Final defense

Tourist Demand and Willingness-to-Pay for Personal Interpretative Service: Application of the Bivariate Models

Presenter: Jenny Yin-Chen Chen Advisors: Dr. Yen-Hsi Lee

Dr. Tzong-Shyuan ChenMay 25, 2010

1

http://www.cyut.edu.tw/new/index.php

Contents I. Introduction

II. Literature Review

III. Methodology

IV. Results

V. Discussions2


Introduction

Research Background

Lukang

Statements of Problem

Purposes of Research

3


Research Background

Distinct benefits of historical tourism include the potential of a

clean industry and a valuable source of income and

employment.

(Orbasli, 2000)

4


Research Background

Interpretation allows visitors to generate a better

understanding of the history and significance of events,

people, and objects with which the site is associated.

(Alderson & Low, 1996)

5


Research Background

Interpretation is one of the key factors to a sustainable

tourism.

(Harris, Griffin, & Williams, 2002)

6


Research Background

Nearly 91% of the citizens traveled at least once domestically

in 2007, and the average number of trips per person was 5.57.

(R. O. C. Tourism Bureau, 2008)

7


Research Background

The number of tourists who have visited historic sites in 2008

was only 5% of the total number of tourists who have visited

the principal scenic spots in Taiwan.


8


Research Background

There are currently a total of 699 historic monuments and 767

historic buildings in Taiwan.

(Headquarters Administration of Cultural Heritage)

9


Lukang

10


Lukang

11


Lukang

12

Primary historic heritage 1

Tertiary heritage sites 6

Valuable heritage sites 7

Designated Heritage Sites in Lukang


Lukang

According to the survey of Visitors to the Principal Scenic Spots

in Taiwan by Month, more than 481,063 tourists visited Lukang

in 2008.


13



Only few of the past studies have examined the need for

interpretative services and the value of these services to

visitors in heritage sites.

14



By probing the visiting patterns and the perceptions of the

tourists, more could be considered to increase satisfaction of

the tourists, and may further increase revisitation.

15



to use the contingent valuation method (CVM) to elicit the

willingness-to-pay (WTP) of the tourists for personal

interpretative service in Lukang, and to analyze WTP

determinants with the application of bivariate models

16



To determine:

1. tourists’ demand on personal interpretative service in Lukang

2. the determinants of tourists’ willingness-to-pay for personal interpretative service in Lukang

3. the determinants of the level of WTP value for personal interpretative service in Lukang

17


Literature Review

18

Interpretative Service

Contingent Valuation Method

Determinants of WTP

Double-Hurdle Model

Infrequency of Purchase Model


Definition of Interpretative Service

Interpretation is an educational activity which aims to reveal

meanings and relationships to people about the places they visit

and the things they see, which in turn improves the quality of

visitor experience.

(Tilden, 1977)

19


Definition of Interpretative Service

Interpretation is a mission-based communication process that

forges emotional and intellectual connections between the

interests of the audience and the meanings inherent in the

resource.

(National Association for Interpretation, 2009)

20


The Importance of Interpretative Service

The goal of interpretation is to increase visitor awareness,

promote learning, appreciation and understanding of places so

that tourists develop empathy towards heritage, conservation,

culture and landscape.

(Stewart, Hayward, & Devlin, 1998)

21


The Importance of Interpretative Service

Interpretation services benefit both the heritage sites and

tourists and draw public support by enhancing visitors’

experiences and educating visitors in appropriate behaviors to

conserve the historical sites.

(Hall & McArthur, 1993)

22


Types of Interpretative Service

23

Personal / Attended

Non-personal / Unattended

guided walks talks presentations drama special events activity programs

interpretative signs interpretative brochures exhibit center audio guide multi-media guide interpretative trail


Importance of Personal Interpretative Service

24

Personal Interpretative Service

diverse audience

needs

more interaction

entertaining and

memorable

notice problems



The contingent valuation method (CVM) is a standard approach

to measuring economic values of non-market goods, such as

recreation resources, wildlife, and environmental quality goods.

(Hanemann, 1994; Lee & Han, 2002)

25



Elicitation techniques:

bidding game approach

payment card approach

dichotomous choice approach (DC)

open-ended elicitation technique

26



Possible biases:

starting-point bias

sequencing effect

information effect

hypothetical bias

strategic bias

27


Determinants of WTP

In travel expenditure studies, economic and socio-

demographic variables were commonly analyzed. Others have

incorporated travel-related variables, constraint factors, and life

cycle stages.

(Dardis, Soberon-Ferrer & Patro, 1994; Hong, Fan, Palmer

& Bhargava, 2005; Jang, Bai, Hong & O’Leary, 2004;

Jang & Ham, 2009; Weagley & Huh, 2004)

28


Statistical Models

Analysis of open-ended bids:

Ordinary least square (OLS) regressions

Tobit analysis

Bivariate models

29


Bivariate Models

models that involve a separate process determining

the zero-one discrete behavior from that determining

the continuous observations

(Blundell & Meghir, 1987)

30


Double-Hurdle Model

Many researchers went through the process of the model

selection tests, and justified the double-hurdle model from their

findings.

(Angulo, Gil & Gracia, 2001; Aristei, Perali & Pieroni, 2008;

Gebremedhin & Swinton, 2003; Matshe & Young, 2004;

Saz-Salazar & Rausell-Koster , 2008)31



Several researches, especially the ones focused on durable

goods, have found the infrequency of purchase model to be a

more suitable specification than Tobit or other models.

(Blisard & Blaylock, 1993; Blundell & Meghir, 1987;

Majima, 2008)

32


Methodology

33

Data Collection

Instrument

Estimation Methods

Data Analysis


Data Collection

34

Sampling size estimation formula

n =

n : sample size

Z : 95 % confidence interval ( Zα/2= 1.96 )

p : population proportion (½)

e : tolerated error (5%)

e2

Zα/22 p(1-p)

385


Data Collection

35

Participants Tourists who have visited Lukang (on-site)

Questionnaire 610 copies

Time 5 minutes

Sampling convenience sampling

Elicitation approach Open-ended


Instrument

36

questionnaire survey

Part 4 Demographic Information

Part 1 Cognition of Personal Interpretative Services

Part 2 Lukang Traveling Experiences

Part 3 Willingness-to-Pay for Personal Interpretative Service in Lukang


D:\?????????\??\Thesis\Thesis\questionnaire.doc

Estimation Methods

Main reasons for zero responses:

the survey period is too short for participants to report

any purchase (infrequency of purchase)

participants are not willing to pay due to personal

preferences (abstention)

participants do not pay due to economic reasons

(corner solution)

37


Estimation Methods

38

ordinary least square (OLS) regression

biased and inconsistent

estimates of the parameters


Estimation Methods

39

Double-hurdle model

Cragg (1971)

considers the possibility of zero outcomes in the second hurdle

two stages of estimation

two sets of variables

Tobit model

Tobin (1958)

all zero observations are interpreted as corner solutions

treats the decisions jointly

same set of variables

Heckman’s sample selection model

Heckman (1979)

there will be no zero observations in the second stage once the first stage selection is passed



Infrequency of purchase model

Deaton and Irish (1984)

the decision to pay is related to the amount willing to pay




Data Analysis

40


Double-Hurdle Model

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1. The decision to pay for personal interpretative service (D):

Di* = Zi α ＋ ui , ui ~ N(0,1) (1a)

Di = 1 if Di* > 0

0 if Di* ≤ 0 (1b)

D* : latent selection variable Z i : vector of explanatory variables α : vector of parameters

u i : error term


Double-Hurdle Model

42

2. The level of WTP value (Y):

Yi* = Xi β ＋ υi , υi ~ N(0, σ2) (2a)

Yi = Yi* if Di = 1 and Yi* > 0

0 otherwise (2b)

Yi : answer to the open-ended valuation question Xi : vector of explanatory variables β : vector of parameters υi : error term


Double-Hurdle Model

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Log-likelihood function:

(3)

ϕ(∙): standard normal density function Φ(∙): standard normal cumulative distribution function φ(∙): density function



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1. Participation decision:

PD* = Zi α ＋ ui , ui ~ N (0,1) (4a)

Di = 1 if PDi* > 0 Di = 0 if PDi* ≤ 0 (4b)

PD* : latent participation variable Zi : vector of explanatory variables α : vector of parameters u i : error term



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2. Expenditure decision:

Yi* = Xi β ＋ υi , υi ~ N(0, σ2) (5)

if PD* > 0 and Yi* > 0

= 0 otherwise (6)

Yi* : latent expenditure variable Xi : vector of explanatory variables β : vector of parameters υi : error term



46

Log-likelihood function:

(7)


Results

47

Descriptive Statistics

Empirical Results



48



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Table 1Socio-Demographic Statistics

N %Gender

female 333 61.0male 213 39.0

Age16~20 years old 50 9.221~30 years old 171 31.331~40 years old 161 29.541~50 years old 96 17.651~60 years old 53 9.761 or above 15 2.7

Education Levelgrade school or less 10 1.8junior high school 17 3.1senior high school 113 20.7vocational school/university 337 61.7graduate school or above 69 12.6



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Marriageunmarried 255 46.7married 291 53.3

Occupationmilitary/government/teacher 66 12.1industry 96 17.6business 78 14.3service 98 17.9freelance 22 4.0agriculture 2 .4housewife 43 7.9student 90 16.5unemployed 6 1.1retired 15 2.7others 30 5.5

N %

Table 1 (Continued).



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N %Income

20,000 NTD or below 177 32.420,001~30,000 NTD 108 19.830,001~40,000 NTD 93 17.040,001~50,000 NTD 64 11.750,001~60,000 NTD 37 6.860,001~70,000 NTD 26 4.870,001~80,000 NTD 15 2.780,001 NTD or above 26 4.8

Number of Children0 348 63.71 55 10.12 103 18.93 39 7.15 1 .2




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N %Residence

north area139 25.5

central area306 56.0

south area93 17.0

east area3 .5

archipelagoes1 .2

others4 .7

Note. N = 546



N %

Domestically or Abroad(within three months)

0 times 86 15.81~2 times 216 39.63~4 times 160 29.35~6 times 42 7.77 times or above 42 7.7

Lukangnever 37 6.8once 61 11.2twice 91 16.7three times 68 12.5four times 29 5.3five times or above 260 47.6


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Table 2Travel

Experiences


N %Travel Companionalone 15 2.7

family or relatives 331 60.6friend(s)/colleague(s)/classmate(s) 169 31.0

club activities 20 3.7others 11 2.0

Transportationcar 412 75.5motorcycle 60 11.0tourist coach 37 6.8bus 25 4.6others 12 2.2

Personal Interpretation Experienceno 502 91.9yes 44 8.1


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Table 3Current Experience in Lukang



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Understanding of Historic Monuments

do not know at all 9 1.6do not know much 111 20.3Neutral 339 62.1know some 77 14.1know very much 10 1.8

Need of Interpretation

do not need at all 5 .9do not need 44 8.1neutral 136 24.9need 308 56.4extremely need 53 9.7

Note. N = 546

N %



N %Favorite Spot

Lung Shan Temple 136 24.9Tien Ho Temple 170 31.1

Lukang Folk Arts Museum 31 5.7Yilou 5 .9Lukang Old Street 176 32.2Zhongshan Road 16 2.9don't know the name 10 1.8others 2 .4

Most Desirable SpotLung Shan Temple 108 19.8Tien Ho Temple 129 23.6Lukang Folk Arts Museum 50 9.2Yilou 20 3.7Lukang Old Street 192 35.2Zhongshan Road 23 4.2don't know the name 17 3.1others 7 1.3


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Table 4Perceptions Towards Historic Spots in Lukang



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Interpretation Required

Lung Shan Temple 178 32.6

Tien Ho Temple 127 23.3

Lukang Folk Arts Museum 79 14.5

Yilou 19 3.5

Lukang Old Street 110 20.1

Zhongshan Road 5 .9

don't know the name 24 4.4

others 1 .2

none 3 .5

Note. N = 546

N %




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Minimum Maximum MeanStd.

DeviationInterest 1 5 3.72 .868

Importance 1 5 4.15 .908

Knowledge1 3 1.02 .134

Culture 1 3 1.02 .134

Preservation 1 3 1.15 .409

Entertainment 1 3 1.20 .473

Promotion 1 3 1.06 .261

Experience 0 5 2.76 2.008

Table 5Cognition of Interpretation



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WTP N %no 202 37.0

yes 344 63.0Total 546 100.0

Table 6Willingness-to-Pay



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Table 7Frequency Table of WTP PriceWTP (price) Frequency %0 202 37.030 1 .250 17 3.180 1 .2100 75 13.7120 3 .5150 25 4.6200 64 11.7225 1 .2250 20 3.7300 39 7.1



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400 5 .9450 2 .4500 76 13.9600 7 1.3750 1 .2800 3 .5850 1 .2900 1 .21000 2 .4

Total 546 100.0

WTP (price) Frequency %


Average = 173 NTD

Empirical Results

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Variables Coefficient Std. Err. ZGEN 0.217446 0.13926 1.56AGE2 0.251039 0.28316 0.89AGE3 -0.08169 0.348207 -0.23AGE4 0.135077 0.368522 0.37AGE5 -0.0386 0.403974 -0.1LOC1 0.272503 0.162924 1.67*LOC3 0.073215 0.1843 0.4EDU3 0.2102 0.311975 0.67EDU4 0.756491 0.30646 2.47**EDU5 0.926543 0.355189 2.61**MAR -0.01385 0.203433 -0.07

Table 9Results of the First Hurdle of the Double Hurdle Model

Participants who lived in north of Taiwan with educational level of vocational school/university, graduate school or above had a higher probability of WTP.

Empirical Results

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OCCU1 0.214026 0.237745 0.9OCCU3 0.314069 0.180184 1.74*OCCU5 -0.0967 0.330041 -0.29OCCU6 0.387278 0.248102 1.56OCCU7 0.49827 0.281064 1.77*OCCU8 0.217078 0.282985 0.77TRAN1 0.068221 0.25447 0.27TRAN2 0.37904 0.325574 1.16TRAN4 0.960131 0.438757 2.19**TRAN5 0.609615 0.537775 1.13

Variables Coefficient Std. Err. Z

Note. *p < 0.1, **p < 0.05


Those whose occupation is business or service, and housewife, and those who arrived by bus had a higher probability of WTP.

Empirical Results

64

SER 0.079032 0.031477 2.51**VISIT 0.034587 0.040567 0.85IMP 0.164878 0.067651 2.44**CUL -0.44197 0.50051 -0.88NEED 0.335526 0.08059 4.16**


Note. *p < 0.1, **p < 0.05


Tourists who had more experiences of accepting personal interpretative service in the past, and who perceived the importance and need of personal interpretative service tended to be more willing to pay.

Empirical Results

65

Variables Coefficient Std. Err. ZGEN 0.110296 0.090606 1.22AGE2 0.120599 0.189958 0.63AGE3 0.051278 0.230249 0.22AGE4 0.04588 0.24174 0.19AGE5 0.114586 0.259569 0.44LOC1 0.204132 0.10404 1.96*LOC3 0.176934 0.12384 1.43EDU3 0.211445 0.259817 0.81EDU4 0.058021 0.253388 0.23EDU5 0.053082 0.27565 0.19MAR -0.01462 0.129433 -0.11

Table 10Results of the Second Hurdle of the Double Hurdle Model

Note. *p < 0.1, **p < 0.05

North residential area had a positive influence on the level of WTP.

Empirical Results

66

OCCU1 -0.0482 0.155819 -0.31OCCU3 -0.08398 0.124956 -0.67OCCU5 0.277577 0.249074 1.11OCCU6 0.106041 0.164264 0.65OCCU7 0.26202 0.222116 1.18OCCU8 0.101301 0.197779 0.51INC2 0.23121 0.147466 1.57INC3 0.318127 0.153024 2.08**INC4 0.125124 0.172149 0.73INC5 0.352857 0.20214 1.75*INC6 0.26721 0.16991 1.57Note. *p < 0.1, **p < 0.05

Variables Coefficient Std. Err. ZTable 10 (Continued).

Participants with an income within the range of 30,001 to 40,000 and 50,001 to 60,000 NTD significantly increased the level of WTP.

Empirical Results

67

TRAN1 0.329219 0.166975 1.97**TRAN2 0.198293 0.212468 0.93TRAN4 0.228786 0.22798 1TRAN5 0.48933 0.279619 1.75*SER 0.014218 0.020963 0.68VISIT 0.00158 0.028086 0.06IMP 0.032284 0.049078 0.66CUL -0.29176 0.424457 -0.69NEED 0.005786 0.059524 0.1_cons 4.693261 0.655023 7.17

Variables Coefficient Std. Err. ZTable 10 (Continued).

Note. *p < 0.1, **p < 0.05

Participants who arrived by car or other transportations were willing to pay a higher price for personal interpretative service.

Empirical Results

68

Variables Coefficient Std. Err. ZGEN 0.224688 0.092001 2.44**AGE2 0.381611 0.209885 1.82*AGE3 0.284645 0.243874 1.17AGE4 0.443205 0.248853 1.78*AGE5 0.487823 0.277679 1.76*LOC1 0.17359 0.106316 1.63LOC3 0.119741 0.125401 0.95EDU3 0.246065 0.240421 1.02EDU4 0.647336 0.236788 2.73**EDU5 0.775677 0.264394 2.93**

Table 11Results of the First Stage of Infrequency of Purchase Model

Note. *p < 0.1, **p < 0.05

Male participants within the age groups of 21 to 30, 41 or above, and with an educational level of vocational school/university, graduate school or above had a higher probability to pay.

Empirical Results

69

MAR -0.37225 0.130534 -2.85**OCCU1 -0.07801 0.153848 -0.51OCCU3 0.277023 0.135485 2.04**OCCU5 -0.15225 0.245432 -0.62OCCU6 0.392794 0.192846 2.04**OCCU7 0.538586 0.212531 2.53**OCCU8 0.18732 0.204526 0.92TRAN1 0.009606 0.195891 0.05TRAN2 0.131724 0.236644 0.56TRAN4 0.205951 0.276415 0.75TRAN5 0.006335 0.335354 0.02Note. *p < 0.1, **p < 0.05



Marriage exerted a significantly negative effect on WTP probability. Occupation category of business or service (OCCU3), agriculture, unemployed, or retired (OCCU6), and housewife (OCCU7) had significant and positive effect on WTP probability.

Empirical Results

70

SER 0.041032 0.022737 1.8*VISIT 0.030555 0.031351 0.97IMP 0.161443 0.047804 3.38**CUL -0.30733 0.373036 -0.82NEED 0.192137 0.058706 3.27**_cons -1.97148 0.605417 -3.26

Note. *p < 0.1, **p < 0.05



Frequency of accepting personal interpretative services in the past, perception of both the importance and need of personal interpretative service to historic monuments had significant and positive impact on WTP probability.

Empirical Results

71

Variables Coefficient Std. Err. ZGEN 0.480192 0.16832 2.85**AGE2 0.783302 0.386828 2.02**AGE3 0.548014 0.439505 1.25AGE4 0.85215 0.455667 1.87*AGE5 0.977989 0.511564 1.91*LOC1 0.412804 0.197708 2.09**LOC3 0.292994 0.230534 1.27EDU3 0.655358 0.505374 1.3EDU4 1.335538 0.487459 2.74**EDU5 1.520705 0.528414 2.88**Note. *p < 0.1, **p < 0.05

Table 12Results of the Second Stage of Infrequency of Purchase Model

Male tourists, within age groups of 21 to 30, or 41 and above, who lived in north of Taiwan, with educational level of vocational school/university or graduate school and above tended to be willing to spend more.

Empirical Results

72

Variables Coefficient Std. Err. ZMAR -0.68706 0.227025 -3.03**OCCU1 -0.15971 0.306173 -0.52OCCU3 0.459032 0.25485 1.8*OCCU5 -0.11516 0.538725 -0.21OCCU6 0.784744 0.341254 2.3**OCCU7 1.175909 0.412248 2.85**OCCU8 0.413387 0.359515 1.15INC2 0.093167 0.100233 0.93INC3 0.180554 0.103918 1.74*INC4 0.057377 0.117494 0.49INC5 0.212785 0.138182 1.54INC6 0.14617 0.115584 1.26


Note. *p < 0.1, **p < 0.05

Single tourists tended to be willing to pay more. Occupation category of business or service (OCCU3), agriculture, unemployed or retired (OCCU6), and housewife (OCCU7), and income of 30,001 to 40,000 NTD had positive association with WTP level.

Empirical Results

73

TRAN1 0.226152 0.347258 0.65TRAN2 0.356522 0.417446 0.85TRAN4 0.468426 0.457214 1.02TRAN5 0.338355 0.603904 0.56SER 0.075679 0.043118 1.76*VISIT 0.050146 0.057882 0.87IMP 0.338524 0.095928 3.53**CUL -0.78802 0.769336 -1.02NEED 0.355363 0.111756 3.18**_cons -1.37613 1.194359 -1.15



Note. *p < 0.1, **p < 0.05

Participants who experienced more personal interpretative service in the past, and those who perceived the importance and need of personal interpretative service in Lukang were willing to pay more.

Discussions

74

Conclusions

Limitations

Suggestions

Conclusions

single male

age groups of 21 to 30, or 41 and above

educational level of vocational school or university, and

graduate school or above

business, service, agriculture, unemployed, retired, and

housewife

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WTP probability

WTP level

Conclusions

a higher frequency of receiving personal interpretative

service in the past

agreement with the statement that personal

interpretative service is important to historic

monuments

perception of the need of personal interpretative service

in historic areas of Lukang

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WTP probability

WTP level

Conclusions

North residential area had a significant and positive effect on the WTP level, but not on the WTP probability.

Income of 30,001 to 40,000 NTD positively influenced the WTP level.

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WTP level

Conclusions

The bivariate models yielded different sets of variables

for the probability of WTP and the level of WTP.

Infrequency of purchase model indicated similar but

more significant WTP determinants than the double

hurdle model.

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Limitations

Lukang was the only study site.

The focus was merely on the demand and the determinants of personal interpretative services.

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include more historic sites

focus on the development of a successful program and the standards of the quality

Suggestions

promotion or marketing strategies

price of the services should be carefully calculated

standards or license for personal interpreters

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Thank you for your attention!

Final defense

Education

Transcript of Final defense