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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 Chen May 25, 2010
Contents   I.  Introduction   II.  Literature Review III.  Methodology   IV.  Results   V.  Discussions
Introduction Research Background Lukang Statements of Problem Purposes of Research
Research Background ,[object Object],[object Object]
Research Background ,[object Object],[object Object]
Research Background ,[object Object],[object Object]
Research Background ,[object Object],[object Object]
Research Background ,[object Object],[object Object]
Research Background ,[object Object],[object Object]
Lukang
Lukang
Lukang Primary historic heritage 1 Tertiary heritage sites 6 Valuable heritage sites 7 Designated Heritage Sites in Lukang
Lukang ,[object Object],[object Object]
Statements of Problem ,[object Object]
Statements of Problem ,[object Object]
Purposes of Research ,[object Object]
Purposes of Research ,[object Object],[object Object],[object Object],[object Object]
Literature Review Interpretative Service Contingent Valuation Method Determinants of WTP Double-Hurdle Model Infrequency of Purchase Model
Definition of Interpretative Service ,[object Object],[object Object]
Definition of Interpretative Service ,[object Object],[object Object]
The Importance of Interpretative Service ,[object Object],[object Object]
The Importance of Interpretative Service ,[object Object],[object Object]
Types of Interpretative Service ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Personal /  Attended Non-personal / Unattended
Importance of Personal Interpretative Service ,[object Object],diverse audience needs more interaction entertaining and memorable notice problems
Contingent Valuation Method ,[object Object],[object Object]
Contingent Valuation Method ,[object Object],[object Object],[object Object],[object Object],[object Object]
Contingent Valuation Method ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Determinants of WTP ,[object Object],[object Object],[object Object],[object Object]
Statistical Models ,[object Object],[object Object],[object Object],[object Object]
Bivariate Models ,[object Object],[object Object]
Double-Hurdle Model ,[object Object],[object Object],[object Object]
Infrequency of Purchase Model ,[object Object],[object Object],[object Object]
Methodology Data Collection Instrument Estimation Methods Data Analysis
Data Collection ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],e 2 Z α /2 2      p (1- p ) 385
Data Collection Participants Tourists who have visited Lukang (on-site) Questionnaire 610 copies Time 5 minutes Sampling convenience sampling Elicitation approach Open-ended
Instrument ,[object Object],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 ,[object Object],[object Object],[object Object],[object Object]
Estimation Methods ordinary least square (OLS) regression biased and inconsistent estimates of the parameters
Estimation Methods 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
Data Analysis
Double-Hurdle Model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Double-Hurdle Model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Double-Hurdle Model ,[object Object],[object Object],[object Object],[object Object],[object Object]
Infrequency of Purchase Model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Infrequency of Purchase Model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Infrequency of Purchase Model ,[object Object],[object Object]
Results Descriptive Statistics Empirical Results
Descriptive Statistics
Descriptive Statistics Table 1 Socio-Demographic Statistics N % Gender female 333 61.0 male 213 39.0 Age 16~20 years old 50 9.2 21~30 years old 171 31.3 31~40 years old 161 29.5 41~50 years old 96 17.6 51~60 years old 53 9.7 61 or above 15 2.7 Education Level grade school or less 10 1.8 junior high school 17 3.1 senior high school 113 20.7 vocational school/university 337 61.7 graduate school or above 69 12.6
Descriptive Statistics Table 1 (Continued). Marriage unmarried 255 46.7 married 291 53.3 Occupation military/government/teacher 66 12.1 industry 96 17.6 business 78 14.3 service 98 17.9 freelance 22 4.0 agriculture 2 .4 housewife 43 7.9 student 90 16.5 unemployed 6 1.1 retired 15 2.7 others 30 5.5 N %
Descriptive Statistics Table 1 (Continued). N % Income 20,000 NTD or below 177 32.4 20,001~30,000 NTD 108 19.8 30,001~40,000 NTD 93 17.0 40,001~50,000 NTD 64 11.7 50,001~60,000 NTD 37 6.8 60,001~70,000 NTD 26 4.8 70,001~80,000 NTD 15 2.7 80,001 NTD or above 26 4.8 Number of Children 0 348 63.7 1 55 10.1 2 103 18.9 3 39 7.1 5 1 .2
Descriptive Statistics Note.  N = 546 Table 1 (Continued). N % Residence north area 139 25.5 central area 306 56.0 south area 93 17.0 east area 3 .5 archipelagoes 1 .2 others 4 .7
Descriptive Statistics Table 2 Travel Experiences N % Domestically or Abroad (within three months) 0 times 86 15.8 1~2 times 216 39.6 3~4 times 160 29.3 5~6 times 42 7.7 7 times or above 42 7.7 Lukang never 37 6.8 once 61 11.2 twice 91 16.7 three times 68 12.5 four times 29 5.3 five times or above 260 47.6
Descriptive Statistics Table 3 Current Experience in Lukang N % Travel Companion alone 15 2.7 family or relatives 331 60.6 friend(s)/colleague(s)/classmate(s) 169 31.0 club activities 20 3.7 others 11 2.0 Transportation car 412 75.5 motorcycle 60 11.0 tourist coach 37 6.8 bus 25 4.6 others 12 2.2 Personal Interpretation Experience no 502 91.9 yes 44 8.1
Descriptive Statistics Note.  N = 546 Table 3 (Continued). Understanding of Historic Monuments do not know at all 9 1.6 do not know much 111 20.3 Neutral 339 62.1 know some 77 14.1 know very much 10 1.8 Need of Interpretation do not need at all 5 .9 do not need 44 8.1 neutral 136 24.9 need 308 56.4 extremely need 53 9.7 N %
Descriptive Statistics Table 4 Perceptions Towards Historic Spots in Lukang N % Favorite Spot Lung Shan Temple 136 24.9 Tien Ho Temple 170 31.1 Lukang Folk Arts Museum 31 5.7 Yilou 5 .9 Lukang Old Street 176 32.2 Zhongshan Road 16 2.9 don't know the name 10 1.8 others 2 .4 Most Desirable Spot Lung Shan Temple 108 19.8 Tien Ho Temple 129 23.6 Lukang Folk Arts Museum 50 9.2 Yilou 20 3.7 Lukang Old Street 192 35.2 Zhongshan Road 23 4.2 don't know the name 17 3.1 others 7 1.3
Descriptive Statistics Note.  N = 546 Table 4 (Continued). 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 N %
Descriptive Statistics Table 5 Cognition of Interpretation Minimum Maximum Mean Std. Deviation Interest 1 5 3.72 .868 Importance 1 5 4.15 .908 Knowledge 1 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
Descriptive Statistics Table 6 Willingness-to-Pay WTP N % no 202 37.0 yes 344 63.0 Total 546 100.0
Descriptive Statistics Table 7 Frequency Table of WTP Price WTP (price) Frequency % 0 202 37.0 30 1 .2 50 17 3.1 80 1 .2 100 75 13.7 120 3 .5 150 25 4.6 200 64 11.7 225 1 .2 250 20 3.7 300 39 7.1
Descriptive Statistics Table 7 (Continued). 400 5 .9 450 2 .4 500 76 13.9 600 7 1.3 750 1 .2 800 3 .5 850 1 .2 900 1 .2 1000 2 .4 Total 546 100.0 WTP (price) Frequency % Average = 173 NTD
Empirical Results Table 9 Results of the First Hurdle of the Double Hurdle Model Variables Coefficient Std. Err. Z GEN 0.217446 0.13926 1.56 AGE2 0.251039 0.28316 0.89 AGE3 -0.08169 0.348207 -0.23 AGE4 0.135077 0.368522 0.37 AGE5 -0.0386 0.403974 -0.1 LOC1 0.272503 0.162924 1.67* LOC3 0.073215 0.1843 0.4 EDU3 0.2102 0.311975 0.67 EDU4 0.756491 0.30646 2.47** EDU5 0.926543 0.355189 2.61** MAR -0.01385 0.203433 -0.07 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 Note.  * p  < 0.1, ** p  < 0.05 Table 9 (Continued). OCCU1 0.214026 0.237745 0.9 OCCU3 0.314069 0.180184 1.74* OCCU5 -0.0967 0.330041 -0.29 OCCU6 0.387278 0.248102 1.56 OCCU7 0.49827 0.281064 1.77* OCCU8 0.217078 0.282985 0.77 TRAN1 0.068221 0.25447 0.27 TRAN2 0.37904 0.325574 1.16 TRAN4 0.960131 0.438757 2.19** TRAN5 0.609615 0.537775 1.13 Variables Coefficient Std. Err. Z Those whose occupation is business or service, and housewife, and those who arrived by bus had a higher probability of WTP.
Empirical Results Note.  * p  < 0.1, ** p  < 0.05 Table 9 (Continued). SER 0.079032 0.031477 2.51** VISIT 0.034587 0.040567 0.85 IMP 0.164878 0.067651 2.44** CUL -0.44197 0.50051 -0.88 NEED 0.335526 0.08059 4.16** Variables Coefficient Std. Err. Z 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 Table 10 Results of the Second Hurdle of the Double Hurdle Model Note.  * p  < 0.1, ** p  < 0.05 Variables Coefficient Std. Err. Z GEN 0.110296 0.090606 1.22 AGE2 0.120599 0.189958 0.63 AGE3 0.051278 0.230249 0.22 AGE4 0.04588 0.24174 0.19 AGE5 0.114586 0.259569 0.44 LOC1 0.204132 0.10404 1.96* LOC3 0.176934 0.12384 1.43 EDU3 0.211445 0.259817 0.81 EDU4 0.058021 0.253388 0.23 EDU5 0.053082 0.27565 0.19 MAR -0.01462 0.129433 -0.11 North residential area had a positive influence on the level of WTP.
Empirical Results Note.  * p  < 0.1, ** p  < 0.05 Table 10 (Continued). OCCU1 -0.0482 0.155819 -0.31 OCCU3 -0.08398 0.124956 -0.67 OCCU5 0.277577 0.249074 1.11 OCCU6 0.106041 0.164264 0.65 OCCU7 0.26202 0.222116 1.18 OCCU8 0.101301 0.197779 0.51 INC2 0.23121 0.147466 1.57 INC3 0.318127 0.153024 2.08** INC4 0.125124 0.172149 0.73 INC5 0.352857 0.20214 1.75* INC6 0.26721 0.16991 1.57 Variables Coefficient Std. Err. Z 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 Table 10 (Continued). Note.  * p  < 0.1, ** p  < 0.05 TRAN1 0.329219 0.166975 1.97** TRAN2 0.198293 0.212468 0.93 TRAN4 0.228786 0.22798 1 TRAN5 0.48933 0.279619 1.75* SER 0.014218 0.020963 0.68 VISIT 0.00158 0.028086 0.06 IMP 0.032284 0.049078 0.66 CUL -0.29176 0.424457 -0.69 NEED 0.005786 0.059524 0.1 _cons 4.693261 0.655023 7.17 Variables Coefficient Std. Err. Z Participants who arrived by car or other transportations were willing to pay a higher price for personal interpretative service.
Empirical Results Table 11 Results of the First Stage of Infrequency of Purchase Model Note.  * p  < 0.1, ** p  < 0.05 Variables Coefficient Std. Err. Z GEN 0.224688 0.092001 2.44** AGE2 0.381611 0.209885 1.82* AGE3 0.284645 0.243874 1.17 AGE4 0.443205 0.248853 1.78* AGE5 0.487823 0.277679 1.76* LOC1 0.17359 0.106316 1.63 LOC3 0.119741 0.125401 0.95 EDU3 0.246065 0.240421 1.02 EDU4 0.647336 0.236788 2.73** EDU5 0.775677 0.264394 2.93** 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 Note.  * p  < 0.1, ** p  < 0.05 Table 11 (Continued). MAR -0.37225 0.130534 -2.85** OCCU1 -0.07801 0.153848 -0.51 OCCU3 0.277023 0.135485 2.04** OCCU5 -0.15225 0.245432 -0.62 OCCU6 0.392794 0.192846 2.04** OCCU7 0.538586 0.212531 2.53** OCCU8 0.18732 0.204526 0.92 TRAN1 0.009606 0.195891 0.05 TRAN2 0.131724 0.236644 0.56 TRAN4 0.205951 0.276415 0.75 TRAN5 0.006335 0.335354 0.02 Variables Coefficient Std. Err. Z 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 Note.  * p  < 0.1, ** p  < 0.05 Table 11 (Continued). SER 0.041032 0.022737 1.8* VISIT 0.030555 0.031351 0.97 IMP 0.161443 0.047804 3.38** CUL -0.30733 0.373036 -0.82 NEED 0.192137 0.058706 3.27** _cons -1.97148 0.605417 -3.26 Variables Coefficient Std. Err. Z 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 Note.  * p  < 0.1, ** p  < 0.05 Table 12 Results of the Second Stage of Infrequency of Purchase Model Variables Coefficient Std. Err. Z GEN 0.480192 0.16832 2.85** AGE2 0.783302 0.386828 2.02** AGE3 0.548014 0.439505 1.25 AGE4 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 1.27 EDU3 0.655358 0.505374 1.3 EDU4 1.335538 0.487459 2.74** EDU5 1.520705 0.528414 2.88** 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 Table 12 (Continued). Note.  * p  < 0.1, ** p  < 0.05 Variables Coefficient Std. Err. Z MAR -0.68706 0.227025 -3.03** OCCU1 -0.15971 0.306173 -0.52 OCCU3 0.459032 0.25485 1.8* OCCU5 -0.11516 0.538725 -0.21 OCCU6 0.784744 0.341254 2.3** OCCU7 1.175909 0.412248 2.85** OCCU8 0.413387 0.359515 1.15 INC2 0.093167 0.100233 0.93 INC3 0.180554 0.103918 1.74* INC4 0.057377 0.117494 0.49 INC5 0.212785 0.138182 1.54 INC6 0.14617 0.115584 1.26 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 Table 12 (Continued). Note.  * p  < 0.1, ** p  < 0.05 TRAN1 0.226152 0.347258 0.65 TRAN2 0.356522 0.417446 0.85 TRAN4 0.468426 0.457214 1.02 TRAN5 0.338355 0.603904 0.56 SER 0.075679 0.043118 1.76* VISIT 0.050146 0.057882 0.87 IMP 0.338524 0.095928 3.53** CUL -0.78802 0.769336 -1.02 NEED 0.355363 0.111756 3.18** _cons -1.37613 1.194359 -1.15 Variables Coefficient Std. Err. Z 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 Conclusions Limitations Suggestions
Conclusions ,[object Object],[object Object],[object Object],[object Object],WTP probability WTP  level
Conclusions ,[object Object],[object Object],[object Object],WTP probability WTP  level
Conclusions ,[object Object],[object Object],WTP  level
Conclusions ,[object Object],[object Object]
Limitations ,[object Object],[object Object],include more historic sites focus on the development of a successful program and the standards of the quality
Suggestions ,[object Object],[object Object],[object Object]
[object Object]

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Final defense

  • 1. 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 Chen May 25, 2010
  • 2. Contents I. Introduction II. Literature Review III. Methodology IV. Results V. Discussions
  • 3. Introduction Research Background Lukang Statements of Problem Purposes of Research
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  • 12. Lukang Primary historic heritage 1 Tertiary heritage sites 6 Valuable heritage sites 7 Designated Heritage Sites in Lukang
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  • 18. Literature Review Interpretative Service Contingent Valuation Method Determinants of WTP Double-Hurdle Model Infrequency of Purchase Model
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  • 33. Methodology Data Collection Instrument Estimation Methods Data Analysis
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  • 35. Data Collection Participants Tourists who have visited Lukang (on-site) Questionnaire 610 copies Time 5 minutes Sampling convenience sampling Elicitation approach Open-ended
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  • 38. Estimation Methods ordinary least square (OLS) regression biased and inconsistent estimates of the parameters
  • 39. Estimation Methods 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
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  • 47. Results Descriptive Statistics Empirical Results
  • 49. Descriptive Statistics Table 1 Socio-Demographic Statistics N % Gender female 333 61.0 male 213 39.0 Age 16~20 years old 50 9.2 21~30 years old 171 31.3 31~40 years old 161 29.5 41~50 years old 96 17.6 51~60 years old 53 9.7 61 or above 15 2.7 Education Level grade school or less 10 1.8 junior high school 17 3.1 senior high school 113 20.7 vocational school/university 337 61.7 graduate school or above 69 12.6
  • 50. Descriptive Statistics Table 1 (Continued). Marriage unmarried 255 46.7 married 291 53.3 Occupation military/government/teacher 66 12.1 industry 96 17.6 business 78 14.3 service 98 17.9 freelance 22 4.0 agriculture 2 .4 housewife 43 7.9 student 90 16.5 unemployed 6 1.1 retired 15 2.7 others 30 5.5 N %
  • 51. Descriptive Statistics Table 1 (Continued). N % Income 20,000 NTD or below 177 32.4 20,001~30,000 NTD 108 19.8 30,001~40,000 NTD 93 17.0 40,001~50,000 NTD 64 11.7 50,001~60,000 NTD 37 6.8 60,001~70,000 NTD 26 4.8 70,001~80,000 NTD 15 2.7 80,001 NTD or above 26 4.8 Number of Children 0 348 63.7 1 55 10.1 2 103 18.9 3 39 7.1 5 1 .2
  • 52. Descriptive Statistics Note. N = 546 Table 1 (Continued). N % Residence north area 139 25.5 central area 306 56.0 south area 93 17.0 east area 3 .5 archipelagoes 1 .2 others 4 .7
  • 53. Descriptive Statistics Table 2 Travel Experiences N % Domestically or Abroad (within three months) 0 times 86 15.8 1~2 times 216 39.6 3~4 times 160 29.3 5~6 times 42 7.7 7 times or above 42 7.7 Lukang never 37 6.8 once 61 11.2 twice 91 16.7 three times 68 12.5 four times 29 5.3 five times or above 260 47.6
  • 54. Descriptive Statistics Table 3 Current Experience in Lukang N % Travel Companion alone 15 2.7 family or relatives 331 60.6 friend(s)/colleague(s)/classmate(s) 169 31.0 club activities 20 3.7 others 11 2.0 Transportation car 412 75.5 motorcycle 60 11.0 tourist coach 37 6.8 bus 25 4.6 others 12 2.2 Personal Interpretation Experience no 502 91.9 yes 44 8.1
  • 55. Descriptive Statistics Note. N = 546 Table 3 (Continued). Understanding of Historic Monuments do not know at all 9 1.6 do not know much 111 20.3 Neutral 339 62.1 know some 77 14.1 know very much 10 1.8 Need of Interpretation do not need at all 5 .9 do not need 44 8.1 neutral 136 24.9 need 308 56.4 extremely need 53 9.7 N %
  • 56. Descriptive Statistics Table 4 Perceptions Towards Historic Spots in Lukang N % Favorite Spot Lung Shan Temple 136 24.9 Tien Ho Temple 170 31.1 Lukang Folk Arts Museum 31 5.7 Yilou 5 .9 Lukang Old Street 176 32.2 Zhongshan Road 16 2.9 don't know the name 10 1.8 others 2 .4 Most Desirable Spot Lung Shan Temple 108 19.8 Tien Ho Temple 129 23.6 Lukang Folk Arts Museum 50 9.2 Yilou 20 3.7 Lukang Old Street 192 35.2 Zhongshan Road 23 4.2 don't know the name 17 3.1 others 7 1.3
  • 57. Descriptive Statistics Note. N = 546 Table 4 (Continued). 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 N %
  • 58. Descriptive Statistics Table 5 Cognition of Interpretation Minimum Maximum Mean Std. Deviation Interest 1 5 3.72 .868 Importance 1 5 4.15 .908 Knowledge 1 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
  • 59. Descriptive Statistics Table 6 Willingness-to-Pay WTP N % no 202 37.0 yes 344 63.0 Total 546 100.0
  • 60. Descriptive Statistics Table 7 Frequency Table of WTP Price WTP (price) Frequency % 0 202 37.0 30 1 .2 50 17 3.1 80 1 .2 100 75 13.7 120 3 .5 150 25 4.6 200 64 11.7 225 1 .2 250 20 3.7 300 39 7.1
  • 61. Descriptive Statistics Table 7 (Continued). 400 5 .9 450 2 .4 500 76 13.9 600 7 1.3 750 1 .2 800 3 .5 850 1 .2 900 1 .2 1000 2 .4 Total 546 100.0 WTP (price) Frequency % Average = 173 NTD
  • 62. Empirical Results Table 9 Results of the First Hurdle of the Double Hurdle Model Variables Coefficient Std. Err. Z GEN 0.217446 0.13926 1.56 AGE2 0.251039 0.28316 0.89 AGE3 -0.08169 0.348207 -0.23 AGE4 0.135077 0.368522 0.37 AGE5 -0.0386 0.403974 -0.1 LOC1 0.272503 0.162924 1.67* LOC3 0.073215 0.1843 0.4 EDU3 0.2102 0.311975 0.67 EDU4 0.756491 0.30646 2.47** EDU5 0.926543 0.355189 2.61** MAR -0.01385 0.203433 -0.07 Participants who lived in north of Taiwan with educational level of vocational school/university, graduate school or above had a higher probability of WTP.
  • 63. Empirical Results Note. * p < 0.1, ** p < 0.05 Table 9 (Continued). OCCU1 0.214026 0.237745 0.9 OCCU3 0.314069 0.180184 1.74* OCCU5 -0.0967 0.330041 -0.29 OCCU6 0.387278 0.248102 1.56 OCCU7 0.49827 0.281064 1.77* OCCU8 0.217078 0.282985 0.77 TRAN1 0.068221 0.25447 0.27 TRAN2 0.37904 0.325574 1.16 TRAN4 0.960131 0.438757 2.19** TRAN5 0.609615 0.537775 1.13 Variables Coefficient Std. Err. Z Those whose occupation is business or service, and housewife, and those who arrived by bus had a higher probability of WTP.
  • 64. Empirical Results Note. * p < 0.1, ** p < 0.05 Table 9 (Continued). SER 0.079032 0.031477 2.51** VISIT 0.034587 0.040567 0.85 IMP 0.164878 0.067651 2.44** CUL -0.44197 0.50051 -0.88 NEED 0.335526 0.08059 4.16** Variables Coefficient Std. Err. Z 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.
  • 65. Empirical Results Table 10 Results of the Second Hurdle of the Double Hurdle Model Note. * p < 0.1, ** p < 0.05 Variables Coefficient Std. Err. Z GEN 0.110296 0.090606 1.22 AGE2 0.120599 0.189958 0.63 AGE3 0.051278 0.230249 0.22 AGE4 0.04588 0.24174 0.19 AGE5 0.114586 0.259569 0.44 LOC1 0.204132 0.10404 1.96* LOC3 0.176934 0.12384 1.43 EDU3 0.211445 0.259817 0.81 EDU4 0.058021 0.253388 0.23 EDU5 0.053082 0.27565 0.19 MAR -0.01462 0.129433 -0.11 North residential area had a positive influence on the level of WTP.
  • 66. Empirical Results Note. * p < 0.1, ** p < 0.05 Table 10 (Continued). OCCU1 -0.0482 0.155819 -0.31 OCCU3 -0.08398 0.124956 -0.67 OCCU5 0.277577 0.249074 1.11 OCCU6 0.106041 0.164264 0.65 OCCU7 0.26202 0.222116 1.18 OCCU8 0.101301 0.197779 0.51 INC2 0.23121 0.147466 1.57 INC3 0.318127 0.153024 2.08** INC4 0.125124 0.172149 0.73 INC5 0.352857 0.20214 1.75* INC6 0.26721 0.16991 1.57 Variables Coefficient Std. Err. Z 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.
  • 67. Empirical Results Table 10 (Continued). Note. * p < 0.1, ** p < 0.05 TRAN1 0.329219 0.166975 1.97** TRAN2 0.198293 0.212468 0.93 TRAN4 0.228786 0.22798 1 TRAN5 0.48933 0.279619 1.75* SER 0.014218 0.020963 0.68 VISIT 0.00158 0.028086 0.06 IMP 0.032284 0.049078 0.66 CUL -0.29176 0.424457 -0.69 NEED 0.005786 0.059524 0.1 _cons 4.693261 0.655023 7.17 Variables Coefficient Std. Err. Z Participants who arrived by car or other transportations were willing to pay a higher price for personal interpretative service.
  • 68. Empirical Results Table 11 Results of the First Stage of Infrequency of Purchase Model Note. * p < 0.1, ** p < 0.05 Variables Coefficient Std. Err. Z GEN 0.224688 0.092001 2.44** AGE2 0.381611 0.209885 1.82* AGE3 0.284645 0.243874 1.17 AGE4 0.443205 0.248853 1.78* AGE5 0.487823 0.277679 1.76* LOC1 0.17359 0.106316 1.63 LOC3 0.119741 0.125401 0.95 EDU3 0.246065 0.240421 1.02 EDU4 0.647336 0.236788 2.73** EDU5 0.775677 0.264394 2.93** 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.
  • 69. Empirical Results Note. * p < 0.1, ** p < 0.05 Table 11 (Continued). MAR -0.37225 0.130534 -2.85** OCCU1 -0.07801 0.153848 -0.51 OCCU3 0.277023 0.135485 2.04** OCCU5 -0.15225 0.245432 -0.62 OCCU6 0.392794 0.192846 2.04** OCCU7 0.538586 0.212531 2.53** OCCU8 0.18732 0.204526 0.92 TRAN1 0.009606 0.195891 0.05 TRAN2 0.131724 0.236644 0.56 TRAN4 0.205951 0.276415 0.75 TRAN5 0.006335 0.335354 0.02 Variables Coefficient Std. Err. Z 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.
  • 70. Empirical Results Note. * p < 0.1, ** p < 0.05 Table 11 (Continued). SER 0.041032 0.022737 1.8* VISIT 0.030555 0.031351 0.97 IMP 0.161443 0.047804 3.38** CUL -0.30733 0.373036 -0.82 NEED 0.192137 0.058706 3.27** _cons -1.97148 0.605417 -3.26 Variables Coefficient Std. Err. Z 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.
  • 71. Empirical Results Note. * p < 0.1, ** p < 0.05 Table 12 Results of the Second Stage of Infrequency of Purchase Model Variables Coefficient Std. Err. Z GEN 0.480192 0.16832 2.85** AGE2 0.783302 0.386828 2.02** AGE3 0.548014 0.439505 1.25 AGE4 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 1.27 EDU3 0.655358 0.505374 1.3 EDU4 1.335538 0.487459 2.74** EDU5 1.520705 0.528414 2.88** 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.
  • 72. Empirical Results Table 12 (Continued). Note. * p < 0.1, ** p < 0.05 Variables Coefficient Std. Err. Z MAR -0.68706 0.227025 -3.03** OCCU1 -0.15971 0.306173 -0.52 OCCU3 0.459032 0.25485 1.8* OCCU5 -0.11516 0.538725 -0.21 OCCU6 0.784744 0.341254 2.3** OCCU7 1.175909 0.412248 2.85** OCCU8 0.413387 0.359515 1.15 INC2 0.093167 0.100233 0.93 INC3 0.180554 0.103918 1.74* INC4 0.057377 0.117494 0.49 INC5 0.212785 0.138182 1.54 INC6 0.14617 0.115584 1.26 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.
  • 73. Empirical Results Table 12 (Continued). Note. * p < 0.1, ** p < 0.05 TRAN1 0.226152 0.347258 0.65 TRAN2 0.356522 0.417446 0.85 TRAN4 0.468426 0.457214 1.02 TRAN5 0.338355 0.603904 0.56 SER 0.075679 0.043118 1.76* VISIT 0.050146 0.057882 0.87 IMP 0.338524 0.095928 3.53** CUL -0.78802 0.769336 -1.02 NEED 0.355363 0.111756 3.18** _cons -1.37613 1.194359 -1.15 Variables Coefficient Std. Err. Z 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.
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