A data frame with 250 observations and 27 variables.
Variables from 1 to 27 refer to six latent concepts: IMAG=Image,
EXPE=Expectations, QUAL=Quality, VAL=Value,
SAT=Satisfaction, and LOY=Loyalty.
Indicators attached to concept IMAG which is supposed to
capture aspects such as the institutions reputation,
trustworthiness, seriousness, solidness, and caring
about customer.
Indicators attached to concept EXPE which is supposed to
capture aspects concerning products and
services provided, customer service, providing solutions,
and expectations for the overall quality.
Indicators attached to concept QUAL which is supposed to
capture aspects concerning reliability of products and services,
the range of products and services, personal advice,
and overall perceived quality.
Indicators attached to concept VAL which is supposed to
capture aspects related to beneficial services and
products, valuable investments, quality relative to
price, and price relative to quality.
Indicators attached to concept SAT which is supposed to
capture aspects concerning overall rating of satisfaction,
fulfillment of expectations, satisfaction relative to
other banks, and performance relative to customer's
ideal bank.
Indicators attached to concept LOY which is supposed to
capture aspects concerning propensity to choose the
same bank again, propensity to switch to other bank,
intention to recommend the bank to friends,
and the sense of loyalty.
satisfactionAn object of class data.frame with 250 rows and 27 columns.
This dataset contains the variables from a customer satisfaction study of
a Spanish credit institution on 250 customers. The data is identical to
the dataset provided by the plspm package
but with the last column (gender) removed. If you are looking for the original
dataset use the satisfaction_gender dataset.