proposal defense (final)
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Research Background
Lukang
Statements of Problem
Purposes of Research
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Distinct benefits of historical tourism include the
potential of a clean industry and a valuable
source of income and employment.
(Orbasli, 2000)
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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)
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Interpretation is one of the key factors to a
sustainable tourism.
(Harris, Griffin, & Williams, 2002)
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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)
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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)
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There are currently a total of 699 historic
monuments and 767 historic buildings in Taiwan.
(Headquarters Administration of Cultural Heritage)
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Primary historic heritage 1
Tertiary heritage sites 6
Valuable heritage sites 7
Designated Heritage Sites in 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)
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Only few of the past studies have examined the
need for interpretative services and the value of
these services to visitors in heritage sites.
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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.
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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 a double-hurdle model
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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
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Interpretative Service
Contingent Valuation Method
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Determinants of WTP
Double-Hurdle Model
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)
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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)
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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)
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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)
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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
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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) 26
Elicitation techniques:
bidding game approach
payment card approach
dichotomous choice approach (DC)
open-ended elicitation technique
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Possible biases:
starting-point bias
sequencing effect
information effect
hypothetical bias
strategic bias
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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)29
Analysis of open-ended bids:
Ordinary least square (OLS) regressions
Tobit analysis
Double-hurdle model
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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
Log likelihood statistics and Hosmer-Lemeshow
statistics were used to confirm that the double-
hurdle model was good fit, and the findings
revealed differences in the variables influencing
travel participation and travel expenditure.
(Jang &Ham, 2009)
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Data Collection
Instrument
Estimation Methods
Data Analysis
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Sampling size estimation formula
n =
n : sample size Z : 95 % confidence interval ( Zα/2= 1.96 )
p : population proportion (½) e : tolerated error (5%)
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e2
Zα/22 p(1-p)
385
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ParticipantsTourists who have visited Lukang (on-site)
Questionnaire 410 copies
Time 5 minutes
Sampling convenience sampling
Elicitation approach
Open-ended
questionnaire survey
Part 4 Demographic Information
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Part 1Cognition of Personal Interpretative Services
Part 2 Lukang Traveling Experiences
Part 3Willingness-to-Pay for Personal Interpretative Service in Lukang
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
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ordinary least square (OLS) regression
biased and inconsistent
estimates of the parameters
Double-hurdle model
Cragg (1971)
considers the possibility of zero outcomes in the second hurdle
two stages of estimation
two sets of variables
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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
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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
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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
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Log-likelihood function:
(3)
ϕ(∙): standard normal density functionΦ(∙): standard normal cumulative distribution
functionφ(∙): density function
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Thank you for your attention!
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