Botti peypoch mcda

Dr. BOTTI Laurent
Dr. PEYPOCH Nicolas

Perpignan University / CAEPEM

77th meeting of the European Group on MCDA
11.04.2013
11th April 2013, University of Rouen
1

Multi-Criteria ELECTRE Method
and Destination Competitiveness

1. Introduction

2. MCDA methods and destination competitiveness

3. ELECTRE I and TDC : the case of Hawaiian islands

4. Interests, limitations and perspectives

11.04.2013
2

1. Introduction
2. MCDA methods and TDC

 The global tourism industry is dynamic
 Competitiveness is a growing interest area

11.04.2013

3

1. Introduction

 Due to their centrality in the tourism system, tourism destinations
(TD) benefit from this interest (Cracolici & Nijkam, 2008)
 To understand TD competitiveness, we dispose of the Ritchie &
Crouch (2003) model, the most cited one
 This model integrates all the relevant factors that might typify the
competitiveness of a destination
 This paper aims to show the interest of MCDA methods regarding
the operationalization of this model
11.04.2013
Let’s move to section 2
4

1. Introduction

 Why are MCDA methods relevant to deal with competitiveness of
tourism destination ?
 MCDA for methods providing quantitative approach to support
decision making in problems involving several criteria and
choices (alternatives or actions) (Figueira, Mousseau & Roy,
2005)
 TD are an integrated set of tourist facilities which have to face the
challenge of operating their resources effectively and efficiently in
11.04.2013

5
order to supply an experience that outperforms alternative

1. Introduction

 Tourists who whish to enjoy a satisfying experience try to select
one destination from a set of n possible alternatives and on the
basis of m criteria
 The main framework to understand TDC is that of Ritchie &
Crouch (2003)
– based on five competitiveness components (criteria)
 Attractors (Climate, History…)
 Supporting factors (Accessibility, Hospitality…)
 Destination management (Marketing, HRM…)
11.04.2013  Destination planning (Positioning, Branding…)
6  Amplifying determinants (Safety…)

1. Introduction

 => Destination selection can be seen as a MCDA problem

11.04.2013
Let’s move to
7
an application

1. Introduction

 Although MCDA methods can be applied to different areas,
the litterature is quite narrow when considering the tourism
field
– TOPSIS was used by Zhang et al. (2011) to rank 16 cities in
China
– TOPSIS, PROMETHEE and the WSM was used by Ishizaka,
Nemery and Lidouh (2013) to select the location of a casino in
London
– ELECTRE II was used by Andrades-Caldito et al. (2013) to rank
11.04.2013 provinces of Andalusia (Spain)
8

1. Introduction

 Here, ELECTRE I (Roy, 1991) is applied to choose the best
destination from a given set of alternatives
 Widely used, the MCDA outranking method ELECTRE I
should be applied when all criteria are coded in numerical
scales with identical ranges (Figueira, Mousseau, Roy, 2005)
– Data are derived from the 2011 Hawaiian VSA Report which
presents results of a survey conducted by the HTA
– The HTA report attempts to portray visitor’s evaluation of their
experience by covering various aspects of their trip for the island
that they stayed the longest

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9

1. Introduction

 Visitors were asked to rate few attributes of islands :
accomodations, restaurant, shopping, golf, attractions,
transportation, airports, parks & beaches
– We use the proportion of very satisfied visitors as measurement of
performance
– Our application focuses
only on visitors from
Europe in 2011
– 6 major islands but due to
data availability, we focus
11.04.2013 on 4 islands (A = ai ; i = 1,
10 …,4)

1. Introduction

 4 criteria, their weights (wj, from Crouch, 2011) and attributes :

 Considering Fj = {ftj ; t=1,…,p}, the set of p attributes of criterion j,
11.04.2013 performances are obtained by :
11

1. Introduction

 Performance of alternatives on each criterion :

11.04.2013

12

1. Introduction

 Concordance and discordance matrixes were performed with
LINAM software (Logiciel Interactif d’Analyse Multicritère by
P. Wieser from Lausanne)
 Second step of ELECTRE I is the derivation of a
recommendation based on the outranking relations i.e.
identify a small as possible subset of actions, from which the
best compromise action(s) could be selected
 Construction of a graph considering the concordance level
11.04.2013
C* and the discordance level D*
13

1. Introduction

 For C* = 0.56 and D*= 0.26  For C* = 0.56 and D*= 0.42

=> O’ahu must be choosen by tourists
This island is the most competitive
By considering that the satisfaction achieved by tourists can
be used to indirectly evaluate the competitive ability of TD to
11.04.2013 outperform others destinations
14
Let’s move to the
last section

1. Introduction

 Interests :
– We show how MCDA outranking approach ELECTRE I can be

used to analyse TDC =>First application of ELECTRE I to this
field
– Quantitative operationalization of the C&R model
 Limitations :
– Performances are obtained via an arithmetic mean
– Data can be considered as reductive as we focus on European
visitors

11.04.2013
– What about indifference ? What about preference (strong and
weak) ?
15

1. Introduction

 Perspectives :

– Rank all the destination belonging to a given set of alternatives

from the best to the worst (ski resorts, seaside resorts, cities…)

with ELECTRE II or ELECTRE III

– Compare ELECTRE rankings with other rankings – for example

efficiency ranking (obtained with DEA method or others)

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16

1. Introduction

 Thank you for attention!

 laurent.botti@univ-perp.fr

 peypoch@univ-perp.fr

11.04.2013

17

Botti peypoch mcda

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