeric)
- american
American brand dummy variable (numeric)
- japanese
Japanese brand dummy variable (numeric)
- chinese
Chinese brand dummy variable (numeric)
- skorean
South Korean brand dummy variable (numeric)
- weights
Survey weights (numeric)
Details
The dataset name has been kept as 'china_cars_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the ChinAPIs package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble (a modern form of data frame). The original content has not been modified in any way.