Tourism ReviewHow to attract more tourists?Hiromi Kamata Yuki Misui Hirotaka Yamauchi

Article information:To cite this document:Hiromi Kamata Yuki Misui Hirotaka Yamauchi, (2010),"How to attract more tourists?", Tourism Review, Vol. 65 Iss 2 pp. 28 - 40Permanent link to this document:http://dx.doi.org/10.1108/16605371011061606

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How to attract more tourists?

Hiromi Kamata, Yuki Misui and Hirotaka Yamauchi

Abstract

Purpose – The objectives of this paper are twofold. First, to develop a framework for estimating the

attractiveness of spas in Japan. Second, based on the results of the estimation, to consider how to

attract more tourists.

Design/methodology/approach – Attractiveness is defined by the results of questionnaires,

composed of a spa’s characteristics, cost and accessibility. Using these aspects of the destination

as measures of its attractiveness, the paper estimates attractiveness conducted with a destination

choice model.

Findings – The results of the estimation provide some findings. First, consumers may value the quality

of hot springs, with atmosphere as one of the most important elements. Second, the attractiveness

varies because of accessibility or cost depending on the origin of each consumer. The management of

each spa should consider where their customers are from; they also need to recognize which spas are

their competitors.

Originality/value – There are many previous studies dealing with the estimation of attractiveness.

However, most of these attractiveness studies do not include cost and accessibility. The attractiveness

measures of this study include cost and accessibility, and provide examples of varying degrees of cost

and accessibility. In this sense, it can be said that this study has originality.

Keywords Tourism, Product management, Consumers, Product image, Japan, Leisure facilities

Paper type Research paper

1. Introduction

The objectives of this paper are the following: first, develop a framework for estimating the

attractiveness of spas in Japan. Second, based on the result of estimation of attractiveness,

consider how to attract more tourists. In this paper, a spa is defined as an ‘‘onsen’’, which is a

Japanese-style spa and refers not only to the hot springs themselves but also to the areas

surrounding them.

As is well known, there are many onsen all over Japan. For most onsen, like other tourist

destinations, local governments or tourism organizations have attempted to attract more

tourists. But, they do not know how attractive these are compared with other onsen, nor do

they have efficient tools to attract tourists. As a result, they repeat the process of trial and

error in their policy making.

It would be helpful for answering various questions in tourism if we could obtain information

by analyzing tourist behavior. Research on consumer behavior contributes to the choice

model in marketing. By identifying consumer behavior through the choice model, it is

possible to understand trends in consumer preferences and also to obtain information on

market segmentation and the development of new products.

Based on the above, we have attempted to develop a framework for estimating the

attractiveness of onsen. We interpret the reason for choice of tourist destination as

PAGE 28 j TOURISM REVIEW j VOL. 65 NO. 2 2010, pp. 28-40, Q Emerald Group Publishing Limited, ISSN 1660-5373 DOI 10.1108/16605371011061606

Hiromi Kamata is Assistant

Professor at Bunri

University of Hospitality,

Sayama City, Japan.

Yuki Misui is Associate

Professor at Takasaki City

University of Economics,

Takasaki, Japan. Hirotaka

Yamauchi is Professor at

the Graduate School of

Commerce and

Management, Hitotsubashi

University, Tokyo, Japan.

Received: 28 February 2009Accepted: 31 August 2009

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attractiveness and attempt to estimate the attractiveness of tourist destinations using

Lancaster’s approach to evaluate consumer utility. This paper is organized as follows. First,

we review previous studies that have applied Lancaster’s approach to destination choice.

Second, we develop a framework for estimating the attractiveness of tourist destinations.

Next, we consider some examples and suggest some implications for tourism strategy.

Contribution and future assignments will be considered in the conclusion.

2. Lancaster’s approach and destination choice in tourism

As various studies have found, tourist destinations have many characteristics. But,

consumers may not clearly describe why they chose a particular destination, because their

reasons are composed of many factors[1].

Consumer behavior is based on the concept of utility maximization. This means that

consumers select the best choice from various options to maximize their utility. However,

because of conventional utility maximization has been defined as the simple situation in

which a consumer consumes goods per se, it cannot describe tourist behavior that is

complicated by various factors. This problem can be solved by Lancaster’s approach

(Lancaster (1966)). It defined consumers as consuming a combination of commodities of

goods, and also derived a utility function for this definition.

Rugg (1973) used Lancaster’s approach to show that tourists choose destinations to

maximize their utility within the constraints of time and income. A consumer chooses the

optimal bundle of characteristics under the constraints of income and time. Depend on

the consumer’s optimal bundle of characteristics, it is limited by income and time is

redundant or it is limited by time and income is redundant. Based on Rugg (1973), Morley

(1992) and Seddighi and Theocharous (2002) considered models of tourist behavior. This

paper will be conducted an empirical analysis of destination choice based on these

studies.

3. Empirical analysis: estimating the attractiveness of onsen

The object of a visit to any onsen is almost the same: to relax, to eat delicious local foods, and

to enjoy other activities. However, tourists distinguish each onsen by some means. They

probably choose the best combination of commodities to maximize their utility. Based on the

above, a framework will be developed for estimating the attractiveness of onsen in Japan.

3.1 Definition of attractiveness

Before developing a framework, it needs to define ‘‘attractiveness.’’ Most previous studies

(Takahashi and Igarashi (1990), Muroya (1998), Hakuhodo (2004)) considered

attractiveness excluding accessibility and cost. Although estimating intrinsic

attractiveness is important, it cannot adequately describe the utility of consumers who

consume the ‘‘commodity’’ of an onsen. As easy to consider, accessibility and cost are

negative elements for consumer’s choice and attractiveness varies because of them. The

reason of this, here, it defines attractiveness as ‘‘onsen’s characteristics,’’ ‘‘accessibility’’

and ‘‘cost.’’ As is well known, like other tourist destinations, ‘‘onsen’s characteristics’’

includes various factor; onsen’s quality, atmosphere, foods and so on. What the factors

construct ‘‘onsen’s characteristics’’ will be analyzed in 3-2.

3.2 Framework

Our framework is as follows (see Figure 1).

The framework comprises three steps:

1. Factor analysis of an onsen’s characteristics:

B Objectives. To derive some characteristics of an onsen; and to compile a list of

evaluation criteria for an onsen.

B Method. Questionnaire survey (respondents are travel specialists).

VOL. 65 NO. 2 2010 jTOURISM REVIEWj PAGE 29

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2. Estimation of a utility function using conjoint analysis:

B Objective. To understand the factor that is the most important for consumers.

B Method. Conjoint analysis (respondents are consumers). We estimate the weight of

factors by logit model with the results.

3. Estimation of the attractiveness of each onsen:

B Objective. To estimate the attractiveness of each onsen.

B Method. To assign the result of utility function estimation to an evaluation list of onsen.

Factor analysis of an onsen’s characteristics

The objective of this research was to:

B derive some characteristics of onsen; and

B compile an evaluation list of onsen.

To derive some characteristics of onsen

Methodology. To derive some characteristics of onsen. There are many and various types

of onsen in Japan: traditional, resort and so on. Because of this, in this paper, it chooses

20 popular onsen from all regions of Japan (Table I and Figure 2) for the sample.

Table I List of 20 onsen

No. Onsen Prefecture

1. Johzankei Hokkaido2. Noboribetsu Hokkaido3. Gin-zan Yamagata4. Akiu Miyagi5. Iizaka Fukushima6. Atami Shizuoka7. Shu-zen-ji Shizuoka8. Hakone-yumoto Kanagawa9. Kusatsu Gunma10. Shirahone Nagano11. Shibu Nagano12. Gero Gifu13. Wakura Ishikawa14. Kinosaki Hyogo15. Shirahama Wakayama16. Tama-tsukuri Shimane17. Dogo Ehime18. Yu-fu-in Oita19. Beppu Oita20. Ibusuki Kagoshima

Figure 1 Framework to estimate attractiveness

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Obtaining the characteristics of onsen, it applies factor analysis using the results of a

questionnaire survey. In the questionnaire, 15 elements based on previous research

(Table II) were employed.

In the questionnaire, respondents were asked to score each of the 15 elements for each

onsen. The score was divided into three levels (maximum 3, average 2, minimum 1).

Respondents can be described as travel specialists who work for travel agencies, and they

had sufficient knowledge of onsen in Japan and could evaluate them fairly.

Descriptive statistics. The descriptive statistics are shown in Table III; 110 responses of the

questionnaire were obtained.

Factor analysis. Factor analysis[2] was performed on the 15 elements to derive the onsen’s

characteristic. As a result, using a varimax rotation, four factors were obtained, which

indicates logical groupings of the onsen’s characteristics shown in Table IV. The ratio of

cumulative contribution is 86.0 per cent.

From the result, these factors were interpreted as follows:

1. ‘‘Amusement’’. The major elements in this factor are ‘‘size of accommodation’’,

‘‘restaurants and pubs’’, ‘‘events’’, and so on. Tourists are able to enjoy facilities or various

events. This factor can be called as ‘‘amusement’’.

2. ‘‘Atmosphere’’. The major elements in this factor are ‘‘traditional atmosphere’’, ‘‘distinct

local style’’, ‘‘strolling areas’’ and ‘‘harmony within onsen area’’. Tourists are able to enjoy

Figure 2 Location of onsen

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walking around the onsen area and experiencing the traditional atmosphere. This factor

can be called ‘‘atmosphere’’.

3. ‘‘Marketing power’’. The major elements in this factor are ‘‘quality of accommodation’’,

‘‘environmental efforts’’ and ‘‘local foods’’. This can be described as ‘‘marketing power’’.

It is especially strong in ‘‘Yu-fu-in’’ which is very famous for providing high-quality service.

4. ‘‘Quality of hot springs and environment’’. The major elements in this factor are ‘‘quality of

hot springs’’, ‘‘nature and scenery’’, and ‘‘volume of hot springs’’. Tourists are able to

enjoy high-quality hot springs. This factor can be called as ‘‘Quality’’ (see Table V).

Table II List of 15 elements

No. Elements

1. Quality of springs2. Volume of onsen a

3. Size of accommodation4. Quality of accommodation5. Harmony within the onsen6. Strolling areas7. Esthetic and medical services8. Preservation of environment9. Local foods10. Events11. Restaurants and pubs12. Nature and scenery13. Lively atmosphere14. Distinct local style15. Traditional atmosphere

Note: a‘‘Volume’’ means liters of spring water per minutes

Table III Descriptive statistics

Elements Sample Minimum Maximum Average SD

1. Quality of hot springs 20 1.68 2.96 2.22 0.382. Volume of onsen 20 1.97 2.84 2.26 0.283. Size of accommodation 20 1.22 2.9 2.32 0.484. Quality of accommodation 20 1.77 2.78 2.17 0.255. Harmony within onsen 20 1.8 2.72 2.20 0.286. Strolling areas 20 1.57 2.77 2.08 0.377. Esthetic and medical services 20 1.67 2.19 1.85 0.128. Preservation of environment 20 1.74 2.29 1.95 0.119. Local foods 20 1.61 2.33 2.02 0.1710. Events 20 1.74 2.54 2.11 0.2311. Restaurants and pubs 20 1.44 2.42 1.95 0.2812. Nature and scenery 20 1.82 2.63 2.26 0.2213. Lively atmosphere 20 1.44 2.53 1.96 0.3114. Distinct local style 20 1.51 2.09 1.83 0.1715. Traditional atmosphere 20 1.44 2.71 2.12 0.30

Note: SD ¼ Standard deviation

Table IV Result of factor analysis

Contribution of each factor (%)Factors Cumulative contribution (%) 1 2 3 4

4 86.0 28.1 23.3 20.0 14.6

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Four factors were derived from factor analysis. But factor 3 was excluded because it was

restricted to ‘‘Yu-fu-in’’ as shown in Table VI. Therefore, it employed the other three factors:

’’amusement’’, ‘‘atmosphere’’ and ‘‘quality’’ for ‘‘onsen’s characteristics’’.

Compiling an evaluation list of onsen

For onsen’s characteristics, 15 elements are categorized according to three factors by the

result of factor analysis (Figure 3.) Based on Figure 3, evaluation list of each onsen is

compiled from the results of the questionnaire survey (Table VII).

Table V Ranked elements of each factor (a part of the result)

Factor 11. Size of accommodation 0.9292. Restaurants and pubs 0.9023. Events 0.8424. Lively atmosphere 0.8395. Volume of onsen 0.678Factor 21. Traditional atmosphere 0.8772. Distinct local style 0.8143. Strolling areas 0.7764. Harmony within onsen 0.7545. Restaurants and pubs 0.387Factor 31. Quality of accommodation 0.8282. Preservation of environment 0.7983. Local foods 0.6414. Nature and scenery 0.5205. Harmony within onsen 0.503Factor 41. Quality of hot spring 0.8572. Nature and scene 0.6993. Volume of onsen 0.6234. Esthetic and medical services 0.4195. Preservation of environment 0.399

Table VI Ranking of onsen on each factor (a part of the result)

Factor 11. Kusatsu 1.3222. Beppu 1.2763. Atami 1.2304. Dogo 0.8795. Hakone-yumoto 0.837Factor 21. Dogo 1.9842. Gin-zan 1.4543. Kinosaki 1.4524. Kusatsu 1.0345. Beppu 0.740Factor 31. Yu-fu-in 2.8202. Wakura 0.8373. Ibusuki 0.7034. Tama-tsukuri 0.6495. Kinosaki 0.539Factor 41. Noboribetsu 2.0212. Kusatsu 1.7403. Shirahone 1.3864. Beppu 0.9845. Ibusuki 0.590

VOL. 65 NO. 2 2010 jTOURISM REVIEWj PAGE 33

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Estimation of utility function using conjoint analysis

The objective is to obtain results revealing the factors that are the most important to

consumers when they choose a destination. In this paper, the conjoint analysis method was

employed to estimate the weight of factors by logit model.

Table VII Evaluation list of onsen

Factor

QualityAmusement Atmosphere

Content elements of each factor

Quality of hot springs, volumeof onsen, preservation of

environment and nature andscenery

Size of accommodation,esthetic and medical

services, events, restaurantsand pubs and lively

atmosphere

Quality of accommodation,harmony within the onsen,strolling areas, local foods,

distinct local style andtraditional atmosphere

1. Johzankei 2.05 1.94 1.692. Noboribetsu 2.55 2.19 2.013. Gin-zan 2.16 1.58 2.164. Akiu 1.99 1.88 1.865. Iizaka 1.86 1.81 1.766. Atami 1.82 2.26 1.807. Shu-zen-ji 2.06 1.92 2.168. Hakone-yumoto 2.20 2.21 2.089. Kusatsu 2.59 2.47 2.3710. Shirahone 2.32 1.58 1.9211. Shibu 2.21 2.08 2.0712. Gero 2.09 1.65 2.0013. Wakura 2.06 2.15 2.0514. Kinosaki 2.15 2.10 2.4215. Shirahama 2.10 2.09 1.9816. Tama-tsukuri 2.08 1.98 2.0817. Dogo 2.12 2.35 2.3718. Yu-fu-in 2.40 2.15 2.4119. Beppu 2.38 2.34 2.1520. Ibusuki 2.30 2.08 2.07

Note: Number of evaluations is an average value by travel specialists

Figure 3 Hierarchy structure of attractiveness of onsen

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First, it defined the utility function based on the attractiveness that was described above

(Figure 3):

Ui ¼ V i þ 1i

V i ¼ a1 þ a2x2 þ a3x3 þ a4x4 þ a5x5ð7Þ

Vi is a deterministic term, and 1i is a random term.Vi is calculated from the following elements: x1,

quality; x2, amusement; x3, atmosphere; x4, accessibility (one way travel time, which remains the

same regardless of mode); and x5, cost (per person: transportation fee, accommodation charge

and miscellaneous costs are included). The first three explanatory variables (x1, x2, x3) are

deterministic terms for the ‘‘onsen’s characteristics,’’ derived from factor analysis.

Based on the utility function defined above, a questionnaire survey of consumers was

designed. This preference enabled us to set virtual onsen by any combination of xi on

three levels as shown in Table VIII. 18 set by orthogonal array and constructed a

questionnaire of paired comparisons (Figure 4). It is difficult to describe ‘‘onsen’s

characteristics’’ (’’amusement’’, ‘‘atmosphere’’ and ‘‘quality’’) by numerically. Because of

this, in this questionnaire, the part of ‘‘onsen’s characteristics’’ was described by radar

chart and also provided some photographs for images of each level of attribution.

Consumers will chose the alternative that best maximizes utility under perfect information

Figure 4 An example of the profiles from the questionnaire

Table VIII Level of attribution

Accessibility (one way) Cost (per person)Quality Amusement Atmosphere (hour) (yen)

3 3 3 5 70,0002 2 2 3 50,0001 1 1 1 30,000

Note: 1 dollar ¼ about 120 yen (at November, 2006)

Table IX Assumptions for the questionnaire

Trip day 3 days and 2 nights Member 2 , 4 persons

Origin Home of respondent Mode Choose after deciding the destinationSame time within modes

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condition. Assumptions of the questionnaire are shown in Table IX. Respondents are

consumers who lives in Tokyo or Osaka and whose age is 30s or 50s. The questionnaire

survey was administered online.

The results of the questionnaire survey were analyzed with a logit model. As defined above,

the utility function is (7). Choice is described as stochastic behavior because of (7), which is

a random utility function:

Pi ¼ probðUi . Uj Þ¼ probðV i þ 1i . V j þ 1j Þ

ð8Þ

Pi ¼ probð1j . V i 2 V j þ 1iÞ ð80Þ

Pi ¼expðV iÞ

PJj¼1 expð j iÞ

: ð9Þ

The probability that alternative i is chosen between i and j is shown in equation (8), which can

be transformed into equation (80). If 1 are independently and identically Gumbel distributed,

can derive equation (9), which is a binomial logit model. The results of the questionnaire

survey are analyzed using equation (9). There were 224 responses in the sample, and the

descriptive statistics are shown in Table X. The signs of all variables were satisfied as follows.

Onsen’s attractiveness, such as ‘‘quality’’, ‘‘amusement’’ and ‘‘atmosphere’’, are positive,

whereas ‘‘accessibility’’ and ‘‘cost’’ were negative.

From Table XI, variables were significant except for ‘‘amusement’’. Tourist behavior can be

understood that they consider ‘‘quality’’ and ‘‘atmosphere’’ to be important factors. Recently

in Japan, in fact, popular onsen arrange accommodation and other facilities which are the

elements included in ‘‘atmosphere’’ (Figure 3).

Second, the signs of ‘‘cost’’ and ‘‘accessibility’’ are negative. It can be said that ‘‘cost’’ and

‘‘accessibility’’ might affect destination choice.

Estimation of the attractiveness of each onsen

Here, it estimated the attractiveness of each 20 onsen using the estimation results (Table XI)

and the evaluation list which is the result of questionnaire by travel specialists (Table VII). To

Table X Descriptive statistics of the questionnaire

Variables Sample Min. Max. Average SD

1. Quality 224 1.00 1.00 2.00 0.822. Amusement 224 1.00 3.00 2.00 0.823. Atmosphere 224 1.00 3.00 2.00 0.824. Accessibility (one way) 224 1.00 5.00 3.00 1.635. Cost (per person) 224 3.00 7.00 5.00 1.63

Note: SD ¼ Standard deviation

Table XI Estimation result

Variables n t-value

x1 quality 0.627 13.686x2 amusement 0.121 1.874x3 atmosphere 0.621 14.096ln x4 accessibility 20.194 29.293ln x5 cost 20.290 211.436L*(0) 21,397.385L*(b̂) 21,199.144r 2 0.142Number of answers 2,016

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estimate attractiveness, the evaluation list of each onsen substituted to derive the

deterministic term from (Table VII). For accessibility and cost, it employs data from NITAS[3].

Accessibility refers to the shortest time from the point of consumer’s origin (Tokyo or Osaka)

to each onsen. Cost is the generalization cost of them. The V value is regarded as the

attractiveness of the onsen. For example, the attractiveness of the Kusatsu onsen was

estimated as follows (x4 and x5 is substituted the data from NITAS):

V Kusatsu ¼ 0:6272:59þ 0:1212:47þ 0:6212:372 0:194 ln x4 2 0:290 ln x5:

Based on the above, two types of attractiveness were estimated:

1. from Tokyo to each onsen (Figure 5); and

2. from Osaka to each onsen (Figure 6).

Figures 5 and 6 show attractiveness to tourists from Tokyo and Osaka respectively to each

onsen. The position of each onsen is according to time distance from each origin.

Attractiveness slopes downward from each origin, which means that attractiveness

generally decreases with increasing distance. It can also find that the difference of each

onsen’s attractiveness by origin (Tokyo or Osaka). For example, although the attractiveness

of ‘‘Hakone-Yumoto’’ from Tokyo is about 2.70, from Osaka it is under 2.00.

In the next section, some examples of strategies employed by onsen are considered.

4. Attractiveness: some examples and implications for tourism strategy

Estimation of attractiveness provides some information on the competition among onsen.

The image of competition among onsen is shown in Figure 7. The attractiveness of A and B

have arch-shaped distributions. This means that attractiveness varies because of

accessibility or cost depending on the origin of each tourist. Competition arises in the

overlapping area (shaded area in Figure 7).

Onsen managers should consider where their customers are from, and they also need to

recognize which onsen are their competitors. For example, in Figure 5, we consider the

attractiveness of two onsen: Atami and Kinosaki. Their attractiveness is almost the same,

and there may be competition between these onsen. When Atami considers how to attract

Figure 5 Attractiveness to tourists from Tokyo

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more people from Tokyo, it should be conscious of the consumers who take more time and go

to Kinosaki. That is to say, the rival of Atami in this case is Kinosaki. Various strategies for Atami

can be considered. For example, it could make an appeal to consumers with a specific

slogan: ‘‘Why take somuch time to go to Kinosaki? Atami gives you the same satisfaction but is

nearer’’, for instance. At present, every onsen in Japan has sufficient appeal to attract

customers, but most only appeal on the basis of their own qualities rather than drawing

comparisons with other onsen. There might be no effective impact on consumer behavior, but

we believe that each onsen should consider how to make a greater impact.

As shown in the examples above, it is important that the management of each onsen knows

who its rivals are. Onsen may consider more effective strategies to attract customers when

relative attractiveness values, such as those in our study, are known.

5. Conclusion

We estimate the attractiveness of onsen based on consumer behavior (Lancaster’s

approach). The framework presented here consists of three stages. In the first stage, we

Figure 6 Attractiveness to tourists from Osaka

Figure 7 An image of competition among onsen

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obtained three factors of onsen by factor analysis using the results of a questionnaire survey

of travel specialists. We also compiled an evaluation list of onsen from this result. Next stage,

we employ conjoint analysis and estimate the weight of factors with a logit model. From the

estimation result, it can be seen that ‘‘quality’’ and ‘‘atmosphere’’ are important influences on

consumer choice. Based on this result, we estimated the attractiveness of each onsen in the

last stage. Estimated attractiveness which varies because of accessibility or cost and

depends on origin provides some useful information for onsen marketing strategies. In

conclusion, our framework may be a useful method for estimating attractiveness, which in

turn provides some policy implications.

Implications for future research are as follows:

B We employed 15 elements to describe the characteristics of onsen. However, they are not

sufficient to reflect consumer preference. We should continue to consider these elements.

B The conjoint analysis requires a larger sample. We will increase the size of the sample to

estimate more precisely.

Notes

1. Myers (1999) indicated that customers may not clearly understand the strongest factors affecting

their choices.

2. Factor analysis is a statistical method based on the correlation analysis of many variables. The

purpose of the analysis is to reduce many variables to a smaller number of underlying factors.

3. NITAS is the data provided by Ministry of Land, Infrastructure, Transportation and Tourism, Japan.

The data is a general cost (transportation and time) between each prefectural capital in Japan.

References

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Further reading

Backer, G. (1965), ‘‘A theory of the allocation of time’’, Economic Journal, Vol. 75, pp. 493-517.

Kamata, H. (2007), ‘‘Why does a traveler choose a particular destination? Effect of accessibility on

destination choice in tourism’’ (‘‘Kotsu access wo kouryo shita kanko chi no miryokudo hyoka’’), Kotsu

Gaku Kenkyu, Japan Society of Transportation Economics, pp. 149-58 (in Japanese).

VOL. 65 NO. 2 2010 jTOURISM REVIEWj PAGE 39

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Kamata, H. and Yamauchi, H. (2006), ‘‘Factors which affect tourism demand – an attempt to estimate

attractiveness’’, (‘‘Kanko juyo ni eikyo wo oyobosu youin ni tsuite – miryokudo keisoku he no kokoromi’’),

IATSS Review, Vol. 30 No. 3, pp. 186-94 (in Japanese).

Kroes, E.P. and Sheldon, R.J. (1988), ‘‘Stated preference methods’’, Journal of Transport Economics

and Policy, Vol. 22 No. 1, pp. 11-25.

Lancaster, K.J. (1971), Consumer Demand – A New Approach, Columbia University Press, New York,

NY.

Louviere, J.J., Hensher, D.A. and Swait, J.D. (2000), Stated Choice Methods, Cambridge University

Press, Cambridge.

Melian-Gonzalez, A. and Garcia-Falcon, J.M. (2003), ‘‘Competitive potential of tourism in destinations’’,

Annals of Tourism Research, Vol. 30 No. 3, pp. 720-40.

Sinclair, M.T. and Stabler, M. (1997), The Economics of Tourism, Routledge, London.

Zwerina, K. (1997), Discrete Choice Experiments in Marketing, Physica-Verlag, Heidelberg.

Corresponding author

Hiromi Kamata can be contacted at: hiromi-k@mercury.ne.jp

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