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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
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.
(R. O. C. Tourism Bureau, 2009)
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
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.
(R. O. C. Tourism Bureau, 2009)
13
Statements of Problem
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
Statements of Problem
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
Purposes of Research
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
Purposes of Research
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
Contingent Valuation Method
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
Contingent Valuation Method
Elicitation techniques:
bidding game approach
payment card approach
dichotomous choice approach (DC)
open-ended elicitation technique
26
Contingent Valuation Method
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
Infrequency of Purchase Model
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
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
two stages of estimation
two sets of variables
Infrequency of purchase model
Deaton and Irish (1984)
the decision to pay is related to the amount willing to pay
two stages of estimation
two sets of variables
Double-Hurdle Model
41
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
43
Log-likelihood function:
(3)
ϕ(∙): standard normal density function Φ(∙): standard normal cumulative distribution function φ(∙): density function
Infrequency of Purchase Model
44
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
Infrequency of Purchase Model
45
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
Descriptive Statistics
49
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
Descriptive Statistics
50
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).
Descriptive Statistics
51
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
Table 1 (Continued).
Descriptive Statistics
52
N %Residence
north area139 25.5
central area306 56.0
south area93 17.0
east area3 .5
archipelagoes1 .2
others4 .7
Note. N = 546
Table 1 (Continued).
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
Descriptive Statistics
53
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
Descriptive Statistics
54
Table 3Current Experience in Lukang
Descriptive Statistics
55
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 %
Table 3 (Continued).
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
Descriptive Statistics
56
Table 4Perceptions Towards Historic Spots in Lukang
Descriptive Statistics
57
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 %
Table 4 (Continued).
Descriptive Statistics
58
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
Descriptive Statistics
59
WTP N %no 202 37.0
yes 344 63.0Total 546 100.0
Table 6Willingness-to-Pay
Descriptive Statistics
60
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
Descriptive Statistics
61
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 %
Table 7 (Continued).
Average = 173 NTD
Empirical Results
62
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
63
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
Table 9 (Continued).
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**
Variables Coefficient Std. Err. Z
Note. *p < 0.1, **p < 0.05
Table 9 (Continued).
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
Variables Coefficient Std. Err. Z
Table 11 (Continued).
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
Variables Coefficient Std. Err. Z
Table 11 (Continued).
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
Table 12 (Continued).
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
Variables Coefficient Std. Err. Z
Table 12 (Continued).
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
75
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
76
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.
77
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.
78
Limitations
Lukang was the only study site.
The focus was merely on the demand and the determinants of personal interpretative services.
79
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
80
81
Thank you for your attention!