INTERNATIONAL CONVENTION SITE SELECTION a further ......A Further Analysis of Factor Importance...

INTERNATIONAL CONVENTION SITE SELECTIONa further analysis of factor importance using best-worst scaling

Geoffrey I. Crouch and Jordan J. Louviere

A Further Analysis of Factor Importance Using Best-Worst Scaling

ii

Technical Reports The technical report series present data and its analysis, meta-studies and conceptual studies, and are considered to be of value to industry, government and researchers. Unlike the Sustainable Tourism Cooperative Research Centre’s Monograph series, these reports have not been subjected to an external peer review process. As such, the scientific accuracy and merit of the research reported here is the responsibility of the authors, who should be contacted for clarification of any content. Author contact details are at the back of this report. Editors Prof Chris Cooper University of Queensland Editor-in-Chief Prof Terry De Lacy Sustainable Tourism CRC Chief Executive Prof Leo Jago Sustainable Tourism CRC Director of Research National Library of Australia Cataloguing-in-Publication Crouch, Geoffrey I. International convention site selection: a further analysis of factor importance using best-worst scaling. Bibliography. ISBN 978 1 920704 99 5. 1. Congresses and conventions – Planning. 2. Convention facilities. I. Louviere, Jordan J. II. Cooperative Research Centre for Sustainable Tourism. III. Title. 338.4791 Copyright © CRC for Sustainable Tourism Pty Ltd 2007 All rights reserved. Apart from fair dealing for the purposes of study, research, criticism or review as permitted under the Copyright Act, no part of this book may be reproduced by any process without written permission from the publisher. Any enquiries should be directed to General Manager Communications & Industry Extension [[email protected]] or Publishing Manager [[email protected]].

INTERNATIONAL CONVENTION SITE SELECTION

iii

CONTENTS

PREFACE _____________________________________________________________________________ IV

SUMMARY _____________________________________________________________________________ V

CHAPTER 1 INTRODUCTION ___________________________________________________________ 1

CHAPTER 2 STUDY DESIGN ____________________________________________________________ 2 BEST-WORST SCALING __________________________________________________________________ 2 BEST-WORST SCALING COMPARED WITH RATING SCALES _______________________________________ 4 SURVEY DESIGN AND IMPLEMENTATION _____________________________________________________ 7

CHAPTER 3 RESULTS OF THE BEST-WORST SCALING FACTOR IMPORTANCE STUDY_____ 8 DISCUSSION ___________________________________________________________________________ 8

APPENDIX A: ONLINE SURVEY_________________________________________________________ 12

APPENDIX B: EXPERIMENTAL DESIGN TABLE__________________________________________ 22 LIST OF CONVENTION SITE SELECTION FEATURES WITH LEVELS (RANGES) _________________________ 22 OVERALL LAYOUT OF THE BEST-WORST COMPARISON SETS BY BLOCK _____________________________ 23 TRANSLATION OF BLOCK 1 INTO A SURVEY QUESTION _________________________________________ 37

REFERENCES _________________________________________________________________________ 38

AUTHORS_____________________________________________________________________________ 39

List of Figures

Figure 1: Outcome of consistent choices in a 2J series of choice sets__________________________________ 3 Figure 2: Regression of Equation 1____________________________________________________________ 4 Figure 3: Best-worst versus best/worst _________________________________________________________ 7 Figure 4: BWS importance measure of site selection factors: SQRT(best/worst) scale ___________________ 10 Figure 5: BWS importance measure of site selection factors: weighted best – weighted worst _____________ 11 List of Tables

Table 1: Outcome of consistent choices in a 2J series of choice sets __________________________________ 2 Table 2: Tabulation of Equation 1 ____________________________________________________________ 3 Table 3: BIBD and Youden design properties ___________________________________________________ 5 Table 4: BIBD for seven items _______________________________________________________________ 5 Table 5: Making sets from the BIBD __________________________________________________________ 5 Table 6: Implementing the BIBD in a BWS choice task____________________________________________ 6 Table 7: Calculating measures for each city based on the task results _________________________________ 6 Table 8: Best-worst results tabulation__________________________________________________________ 8


iv

PREFACE

This report extends earlier research on Australian domestic convention site selection issues which was published by STCRC in 2004 – Convention Site Selection: Determinants of Destination Choice in the Australian Domestic Conventions Industry (Crouch & Louviere 2004b). As that report provided a comprehensive background, literature review, and conceptual foundation, readers are referred to the report for detail. This report summarises the results of additional research which has extended that earlier work by examining new issues involved in terms of international conventions using a method known as best-worst scaling.

Acknowledgements The Sustainable Tourism Cooperative Research Centre, an Australian Government initiative, funded this research.

Thanks are extended to the respondents from the international associations who participated in the online best-worst survey.


v

SUMMARY

Objectives of Study The principal aim of the current study has been to evaluate the relative importance of convention site selection factors in the context of the competition for the hosting of international association conventions. The international conventions industry has grown considerably. For major cities, particularly, this market represents a major part of their tourism planning and marketing activity. Yet, other than anecdotal information, little research has examined which destination attributes account for the majority of a convention destination’s competitiveness. This study surveyed a sample of international meeting planners in order to add to this knowledge.

Methodology The survey employed a method known as Best-Worst Scaling. A sample of international association convention planners participated in the study. An online survey was developed based on an experimental design which manipulated the convention site selection factors of interest. A series of sets of site selection factors was presented to each respondent. For each set, respondents were asked to nominate which of the factors they believed exerted the most influence on the choice of convention site and which factor exerted the least influence. The advantage of this technique is that it is much easier for respondents to answer relatively simple questions of this nature without much loss of information, compared to profiling complete sets of site attributes.

Key Findings Based on the results of the Best-Worst Scaling analysis, these results provide a clear differentiation in importance, showing that the twelve most important site selection factors are:

• Frequency and convenience of flight schedules and connections • Quality of the general infrastructure • Accommodation rate for conference delegates by accommodation • Venue cost relative to international average • Break-out/session rooms • Possibility that there might be a subsidy to defray costs • Range and availability of audio/visual systems/facilities • Plenary room capacity • Opportunities for professional networking • Ambience and layout of facility • Inbound travel barriers and formalities • Level of assistance expected from the local chapter of the association.

The ten least important factors were found to be: • How good was your previous experience running a convention here • How favourable is the word-of-mouth reputation here • Range of four-star accommodation within 15 minutes of the facility • Average standard economy domestic return airfares • Perceived quality of the food • Typical weather and climate at the time of the convention • Accommodation location relative to airport • Opportunities for recreational activities • Opportunities for entertainment • Opportunities for shopping.

Future Action Destinations competing for international association conventions should utilise these results in terms of their strategic planning, marketing and convention site development. The results indicate which factors exert the greatest influence on convention site selection. Convention destinations should assess their relative strengths and weaknesses against each of these site attributes, paying particular attention to those which rate highly in the site assessment of international association convention planners.

Marketing strategies should emphasise strengths in those factors which are both important and on which the particular destination performs particularly well. Where a destination is weak in an important factor, a particular


vi

effort is required to overcome that weakness if at all possible. The capacity for a destination to improve its performance on each site selection factor will depend upon the nature of the factor. In some cases it may not be possible to alter or improve a destination’s performance. For example, there is little that a destination can do to improve its actual weather or climate. However, it may be that the perception of the destination’s weather or climate is negatively distorted. In such a case, destination promotion may seek to correct or improve such negative impressions. Where a destination possesses a major strength on an important factor, efforts are required to ensure that strength is clearly known and understood within the international association conventions market.

This present study has addressed the issue of convention site selection by international associations. Association conventions and corporate meetings and conventions differ in terms of the process and factors which may drive site selection. Similarly, the issue of site selection in the case of exhibitions and events (such as sporting competitions, cultural programs, etc.) would be expected also to differ. Further similar research could be undertaken to address these markets as well.


1

Chapter 1

INTRODUCTION

The selection of sites to host major conventions is of substantial interest and importance to cities worldwide. If cities knew the factors involved in these decisions, and how important they were to convention planners who make the site selection decisions, it would significantly enhance their ability to compete for conventions, as well as allow the cities to target certain types of conferences by emphasising the factors that matter on which they score particularly well.

Previous research by Crouch and Ritchie (1998) provides a starting point for our research because they provide a relatively comprehensive listing of potential factors that underlie the selection decisions. Crouch and Louviere (2004a, b) used the Crouch and Ritchie list to identify potential decision factors that matter in domestic convention site selection decisions in Australia.

This present report extends the previous research to the international arena by using a relatively novel approach to measuring the likely importance of the site selection factors from the Crouch and Ritchie list for international site selection decisions. The list of factors which may affect international site selection is considerably longer compared to domestic convention site competition, since international competition is essentially affected by the same factors affecting domestic competition, plus a number of additional factors specific to the international situation. On an international scale, there may be a great deal of variation in a number of factors which, at the domestic or national level, vary very little between alternative convention sites. For example, climate, infrastructure, safety and security issues, and accessibility, among others, can be expected to vary to a greater extent from country to country than is likely from city to city within a particular country.

Since the size and complexity of choice experiments increase exponentially with the number of pivotal choice attributes to be experimentally varied, the task of undertaking a choice experiment becomes more problematic. This is exacerbated by the fact that the international survey is to be conducted online. For practical reasons, online surveys present some constraints related to screen size, the need for ‘scrolling’, survey duration, etc. However, the advantages of conducting an online survey when respondents are scattered in different parts of the globe outweigh these limitations. For this reason we chose to conduct this study using best-worst scaling due to its greater efficiency without undue loss of information. This method is outlined in greater detail in Chapter 2.


2

Chapter 2

STUDY DESIGN

Best-Worst Scaling Best-worst scaling (BWS) was developed by Louviere at the University of Alberta in 1988, and its properties were demonstrated at the first American Marketing Association Advanced Research Techniques Forum. Finn and Louviere (1992) showed how to use BWS in polling applications, and demonstrated that information provided by typical polls can be very misleading. These early applications were followed by several working papers by combinations of Swait and Louviere (1993) and Louviere (1994), which extended BWS to conjoint analysis and discrete choice experiments. BWS languished until the late 1990s when applied economists began to use BWS, and a number of major American marketing research companies also began to use it (see for example McIntosh & Louviere (2002) who applied BWS to a problem in measuring preferences for dental treatments in the UK; and Cohen (2003) who examined the use of BWS to address cross-cultural scale bias). Marley and Louviere (2005) provided formal proofs of the measurement properties of BWS, paving the way for researchers to have confidence in the theory and measurement models associated with the approach. Currently, worldwide, there are many more applications underway.

BWS is a theory about how humans choose the best and worst items in a set of three or more items. For example, suppose we have a set of five cities, such as Sydney, Melbourne, Auckland, Los Angeles and Seattle, and suppose that the latent dimension of research and measurement interest is ‘number of available venues to host a convention of 5000 delegates’. We ask a sample of suitable individuals to choose two cities in the set of five. The two cities to be chosen are, respectively, the one with the most number of suitable venues (the ‘best’) and the one with the least number of suitable venues (the ‘worst’). Because the individuals in this sample theoretically choose the two cities that are the farthest apart in the underlying dimension, BWS is sometimes called ‘maximum difference scaling’. That is, the best and worst choices represent the two cities (in this case) that are the farthest apart on the underlying latent scale.

If there are J items or objects to be chosen, all possible subsets of choices is given by a 2J factorial expansion of the J items or objects. So, in our example of a set of five cities, J = 5, and 25 = 32. If each person in the sample chooses perfectly consistently in all 32 sets, we would observe that the first ranked city was chosen as best 16 times, the second ranked city was chosen 8 times, the third ranked was chosen 4 times, the fourth ranked was chosen twice and the last ranked was chosen once. These choices form a base 2 series, and are the simple consequence of the fact that all possible sets are given by a 2J factorial.

We illustrate this property of the best and worst choices in Table 1 and Figure 1, which illustrate how a perfectly consistent person should choose if there are 256 possible choice sets of 8 cities.

Table 1: Outcome of consistent choices in a 2J series of choice sets

City Total best Total worst Best x worst (=k)

1 128 1 128

2 64 2 128

3 32 4 128

4 16 8 128

5 8 16 128

6 4 32 128

7 2 64 128

8 1 128 128


3

Figure 1: Outcome of consistent choices in a 2J series of choice sets

This table and figure allow us to derive some useful relationships that must obtain for best and worst choices if an individual is perfectly consistent. That is,

Total(best) = k / Total(worst); Total(worst) = k / Total(best); Total(best) x Total(worst) = k, where k = max(total, e.g. in Table 1, it equals 128). The above relationships allow us to derive what is known as a Fixed Utility version of BWS, which in turn

allows us to prove certain measurement properties associated with the general procedure. In particular, the ratio of best choice totals to worst choice totals forms a ratio scale, as we now show:

Total(best) / Total(worst) = Total(best) / [k / Total(best)] = Total(best)2 / k. Therefore, the square root of the ratio of Total best choices to Total worst choices is a ratio scale of ‘best’. That is, SQRT{[Total(best) / Total(worst)]} = Total(best) / √k (Equation 1) Table 2 and Figure 2 illustrate this relationship in which the slope coefficient is equal to the inverse of the

square root of k (i.e. 1 / 11.31371 = 0.088) and the intercept is due merely to rounding.

Table 2: Tabulation of Equation 1

Total (best)

Total (worst)

Total (best)/Total

(worst)

Sqrt (best/worst)

Total best^2 Sqrt (128) Sqrt (Total

best^2/128)

128 1 128 11.313708 16384 11.313708 11.31

64 2 32 5.6568542 4096 11.313708 5.66

32 4 8 2.8284271 1024 11.313708 2.82

16 8 2 1.4142136 256 11.313708 1.41

8 16 0.5 0.7071068 64 11.313708 0.71

4 32 0.125 0.3535534 16 11.313708 0.35

2 64 0.03125 0.1767767 4 11.313708 0.18

1 128 0.0078125 0.0883883 1 11.313708 0.09

Graph of Best Vs Worst y = 128x-1

020406080

100120140

0 20 40 60 80 100 120 140

Best Choice Frequencies

Wor

st Ch

oice

Fre

quen

cies


4

Figure 2: Regression of Equation 1

The previous discussion implies that one simply follows the following procedure to measure each of the items/objects on a ratio scale: a) Count the best and worst choice totals (frequencies) for each item; b) Test to see how consistent the choices have been by checking if Total(best) = k/Total(worst), or Total(best)

x Total(worst) = k. In reality, individuals are almost never perfectly consistent and so some variation from this relationship is to be expected; and

c) Calculate SQRT(best/worst) to derive a ratio scale of the results. If there are 0 choice totals for some items, one can add 1/(number of items) to all counts to get a consistent

estimate. If one is interested in measuring the items/objects on an absolute instead of a relative scale, one can add response categories like ‘none of these are bad’ and ‘none of these are good’ (or similar) to each set to allow these choices to be included.

Best-Worst Scaling Compared With Rating Scales It is well-known that ratings often do not discriminate between items (e.g. Cohen 2003). Indeed, it is precisely in the measurement of factor importance where rating scales typically fail to provide much discrimination among factors, and one typically finds that almost all factors are ‘important’. The reason for this outcome is that rating scales do not require individuals to trade off or make choices among the factors, and rating scales also encourage similarity in responses because this represents the ‘easy option’ for respondents in surveys. BWS avoids these problems because it requires individuals to make tradeoffs and choices, thus revealing important differences in factor importance, and allowing much finer discriminations in degrees of importance. Moreover, BWS typically requires only a small number of additional responses compared with rating scales, as we now discuss.

Suppose one wants to measure six cities on five latent factors like number of suitable convention venues, weather, number of interesting local activities, etc. One typically would ask a suitable sample of individuals to rate each of the six cities on each of the factors, which would require 30 responses (six per trait). One alternative would be to construct all possible pairs and ask the individuals to choose the best city in each pair on each factor. In this case, there are 15 pairs x five traits, or 75 responses, which might be feasible, but clearly is not desirable for field applications. If, instead, one designs a BWS exercise, one can treat the problem as one of sampling from the 26 factorial to create subsets of the six cities. In this example, one can construct seven sets to serve as a sample from the 26 factorial, which means that one needs five factors x seven sets = 35 subsets.

Thus, if one uses 2J orthogonal main effects plans (OMEPs) to design the sample of sets, one needs only five more responses than the simple rating task. The use of OMEPs as a basis for sampling from 2J factorials was provided by Louviere and Woodworth (1983), who demonstrate that it is optimally statistically efficient for estimation of certain types of choice models, of which BWS is a subset. Yet, the sampling problem often can be even further reduced by using balanced incomplete block designs (BIBDs) and related designs like Youden designs, which typically produce even smaller numbers of subsets. Examples of BIBD and Youden designs and the associated numbers of sets that they would produce are given in Table 3.

Best Totals Vs Sqrt(B/W)

y = 0.088x - 0.004, R2 = 1

0

5

10

15

0 50 100 150Best totals

Sqrt(

B/W

)


5

Table 3: BIBD and Youden design properties

Items Subsets Reps Set Size Pair Freq Type 6 6 5 5 4 Youden

7 7 3 3 1 Youden

8 14 7 4 3 BIBD

9 18 8 4 3 BIBD

10 15 6 4 2 BIBD

11 11 5 5 2 Youden

13 13 4 4 1 Youden

14 26 13 7 6 BIBD

15 15 7 7 3 Youden

16 20 5 4 1 BIBD

19 19 9 9 4 Youden

21 21 5 5 1 Youden

25 30 6 5 1 BIBD

Now we illustrate the use of a BIBD to make sets suitable for use with BWS. The example below involves seven cities, and the BIBD produces seven sets of three cities each. This latter property of BIBD and Youden designs also is noteworthy; that is, they create sets of fixed sizes, which in the following example equals three. Let the cities be Sydney, Melbourne, Moscow, Paris, London, Rome and Madrid, and let the latent factor of interest be “a safe place to hold a convention”. Table 4 shows a BIBD for seven cities that produces seven sets. Table 5 shows how the BIBD is translated into sets of cities.

Table 4: BIBD for seven items

Set # BIBD for seven items 1 2 4 6

2 1 4 5

3 3 4 7

4 1 2 3

5 2 5 7

6 1 6 7

7 3 5 6

Table 5: Making sets from the BIBD

Set # City sets 1 Melbourne Paris Rome

2 Sydney Paris London

3 Moscow Paris Madrid

4 Sydney Melbourne Moscow

5 Melbourne London Madrid

6 Sydney Rome Madrid

7 Moscow London Rome


6

Now, one asks a person to make best and worst choices in each set. That is, a person is asked to choose the most and least safe cities in which to hold a convention, as shown in Table 6, which also shows one possible set of choices.

Table 6: Implementing the BIBD in a BWS choice task

Set # Sets of three cities for BWS task Most Least 1 Melbourne Paris Rome Melbourne Rome

2 Sydney Paris London Sydney London

3 Moscow Paris Madrid Paris Moscow

4 Sydney Melbourne Moscow Melbourne Moscow

5 Melbourne London Madrid Melbourne Madrid

6 Sydney Rome Madrid Sydney Rome

7 Moscow London Rome London Moscow This example allows us to illustrate the use of BWS to derive a scale. One simply counts the number of most

(best) and least (worst) choices for each city, as shown in Table 7. The results clearly show that the person who made the choices thinks the safest place is Melbourne and the least safe place is Moscow. The table illustrates two ways of deriving a scale, the primary one being based on the earlier derivation that proves that one can obtain a ratio scale by taking the square root of the ratio of best choices to worst choices. In the case of this example, however, there are zero choice frequencies, and some of the ratios will equal infinity. Table 7 illustrates the use of adding a small fraction equal to the number of items being measured to the best and worst choice totals. Ben-Akiva and Lerman (1985) and Louviere, Hensher and Swait (2000) discuss the addition of these constants, which are based on well-known results in the literature on contingency tables in discrete multivariate statistics that demonstrate that this procedure yields consistent estimates.

Table 7: Calculating measures for each city based on the task results

City Most Totals Least Totals Most-Least Most/Least* London 1 1 0 1.00

Madrid 0 1 -1 0.35

Melbourne 3 0 3 4.69

Moscow 0 3 -3 0.21

Paris 1 0 1 2.83

Rome 0 2 -2 0.26

Sydney 2 0 2 3.87 *The ratio is square root of [(most+1/7) / (least+1/7)]

The second approach to deriving a scale is based on simply subtracting the least totals from the most totals,

which is simple. Marley and Louviere (2005) show that this is a biased estimate of the true measurement scale values, but it’s not very biased, as shown in Figure 3. That is, the intercept is zero, and the bias is concentrated in the cubic term of the polynomial relationship, as can be seen in Figure 3. That is, the two sets of numbers are monotonically related to one another, and the more items that are being measured, the less the bias. Due to the simplicity of the measures, and the fact that the two sets of measures always relate in this way, it often is easier to use best minus worst than to use the square root of the best-worst ratio.

Thus, one can conclude that BWS is easy to apply, and is easy for human subjects to respond to. The resulting scales or measures have known measurement properties (i.e. they produce interval or ratio scales). The tasks are easy to design and implement using 2J or BIBD designs. In comparisons with rating tasks, BWS has been found to dominate rating results on dimensionality, discrimination, and validation (Cohen 2003). BWS measures the latent quantities on a common scale which facilitates interdimensional comparisons, and removes differences in the ways that individuals and cultures use rating scales. BWS also typically allows one to develop measures or semi-orders for each individual in a study. For these reasons we chose to use it to study how convention planners assess attributes of convention sites when selecting a suitable site for a convention. The following chapter discusses the results of this analysis.


7

Figure 5: B-W Versus B/W

Ln[Sqrt(B/W)] = -0.047(B-W)3 + 0.93(B-W), R2 = 0.99

LN[Sqrt(B/W)] = 0.60(B-W), R2 = 0.9469

-2

-1

0

1

2

-4 -3 -2 -1 0 1 2 3 4

Best Minus Worst

Ln(B

est D

ivid

ed b

y W

orst

)

Figure 3: Best-worst versus best/worst

Survey Design and Implementation We implemented the BWS task using a BIBD that creates sets of five factors at a time for convention planner respondents to evaluate. There were far too many sets of factors to ask any one planner to evaluate all of them, so we randomly blocked the task into nine versions of the survey by randomly assigning different sets from the BIBD to each version without replacement, and then randomly assigning the sampled individuals to each version.

The survey was implemented as an online survey. International convention planners were recruited from a list provided by the Melbourne Convention and Visitors Bureau. Individuals were emailed a recruitment request, and were provided a web address where the survey was hosted. In total, the data set comprised 338 best/worst response pairs.

Appendix A includes a copy of the online survey. The first page of the survey explained the purpose and nature of the research and outlined the usual ethics requirements. Respondents were then asked to recall the last international convention held by an international association with which they were involved in the role of evaluating international host sites for that convention, whether as an employee of, or as a consultant to, that association. Respondents were then directed to answer all parts of the survey with that particular association and their last convention in mind.

Part 1 of the survey included several questions which gathered information about the association, the association’s conventions, membership, scope, age, etc, and some details regarding the respondent. Following this, the online survey presented a glossary of convention site attributes with details explaining each attribute. In total, 41 site attributes were included. These 41 site attributes were derived from Crouch and Louviere (1998), further refined from the outcomes of the earlier Australian domestic convention site selection study (Crouch & Louviere 2004a, b). The next part of the survey then introduced eight different sets of site attributes. Each set contained five attributes and respondents were asked to identify the most and least important of these attributes in each set, with respect to the selection of a host convention site, by clicking on the relevant ratio buttons. The survey was set up so that respondents were able to access the glossary details for any attribute in the set, in the form of a pop-up window, without having to return to the entire glossary web page.

The combination of five attributes in each set and the nine different survey versions were determined according to an experimental design. Appendix B includes the details of the experimental design employed.


8

Chapter 3

RESULTS OF THE BEST-WORST SCALING FACTOR IMPORTANCE STUDY

Discussion Because we could not easily control the number of non-respondents, different versions of the BWS survey produced different numbers of respondents. To control for this, we weighted each of the observations by calculating the mean number of respondents across all versions, with the weight for each version being this mean divided by the actual number of respondents in each version. This weighting procedure has the effect of weighting up versions with smaller numbers of respondents, and weighting down versions with larger numbers of respondents, and is based on the notion that with sufficient time and resources (sample size) the number of individuals in each version should be exactly the same due to the central limit theorem and random sampling. Therefore, differences in versions are purely the outcome of slightly different sized samples being assigned to versions, and can be re-weighted to control for sampling variations. The weighting used also has the property that the total number of observations across all versions remains unchanged.

The results are summarised in Table 8, which provides weighted and unweighted choice frequency counts for best and worst choices, as well as further calculations to obtain best minus worst scores and the square root of best totals divided by worst totals.

Table 8: Best-worst results tabulation

Attribute

Bes

t Tot

als

Wor

st T

otal

s

Wei

ghte

d B

est

Wei

ghte

d W

orst

Wei

ghte

d B

est +

1/

41

Wei

ghte

d W

orst

+

1/41

Wei

ghte

d B

est -

W

orst

Wei

ghte

d B

est /

W

orst

Sqrt

Wei

ghte

d B

est /

Wei

ghte

d W

orst

Frequency and convenience of flight schedules and connections

15 0 14.05 0.00 14.08 0.02 14.05 577.14 24.02

Quality of the general infrastructure 21 1 20.13 0.96 20.15 0.98 19.17 20.50 4.53

Accommodation rate for conference delegates by accommodation

18 1 19.53 1.08 19.55 1.11 18.44 17.63 4.20

Venue cost relative to international average 18 1 19.53 1.08 19.55 1.11 18.44 17.63 4.20

Break-out/session rooms 21 3 20.61 2.94 20.63 2.97 17.67 6.95 2.64

Possibility that there might be a subsidy to defray costs 14 2 16.03 2.29 16.05 2.31 13.74 6.94 2.63

Range and availability of audio/visual systems/facilities 13 2 12.18 1.87 12.20 1.90 10.30 6.43 2.54

Plenary room capacity 15 3 15.85 3.17 15.88 3.20 12.68 4.97 2.23

Opportunities for professional networking 15 3 14.05 2.81 14.08 2.83 11.24 4.97 2.23

Ambience and layout of facility 10 2 10.57 2.11 10.59 2.14 8.46 4.95 2.23

Inbound travel barriers and formalities 10 2 9.37 1.87 9.39 1.90 7.49 4.95 2.22

Level of assistance expected from the local chapter of the association

20 5 19.17 4.79 19.20 4.82 14.38 3.98 2.00


9

Attribute

Bes

t Tot

als

Wor

st T

otal

s

Wei

ghte

d B

est

Wei

ghte

d W

orst

Wei

ghte

d B

est +

1/

41

Wei

ghte

d W

orst

+

1/41

Wei

ghte

d B

est -

W

orst

Wei

ghte

d B

est /

W

orst

Sqrt

Wei

ghte

d B

est /

Wei

ghte

d W

orst

Amount of concern over delegate safety/security 11 4 10.80 3.93 10.82 3.95 6.87 2.74 1.66

Percent of convention delegates that can be accommodated on-site

11 5 12.59 5.72 12.62 5.75 6.87 2.19 1.48

Level of assistance expected from the local convention and visitors

12 8 12.06 8.04 12.09 8.07 4.02 1.50 1.22

Local hospitality and friendliness 3 2 3.09 2.06 3.12 2.09 1.03 1.49 1.22

Range of three-star accommodation within 15 minutes of the facility

9 7 8.06 6.27 8.09 6.30 1.79 1.28 1.13

How many years ago the association held a convention here

13 11 11.91 10.08 11.93 10.10 1.83 1.18 1.09

Average standard economy international long-haul return airfares

8 7 7.85 6.87 7.88 6.89 0.98 1.14 1.07

Average standard economy international short-haul return airfares

5 5 4.79 4.79 4.82 4.82 0.00 1.00 1.00

Perception of reliability/customer service 5 5 4.58 4.58 4.60 4.60 0.00 1.00 1.00

Potential risk of convention disruption 7 10 6.87 9.81 6.89 9.84 -2.94 0.70 0.84

% who have to travel domestically 6 9 5.75 8.63 5.78 8.65 -2.88 0.67 0.82

Exhibition space 8 12 9.16 13.74 9.18 13.76 -4.58 0.67 0.82

% of international members who have to travel long haul 5 10 5.28 10.57 5.31 10.59 -5.28 0.50 0.71

Range of five-star accommodation within 15 minutes of the facility

5 11 5.72 12.59 5.75 12.62 -6.87 0.46 0.67

% national members who live locally 3 8 3.09 8.24 3.12 8.27 -5.15 0.38 0.61

Unique physical setting 5 14 4.79 13.42 4.82 13.44 -8.63 0.36 0.60

Unique cultural and social setting 2 6 2.11 6.34 2.14 6.37 -4.23 0.34 0.58

Opportunities for sightseeing/tours 3 9 3.25 9.76 3.28 9.79 -6.51 0.33 0.58

Ball room/dining venues 5 15 4.04 12.12 4.07 12.15 -8.08 0.33 0.58

How good was your previous experience running a convention here

5 15 5.15 15.46 5.18 15.48 -10.30 0.33 0.58

How favourable is the word-of-mouth reputation here 4 13 3.58 11.65 3.61 11.67 -8.06 0.31 0.56

Range of four-star accommodation within 15 minutes of the facility

3 11 3.43 12.59 3.46 12.62 -9.16 0.27 0.52


10

Attribute

Bes

t Tot

als

Wor

st T

otal

s

Wei

ghte

d B

est

Wei

ghte

d W

orst

Wei

ghte

d B

est +

1/

41

Wei

ghte

d W

orst

+

1/41

Wei

ghte

d B

est -

W

orst

Wei

ghte

d B

est /

W

orst

Sqrt

Wei

ghte

d B

est /

Wei

ghte

d W

orst

Average standard economy domestic return airfares 2 9 1.96 8.83 1.99 8.86 -6.87 0.22 0.47

Perceived quality of the food 3 14 3.17 14.80 3.20 14.82 -11.63 0.22 0.46

Typical weather and climate at the time of the convention 2 15 1.92 14.38 1.94 14.40 -12.46 0.13 0.37

Accommodation location relative to airport 1 13 1.11 14.48 1.14 14.51 -13.37 0.08 0.28

Opportunities for recreational activities 1 15 1.06 15.85 1.08 15.88 -14.80 0.07 0.26

Opportunities for entertainment 1 20 0.92 18.32 0.94 18.34 -17.40 0.05 0.23

Opportunities for shopping 0 30 0.00 29.44 0.02 29.47 -29.44 0.00 0.03 In graphical form, the relative importance of the factors is also displayed in Figures 4 and 5. Figure 4

displays the results based on the scale of the square root of weighted best divided weighted worst. Note that the measure for the feature “Frequency and convenience of flight schedules and connections” is likely to be exaggerated due to that feature scoring no worst ratings. Consequently, Figure 5 illustrates the results based on the alternative measure of weighted best minus weighted worst.

Figure 4: BWS importance measure of site selection factors: SQRT (best/worst) scale

0

5

10

15

20

25

30

Freq

uenc

y &

con

veni

ence

of f

light

sch

edul

es &

con

nect

ions

Qua

lity

of th

e ge

nera

l inf

rast

ruct

ure

Acc

omm

odat

ion

rate

for c

onfe

renc

e de

lega

tes

by a

ccom

mod

atio

n

Ven

ue c

ost r

elat

ive

to in

tern

atio

nal a

vera

ge

Bre

ak-o

ut/s

essi

on ro

oms

Pos

sibi

lity

that

ther

e m

ight

be

a su

bsid

y to

def

ray

cost

s

Ran

ge &

ava

ilabi

lity

of a

udio

/vis

ual s

yste

ms/

faci

litie

s

Ple

nary

room

cap

acity

Opp

ortu

nitie

s fo

r pro

fess

iona

l net

wor

king

Am

bien

ce &

layo

ut o

f fac

ility

Inbo

und

trave

l bar

riers

& fo

rmal

ities

Leve

l of a

ssis

tanc

e ex

pect

ed fr

om th

e lo

cal c

hapt

er o

f the

ass

oc

Am

ount

of c

once

rn o

ver d

eleg

ate

safe

ty/s

ecur

ity

Per

cent

of c

onve

ntio

n de

lega

tes

that

can

be

acco

mm

odat

ed o

n-si

te

Leve

l of a

ssis

tanc

e ex

pect

ed fr

om th

e lo

cal c

onve

ntio

n &

vis

itors

Loca

l hos

pita

lity

& fr

iend

lines

s

Ran

ge o

f thr

ee-s

tar a

ccom

mod

atio

n w

ithin

15

min

s of

the

faci

lity

How

man

y ye

ars

ago

the

asso

ciat

ion

held

a c

onve

ntio

n he

re

Ave

rage

sta

ndar

d ec

onom

y in

tern

atio

nal l

ong-

haul

retu

rn a

irfar

es

Ave

rage

sta

ndar

d ec

onom

y in

tern

atio

nal s

hort-

haul

retu

rn a

irfar

es

Per

cept

ion

of re

liabi

lity/

cust

omer

ser

vice

Pot

entia

l ris

k of

con

vent

ion

disr

uptio

n

% w

ho h

ave

to tr

avel

dom

estic

ally

Exh

ibiti

on s

pace

% o

f int

erna

tiona

l mem

bers

who

hav

e to

trav

el lo

ng h

aul

Ran

ge o

f fiv

e-st

ar a

ccom

mod

atio

n w

ithin

15

min

s of

the

faci

lity

% n

atio

nal m

embe

rs w

ho li

ve lo

cally

Uni

que

phys

ical

set

ting

Uni

que

cultu

ral &

soc

ial s

ettin

g

Opp

ortu

nitie

s fo

r sig

htse

eing

/tour

s

Bal

l roo

m/d

inin

g ve

nues

How

goo

d w

as y

our p

revi

ous

expe

rienc

e ru

nnin

g a

conv

entio

n he

re

How

favo

urab

le is

the

wor

d-of

-mou

th re

puta

tion

here

Ran

ge o

f fou

r-sta

r acc

omm

odat

ion

with

in 1

5 m

ins

of th

e fa

cilit

y

Ave

rage

sta

ndar

d ec

onom

y do

mes

tic re

turn

airf

ares

Per

ceiv

ed q

ualit

y of

the

food

Typi

cal w

eath

er &

clim

ate

at th

e tim

e of

the

conv

entio

n

Acc

omm

odat

ion

loca

tion

rela

tive

to a

irpor

t

Opp

ortu

nitie

s fo

r rec

reat

iona

l act

iviti

es

Opp

ortu

nitie

s fo

r ent

erta

inm

ent

Opp

ortu

nitie

s fo

r sho

ppin

g

SQR

T(B

/W)


11

Figure 5: BWS importance measure of site selection factors: weighted best – weighted worst

-40

-30

-20

-10

0

10

20

30Fr

eque

ncy

& c

onve

nien

ce o

f flig

ht s

ched

ules

& c

onne

ctio

ns

Qua

lity

of th

e ge

nera

l inf

rast

ruct

ure

Acc

omm

odat

ion

rate

for c

onfe

renc

e de

lega

tes

by a

ccom

mod

atio

n

Ven

ue c

ost r

elat

ive

to in

tern

atio

nal a

vera

ge

Bre

ak-o

ut/s

essi

on ro

oms

Pos

sibi

lity

that

ther

e m

ight

be

a su

bsid

y to

def

ray

cost

s

Ran

ge &

ava

ilabi

lity

of a

udio

/vis

ual s

yste

ms/

faci

litie

s

Ple

nary

room

cap

acity

Opp

ortu

nitie

s fo

r pro

fess

iona

l net

wor

king

Am

bien

ce &

layo

ut o

f fac

ility

Inbo

und

trave

l bar

riers

& fo

rmal

ities

Leve

l of a

ssis

tanc

e ex

pect

ed fr

om th

e lo

cal c

hapt

er o

f the

ass

oc

Am

ount

of c

once

rn o

ver d

eleg

ate

safe

ty/s

ecur

ity

Per

cent

of c

onve

ntio

n de

lega

tes

that

can

be

acco

mm

odat

ed o

n-si

te

Leve

l of a

ssis

tanc

e ex

pect

ed fr

om th

e lo

cal c

onve

ntio

n &

vis

itors

Loca

l hos

pita

lity

& fr

iend

lines

s

Ran

ge o

f thr

ee-s

tar a

ccom

mod

atio

n w

ithin

15

min

s of

the

faci

lity

How

man

y ye

ars

ago

the

asso

ciat

ion

held

a c

onve

ntio

n he

re

Ave

rage

sta

ndar

d ec

onom

y in

tern

atio

nal l

ong-

haul

retu

rn a

irfar

es

Ave

rage

sta

ndar

d ec

onom

y in

tern

atio

nal s

hort-

haul

retu

rn a

irfar

es

Per

cept

ion

of re

liabi

lity/

cust

omer

ser

vice

Pot

entia

l ris

k of

con

vent

ion

disr

uptio

n

% w

ho h

ave

to tr

avel

dom

estic

ally

Exh

ibiti

on s

pace

% o

f int

erna

tiona

l mem

bers

who

hav

e to

trav

el lo

ng h

aul

Ran

ge o

f fiv

e-st

ar a

ccom

mod

atio

n w

ithin

15

min

s of

the

faci

lity

% n

atio

nal m

embe

rs w

ho li

ve lo

cally

Uni

que

phys

ical

set

ting

Uni

que

cultu

ral &

soc

ial s

ettin

g

Opp

ortu

nitie

s fo

r sig

htse

eing

/tour

s

Bal

l roo

m/d

inin

g ve

nues

How

goo

d w

as y

our p

revi

ous

expe

rienc

e ru

nnin

g a

conv

entio

n he

re

How

favo

urab

le is

the

wor

d-of

-mou

th re

puta

tion

here

Ran

ge o

f fou

r-sta

r acc

omm

odat

ion

with

in 1

5 m

ins

of th

e fa

cilit

y

Ave

rage

sta

ndar

d ec

onom

y do

mes

tic re

turn

airf

ares

Per

ceiv

ed q

ualit

y of

the

food

Typi

cal w

eath

er &

clim

ate

at th

e tim

e of

the

conv

entio

n

Acc

omm

odat

ion

loca

tion

rela

tive

to a

irpor

t

Opp

ortu

nitie

s fo

r rec

reat

iona

l act

iviti

es

Opp

ortu

nitie

s fo

r ent

erta

inm

ent

Opp

ortu

nitie

s fo

r sho

ppin

g

Wei

ghte

d B

est -

Wei

ghte

d W

orst

These results provide a clear differentiation in importance, showing that the twelve most important site selection factors are: • Frequency and convenience of flight schedules and connections • Quality of the general infrastructure • Accommodation rate for conference delegates by accommodation • Venue cost relative to international average • Break-out/session rooms • Possibility that there might be a subsidy to defray costs • Range and availability of audio/visual systems/facilities • Plenary room capacity • Opportunities for professional networking • Ambience and layout of facility • Inbound travel barriers and formalities • Level of assistance expected from the local chapter of the association

The ten least important factors were found to be: • How good was your previous experience running a convention here • How favourable is the word-of-mouth reputation here • Range of four-star accommodation within 15 minutes of the facility • Average standard economy domestic return airfares • Perceived quality of the food • Typical weather and climate at the time of the convention • Accommodation location relative to airport • Opportunities for recreational activities • Opportunities for entertainment • Opportunities for shopping


12

APPENDIX A: ONLINE SURVEY


13


14


15


16


17


18


19


20


21


22

APPENDIX B: EXPERIMENTAL DESIGN TABLE

List of Convention Site Selection Features with Levels (Ranges) Convention Site Scenario: Factor Levels

10 - 70 % of members have to travel domestically 90 - 30 % of members have to travel internationally

20 - 80 % of national members live locally (no need to fly) 80 - 20 % of national members travel by domestic air

Proximity of the site to convention participants 1. National v. international: 2. Travel by national members: 3. Travel by international members: 20 - 80 % of international members travel short-haul

80 - 20 % of international members travel long-haul

$200 - $500

$600 - $1,200

Available average standard economy return airfares 4. Domestic air travel: 5. International short-haul: 6. International long-haul: $1,500 - $3,000

7. Frequency and convenience of flight schedules and connections frequent, direct flights or infrequent and/or indirect flights

8. Inbound travel barriers and formalities no cost, simple, straight-forward or there is a fee, and visa processing can be slow at times

9. Percentage of convention delegates that can be accommodated on-site vs off-site

on-site accommodation: 100% - 0% off-site accommodation: 0% - 100%

2 - 8+ hotel(s)

1 - 4+ hotel(s)

Range (by class) of accommodation at/within 15 minutes of the facility 10. Three star: 11. Four star: 12. Five star: 0 - 3 hotel(s)

13. Representative accommodation rates available to conference delegates by class of accommodation (room only)

three star: $90 - $150 four star: $120 - $210 five star: $180 - $330

14. Accommodation location re airport 10 - 40 minute taxi ride

15. Venue cost re international average 40% below to 40% above

16. Exhibition space adequate or exceptional

17. Plenary room adequate or exceptional

18. Break-out/session rooms adequate or exceptional

19. Ball room/dining venues adequate or exceptional

20. Overall ambience and layout adequate or exceptional

21. Overall perception of reliability and customer service adequate or exceptional

22. Range and availability of audio/visual systems and facilities adequate or exceptional

23. Perceived quality of food below average to exceptional

24. Opportunities for entertainment little or many

25. Opportunities for shopping little or many

26. Opportunities for sightseeing/tours little or many


23

27. Opportunities for recreational activities little or many

28. Opportunities for professional networking little or many

29. A unique physical setting No or yes

30. A unique social and cultural setting No or yes

31. Typical weather and climate at the time of the convention warm and humid/warm and dry/cool and damp/cool and dry

32. The quality of the general infrastructure adequate or exceptional

33. The local hospitality and friendliness adequate or exceptional

34. Expected level of assistance from the local chapter of the association adequate or exceptional

35. Expected level of assistance from the local convention and visitors bureau adequate or exceptional

36. Possibility of a subsidy to defray costs if convention has a major economic impact Never/slight/moderate/significant

37. Concern over delegate safety/security Little or there could be risks

38. Your previous experience running a convention at the site None/poor/favorable/exceptional

39. Word-of-mouth reputation of the site among convention planners in general None/poor/favorable/exceptional

40. The association held its convention at this site Never/many years ago/a few years ago/very recently

41. Potential risk of convention disruption (eg labor strikes, political instability, etc.) Little or there could be disruptions

Overall layout of the best-worst comparison sets by block Each block (1 to 82) is a comparison set – the feature wording on the right is what is being compared in each block y the respondents. The task layout for block 1 below is shown on the last page.

Block Feature #

in each block

Feature description to be displayed to survey respondents

1 2 Proportion of national members who live locally versus those who have to fly

1 11 Range of four-star accommodation within 15 minutes of the facility

1 18 Break-out session rooms

1 17 Plenary room

1 38 How good was your previous experience running a convention at this site

2 3 Proportion of international members who have to travel long- versus short-haul

2 12 Range of five-star accommodation within 15 minutes of the facility

2 20 Ambience and layout of facility

2 19 Ball-room/dining venues


24

Block Feature #

in each block


2 39 How favorable is the word-of-mouth reputation of this site among convention planners in general

3 4 Average standard economy domestic return airfares

3 13 Accommodation rate for conference delegates by accommodation class (room only)

3 21 Perception of reliability/customer service


3 40 How many years ago the association held its convention at this site

4 5 Average standard economy international short-haul return airfares

4 14 Accommodation location relative to airport

4 22 Range and availability of audio/visual systems/facilities


4 41 Potential risk of convention disruption

5 6 Average standard economy return international long-haul airfares

5 15 Venue cost relative to international average

5 23 Perceived quality of the food


5 1 Proportion of members who have to travel domestically versus internationally

6 7 Frequency and convenience of flight schedules and connections

6 16 Exhibition space

6 24 Opportunities for entertainment



7 8 Inbound travel barriers and formalities

7 17 Plenary room

7 25 Opportunities for shopping



8 9 Percent of convention delegates that can be accommodated on- versus off-site


8 26 Opportunities for sightseeing/tours



9 10 Range of three-star accommodation within 15 minutes of the facility



25

Block Feature #

in each block


9 27 Opportunities for recreational activities





10 28 Opportunities for professional networking





11 29 Unique physical setting





12 30 Unique cultural and social setting





13 31 Typical weather and climate at the time of the convention





14 32 Quality of the general infrastructure





15 33 Local hospitality and friendliness



16 17 Plenary room


26

Block Feature #

in each block



16 34 Level of assistance expected from the local chapter of the association





17 35 Level of assistance expected from the local convention and visitors bureau





18 36 Possibility that there might be a subsidy to defray costs if convention has a major economic impact





19 37 Amount of concern over delegate safety/security












21 17 Plenary room






27

Block Feature #

in each block



































28

Block Feature #

in each block




































29

Block Feature #

in each block

























40 17 Plenary room











30

Block Feature #

in each block



































31

Block Feature #

in each block




































32

Block Feature #

in each block








56 17 Plenary room




























33

Block Feature #

in each block







63 17 Plenary room

















66 17 Plenary room




67 17 Plenary room








34

Block Feature #

in each block






































35

Block Feature #

in each block























79 17 Plenary room













36

Block Feature #

in each block





82 20 Ambience and layout of facility Below are the randomised blocks that make up each version of the survey. There are nine survey versions – eight of these versions have exactly nine blocks or sets of comparisons, and the ninth version has 10 blocks or sets of comparisons. 9 x 8 = 72 + 10 = 82, which is the total number of blocks above.

Version Blocks in Version Version Blocks in

Version Version Blocks in Version

1 60 4 43 7 13

1 58 4 46 7 34

1 64 4 8 7 61

1 33 4 44 7 1

1 70 4 41 7 55

1 71 4 77 7 62

1 7 4 22 7 66

1 18 4 14 8 5

1 28 5 63 8 38

2 25 5 11 8 52

2 56 5 42 8 51

2 36 5 19 8 26

2 45 5 37 8 47

2 30 5 15 8 67

2 31 5 20 8 27

2 21 5 59 8 39

2 24 5 57 9 72

2 50 6 82 9 29

3 80 6 12 9 69

3 3 6 65 9 54

3 2 6 40 9 73

3 68 6 81 9 35

3 32 6 74 9 16

3 17 6 48 9 4

3 79 6 53 9 49


37

3 78 6 23 9 10

3 6 7 75

4 9 7 76

Translation of Block 1 into a Survey Question This is the layout of the survey questions. Versions 1 to 8 have exactly nine of these comparison questions, and Version 9 has ten comparison questions. Thus, to be clear, there are 8 more comparison questions that make up a version in the case of Versions 1 to 8, with nine more comparison questions like the one below for Version 9.

The most important feature in this set (

only one)

Question 1: Compare the features shown below and choose the one most important and the one

least important feature in the set.

The least important feature in this set (

only one)

Proportion of national members who live locally versus those who have to fly

Range of four-star accommodation within 15 minutes of the facility

Break-out session rooms

Plenary room

How good was your previous experience running a convention at this site


38

REFERENCES

Ben-Akiva, M. and Lerman, S.R. (1985). Discrete Choice Analysis, MIT Press, Cambridge, Massachusetts. Cohen, S. and Neira, L. (2003). “Measuring Preference for Product Benefits Across Countries: Overcoming

Scale Usage Bias with Maximum Difference Scaling”, 2003 ESOMAR Conference. Crouch, G.I. and Ritchie, J.R.B. (1998). “Convention Site Selection Research: A Review, Conceptual Model,

and Propositional Framework”, Journal of Convention and Exhibition Management, 1 (1), pp.49-69. Crouch, G.I. and Louviere, J.J. (2001). “A Review of Choice Modelling Research in Tourism, Hospitality and

Leisure”, Consumer Psychology of Tourism, Hospitality and Leisure – Volume 2, J. A. Mazanec, G. I. Crouch, J. R. B. Ritchie, and A. G. Woodside (eds.), CABI Publishing, Wallingford, UK.

Crouch, G.I. and Jordan J. Louviere (2004a). “The Determinants of Convention Site Selection: A Logistic Choice Model from Experimental Data”, Journal of Travel Research, 43 (2), pp.118-130.

Crouch, Geoffrey I. and Louviere, J.J. (2004b). Convention Site Selection: Determinants of Destination Choice in the Australian Domestic Conventions Sector, Technical Report for the CRC for Sustainable Tourism Pty. Ltd., Griffith University, Gold Coast, Queensland.

Finn, A. and Louviere, J.J. (1992). “Determining the Appropriate Response to Evidence of Public Concern: The Case of Food Safety”, Journal of Public Policy and Marketing. 11 (2), pp.12-25.

Louviere, J.J. (1994), “Conjoint Analysis”, in Advanced Marketing Research, R. Bagozzi (ed.), Blackwell Publishers, Cambridge, MA.

Louviere, J.J., Hensher, D.A. and Swait, J.D. (2000). Stated Choice Methods: Analysis and Applications, Cambridge University Press, Cambridge, UK.

Louviere, J.J. and Woodworth, G. (1983). “Design and Analysis of Simulated Consumer Choice or Allocation Experiments: An Approach Based on Aggregate Data”, Journal of Marketing Research, 20, pp.350-367.

Marley, A.A.J. and Louviere, J.J. (2005). “Some Probabilistic Models of Best, Worst, and Best-Worst Choices,” Journal of Mathematical Psychology, 49 (6), pp.464-480.

McIntosh, E. and Louviere, J.J. (2002). “Separating Weight and Scale Value: an Exploration of Best-attribute Scaling in Health Economics”, unpublished paper presented at the Health Economics Study Group, Odense, Dinamarca.

Swait, J.D. and Louviere, J.J. (1993). “The Role of the Scale Parameter in the Estimation and Comparison of Multinomial Logit Models”, Journal of Marketing Research, 30 (3), pp.305-314.


39

AUTHORS

Geoffrey I. Crouch Geoffrey Crouch is a Professor of Marketing in the School of Business at La Trobe University. His research interests broadly fall into the area of tourism marketing. Topics of particular interest include tourist choice modelling, destination marketing and competitiveness, tourism psychology and consumer behaviour, and space tourism. He was also an elected member of the Board of Directors of the Calgary Convention and Visitors Bureau. Professor Crouch serves on a number of Editorial Review Boards of scholarly journals and is Co-Editor-in-Chief of the journal Tourism Analysis. Professor Crouch was the Organising Chair of the Third Symposium on the Consumer Psychology of Tourism, Hospitality and Leisure in 2003. He is an elected Fellow and Treasurer of the International Academy for the Study of Tourism, and is a member of several Australian and international scholarly associations in marketing and tourism management. Email: [email protected] Jordan J. Louviere Jordan Louviere is a Professor of Marketing in the School of Marketing at the University of Technology, Sydney. Jordan is internationally recognised as an expert in conjoint analysis and consumer choice modelling. He developed and pioneered the design and analysis of choice experiments and teaches courses in choice modelling and design of choice experiments. Jordan has authored or co-authored more than 150 scholarly publications, including books, book chapters, journal articles and working papers that deal with Consumer Choice Models, Design of Experiments, Discrete Multivariate Analysis, Marketing Research Methods, Consumer Behaviour, Marketing Strategy and Planning, Transportation Planning, Demand Forecasting, Brand Equity Analysis, Measurement of Service Quality, Retailing and Consumer Services, and Marketing Management, to name a few. Email: [email protected]


40

The Sustainable Tourism Cooperative Research Centre (STCRC) is

established under the Australian Government’s Cooperative Research

Centres Program. STCRC is the world’s leading scientific institution

delivering research to support the sustainability of travel and tourism -

one of the world’s largest and fastest growing industries.

Research Programs

Tourism is a dynamic industry comprising many sectors from accommodation to hospitality, transportation to retail and many

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more likely to prosper.

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examined simultaneously.

Website: www.crctourism.com.au I Bookshop: www.crctourism.com.au/bookshop I Email: [email protected]

Postgraduate Students: STCRC’s Education Program recruits high quality postgraduate students and provides scholarships,

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Education

STCRC uses its research network, spin-off companies and partnerships to extend knowledge and deliver innovation to the

tourism industry. STCRC endeavours to secure investment in the development of its research into new services, technologies

and commercial operations.

Australia’s CRC Program

The Cooperative Research Centres (CRC) Program brings

together researchers and research users. The program

maximises the benefits of research through an enhanced

process of utilisation, commercialisation and technology

transfer. It also has a strong education component

producing graduates with skills relevant to industry

needs.

Extension & Commercialisation

CAIRNSNQ CoordinatorProf Bruce Prideaux

Tel: +61 7 4042 1039

[email protected] CoordinatorMs Alicia Boyle

Tel: + 61 8 8946 7267

[email protected] QLD CoordinatorMr Noel Scott

Tel: +61 7 3381 1024

[email protected]

LISMORENSW CoordinatorRegional Tourism ResearchDr Jeremy Buultjens

Tel: +61 2 6620 3382

[email protected]

SYDNEYSustainable DestinationsMr Ray Spurr

Tel: +61 2 9385 1600

[email protected] CoordinatorAdjunct Prof Malcolm Wells

Tel: + 61 3 6226 7686

[email protected]

CANBERRAACT CoordinatorDr Brent Ritchie

Tel: +61 2 6201 5016

[email protected]

ADELAIDESA CoordinatorGary Crilley

Tel: +61 8 8302 5163

[email protected]

PERTHWA CoordinatorDr Jeremy Northcote

Tel: + 61 8 6304 2307

[email protected]

MELBOURNEVIC CoordinatorA/Prof Sue Beeton

Tel: +61 3 9479 3500

[email protected]

NATIONAL NETWORK

Sustainable Tourism Cooperative Research Centre

A U S T R A L I A N C A P I T A L T O U R I S M

S P I N - O F F C O M P A N I E SU N I V E R S I T Y P A R T N E R SI N D U S T R Y P A R T N E R S

CRC for Sustainable Tourism Pty Ltd

ABN 53 077 407 286

PMB 50 Gold Coast MC

Queensland 9726 Australia

Telephone: +61 7 5552 8172

Facsimile: +61 7 5552 8171

Chairman: Sir Frank Moore AO

Chief Executive: Prof Terry De Lacy

Director of Research: Prof Leo Jago

Website: www.crctourism.com.au

Bookshop: www.crctourism.com.au/bookshop

Email: [email protected]

INTERNATIONAL CONVENTION SITE SELECTION a further ......A Further Analysis of Factor Importance...

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