Conjoint Analysis Experimental Design for
Services Involving Multiple Options
E. Fragniere, N. Javanmardi, and F. Moresino, “Conjoint Analysis Experimental Design for Services Involving
Multiple Options”, IEEE International Conference on Service Operations and Logistics, and Informatics,
China, 2010.
Presented by: Neda Javanmardi
Airline flights usually include multiple additional services to differentiate their offer from the
competition. In particular, the number of stimuli (combination of attributes) becomes huge and
difficult to evaluate through conjoint analysis. In this paper, a new hybrid method is proposed
in order to produce relevant card systems of reasonable sizes. First, a pre-selection of stimuli is
conducted based on logical survey and expert testing procedures. Second, an algorithm using
the criterion of D-optimality is programmed to select the final set of stimuli. The method has
been employed for the design of flights between Tehran and Dubai.
Context
The research is customized for Airline industry.
An integrated model is applied to find the best flight
design, which is combination of Share-of-Choice model
and Mathematical Model.
Researchers try to solve the problem of the designs
which are not realistic.
Context
Research question
Literature review
Methodology
Findings
2/6
Research question
Research question:
What is the best service design for our partner airline
company for the flight from Tehran to Dubai?
Research objective:
Finding the most desirable flight design (ticket design) which
brings the highest profit to our partner company.
Context
Research question
Literature review
Methodology
Findings
3/6
Literature review
“By breaking down attributes, to derive the part-worth associated with
each level of a product based on the overall preferences of alternatives,
by a group of respondents, conjoint analysis helps the marketing
manager to determine which of the product's or service's qualities are
most important to the Customer.”
Thomas Reutterer
T. Reutterer, H. W. Kotzab, ''The use of Conjoint Analysis for Measuring Preferences in Supply Chain Design",
Industrial Marketing Management, Vol. 29, PP. 27- 35, 2000.
“Full-profile methods cannot be conducted with the whole possible
stimuli set. The number of stimuli presented in a survey shouldn't be too
high. In order to reduce the number of stimuli, Green proposed the use
of orthogonal design. The main drawback of the orthogonal designs lies
in the fact that it can contain stimuli that are impossible or irrelevant.”
Paul Green
Context
P. E.Green, "On the Design of Choice Experiments Involving Multifactor Alternatives", Journal of Customr
Research, Vol. 1, PP. 61-68, 1974.
Research question
Literature review
Methodology
Findings
4/6
Methodology
Pre-survey:
a. Self-explicated conjoint analysis
 Interview
 Questionnaire
Survey part I:
b. Conjoint analysis
 Vignette study
 Part-worth estimation (Quantitative method)
Survey part II:
c. Mathematical model
 Optimization (Quantitative method)
Context
Research question
Literature review
Methodology
Findings
5/6
Findings
A new model is proposed based on a self-explicated card-based method,
which reduces all combinations of attributes only to those which can be
potentially possible.
The method is applied to an airline industry case. By comparing the algorithm
results with some traditional orthogonal designs, it is found that our cards are
more realistic than the orthogonal cards.
Limitations:
Dependency on expert judgment.
Final selected set is not completely orthogonal.
Future works:
Since some attributes are impractical to evaluate, information
may be difficult to obtain and complex to analyze, so further study
can be based on the Fuzzy Set Theory (FST) which could effectively
helps to better model uncertainties and imprecision.
Context
Research question
Literature review
Methodology
Findings
6/6