A benchmark data envelopment analysis (DEA) dataset describing 35 major Chinese cities by three inputs and three outputs. Originally introduced by Sueyoshi (1992), it is the example dataset used to illustrate the DEA-Viz methods in Ashkiani (2019) and has appeared in several DEA studies.
Format
A data frame with 35 rows and 7 variables:
- DMU
City name (the decision-making unit label).
- industrial_labour_force
Input 1: industrial labour force.
- working_funds
Input 2: working funds.
- investments
Input 3: investment.
- gross_industrial_output
Output 1: gross industrial output.
- profit_and_tax
Output 2: profit and tax.
- retail_sales
Output 3: retail sales.
Source
Sueyoshi, T. (1992). Measuring the industrial performance of Chinese cities by data envelopment analysis. Socio-Economic Planning Sciences, 26(2), 75-88. doi:10.1016/0038-0121(92)90015-W
Reproduced as the worked example in Ashkiani, S. (2019), Four Essays on Data Visualization and Anomaly Detection of Data Envelopment Analysis Problems (PhD thesis), Universitat Autonoma de Barcelona.
Details
Columns 2–4 are inputs and columns 5–7 are outputs; column 1 holds
the DMU labels. Because the columns are not i_/o_ prefixed,
pass them explicitly to dea_data (see Examples).
Examples
d <- dea_data(
chinese_cities,
inputs = c("industrial_labour_force", "working_funds", "investments"),
outputs = c("gross_industrial_output", "profit_and_tax", "retail_sales"),
id = "DMU"
)
d
#> <dea_data>
#> DMUs : 35
#> Inputs : 3 (industrial_labour_force, working_funds, investments)
#> Outputs : 3 (gross_industrial_output, profit_and_tax, retail_sales)