Website quality evaluations projects require different approaches according to their goals.

1. Supporting decision making
in quality projects for Web sites:
a framework for tourist destinations
Luisa Mich, Mariangela Franch,
Pier Luigi Novi Inverardi, Pietro Marzani
Research group eTourism
University of Trento, Italy

2. Structure of the presentation
• Context:
role of Web sites for tourist destinations
• Problem:
ENTER 2004 Research Track Slide Number 2
• Problem:
management and redesigning of the
Web site of a tourist destination
• Our approach:
innovative decision support framework

3. Role of Web sites for tourist
destinations
• Web sites can play the role of Destination
Management Systems (DMS)
(e.g., to gather information about services, attractions and
tourist products)
ENTER 2004 Research Track Slide Number 3
tourist products)
• Web sites can be used to implement the strategies
of the destination
Increasing demand for quality in tourist Web sites:
Web sites have to be realised taking into account the
elements that are unique to a tourist destination and the
needs and strategies of the various actors

4. Management and redesigning
of a destination’s Web site
• Large number of models and frameworks to
evaluate the quality of a tourist Web site
(http://www.economia.unitn.it/etourism/wqresourc
es.asp)
ENTER 2004 Research Track Slide Number 4
es.asp)
• Few tools and resources available to make
targeted interventions:
– difficulty of extracting information from the results of
an evaluation focused on the quality of a Web site
– 2 kinds of problems:
• which data to collect
• how to interpret them

5. Our decision support framework
• Two steps:
– Choice of the “rightweight” Web site quality
evaluation model
– Application of suitable statistical techniques to
ENTER 2004 Research Track Slide Number 5
– Application of suitable statistical techniques to
analyse the results of the evaluation
• To illustrate our approach we will refer to a
project for the evaluation of the quality of
Web sites of tourist destinations in the Alps
(Mich et al., Enter 2003)

6. Choice of the “rightweight”
quality evaluation model
• 2QCV2Q 2QCV3Q 7Loci
– Allows for a flexible analysis
ENTER 2004 Research Track Slide Number 6
– Allows for a flexible analysis
– Takes into account the goals of the project
– Optimises the use of resources needed for data
collection

7. Decision making and lightweight
Web site quality evaluation
• Lightweight version of the meta-model
– 2QCV2Q 6 dimensions
ENTER 2004 Research Track Slide Number 7
– 2QCV2Q 6 dimensions
– 24 questions
– Points from 0 to 4
– Score for each dimension = weighted average
of points from the questions they contain

8. Results of the lightweight evaluation
ENTER 2004 Research Track Slide Number 8
Each branch represents a dimension, starting from Identity at the top and continuing clockwise
with Content, Services, Location, Maintenance and Usability

9. Indications for the decision maker
from the lightweight evaluation
• Dimensions to improve in order to augment
the performance of the site with respect to
other sites or a specific competitor
ENTER 2004 Research Track Slide Number 9
other sites or a specific competitor
• Do not provide specific indications about
how to improve the performance of the site
in these areas

10. Decision making and heavyweight
Web site quality evaluation
• Heavyweight version of the meta-model
– 7Loci 7 dimensions
ENTER 2004 Research Track Slide Number 10
– 7Loci 7 dimensions
– 97 questions
– Boolean questions
– Score for each dimension = number of
requirements fulfilled

11. Results of the heavyweight evaluation:
Principal Components Analysis
IIPC Content
Identity
Usability
Canton Ticino
Trentino
Alto Adige
Valle d'Aosta
Piemonte
Veneto
Valais
Tirol
ENTER 2004 Research Track Slide Number 11
I PC
Component weights Observations
Services
Location
Veneto
Zentralschw eiz
Valais
A Principal Components Analysis of the results obtained is undertaken in order to
provide indications that are of use to managers when deciding how best to intervene
in order to improve site performance and competitiveness

12. Results of the heavyweight evaluation:
Principal Components Analysis
• Maintenance is uncorrelated to other dimensions: having high standards of
maintenance does not guarantee high quality in the other dimensions
• The first PC can be interpreted as a measure of the overall quality of a site
• The second PC measures a contrast between Content, Identity and Usability on
ENTER 2004 Research Track Slide Number 12
• The second PC measures a contrast between Content, Identity and Usability on
one side and Services and Location on the other
• An analysis of such a graphic can help managers of destinations to take decisions
regarding possible interventions to apply to their Web sites
• It is possible for site managers to identify their site’s position with respect to
others in the area of overall quality (horizontal axis) and also which aspects of
the site are outside the norm (vertical axis)

13. Results of the heavyweight evaluation:
Multiple Correspondence Analysis
I - Evocation (8) - 6
I - Evocation (8) - 7
I - Characteristics (7) - 6
I - Characteristics (7) - 7
Bayern
Berner Oberland
Burgenland
Canton Ticino
Graubünden
Niederösterreich
Oberösterreich
Provence Alpes-Côte d’AzurRhône-Alpes
Steiermark
ENTER 2004 Research Track Slide Number 13
Groups of homogeneous questions (subdimensions) were identified within each
dimension; these questions dealt with a particular aspect of the dimension. The figure
gives the results of a Multiple Correspondence Analysis for data corresponding to the
Identity dimension: the 15 questions related to it have been grouped into two
homogeneous categories (Evocation and Characteristics)
I - Evocation (8) - 5I - Evocation (8) - 8
I - Characteristics (7) - 4
I - Characteristics (7) - 5
I - Characteristics (7) - 7
Alto Adige
Canton de Vaud
Friuli Venezia Giulia
Graubünden
Kärnten
Lombardia Piemonte
Riviera Côte - d’Azur
Salzburger Land
Slovenjia
Tirol
Trentino
Valais
Valle d'Aosta Veneto
Voralberg

14. Results of the heavyweight evaluation:
Multiple Correspondence Analysis
• It is possible to identify which sites have the best performance in
this dimension (Kärnten, Trentino, Tirol, Vorarlberg, Alto Adige
and Salzburgerland)
• By analysing this graphic the manager of a site can identify
ENTER 2004 Research Track Slide Number 14
• By analysing this graphic the manager of a site can identify
specific points where intervention can result in significant
improvements
• At the same time the manager has a tool available whereby she
can also monitor the site’s position relative to the other sites of
Alpine RTBs

15. Conclusions
• An analysis of Web site quality, depending on the aims
of the site manager, must be done at different levels,
with different possible outcomes in terms of
benchmarking and suggestions for site improvement or
reengineering.
• The initial decisions regarding these aims can be made
ENTER 2004 Research Track Slide Number 15
• The initial decisions regarding these aims can be made
by taking into account the human and financial
resources available.
• Our approach represents a first step toward the
development of an integrated environment for the
support of Web site quality evaluation projects that
incorporate a logic of continuous improvement.