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UNIVERSITY OF HAIFA Natural Resources &Environmental Research Center
אוניברסיטת חיפה המרכז לחקר משאבי טבע וסביבה
TEL-HAI חי-מרכז להשכלה תלRODMAN REGIONAL COLLEGE רודמן. ומ. ש ג"ע
EXPECTED RECREATIONAL BENEFITS OF THE
HULA PROJECT: ECONOMIC ANALYSIS
Final Report
Mira G. Baron, Natalia Zaitsev and Mordechai Shechter
Submitted to the Hula Project Authority
MIGAL - Galilee Technological Center
September 1997
Principal Researchers:
Dr. Mira G. Baron
Natural Resources and Environmental Research Center, University of Haifa, and
Faculty of Industrial Engineering and Management, Technion - Israel Institute of
Technology
Dr. Natalia Zaitsev
Natural Resource and Environmental Research Center, University of Haifa, Research
Branch at the Tel-Hai Rodman Galilee College, Upper Galilee
Prof. Mordechai Shechter
Natural Resources and Environmental Research Center, Department of Economics,
University of Haifa
Research Assistants:
Saggi Nevo (M.A)
Natural Resources and Environmental Research Center, University of Haifa
Zvi Asher (B.A)
Natural Resources and Environmental Research Center, University of Haifa
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ACKNOWLEDGMENTS
This research was funded by the Hula Project Authority:
Keren Kayemeth LeIsrael, Israel Land Administration, Ministry of Agriculture,
Ministry of Tourism, Water Commission, Ministry of the Interior, Regional Councils:
Upper Galilee, Merom Galil, Mevo Hamma
Thanks are due to Professor Michael Nudelman who participated in the early stages of
the research.
We would like to thank the following people and organizations:
Mr. Amos Harpas, the Chairman of the Research Committee in the Hula
Professor Moshe Gophen, the Scientific Coordinator of the research works in the
Hula
Mr. Giora Shaham, the manager of the Project.
Ms. Dina Weinstein, Nature Reserve Authority
Ms. Aviva Leonov, Nature Reserve Authority
Mr. Avi Sharon, Golan Regional Council
Mr. Amitai Rotem, National Parks Authority
Mr. Moshe Atiya, the Galilee Tourist Authority
Our thanks to the Nature Reserve Authority, National Parks Authority, Golan Regional
Council for their permission to conduct surveys in the Upper Galilee parks. Thanks to
the managers and workers of the parks who were very helpful and cooperative.
Of course, the authors remain solely responsible for any remaining errors.
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ABSTRACT
The Hula Project aims at recreating a marsh in order to avoid the negative environmental externalities
of the current situation - nitrification of the Kinneret, spontaneous fires, low water level. Recreating
the marsh landscape is achieved by digging canals and a lake, “creating” islands, populating the area
with wild animals, planting characteristic vegetation, and attracting birds. It is hoped that this
landscape will be attractive to recreation, prompting safari, bird watching, and boating. The research
assesses the expected benefits of the Project for entrepreneurs and for society.
The study is based on surveys of Israeli recreationists that were conducted in all seasons in 1995-
1996. The surveys were conducted in seven recreational sites in Upper Galilee. Altogether 800 people
were interviewed. The questionnaire included questions on recreational patterns in existing parks, on
willingness to visit a hypothetical park, the Hula Project, willingness to pay an entrance fee, etc.
The study summarizes the recreation patterns in existing parks and nature reserves in Upper Galilee:
It is estimated that 700,000 people visit the Upper Galilee parks annually. 95% of the visitors visited
the area in addition to the current visit within the last five years, and 72% visited within the past
twelve months. The activities in the parks vary by season. Picnicking is the most popular activity and
60-94% engage in it (it is more popular in the winter than in summer). Recreation is characterized by
young visitors. Only 8% of the visitors are 50 years and older vs. 31% in the general population.
People go to the parks in large groups. Among the young visitors, those in the 18-29 age-group, 50%
go in a group of at least 4 members, but among those in the 30-49 age-group these groups constitute
84%. These two groups constitute 28% and 63% of the visitors respectively. The length of stay varies
by season. In the summer 64% come for a few days, while in the winter and spring only 30% stay
overnight. The length of stay has implications for visiting restaurants and using accommodation
facilities. Throughout the year about 50% ate at a restaurant or planned to visit one during their stay
in the area. The division between those who ate or planned to eat at a restaurant varies by season. In
the summer 36% of the visitors ate at a restaurant during the current visit, and another 15% planned to
do so. In the winter 24% ate at a restaurant and 28% planned to do so . The major difference between
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the seasons is in the mean expenditure per family for those who ate in a restaurant. It varies between
NIS 273 in summer and NIS 57 in winter. The use of accommodation facilities means that 33% stay
at bed & breakfast accommodation (zimmers), 32% stay in guest houses and hotels, 17% in tents and
bungalows, and the rest stay with friends and family. Capacity of hotel rooms and beds in the area is
apparently in excess. Another question analyzed is the actual behavior of recreationists, in terms of
the distance between two adjacent groups of visitors. It was observed that 23% of the groups are less
than 5 meters apart, and 61% of the groups are less than 10 meters apart. The observed proximity is
not disturbing (a subjective reaction). When asked if the neighbors disturbed them, 84% answered
that they were not disturbed, and only 3% were very disturbed. We have to conclude that the visitors
are tolerant to proximity.
Analyzing the reaction to proximity using logistic analysis, we find that income increased the
response of being disturbed, engaging in picnic made people more tolerant, and engaging in sport
made people less tolerant.
In analyzing the response to a hypothetical non-existing park, the Hula Project, we addressed several
issues:
Evaluating the expected entrance fee. Using the Contingent Valuation Method we evaluate the
Willingness To Pay (WTP) entrance fee. On average people are willing to pay NIS 30. 63.5% of the
respondents are willing to pay NIS 30 and more. Only 1% of the respondents refuse to pay at all.
Analysis of the factors affecting WTP shows that income affects positively (normal good), family size
affects negatively, distance affects positively, and the activities preferred by the individual affect as
follows: safari, a unique activity to the park, affects positively, horse riding and swimming affect
negatively. The last two activities are offered at alternative sites with a lower entrance fee, and the
result is reasonable.
Evaluating the expected number of visitors. 87% of the visitors to Upper Galilee would like to visit
the Hula Project. If the park were opened today, and NIS 30 were charged, 380,000 visitors may be
expected. Due to the expected increase in population and increase in standard of living we expect an
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annual increase in the number of visitors by 2-4% per year. In ten years 460,000-560,000 visitors are
expected, besides overseas tourists.
Expected revenues and benefits were calculated assuming NIS 30 per person is charged. Since
380,000 visitors are expected, annual revenues of NIS 11.4 million are expected in the first year of
operation. Under reasonable assumptions, in 25 years of operation a present value in the range of NIS
123-323 million may be expected.
The expected social benefits were calculated referring to the WTP of interviewees to pay an entrance
fee of NIS 30 and higher values. At the first year of operation the benefits are expected to total NIS
14.1 million. In 25 years of operation, a present value of total benefits in the range of NIS 152-400
million may be expected.
The study shows that there is a large interest in visiting the Project, and people are willing to pay high
sums as entrance fee. It is likely that the project will generate revenues to the entrepreneurs, and that
society will earn net benefits.
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TABLE OF CONTENTS
Final Report...........................................................................................................................................iMira G. Baron, Natalia Zaitsev and Mordechai Shechter................................................................................i
APPENDIX A: QUESTIONNAIRE……...………...………………………………………………49APPENDIX B: LIST OF VARIABLES ….………………...………………..…..……………………..60APPENDIX C: LOGISTIREGRESSION…………………………………………...……………61APPENDIX D: MATHEMATICAL APPENDIX………………………………………………………..……..64
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LIST OF TABLES
Table C1. Logistic Model for Predicting WTP in Hula Project 62LIST OF FIGURESFigure 1. Expected Demand Curve for the Hula Project Using CVM.......................................... ....39Figure 2. Revenues, Total Benefits and Net Benefits as Measured from a Demand Curve.............. 40
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INTRODUCTION
The Hula Project in the north of Israel aims at recreating a marsh that was drained in the early 1950s.
The re-flooding aims at solving environmental problems such as nitrification of Lake Kinneret, level
and quality of water, dust, spontaneous fires, and non-productive soil and also regional
unemployment. Recreating the marsh landscape is achieved by digging canals and a lake, “creating”
islands, populating the area with wild animals, planting characteristic vegetation, and attracting birds
(to recreate the role of the marsh in the birds’ migration route).The planners hope that this landscape
will be attractive for recreation, fostering safaris, bird watching, boating, picnicking, etc.
The present report aims at predicting the recreation potential of the area, referred to as the Hula
Project. It deals with the following issues:
- the recreation potential in the Hula Project;
-activities that will attract potential visitors;
- the expected recreational benefits in economic terms from the Hula Project;
- the interaction of environment and human beings with respect to social carrying capacity.
Chapter 1 describes surveys conducted in various Upper Galilee parks, where samples of
recreationists were interviewed in different seasons. At present 700,000 recreationists are estimated to
visit Upper Galilee annually, besides overseas tourists. The remaining chapters are divided into two
major parts: the first (Chapters 2 and 3) analyze the recreational patterns in already existing Upper
Galilee parks. Chapter 2 focuses on activities undertaken, number of past visits , visits to restaurants,
staying in accommodation facilities, etc. Chapter 3 analyzes the reaction of visitors to proximity and
close contact, asking if visitors are disturbed if the site is crowded. The second part (Chapter 4) deals
with the expected demand for the new Hula Project. We estimated the expected revenues and benefits
from operating the park, from answers to questions on willingness to visit a hypothetical park and
willingness to pay entrance fees. Chapter 5 offers concluding remarks.
CHAPTER 1
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THE SURVEYS
1.1 The Surveys
Forecasting the demand for a non-existing, planned park could be based on a national sample or on
an on-site survey conducted at existing parks. We decided against a national survey since a high
percentage of the population does not actively participate in recreation: only 26 percent of the urban
Jewish population visited Upper Galilee in 1994 for recreation purposes (Fleisher and Saati, 1994),
and the figures for non-Jews and for the rural population are unknown. A national survey would
require many interviews to get a reasonable representation of people acquainted with recreation in the
area, and would be costly. Since our budget was limited, we opted for an on-site survey of visitors to
existing Upper Galilee parks. This choice ensured that the interviewees were familiar with the area
and its potential for recreation, travel conditions, lodging conditions, etc.
We conducted surveys in four different seasons: August 1995, in the peak of the summer vacation
period in Israel (the effective size of this sub-sample was 227 observations), October during the
Succoth holiday (the effective size of this sub-sample was 198 observations), March 1996, the end of
the winter season (the effective size of this sub-sample was 177 observations), and May and June
1996 (the effective size of this sub-samples was 197 observations). The effective size of the entire
sample of seven sub-samples was 799 observations.
Seven recreational sites were included in the surveys: Banias, Tel Dan, Nahal Ayun (Tanur), Hula
Reserve, Hula Project, Hurshat Tal and Yarden Park. In the new Hula Project we interviewed a small
group of visitors only in the winter (the Hula Park is still at the construction stage). Sites were
included or excluded for various reasons. Some sites are closed in certain seasons, e.g., Nahal Ayun
in the ‘dry’ season, whereas Hurshat Tal, hardly operates in the cold season.
All these parks are located in Upper Galilee (in the north of Israel). Each site is unique in
geographical characteristics, landscape, and attractions, a fact which affects the results discussed,
such as the activities characteristic to each site (see Chapter 2). Although these sites offer different
recreational attractions from those offered by the planned Hula Project, we surmised that the sites
could offer the best basis for making projections for the new site.
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The interviewers were instructed to sample groups of vacationers randomly (a family or a group of
individuals or a few families staying together). In each group, one individual was chosen to represent
the group as a whole. Group size, group activities and group age composition were probed in the
questionnaire. Although the individuals answered according to their own preferences, we assume that
in certain aspects their views represent the group as a whole.
1.2 The Questionnaire
The questionnaire contains five categories of questions:
* Hypothetical questions about the proposed Hula Park
* Recreational patterns of visits to existing parks: number of past visits, length of stay, expenditure,
activities, etc.
* Social carrying capacity
* Demographic and socio-economic characteristics.
Frequency tables for all responses and for each season are given in Appendix A.
1.3 Sample Size and Sampling Ratio
The surveys were conducted on seven days in seven different parks. The sampling ratio varied by
season and by recreation site between 0.07 and 0.61, members. The sampling ratio was calculated by
dividing the number sampled, assuming that the mean group has 6 members, by the number of
visitors on the same date in the specific site:
[Number Interviewed in Site j at Date t] multiplied by [Mean Size of a Group] divided by [Number of
Visitors in Site j at Date t].
For example, the sampling ratio at the Banias (site j) in the summer (date t ) is 27 x 6 /1338 = 0.12.
The number of visitors on our survey days was provided by the Nature Reserves Authority. These are
presented in Table 1, together with the number of respondents interviewed at those sites. (the number
of visitors includes adults and children. We could not separate the overseas tourists from the total.)
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Table 1. Number of Visitors, Interviewees and Sampling Ratio at the Survey Days
Site Date:19.8.1995
Date:22.8.1995
Date:11.10.1995
Date:14.10.1995
Date:16.3.1996
Date:18.5.1996
Date:1.6.1996
Hula Reserve Number of visitors Number interviewed (adults) Sampling ratioTel Dan Number of visitors Number interviewed (adults) Sampling ratioHurshat Tal Number of visitors Number interviewed (adults) Sampling ratioBanias Number of visitors Number interviewed (adults) Sampling ratioYarden Park Number of visitors Number interviewed (adults) Sampling ratioNahal Ayun Number of visitors Number interviewed (adults) Sampling ratioNew Hula Project Number interviewed (adults)
340290.51
1122320.17
*31-
1560270.10
*00
*00
0
504160.19
1801300.10
*30-
2469320.08
*00
*00
0
102800
1721260.09
*27-
2620240.05
*34-
*00
0
195100
1432300.12
*00
309900
*43-
*00
0
847360.25
992450.27
*00
1962400.12
*00
724370.30
21
31700
936340.22
*00
1576280.10
*00
267300.67
0
41800
977420.26
*38-
1562220.08
*00
105260.03
0
*number of visitors is not available
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1.4 Demographic and Socio-Economic Profile
Comparing the characteristics of the visitors at Upper Galilee parks with the Israeli population at
large, one may infer that the visitors are more educated, have a higher income, are mostly in the 30-
40 age group, and a high percentage of them have larger households (see Table 2).
These socio-economic characteristics are typical for visitors at recreation sites in Israel. Similar
respondents’ features were found in surveys in the Carmel Park (see Enis et al., 1974; Shechter and
Baron, 1976; Nevo et al., 1997).
Table 2. Demographic and Socio-Economic Characteristics: Sample vs. Israeli
Population*
Characteristics Sample (%) Israeli population(%)
Education: 10 years’ schooling or less University degreeGross income per family** above national average about national average below national averageCar ownershipAge structure (for adults 18+) 18-29 30-49 older than 50 Family structure 4 members or less 5 members or more
4.732.5
50.326.922.882.8
28.463.18.5
62.237.8
13.118.7
50.010.040.050.4
30.239.130.7
70.030.0
* Data for the Israeli population are based on the Central Bureau of Statistics, Statistical Yearbook,
1995 ** The most recent data on gross average income are from a survey conducted in 1992/1993, and itwas NIS 5,348 Our question related to this value, although in 1995/1996, the income was mostprobably higher.
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CHAPTER 2
RECREATIONAL PATTERNS IN THE UPPER GALILEE AREA
This chapter summarizes the recreation patterns in existing parks and nature reserves in UpperGalilee. It is estimated that 700,000 people visit the parks annually. 95% of the visitors visited thearea in addition to the current visit within the last five years, and 72% visited within the past twelvemonths. The activities in the parks vary by season. Picnicking is the most popular activity and 60-94% engage in it (it is more popular in the winter than in summer). Recreation is characterized byyoung visitors. Only 8% of the visitors are 50 years and older vs. 31% in the general population.People go to the parks in large groups. Among the young visitors, of those in the 18-29 age-group,50% go in a group of at least 4 members, but among those of the 30-49 age-group these groupsconstitute 84%. These two groups constitute 28% and 63% of the visitors respectively. The length ofthe stay varies by season. In the summer 64% come for a few days, while in the winter and springonly 30% stay overnight. The length of stay has implications for visiting restaurants and to usingaccommodation facilities. Throughout the year about 50%ate at a restaurant or planned to visit duringtheir stay in the area. The division between those who ate or planned to eat varies by season. In thesummer 36% of the visitors ate at a restaurant during the current visit, and another 15% planned to eatin a restaurant. In the winter 24% ate at a restaurant and 28% planned to eat. The major differencebetween the seasons is in the mean expenditure per family for those who ate in a restaurant. It variesbetween NIS 273 in summer and NIS 57 in winter. The use of accommodation facilities means that33% stay at bed & breakfast accommodation (zimmers), 32% stay in guest houses and hotels, 17% intents and bungalows, and the rest stay with friends and family. Capacity of hotel rooms and beds inthe area is apparently in excess.
This chapter reviews different aspects of the current recreational patterns in Upper Galilee as reflected
in our survey. It provides information on people’s actual behavior (revealed behavior) in the various
parks, to be compared with their responses to a hypothetical situation regarding the Hula Project (see
Chapter 4).
2.1 Number of Visitors to the Upper Galilee Area
A major question of importance for studying present recreation is estimating the total number of
visitors in the area. Two alternatives are discussed:
Fleisher and Saati (1995) studied the recreational patterns in the Upper Galilee area. Using a national
survey of the adult Jewish urban population they estimated that 38% visited the area in the twelve
months prior to the survey, and 68% of these visits were for recreation, which means that 26% of the
Jewish urban population were in Upper Galilee for recreation purposes. Since the survey was not
conducted among the non-Jewish population, we have to make assumptions regarding their behavior.
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We also have to make assumptions regarding the Jewish non-urban population since they were not
included in the survey, as well. A maximal number of visitors results from the assumption that the
recreation patterns in the entire Israeli population are like those among those interviewed
(justification for assuming that the non-Jewish population behaves like the Jewish population might
be the fact that they reside closer to the Galilee area than the majority of the Jewish population). From
the size of the Israeli population of 1995, a maximum estimate of Israelis vacating in Upper Galilee in
1995 is estimated at 1.4 million people (excluding the overseas tourists who visited the area). Use of
alternative assumptions for non-Jews and for non-urban population will result in lower estimates.
As the second alternative, we collected data on the number of visitors at the major parks in the
Galilee area: Banias, Tel Dan, Hula Reserve, Hurshat Tal and Nahal Ayun (see Table 3)1.
Table 3. Actual Number of Visitors at Upper Galilee Recreation Sites
Number of visitors Sites 1994 1995BaniasTel DanNahal AyunHula ReserveHurshat TalTotal Israelis
Total overseas tourists% of tourists of all visitors
213,155171,06845,94771,84266,617568,629
183,52224.4
254,986188,97878,73888,75981,139692,600
191,66221.7
In 1994 the total number of visits by Israelis at these parks was 570,000, and in 1995 it increased to
700,000. We decided to adopt the number of 700,000 as a reasonable baseline estimate of the number
of visitors at parks in the region. We are aware that some people might visit other parks than those in
our survey of the region e.g., Beit Ussishkin, Tel Hai, etc., so our figure may be an underestimate.
But it may also be an overestimate: (a) high percentage of visitors move from one site to another (see
Section 2.5) and are therefore counted more than once, wherever they pay an entrance fee; (b) some
people visit the region more than once a year (see Section 2.2), and are counted on each visit. To
1 The data was provided by the Nature Reserve Authority and by the National Parks Authority.
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summarize, throughout this document the figure 700.000 is taken as the number of visitors to the area
in 1995. We disregard overseas tourists, and concentrate on the behavior of Israelis.
The gap between the values of 1.4 million and 0.7 million may seem unreasonable. Note, however,
that some people interviewed at home misremembered visits not made during the previous 12 months
as if they had been; some among the 28% who went to Galilee for recreation traveled the area without
visiting parks, and were not counted;, they might include visitors to restaurants in the area, people
going to festivals, or just driving around.
2.2 Previous Visits in the Preceding Five Years
Table 4 shows that according to our surveys, 95% of the respondents visited Upper Galilee, in
addition to the current visit, during the preceding five years. 72% of the respondents visited Upper
Galilee in the preceding 12 months, but the percentage varies according to the distance traveled from
their residential origin to Upper Galilee. The larger the distance traveled, with higher travel costs, the
smaller the percentage of visitors to the area more than once in the previous 12 months, and the
smaller the average number of visits per visitor during this period.
Most of the visitors, regardless of where they reside, visited Upper Galilee previously in the
preceding five years. Out of those living within 49 km of Upper Galilee 98% visited in the preceding
five years; the percentage slightly decreases to 95% for those living 150 km and more away. The
effect of distance is crucial for visits during the preceding12 months: the respective percentages are
88% and 57%.. As expected, the complementary percentage, the percentage of those who visited (in
addition to the current visit) within the preceding 1-5 years, increases with distance. This result partly
reflects the ‘selection’ procedure. The question regarding visits 1-5 years previously was addressed
only to those who did not visit during the last year.
Table 4. Previous Visits to Upper Galilee by Distance Traveled
Percentage of( % of
visitorsdistance group)
Meanof
numbervisits
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Distance previous visits no visitwithintheprevious5 years
total (%ofvisitors)
withintheprevious12months
withintheprevious1-5years*
(km) within theprevious 12months
within theprevious 1-5years
0 - 49 87.7 10.5 1.8 100.0 3.4 2.850 - 99 73.5 21.4 5.1 100.0 2.5 2.6100 - 149 66.6 29.3 5.1 100.0 2.3 2.7150 + 57.4 38.0 4.6 100.0 2.3 2.7
* The mean number refers only to those who visited 1-5 years previously - a period of four years.Consequently we do not have information on those who have visited in the previous year and alsovisited 1-5 years previously.
Table 4 shows the distribution of previous visits as a function of distance traveled. The change in the
number of visits per visitor is interesting. The number of visits slightly decreased with the distance
traveled for those visiting within the previous 12 months from 3.4 to 2.3. The number of visits within
the previous 1-5 years is for a period of four years, and not a single year, and applies only to those
who did not visit in the previous year.
To conclude, visits to Upper Galilee are apparently a recurrent rather than a rare experience for most
of visitors. Note that the question did not refer to visits to a specific park, but the area in general.
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2.3 Activities at the Recreation Sites
The interviewees were asked about the two activities they did at the park where they were
interviewed. Since the interviewees were asked about two activities, the columns in the table
reporting the answers for each site sum to more than 100%. The most common activities were hiking,
picnicking, and swimming. The type of recreational activity depends on the season (see below). Table
5 presents the (significant) relationship between activities and the survey season 2.
Table 5. Activities and Survey Season
Activities SeasonsSummer Fall Winter Spring
SwimmingPicnicHikingSportsOther
31.753.770.92.21.8
31.759.159.17.6
28.3*
1.136.793.85.1
5.1**
22.344.779.28.12.5
Chi - square value - 175.55 Degrees of freedom - 12 P< 0.0001
* “Other” in fall represents mainly rafting. This activity characterizes the Yarden Park, where weinterviewed only in fall.** “Other” in winter represents mainly fishing and bird watching in the Hula Project, where weinterviewed only in winter. The size of the sample in the Hula Project is too small for any significantconclusions.
Table 5 shows that the activities vary by season. Hiking was very popular in the cold seasons, and it
lost popularity to swimming when it gets warmer. Picnicking retained a similar importance
throughout the year. The results partly reflect the fact that interviews were conducted in each season,
at different sites (see Section 1.1).
We find a significant relationship between the respondent’s age and the activities specified. All age-
groups engaged in hiking more than in other activities (Table 6), but visitors in the 18-29 age-group
2The chi-square and the probability values show that the relationship is significant, meaning that there is a probability (asspecified) that the activities are the same for all sites (the null hypothesis). Since the probability is low (less than 0.0001 inthis case) we cannot accept this claim but reject the null hypothesis and conclude that the activities are different (thealternative hypothesis). In the following analysis we refer to a relationship as significant when the probability is smallerthan 0.10. The test is performed using the chi-square values.
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participated more often in swimming and other sports than other age groups, while visitors in the 30+
age-group engaged more in hiking.
Table 6. Interviewee’s Age and Preferred Activities
Activities done Age-groups18-29 30-49 older than
50SwimmingPicnicHikingSportsOtherTotal
18.431.242.54.13.8
100.0
12.329.348.23.66.6
100.0
9.930.749.52.07.9
100.0Chi-square value15.107
Degrees of freedom - 8 P<0.057
As expected, the survey site affects the recreational behavior of visitors. Table 7 shows that one
recreational activity is dominant at each site due to its physical attributes. The recreational activities
refer to the site of the interview, not to the region generally.
Since the interviewees were asked about two activities, the columns in the table reporting the answers
at each site sum to more than 100%, but they show how many visitors at a certain park engaged in a
certain activity. This question is important for designing the number of picnic tables or the length of
hiking trails.
Most (more than 90%) of the recreationists who visited the Hula Reserve, Tel Dan, Banias and Nahal
Ayun engaged in hiking, a reasonable result since these sites offer attractive scenery and trails. 100%
of Hurshat Tal visitors went swimming, a result reflecting the fact that the surveys were conducted
only in summer and fall; the 60% at Yarden Park who engaged in “other” activity, went rafting, an
activity characteristic only for this site. The result reflects that interviews at this park were conducted
only in October, and generalization to other seasons would be misleading. The results for the Hula
Project should not be generalized either. Interviews at the Hula Project were conducted only in
March, and the number interviewed was limited. At the Hula Project, unlike other sites, picnicking
was not one of the two activities undertaken by visitors since as yet no picnic facilities exist there.
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The “other” activity by 12.5% at the Hula Project was fishing or bird watching, which will probably
characterize this park.
Table 7. Survey Site and Recreational Activities
The sitesActivitiesUndertaken
HulaReserve
Tel Dan HurshatTal
Banias YardenPark
NahalAyun
HulaProject
Totalsample
SwimmingPicnicHikingSportsOther
0.029.695.11.24.9
7.147.294.15.82.1
100.089.817.16.210.1
7.547.490.75.21.1
23.344.142.810.459.7*
5.530.193.16.81.3
4.79.485.70.0
14.3**
22.649.175.15.69.2
Chi-square value - 656.9 Degrees of freedom - 24 P < 0.0001
*, ** See footnotes to Table 5.
The significant relationship between the survey site and recreation activities shows that the visitors
chose the site due to their preferred activities, and activities were determined by the attributes of the
site.
2.4 Group Size and Recreation
People seem not to limit themselves to recreating with their own family but do so in larger groups.
The size varies among the recreation sites.
Groups with more than 6 visitors constituted 45% of the groups at Hurshat Tal (see Table 8), 52% of
the groups at Yarden Park, and over 53% of the groups at Nahal Ayun. On the other hand these large
groups were only 21% at the Hula Project and 33% at the Hula Reserve.
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Table 8. Survey Site and Group Size
Group SizeSurvey Site 1-3
people4-5people
6 andmore
Total
Hula ReserveTel DanHurshat TalBaniasYarden ParkNahal AyunHula Project
30.926.224.830.021.328.236.8
35.835.629.728.226.718.342.1
33.338.245.541.852.053.521.1
100.0100.0100.0100.0100.0100.0100.0
Chi-square value 19.241
Degrees of freedom - 12
P < 0.083
The relationship between group size and respondents’ age is significant(see Table 9). 50% of young
people (18-29 years old) recreated in a small company (1-3 members), as did 43% of respondents
aged 50 and older. Respondents aged 30-49 were characterized by large groups: 36% of them had 4-5
members, and 48% had 6 and more members. The 30-49 age group probably recreated with friends
besides their own family, unlike the other age groups.
Table 9. Age and Group Size
Age groupGroup Size 18 - 29 30 - 49 50 and older1 - 3 members4 - 5 membersmore than 6 membersTotal
50.222.427.4
100.0
15.736.547.8
100.0
43.317.938.8
100.0Chi-square value 101.5 Degrees of freedom - 4 P < 0.0001
2.5 Visiting Additional Sites
About half the vacationers visited only the site where they were interviewed, and the other half
moved around from one site to another. The question referred to the number of sites that the
interviewee visited during the current visit prior to the interview (visits and not intentions), and
should be interpreted as the minimum number of sites visited in the region during the current visit.
The interview might have been conducted in an early stage of the visit, and reflects only some of the
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sites visited. According to Table 10, 47% of the visitors moved from one site to another, and on
average they visited 1.8 additional sites on the same trip.
Table 10. Survey Site and Visiting Several Sites
Survey site Only one site (%of the sample)
More than one site(% of the sample)
Mean number ofadditional sites
Hula ReserveTel DanHurshat TalBaniasYarden ParkNahal AyunHula ProjectTotal sample
45.053.065.548.052.046.570.053.0
55.047.034.552.048.053.530.047.0
2.02.12.01.71.61.71.71.8
The visitors to Hurshat Tal and the Hula Project were less likely to move from one site to another
(only 35% and 30% respectively moved around). A possible explanation is that Hurshat Tal is
characterized by large groups (see Table 8), and large groups are less likely to move around. An
alternative explanation is the range of activities available in the site. The situation at the Hula Project
is unclear, but since the sample was very small we prefer not to generalize.
Visitors apparently treat the region as a series of parks and move from one to another.
2.6 Duration of Stay
56% of the respondents came to the area for a single day, while 44% of the visitors stayed a few days
(in the area itself or nearby). The percentage of the visitors who spent a few days in Upper Galilee
depended on the season of interview (see Table 11): 64% of the respondents went there for a few days
in August compared with 51% in October. In winter and spring a majority went for a single day (69%
in winter and 71% in spring).
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Table 11. Seasons and Duration of Visit to Upper Galilee
Duration of visitSeason A single day A few days Total
SummerFallWinterSpringTotal
36.349.269.471.156.1
63.750.830.628.943.9
100.0100.0100.0100.0100.0
Chi-square value - 79.3 Degrees of freedom - 6 P<0.0001
The duration of the visit naturally affects the demand for accommodation and restaurants, and has an
economic impact on the region (see Sections 2.7, 2.8).
The relationship between length of stay and distance traveled from place of residence is positive. The
farther you reside, the more likely are you to stay overnight, since you spend more money on travel
expenses and spend longer on travel. The results are summarized in Table 12.
The probability of staying overnight rises from 7% for those who traveled 50 km or less to 81% for
those residing 150 km away or more.
Table 12. Length of Stay and Distance Traveled
Distance (km) Single day’sstay
Few days’ stay Total
0 - 4950 - 99100 - 149150 +
93.370.131.519.1
6.729.968.580.9
100.0100.0100.0100.0
Chi-square value = 217.7 Degrees of freedom = 3 P<0.0001
2.7 Visits to Restaurants
We were interested in visits to restaurants and expenditure on food and drink during the visit. 27% of
the visitors said they had already visited a restaurant, 51% did not intend to visit one on the current
trip, and the rest had not visited but planned to do so (see Table 13). Those who actually visited a
restaurant were asked about their expenditure there.
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Table 13. Visits to Restaurants vs. Season
Seasons% of allsample
Summer Fall Winter Spring
Did not intend to visitrestaurantsHad not visited butintended to visitHad visited restaurantsTotal
51.3
21.227.5
100.0
48.9
15.435.7100.0
44.9
26.029.1
100.0
48.3
27.823.9
100.0
63.2
17.119.7100.0
The percentage of those who ate at a restaurant was larger in the summer (36%) and in the fall (29%).
This is reasonable, since in these seasons the stay is relatively longer (see Table 11).
We asked those who ate at a restaurant about expenditure per family. The amount varied for the
season (see Table 14), and was higher in summer and fall. This was manifested in a higher percentage
who spent NIS 200 and more (about 40% in these seasons, vs. less than 20% in winter and spring),
and also in the mean expenditure. The mean annual expenditure per family was NIS 187, and varied
between NIS 33 and NIS 273 in spring and summer respectively .
Table 14. Expenditures in Restaurants by Season (Contingent on a Visit)
Sum (NIS) % of restaurantvisitors
Summer Fall Winter Spring
NIS 1 - 99 NIS 100 - 200Above NIS 200Total
32.139.728.2
100.0
12.643.344.1100.0
20.340.639.1
100.0
46.433.320.3100.0
56.134.89.1
100.0Mean expenditureper family
273 218 57 33
The statistical analysis shows no significant relationship between the socio-economic characteristics
and expenditure at restaurants.
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2.8 Accommodation Facilities in Upper Galilee
The demand for accommodation plays an important role in evaluating the profitability of investments
in recreation. First we describe the results of our surveys: the use of different facilities (sub-section
2.8.1) and expenditure per family and per individual for overnight accommodation (sub-section
2.8.2). These values are compared with the supply of rooms and beds in the region (sub-section
2.8.3); we conclude by comparing demand and supply (sub-section 2.8.4).
This discussion is of relevance to the Hula Project, since we expect it to generate additional demand
for accommodation, in the park itself or in Upper Galilee area, and we should know whether at
present demand or supply is in excess.
2.8.1 Demand for Accommodation Facilities
The number of nights spent in accommodation facilities depends on the number of recreationists
staying overnight and the duration of the stay, and whether people stay with friends or in commercial
facilities. Table 11 shows that the percentage of visitors staying overnight varied by the season of the
visit: visitors were more likely to stay overnight in summer and fall (64% and 51% respectively) than
in winter and the spring (31% and 29%, respectively).
Those who stayed overnight were asked about their accommodation arrangements. They can be
divided into three groups (see Table 15): (a) those staying with friends and family (14%); (b) the
majority, those staying at less expensive facilities - bed & breakfast (zimmers), tents and bungalows
(50.4%); ( c ) those staying at hotels and guest houses (32%).
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Table 15. Type of Accommodation Arrangements
Type of lodging % of sampleFriends and familyBed &breakfastTents, bungalowHotelGuest houseOtherTotal
14.433.417.010.920.83.5
100.0
2.8.2. Expenditure per Overnight Stay
Expenditure per family per overnight stay depends on the type of facility selected, socio-economic
characteristics, and duration of stay. Table 16 shows that these values vary considerably from less
than NIS 300 to over NIS 600. The high expenses characterize summer, when 67% of those staying
overnight spend more than NIS 600 . Mean annual expenditure per family according to our sample is
NIS 633.
Table 16. Expenditure per Family per Total Overnight Stay by Season
SeasonSum (NIS) perseason
Summer Fall Winter Spring Total
1 - 299300 - 600more than 601
10.229.272.4
30.637.520.7
26.512.53.5
32.720.33.4
100.0100.0100.0
Seasons per sumSum (NIS) Summer Fall Winter Spring1 - 299300 - 600More than 601Total
7.430.961.7
100.0
27.850.022.2
100.0
54.237.58.3
100.0
48.545.46.1
100.0Chi-square value - 55.8 Degrees of freedom - 6 P > 0.0001
Statistical analysis of the factors affecting the total overnight expenditure shows that socio-economic
characteristics such as income, gender, age, and education had no significant effect on the amount.
The only variable with a significant effect was the number of vacation days (chi-square value =
13.22, P<0.07). As the number of days increased, total expenditure increased also.
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Expenditure per single night of stay per family depended on income, education, and number of
vacation days (see Table 17).
Table 17. Expenditure per Single Overnight Day vs. Socio-Economic Characteristics
Expenditure per day (N), in NISCharacteristics N<20 20<N<200 200<N<350 350<N<2500 TotalIncome (nationalaverage):Below averageApprox. averageAbove averageMuch above averageAll sample
76.970.165.754.364.9
9.911.110.19.110.0
7.78.515.118.913.4
5.910.39.117.711.7
100.0100.0100.0100.0100.0
Chi-square value - 22.67 Degrees of freedom - 9 P < 0.007Education (SchoolingYears)11-12without Univ degreeUniversity degreeAll sample
64.367.262.864.5
15.75.58.210.3
9.215.616.913.7
10.811.712.111.5
100.0100.0100.0100.0
Chi-square value = 13.73 Degrees of freedom - 6 P < 0.033Days of Staywithout overnightone daytwo daysthree daysAll sample
100.06.89.532.048.4
028.833.316.016.4
033.933.328.019.3
030.523.824.016.9
100.0100.0100.0100.0100.0
Chi-square value = 163.65 Degrees of freedom - 9 P < 0.001
Income. The difference among the income groups can be seen from the frequency of those spending
less than NIS 20 (including zero): as income increases the frequency of this group decreases. The
decrease is from 77% to 54% among those with income below and much above average, respectively.
About 10% of the respondents spent between NIS 20 and NIS 200, regardless of income. But the two
high expenditure classes, NIS 200-350 and NIS 350-2000 are more frequent as income increases.
Among those with income below the national average these groups constitute 14%, among those with
income above average they constitute 24%, and among those with income much above average they
constitute 37%. In general recreationists are a population with high incomes (56% of the respondents
had above-average family income, an overrepresentation of these income groups).
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Education. The table shows that a small difference exists among the groups in the percentage who
spend less than NIS 20 per night, about 65%. However, the percentage of those with expenditure over
NIS 200 increased with education, from 20% for those with 11-12 years’ schooling to 29% for those
with university degree.
Days of stay. The table shows that the longer one stayed, the less one spent per day. Probably the
lower spenders were the people who stayed at less expensive accommodation facilities.
2.8.3 Availability of Accommodation Facilities in Upper Galilee
The Galilee Tourist Authority provided us with data of availability of rooms and beds in the area as
well as occupancy rates, but the data were for 1993 (the Authority lacks updated data). In 1993 there
were 2,500 rooms and 8,500 beds at all types of accommodation facilities in Galilee (their spread, and
consequently statistics, cover an area larger than Upper Galilee). 50% of the beds were in bed &
breakfast accommodation, a relatively new type of facility in 1993, and 41% were in hotels and guest
houses (see Table 18). Analysis of distribution of overnight stays shows that the number of nights at
bed & breakfast rooms is 50% of the total, equal to their share in availability of beds. The percentage
of nights at hotels is very low, only 7% of the nights spent in the area, whereas the percentage of
nights in guest houses is 30%, much higher than their share of beds.
Percentage occupancy varied among the different types of facilities. On average it was 26% (see
Table 18): lowest in hotels, 14%, and highest, 58%, in guest houses (which are close substitutes). The
reason for this divergence is unclear. Occupancy of bed & breakfast rooms was relatively low, 21%,
perhaps reflecting the short experience in this type of facility or the owners’ tastes. In general this
occupancy rate is very low and can be compared to the occupancy rate in other regions in the country.
The Central Bureau of Statistics provides data for the bed occupancy in two types of facility, showing
that 142,000 guests stayed at these facilities in 1995 : (a) The rates range between 28% and 36% at
tourist hotels and ‘not yet listed hotels’ in Galilee in 1991-96. In 1995, 11,000 guests stayed at these
facilities in the area (CBS, 1997, p. 95). (b) Bed occupancy at four hotels in kibbuzim and moshavim
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in Upper Galilee ranged between 54% and 58% in 1993-1996 (CBS, 1997, p. 112). In 1995, 131,000
guests stayed at these hotels.
Table 18. Supply and Occupancy at Accommodation Facilities in Galilee (1993)
Type of facility Frequency of facilities(% of rooms)
Frequency of stay bytype of facility (% ofnights)
Annual occupancy bytype of facility (%)
Bed & breakfastGuest housesHostelsHotels and otherTotal
50.022.08.019.0100.0
51.030.012.07.0
100.0
21.058.028.014.0
26.0 (mean)
Source: The Galilee Tourist Authority
The 1993 data show an excess supply of beds in the area. The occupancy rate may vary between
seasons and localities, but we do not have data to support more specific conclusions. The Galilee
Tourist Authority, which provided us with data for 1993, could not provide us with more recent
figures. The data of the Central Bureau of Statistics show higher occupancy rates, but the area and
lists of hotels are not comparable.
2.8.4. The Accommodation Market
In the previous sections we discussed demand and supply for accommodation facilities in the area.
The most recent data on hotel occupancy from 1993 (see Table 18) show very low rates. Demand for
overnight accommodation is expected to rise especially with the addition of new attractions to the
area. As these become more diverse, whether the Hula Project or other attractions, the duration of stay
in the area will increase, as will the likelihood of overnight stay. Overnight expenditure will
probablyincrease in the future, as family income increase, since income has a positive effect on
expenditure per night. Since the occupancy rate in the area is low, the profitability of constructing
additional hotel beds has to be examined carefully.
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CHAPTER 3
SOCIAL CARRYING CAPACITY
This chapter analyzes the actual behavior of recreationists, in terms of the distance between twoadjacent groups of visitors. It was observed that 23% of the groups are less than 5 meters apart, and61% of the groups are less than 10 meters apart. The observed proximity is not disturbing (asubjective reaction). When asked if the neighbors disturbed them, 84% answered that they were notdisturbed, and only 3% were very disturbed. We have to conclude that the visitors are tolerant toproximity. Analyzing the reaction to proximity using logistic analysis, we find that income increased theresponse of being disturbed, engaging in picnic made people more tolerant, and engaging in sportmade people less tolerant.
In the designing of a park for outdoor recreation, capacity limitation is crucial. We distinguish
different definitions of capacity. Physical capacity is “the maximum number of persons who can
occupy a site at one time” (Walsh, 1986). This number depends on the type of activities (e.g., football
vs. picnic, where a picnic allows more people per unit area). Using a physical criterion, however,
could result in damage to the natural environment due to overuse. Ashworth (1984) refers to
ecological capacity, which depends on the environmental carrying capacity.
As social scientists, we are interested in social carrying capacity, namely the number of visitors that
maximizes social benefit (i.e., satisfaction with the visit) of all visitors in any given time. The
hypothesis is that each user is concerned with his or her benefit from the recreation experience net
after deduction of benefits due to crowding (imposed by the presence of other users). If congestion is
too high it might result in net negative benefits. The user can adjust by moving to another site or by
leaving.
3.1. Measuring Crowding
We measure the social carrying capacity by estimating the observed minimal distance between the
interviewed group and the adjacent group. The findings show that 23% of the groups are located
within 5 meters of the adjacent group (see Table 19), 38% are 5-10 meters apart, and 25% are 11
meters and more apart (for 14% of the interviewees an adjacent group was not seen or heard,
sometimes due to the surface conditions, but sometimes since the distance was too large. Perhaps this
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group could have been added to those with a distance of more than 20 meters, but we preferred to
leave it ‘as is’). The observed behavior reveals that closeness was acceptable to the visitors at least at
the sites surveyed. Interviewees were asked whether other visitors impaired their experience. For 84%
of the respondents the close presence of other visitors did not disturb them; for 12% it disturbed
them a little, and only for 3% was it very disturbing. The negative reaction was explained by
congestion, noise, smoke from barbecues and dirt.
Table 19. Social Carrying Capacity Characteristics
Characteristics Sample (%)Distance between the interviewed groups less than 5 meters 5-10 meters 11- 20 meters more than 20 meters distance can’t be estimatedDisturbance : none some much
23.338.117.67.214.084.412.7 2.9
Table 20 lists the mean distance between visitors’ groups in all sites sampled. Apart from the Hula
Project, where the number interviewed is small, at the other sites the mean distance varied between 14
and 43 meters. The distances varied between the seasons and in summer we re much smaller than in
the winter.
Table 20. Observed Mean Distance between Groups of Visitors
Survey place Mean distance (meters)Hula ReserveTel DanHurshat TalBaniasYarden ParkNahal AyunHula ProjectTotal
26.114.721.225.115.643.368.830.7
Table 21 presents the relationship between age and disturbance. It shows that, as might be expected,
younger visitors are less disturbed by crowdness compared to the older groups, while for those 18-29
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years old 12% complain that they are disturbed, the percentage increases to 18% for those 50 years
and over.
Table 21. Disturbance and Respondent’s Age
Respondent’s age Not disturbing Disturbing Total sample18-29 years 30-49 years older than 50
88.283.181.5
11.816.918.5
100.0100.0100.0
Table 22 shows a significant relationship between the type of recreational activity and the reaction to
congestion. Proximity is relatively more disturbing in the case of hiking and sports, and least
disturbing in the case of picnicking and swimming.
Table 22. Disturbance and Type of Recreational Activity
Activity Not disturbing Disturbing Total sampleSwimmingPicnicHikingSportsOther
89.189.282.671.190.5
10.910.817.428.99.5
100.0100.0100.0100.0100.0
Chi-square value - 19.0 Degrees of freedom - 4 P<0.001
3.2. Proximity and Logistic Regression
We used logistic analysis to seek the reasons for disturbance due to proximity (for theoretical
background see Appendix C; for additional analysis see Section 4.4). We examined the dependent
variable disturbance as a binary variable, with the value 1 when the individual is disturbed due to
proximity and 0 otherwise. The explanatory variables are the activities which the individual does in
his or her current visit, the socio-economic characteristics, and distance between groups (see
Appendix B for list of variables). The data were run with the logistic procedure in SAS. The results
were reached by stepwise regression with a backward procedure.
Table 23 shows the parameter estimates, Wald’s chi-square, the probability of this value, and the odds
ratio.
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Table 23. Logistic Model for Analyzing the Disturbance due to Proximity
Variables Parameter estimate P > chi - square Odds ratioInterceptPicnicSportsIncomeN = 754 -2LOG L
-2.4294-0.6297 0.8593 0.2553
Intercept only 647.4Intercept and covariates 620.1
0.00010.00350.01620.0033
0.0001
0.0880.5332.3621.291
The results show that the reaction to proximity depends on income level and on the activities
performed. The higher the income, the more likely is the person to say that proximity disturbs. As
income rises and moves one from one quintile to the next, one is 30% more likely to say that
proximity disturbs. The activities performed have opposite effects. Picnicking participants are very
tolerant to proximity, whereas sports participants are very intolerant to it.
3.3 Implications for the Hula Project
The analysis of the reaction to crowding and the observed behavior have implications for the Hula
Project, where crowding is likely. As discussed in Chapter 4 , we expect 380,000 visitors to the park
in the base year if the entrance fee is NIS 30 and the number of visitors in parks to the area remains
700,000. As stated there, this forecast disregards people who at present do not visit the area, but with
the addition of the Hula Project will start to do so, thus raising the number of visitors above 700,000.
It also disregards overseas tourists, about 200,000 of whom visited parks in Upper Galilee in 1994-
1995 (see Table 3). Consequently, the value of 380,000 is a conservative forecast for the base year.
Assuming that the number of visitors will increase, the number is expected to rise. The problem is
exacerbated due to the uneven distribution of visitors in months, on holidays and on days of the week.
From the analysis in this chapterwe may infer that since the majority of visitors are tolerant to
crowding we might find the same tolerance in the Hula. However, since the visitors’ reaction depends
positively on income, we can expect that the tolerance will turn into intolerance in the future. As for
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activities, picnicking makes for more tolerance of proximity, sports for less. Therefore, the designers
would do well to disperse picnic areas throughout the park, and avoid planning for sport activities.
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CHAPTER 4
EXPECTED RECREATIONAL BENEFITS IN THE HULA PROJECT
The Hula Project aims at recreating a marsh in order to avoid the negative environmental externalitiesof the current situation - nitrification of the Kinneret, spontaneous fires, low water level. Recreatingthe marsh landscape is achieved by digging canals and a lake, “creating” islands, populating the areawith wild animals, planting characteristic vegetation, and attracting birds. It is hoped that thislandscape will be attractive to recreation, prompting safari, bird watching, and boating. The researchdeals with assessing the expected benefits of the Project for entrepreneurs and for society. Theevaluation is composed of a few steps:Evaluating the expected number of visitors. 87% of the visitors to Upper Galilee expect to visit theHula Project. If the park were opened today, 381,000 visitors may be expected. Due to the expectedincrease in population and increase in standard of living we expect an annual increase in the numberof visitors 2-4% per year. In ten years 460,000-560,000 visitors are expected, besides overseastourists. Evaluating the expected entrance fee. Using Contingent Valuation Method we evaluate theWillingness To Pay (WTP) entrance fee. On average people are willing to pay NIS 30. 63.5% of therespondents are willing NIS to pay 30 and more. Only 1% of the respondents refuse to pay at all.Analysis of the factors affecting WTP shows that income affects positively (normal good), family sizeaffects negatively, distance affects positively, and the activities preferred by the individual affect asfollows: safari, a unique activity to the park, affects positively, horse riding and swimming affectnegatively. The last two activities are offered at alternative sites with a lower entrance fee, and theresult is reasonable.The expected revenues were calculated assuming NIS 30 per person is charged. Since 380,000visitors are expected, annual revenues of NIS 11.4 million are expected in the first year of operation.Under reasonable assumptions, in 25 years of operation a present value in the range of NIS 123-400million may be expected.
4.1 Introduction
Forecasting the benefits of the Hula Project requires a distinction between two different terms,
revenues for the entrepreneurs and benefits for society. These reflect two perspectives, the private
and the public, which characterize the project from its construction stage and will continue during
its operation. Some expenses are covered by the government and others by the private sector. The
government finances construction of the canals, digging the lake, etc. The justification for this
involvement is that re-flooding the Hula will reduce environmental degradation. The Hula in its
present state is indirectly blamed for the nitrification of the Kinneret, the danger of spontaneous
fires, and the dust storms in the region. The benefits from reducing environmental degradation are
difficult to quantify. However, construction of the park was made possible by these public
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investments, and the expected benefits of the park to recreationists can be calculated against
government expenditure, and will justify it.
Private entrepreneurs have two types of costs, the opportunity (or alternative) cost, their revenues
from agriculture lost by constructing the Project, and direct costs during the construction stage and
during the operation of the project. These costs are expected to generate revenues that will cover the
expenses.
In forecasting expected economic benefits we refer only to those from expected visits to the planned
site, disregarding those from hotels, restaurants or commercial areas; this means that we calculate a
lower boundary of benefits.
Since the environmental resource to be analyzed - the Hula Project (Hula Park) - is under
construction, we can only set up a hypothetical market through which its economic benefits may be
assessed.
Estimation of benefits and revenues follows several steps:
* Forecasting the expected number of visitors to the Hula Park (Section 4.2);
* Estimating the entrance fee per visitor (Sections 4.3 and 4.4);
* Calculating the demand curve (Section 4.5);
* Computing the recreational benefits of the park in economic terms for entrepreneurs and for society
(Section 4.6);
* Calculating future benefits of the park (Section 4.7).
4.2 Forecasting the Number of Visitors
4.2.1 Willingness To Visit the Hula Project
A regular demand curve shows the relationship between the quantity demanded of some commodity,
recreation, , and the price of that commodity. In trying to construct a demand curve for recreation, we
have to clarify what quantity is demanded, and the meaning of the price. The quantity demanded may
be represented by the number of visits per year, or the number of visitors to a site per year. The first
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approach is desirable for analysis of visits to a beach or a playground, where frequent visits by a
person may reasonably be found, and where the number of visits per person is (relatively) large.
When we analyze the number of visits to a unique site, e.g., an archeological site, a person may be
presumed to visit at most once a year, and the number of visitors is the correct variable. In analyzing
Upper Galilee area, we might assume a few visits per person per year, but in analysis of the Hula
each person is more likely to visit once per year, and we shall analyze the number of visitors.
In Section 2.1 we estimated the number of visits (not visitors) to Upper Galilee, concluding that in
1995 the total was 700,000 visits. Disregarding recurrent visits, we regard this as the potential
number of visitors to Upper Galilee, only slightly an over-estimate.
Forecasting future visits in the Hula Project is based on hypothetical questionsabout willingness to
visit. To clarify the hypothetical ‘commodity’, the questionnaire described to the respondents the
main features of the proposed park: artificial lake, safari park, bird sanctuary, etc., and then asked
respondents to indicate their willingness to visit such a park.. 87% of the interviewees responded
positively, 12% were not sure or did not know, and only less than 1% of the respondents answered
negatively (see Table 24). Given current level of visits to Upper Galilee (0.7 million visits annually,
see Section 2.1), if these intentions were realized, they might result in 600,000 visitors to the park.
Table 24. Willingness to Visit the Planned Hula Park
Characteristics Sample (%)Willingness to visit Hula Park wish to visit not sure or does not know does not expect to visit Total sample
87.4 11.7 0.9100.0
The Hula Park may be expected to generate new visits to the area, since it will appeal to people who
at present do not visit it. However, since our survey was not a national home survey, we cannot
estimate the impact on the population at large. Our surveys were restricted to parks in the Galilee
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area and included only those that are at present in the area, so we can estimate only the impact on
current visitors.
In our analysis we disregarded overseas tourists. Note that in 1994-1995 200,000 tourists visited the
Upper Galilee parks (see Table 3), and some of them may be expected to visit the Hula Project. We
disregard the potential contribution of overseas tourists since we have not questioned them, and we
cannot predict their response.
These results should not be accepted literally, as one would expect a discrepancy between intentions,
which do not involve an actual commitment and allocation of time and money resources, and
realization. The results do indicate, however, a large potential demand which could be realized, at
least in part, through proper marketing
4.2.2 Willingness to Visit the Park and Socio-Economic Characteristics
We analyzed the effect of socio-economic variables on willingness to visit the park. Regarding age,
we found that the older the age the greater the willingness to visit the new park ( see Table 25);
perhaps this result reflects the recollections of people in the 50+ age group of the Hula in its former
condition, as a marsh, before it was drained in the1950s.
Table 25. Age and Willingness to Visit the Hula Project
Age group Wish to visit Do not expect to visitor not sure
Total
18 - 29 years 30 - 49 years50 years and olderTotal
81.689.991.987.5
18.410.1 8.112.5
100.0100.0100.0100.0
Chi-square value 13.733 Degrees of freedom 4 P < 0.008
As for income, we find that the higher the income the greater the willingness to visit ( see Table 26).
The major difference is between those below average income and the rest. Only 81% of those below
average income wish to visit as against almost 90% among the other groups. Though the relationship
is significant, the major impression is that people wish to visit the new project.
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Table 26. Income and Willingness to Visit the Hula Park
Income Group Wish to visit Do not expect tovisit or not sure
Total
Below national averageAbout national averageAbove national averageTotal
81.488.988.487.4
18.611.111.612.6
100.0100.0100.0100.0
Chi-square 12.895 Degrees of freedom - 4 P < 0.012
The relationship between willingness to visit the new park and the respondent’s family size, gender,
country of birth and education was found to be insignificant.
4.2.3 Preferred Activities
Respondents were asked about the activities in which they plan to participate (the interviewers read
aloud a list of the planned activities in the park). Each person was asked to indicate his or her two
most preferred activities, and the responses are summarized in Table 27. The stated activities are
those that are unique to this park: visiting the safari park (45%), boating (42%), and visiting the fowl
and bird sanctuary (38%); activities available in other parks were hardly mentioned, i.e., picnicking
which is very popular at present in Upper Galilee parks, attracted 9% of the respondents, and
swimming appealed to 14%.
Table 27. Preferred Activities in the Park*
Activities % of sampleFowl and bird sanctuarySafari parkBoatingPicnickingSwimming in a poolFishingHorseback riding
38.245.042.09.414.115.021.5
* Respondents were asked to state two preferred activities.
We may conclude that visitors look for unique activities, not those available in existing sites. The
relationship between the preferred activities and socio-economic variables was examined (see Table
28). The relationships with age and education were found to be significant, while characteristics such
as income, respondent’s gender and car ownership were found to be insignificant.
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Table 28. Preferred Activities and Socio-Demographic Characteristics
Characteristics Birds Safari Boating Picnic Swim Fishing HorseAge group 18-29 30-49 50 + All sample*Schooling years 9-10 11-12 without univ. degreeUniv. degree All sample**
20.366.812.920.4
5.730.6
26.936.720.4
22.568.68.924.0
4.929.6
27.038.524.0
28.164.57.022.9
4.241.6
22.931.322.9
31.352.216.44.6
11.946.3
17.923.94.6
39.652.87.67.3
7.543.9
19.628.97.3
24.664.411.08.2
3.445.4
28.622.78.2
43.354.42.212.5
3.935.6
33.926.712.5
*Chi-square 59.634**Chi-square 47.293
* Degrees of freedom = 12** Degrees of freedom = 18
* P < 0.0001**P < 0.0001
The diverse interests in terms of activities might facilitate management of the expected number of
visitors by allocating them among the park’s activities, thereby reducing potential crowding.
4.3 WTP for Entrance Fee
The economic value of the Hula Park cannot be estimated directly as the environmental resource still
does not exist. It can be projected, however, by means of a hypothetical market technique, termed the
Contingent Valuation Method (CVM) (see Mitchell and Carson, 1989).
CVM assumes that any change in the provision of some environmental amenity results in positive (or
negative) change in benefits to consumers, which can be ‘translated’ into a monetary amount.
Economists consider the maximum sum individuals are willing to pay for an increase in the provision
of some environmental amenity (given income level and other relevant attributes) to be a reasonable
estimate of its economic value or ‘price’; this sum is termed Willingness To Pay (WTP) (Shechter,
1994).
In our surveys interviewees were induced to state the maximum sum of money they would be willing
to pay as an entrance fee to the Hula park, as if they were able to ‘purchase’ the park’s amenities on a
hypothetical market. In eliciting WTP, the first steps are to describe the hypothetical commodity
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(market) and the ‘bid vehicle’ of collecting payment. After describing the planned park, the
commodity, the interviewees were asked about their willingness to pay an entrance fee per adult. We
could have asked individuals to pay a rate per each attraction, or for two or three attractions, or to
purchase an annual subscription (in on-site surveys it is common to ask for entrance fee, while in
home surveys researchers ask for a tax increase). We asked for WTP an entrance fee that would
provide access to any two attractions on a list of various attractions.
Quite often the WTP elicitation is conducted in dichotomous choice framework, e.g., ‘Are you
willing to pay an entrance fee of NIS ...?’. We tried to find the maximal WTP, which in our case
could be NIS 50, 40, 30, 20, 10, 3, or zero. (The procedure for eliciting the WTP was as follows:
interviewees were asked about their willingness to pay NIS 30 (equivalent to $10) as entrance fee per
individual. If they agreed, they were then asked about higher sums, NIS 40 or 50; if they disagreed,
they were asked about lower sums, NIS 20 and 10. If they refused to pay NIS 10, they were asked,
‘Are you willing to pay any amount at all?’.
Table 29 presents the answers to the WTP question. 32% of the respondents were willing to pay NIS
30 (a possible ‘anchoring effect’; see Mitchell and Carson, 1989), and 63% were willing to pay NIS
30 and more. The mean payment was NIS 30 per individual (the median is the same). By aggregating
WTP responses over the sampled population, one may obtain an indication of the economic value of
the environmental good under investigation.
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Table 29. Maximal Willingness to Pay for Entrance to the Hula Park
WTP Sample (%) NIS 50 NIS 40 NIS 30 NIS 20 NIS 10 Some positive sum Zero WTP
13.2 18.1 32.2 23.7 10.7 0.9 1.1
Mean WTP sum 30.2
A few comments are due. Unlike previous studies on recreation in Israel (Shechter et al., 1974; Nevo
et al., 1997), 99% of the respondents were willing to pay a positive amount, and 88% were willing to
pay NIS 20 and more. By contrast, in previous studies a relatively high percentage refused to pay
anything. Possible explanations are that our survey was conducted in parks with an entrance fee, and
in general most parks in Israel have an entrance fee; in 1974 entrance into most parks was free.
While the entrance fee to nature reserves in 1995-96 was NIS 12, people were willing to pay more
for the Hula, and the mean, as mentioned, is NIS 30. A possible explanation for the high WTP
values is the unique activities and attractions described to the interviewee (see Section 4.4, the
discussion of the results of Logistic regression). Note that we did not ask about WTP values above
NIS 50. This upper limit might be an under-estimate for some people (a truncated value), but we do
not have to worry about outliers (people who bias and exaggerate their WTP in order to achieve a
desirable result: see Hanley and Spash, 1993, Ch. 3).
The responses on WTP were examined with the various socio-economic characteristics, to find which
affected the values. The only variable with a significant effect was income (see Table 30). The higher
the income, the higher the WTP amount. Other socio-demographic variables, such as age, education,
gender and family size, were found insignificant for explaining the WTP values.
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Table 30. WTP Amounts and Income Level
Income level per WTP amountWTP (NIS) Below national
averageAbout nationalaverage
Above nationalaverage
10 20 304050
Total
13.725.537.916.16.8
100.0
10.725.432.517.214.2
100.0
9.222.629.921.217.1
100.0Income level
WTP (NIS)per income
Below nationalaverage
About nationalaverage
Above nationalaverage
Total
10203040 50
28.623.626.018.810.8
27.328.727.224.627.5
44.147.746.856.661.7
100.0100.0100.0
100.0100.0
Chi-square value - 33.45 Degrees of freedom - 16 P < 0.006
4.4 Logistic Regression Analysis of WTP
To explain the factors affecting the WTP we used econometric methods. We examined whether the
dependent variable, the value people were willing to pay, is distributed normally, in order to treat the
variable as continuous, but the results showed that the hypothesis of normal distribution had to be
rejected.
Instead we decided to analyze the amounts people were willing to pay using logistic regression (for
theoretical background see Appendix C). This method required transforming the dependent variable
into a set of discrete (binary) dependent variables. The new dependent variable can be interpreted as,
‘Are you willing to pay a certain sum of money (e.g. NIS 30), and you refuse to pay a higher sum?.’
Note that our question was not phrased, ‘What is the sum that you are WTP as entrance fee?’, which
might lead us to continuous values for the dependent variable. Our question referred to pre-specified
values, and can be rephrased as ‘Is the maximum amount you are willing to pay a specified amount
(e.g., NIS 40) ?’ the answer being discrete-‘yes’ or ‘no’.
The hypothesis is that a person’s WTP is a function of that individual’s characteristics. We examined
the WTP, the dependent variable, as a binary variable which gets the value 1 when the individual is
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willing to pay a certain value or higher, and otherwise 0. Alternative values were used ranging from
20 to 50, and each was run separately.
The explanatory variables are (a) the individual’s characteristics: age, education, income, family size,
employment , income;(b) the individual’s previous experience in recreation - number of visits in the
past, type of activities at present visit; and (c) distance traveled from home to Upper Galilee area as a
proxy for expenditures on the recreation trip. ( See Appendix B for a list of variables and details on
each of the variables ).
Table 31 lists the significant variables and their sign, to emphasize whether the variable adds to or
subtracts from the odds ratio.
Table 31. Logistic Model for Predicting Willingness To Pay (WTP) in Hula Project ,
Sign Analysis
Variables Sign of parameter estimateWTP = 20SwimmingHorsesDistanceWTP = 30IncomeFamily sizeDistanceWTP = 40SafariIncomeFamily sizeDistanceWTP = 50IncomeFamily size
--+
+-+
++-+
+-
Table 31 shows that income has a positive effect on WTP. This result is reasonable and was found in
previous works (Enis et al., 1974), since recreation is a normal good. Family size affects negatively,
which means that large families find it difficult to pay the large sums for new attractions. This is
important for determining policy on the entrance feefor big families.
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Another variable which affects positively is distance. An increase in distance will increase the odds
that one is willing to pay high sums vs. not willing. Three activities affect one’s WTP. Safari affects
positively, whereas swimming and horse riding affect negatively. This shows that visitors are willing
to pay high sums as entrance fee only for activities which are unique, while activities available at
alternative sites (i.e., swimming and horse riding) have a negative effect on the WTP.
(For further details see Appendix C)
4.5 Constructing a Demand Curve
Using CVM we asked about the WTP for the Hula Park. We asked the maximum amount that the
individual was willing to pay per visit. For some people the actual entrance fee will be lower than
their WTP, for others it will be higher. Those for whom the entrance fee will be higher will ‘exit’ the
market, and will not purchase the good.
We construct the demand curve by assuming one visit per person for the price range which is lower
than the individual’s WTP, i.e., we aggregate the number of people willing to pay a certain value and
higher.
We found (see Table 29) that 13.2% of the expected visitors to the park were willing to pay NIS 50
per visit. We interpret this to mean that 13.2% out of 600,000 are expected to visit the park if the
entrance fee is NIS 50 (Table 32), i.e., 78,000 future visitors. The same method allows us to calculate
the number of visitors expected to pay NIS 40 per visit or higher (this figure includes the visitors who
consent to pay the higher sum, i.e., NIS 50, as well as those willing to pay NIS 40). Table 32 presents
the expected demand for Hula Project, by calculating for each price level the cumulative number of
visitors. Figure 1 presents the demand schedule as a graph.
Table 32. Expected Demand for the Hula Project using Contingent Valuation Method
Expected number of visitors (cumulativepercentage and number)
Willingness to pay per visit
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78,000 (13.2%) 187,800 (31.3%) 381.000 (63.5%) 523,200 (87.2%) 587,400 (97.9%) 592,800 (98.8%)Total - 600,000 (100.0%)
NIS 50NIS 40NIS 30NIS 20NIS 10
Some positive sum (NIS 3)0
From the table we see that as in every demand curve the lower the entrance fee, the higher the
number of expected visits. In constructing the demand schedule we assumed that income, substitute
sites, and tastes are given.
Figure 1. Expected Demand Curve for the Hula Project Using CVM
Page
78.0
10
20
30
40
50
WTP(NIS)
Number of visitors (thousands)
188.00 381.0 523.0 587.0
3
4.6 Revenues, Total and Net Benefits from the Hula Project
This section looks at the benefits that will accrue to society and to entrepreneurs if the Hula is
developed for recreation. If the demand curve is known, assuming that the entrance fee is given, the
benefits can be calculated as follows:
Total revenues (TR) to the entrepreneurs are the entrance fee multiplied by the number of visitors,
i.e., the product of price (P) by quantity (Q). In Figure 2 this area is denoted B. Total benefit (TB) is
the total area under the demand curve up to the quantity actually consumed. In Figure 2 this area is
denoted A + B. In calculating the total benefits, we accumulate for each individual the maximum
amount that the individual is willing to pay for an additional unit, a value which is higher than the
actual price charged. The social net benefit (NB), or consumer surplus, can be measured as the
Figure 2. Revenues (B), Total Benefits (A+B) and Net Benefits (A), as Measured from a Demand
Curve.
Page
78.0
10
20
30
40
50
WTP(NIS)
Number of visitors (thousands)
188.00 381.0 523.0 587.0
3
A
B
C
difference between total benefit and the actual expenditure on recreation. We measure the Net
Benefit (NB) as the area below the demand curve and above the entrance fee level, ‘the utility which
the visitor does not pay for’, area A in Figure 2.
In forecasting benefits we start by presenting them as if the project existed at present, and the items
were calculated for this year, the base year.
Using the demand, function we calculate revenues, and total benefits for alternative entrance fees.
The results are presented in Table 33.
“The Program for Development of Tourism - Hula Project” refers to NIS 30 as the recommended
entrance fee in operating the project. If this price is charged, the revenues to the entrepreneurs will be
maximized; 380,000 visitors will visit the park annually, revenues will total NIS 11.4 million and
total benefits will be NIS 14.1 million.
The demand function has two sections; for prices higher than NIS 30 the demand curve is elastic, and
for lower prices the demand curve becomes inelastic. The different elasticities mean that when prices
are lowered from 50 NIS 50 to 30 NIS 30, the revenues increase, whereas further decrease from 30
NIS 30, results in lower revenues.
Total benefits are maximized when entrance is free and the park has maximal attendance—600,000
visitors annually, and the benefits total NIS 17.6 million.
Table 33. Revenues, Total and Net Social Benefits
Entrance feeNIS
Number ofvisitors
Total revenue(million NIS)
Total benefit(million NIS)
Net benefit (million NIS)
5040302010
78,000187,800381,000523,200587,400
3.97.511.410.55.9
3.9 8.2814.116.917.6
00.782.666.5011.7
The figure of 380,000 visitors is based on the response of visitors at the Upper Galilee parks in 1995-
1996. For the limitations of this figure, see Section 4.2.1. The result of these limitations is that the
total revenues in the base year and the total benefits are conservative estimates.
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4.7 Forecasting the Present Value of the Expected Revenues and Benefits
4.7.1 Assumptions
We are not concerned with the revenues and benefits in a single year, since the park is expected to
last indefinitely.
To translate the values base year values into expected revenues and benefits we assume:
1. all the prices are constant at the 1995-1996 level in NIS, and for convenience can be translated into
dollars (the exchange rate is NIS 3.0 per dollar);
2. the population will increase, according to forecasts of the Central Bureau of Statistics (1992), at an
annual rate of 1.0-1.3%;
3. real income per capita will increase in the long run by an annual rate of 1.5 - 2.5%. These values
are based on Bank of Israel reports that GDP per capita increased at a mean rate of 2.5% during 1990-
1995, and on the values in other periods;
4. due to assumptions 2 and 3 we assume an annual increase in the number of visitors by 2, 4 and 6%,
alternatively;
5. all the calculations refer only to Israeli visitors, disregarding overseas tourists. The park has a big
potential for ornithologists as well as for the increasing number of tourists interested in wildlife (eco-
tourism). In 1994-1995 overseas tourists accounted
30% of the visitors to the area;
6. all the calculations are performed assuming that the political situation remains unchanged. Peace
relations with Lebanon, Syria, and Jordan will probably attract many visitors from these countries to
Upper Galilee due to the proximity, and will mean additional overseas tourists in the Hula;
7. the real interest rate is assumed alternatively as 5, 8, 10 % in real terms. All the calculations are
performed for these alternative rates;
8. the project will operate for 25 years;
9. only recreational benefits are calculated. We disregard additional income generated in hotels,
restaurants and commercial institutes;
Page
10. total revenue in the base year (TR0) is NIS 11.4 million, and total social benefit (TB0) is NIS 15.7
million.
4.7.2 Recreational Benefits
We expect the number of visitors to increase for two reasons: the population is increasing (assumption
2) and recreation is a normal good, and with increase in income per capita (assumption 3) more people
will recreate in Upper Galilee and visit the Hula Park. Assuming alternatively 2%, 4%, and 6%,
annual increase in the number of visitors, the figures will be ( see Table 34 ):
Table 34. Forecasting Increase in the Number of Visitors
Increase in population Number of visitors in 10 years
Number of visitors in 20 years
Number of visitors in 25 years
2% 4% 6%
455,300562,000680,000
555,000802,700
1,221,900
612,800976,600
1,635,200
The present value of the entrepreneurs’ revenues and the increase in social welfare are calculated
assuming that the number of visitors increases and for various real interest rates (according to the
mathematical appendix: see Appendix D). Table 35. presents the results for alternative rates of
increase in visitors.
Table 35. Present Value of Expected Revenues and Benefits(million NIS) Assuming Annual
Increase in Visits of 2, 4, 6%.
Real interest rates 2% increase ofvisitors
4% increase ofvisitors
6% increase ofvisitors
Present Revenue 5%8%10%Present Total Benefit5%8%10%
200.1147.5123.0
247.0178.8152.3
252.7181.5146.1
311.9224.7183.7
323.9225.8182.7
400.0278.9225.7
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Revenues and the benefits vary according to the assumptions regarding the expected increase in the
annual number of visitors, and according to the interest rate. If wetake the interest rate as given (e.g.,
8%), as the number of visitors increases, the present value of revenues and benefits increases. With
2% increase in visits total revenue will be NIS 147.8 million, and with 6% increase it will rise to
225.5 million. Alternatively, if the rate of change of visitors is given (e.g.,4%), an increase in interest
rate will decrease the present value of revenues and profits, since the value of money received in the
future will be less. The present value of revenues is NIS 252.3 million assuming 5% interest rate, and
it decreases to NIS 149.0 million assuming 10% interest rate. With the alternative assumptions,
revenues range between NIS 123.7 and 325.6 million. From Table 35 we see that total benefits vary
between NIS 123.0 and 399.6 million.
The present value of the revenues has to be compared with the investment in the construction phase
and with maintenance costs. If the net present value is positive, it means that the entrepreneurs will
have profits. The recreational benefits are compared with the government’s expenditure on the
construction of the canals and the islands. However, we have to recall that the government’s
investments were justified by environmental degradation, which is not quantifiable. Obviously, the
additional park will contribute to the demand for existing parks, restaurants and accommodation
facilities in the region, which will generate additional incomes and employment, but these too were
disregarded in this study.
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CHAPTER 5
CONCLUDING REMARKS
The analysis shows that the Hula Project will attract a large population of visitors, mostly visitors to
the region at present. The Project is likely to generate additionality and not replacement, in that
visitors will go to the park in addition to the parks they visit at present. We do not expect
replacement, since many of the attributes of the park are unique and cannot be found elsewhere; we
found that they were mentioned by potential visitors as the attractions. Additionality is expected also
in the respect of people who at present do not visit Upper Galilee due to lack of interest, but who are
expected to go to the area because the attractions offered by the park.
The additionality of visitors has implicationsfor the region at large. The demand for accommodation
and for restaurants will increase, and will generate more employment and income. Though our data on
accommodation imply an excess supply of rooms and beds in the area, as mentioned in Section 2.8,
we could not obtain updated figures, and the current situation is not clear. Only if there is excess
demand for accommodation will the construction of new facilities be justified.
The added demand for accommodation does not imply that hotels have to be located within the
Project, although its entrepreneurs are interested in this location. The exact location of the facilities is
irrelevant for the region, since excess demand for recreation services will generate additional income
and additional employment.
***
Forecasting the number of visitors in the Hula Project, we have to consider the likelihood of crowding
in the park. We forecast 380,000 visitors per year, if the park were opened today. A 2% (alternatively
4%, 6%) annual increase in the number of visitors would mean that in ten years the park will have
455,000 (562,000, 680,000) visitors not counting overseas tourists, who in 1994 1995 added 30% to
the number. While respondents at present show tolerance for crowding (see Chapter 3), as income
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increases one is more likely to become disturbed and intolerant of it. Income per capita is increasing,
so visitors are expected to react with less tolerance in the future.
Crowding means environmental degradation as well, and the expected number of visitors might
threaten the park and its unique characteristics.
Three reservations exist about the pressure of recreationists:
a) The unique characteristics of the park are likely to spread the visitors (relatively)evenly
throughout the year:
In considering the annual number of visitors we recall that the distribution over the year in terms of
months and days of the week is not uniform. Some months are much busier than others. The data for
recent years (1994-1995) in Tel Dan are revealing: 17.6% of the annual number of visitors went there
in August, vs. 2.5% who went in December, namely in August seven times more people visited than
in December. If this distribution were in the Hula, then 67,000 visitors would be expected in August
and 9,500 in December.
The distribution of potential visitors over the seasons might be advantageous for the park. Bird
watching is mostly in the spring and fall, and 38% of the visitors mentioned bird watching as one of
their desired activities in the park. Proper marketing might encourage visiting in these periods and not
in August specifically. This might ease the pressure on the park in the summer, and might benefit the
region generally by extending the season over more months.
b) Proper design of activities will disperse the recreationists throughout the park area.
Proper planning of various activities throughout the park may ease the problem of crowding. Our
analysis and previous studies show that people are more sensitive to crowding when doing certain
activities than others. It would be advisable to disperse throughout the park picnic areas, where people
are less sensitive to proximity, and avoid planning for activities like sports, where physical capacity is
limited and proximity generates disturbance.
Page
c) Entrance fees may be used to control the number of visitors.
Entrance fees can be used to disperse the visitors among the seasons and days of the week, with
lower prices for the desired times and higher prices for other times. The experience and methods of
other parks in this respect may well be followed.
***
Expected revenues were estimated under different assumptions. We used conservative values to
present the demand only of Israelis, disregarding overseas tourists, though these seem to be 25% of
the visitors to the region. We calculated only revenues from park entrance fees, disregarding revenues
from restaurants or hotels. We assumed alternatively a low annual increase in the number of visitors
( 2%) and a high increase (6%), a low real interest rate (5%), and a high real interest rate (10%). The
minimum present value of expected revenues amounts to NIS 123 million. If the expected present
value of expenditure on the infrastructure and the operating costs are lower, the entrepreneurs are
expected to make profits. However, revenues are likely to be higher, which will increase the
profitability of the project.
Page
REFERENCES
Ashworth, G.J. 1984. Recreation and Tourism. First Edition, Bell and Hyman.
Central Bureau of Statistics. 1992. Projection of Population in Israel up to 2005. Special series No.
913. Jerusalem.
Central Bureau of Statistics. 1996. Statistical Yearbook 1995. Jerusalem
Central Bureau of Statistics, 1997, Tourism and Hotel Services Statistics Quarterly, Vol. 25.
Enis, R., Baron M. G., and Shechter, M., 1974. Demand for Recreation in Carmel, Haifa: Center for
Urban and Regional Studies, Technion (in Hebrew)
Fleisher, A. and Saati, S. 1995. Recreation in Upper Galilee. Rehovot: Development Study Center.
(in Hebrew)
Hanley, N. and C. Spash. 1993. Cost Benefit Analysis and the Environment. Hants, England: Elgar
Publishing.
Mitchell, R.C. and Carson, R.T., 1989. Using Surveys to Value Public Goods: The Contingent
Valuation Method. Resources for the Future.
Nevo S., N. Zeitsev, M. Shechter and B. Reiser. “Existence Value of an Environmental Asset”
Riv’on Lekalkala (The Economic Quarterly) June 1997, pp. 263-283 (in Hebrew).
Shechter M. , 1994. “Valuing the Environment”. in Folmer, H., Gabel, H.L., and Opschoor, H. (eds),
Principles of Environmental and Resource Economics: A Guide to Students and Decision Makers,
Ch. 8 Aldershot, UK, Edward Elgar Publishing.
Shechter, M. , and Baron, M. G. 1976. “Outdoor Recreation as an Economic Service”
Riv’on Lekalkala (Economic Quarterly) No. 91, pp. 401-408 (in Hebrew).
Shechter M., Enis, R., Reiser B., and Tzamir, Y. 1981. ”Evaluation of Landscape Resources for
Recreational Planning”. Regional Studies, Vol. 15, No 5, pp. 373-390.
Shechter M. and Lucas, R.C. 1979. Simulation of Recreational Use for Parks and Wilderness
Management. Baltimore, MD. Johns Hopkins University Press for Resources For the Future,
Walsh, R.G. 1986. Recreation Economic Decisions: Comparing Benefits and Costs. Ventura
Publishing.
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APPENDIX A
QUESTIONNAIRE
Page
המרכז לחקר משאבי טבע וסביבה
אוניברסיטת חיפה
19953\1996סקר באתרי הגליל העליון
תאריך הראיון. 1
, בניאס 4, חורשת טל 3, תל דן 2, שמורת החולה 1: מקום הראיון. 2
נחל עיון 6, פארק הירדן 5
200 179 204 227מספר המרואיין . 3
שעת התחלת הראיון. 4
תוצאותיו . אוניברסיטת חיפה עורכת מחקר ביחס לטיולים באזור הגליל העליון, שלום
נודה לך אם . תעזורנה למתכננים להתאים את התכנון של האזור לדרישות האוכלוסייה
. תוכל להקדיש כמה דקות כדי לענות על השאלות
? ______________________מהו מקום מגוריך. 5
: באיזה אמצעי תחבורה הגעת לכאן היום. 6
89.8 90.4 89.7 92.1במכונית פרטית 1
3.6 1.1 3.9- בטרמפ או ברגל 2
1.0 1.7 2.0 1.3( כולל מוניות(בתחבורה ציבורית 3
(:ב"מועצה מקומית וכיו, י חברה מסחרית"ע(בטיול מאורגן מה מעמדך -
4.1 5.6 1.5 6.6משתתף בטיול מאורגן 4
0.5 0.6 1.5- ) 20שאל עד שאלה : למראיין(מדריך או נהג בקבוצת ילדים 5
1.0 0.6 1.5- חפש מבוגר המשתתף : למראיין(מדריך או נהג בקבוצת מבוגרים 6
)שאל עד סוף השאלון בטיול ואז
? בקבוצה שלכם כמה מבוגרים יש וכמה ילדים. 7
(הקבוצה כוללת את האנשים איתם המרואיין מטייל או עורך פקניק: למראיין)
6 6 4 5) ממוצע(מבוגרים ________ 1
3 3 4 4) ממוצע( ילדים ________ 2
אביב, חורף, סתיו, קיץ: הממצאים מדווחים עבור כל עונה בנפרד 3
Page
? בביקור הנוכחיכמה ימים אתם שוהים או מתכוונים לשהות מחוץ לבית . 8
24.4 25.1 9.3 9.7שעות אחדות 1
47.2 44.0 40.7 28.8יום שלם 2
22.8 22.9 17.2 11.9יומיים 3
4.6 6.9 15.2 20.8ימים 3 4
-0.6 11.3 16.4ימים 4 5
1.0 0.6 6.4 12.4ימים ויותר 5 6
מהו הישוב בו אתם מתאכסנים או תתאכסנו . 9
)אם התאכסנו ביותר ממקום אחד רשום את כולם וכמה ימים בכל אחד: למראיין(
___________ שם הישוב 1
0.4 0.4 2.2 2.7) ממוצע______ (כמה לילות 2
__________ שם הישוב 3
0 0 1.6 1.5) ממוצע______ (כמה לילות 4
__________ שם הישוב 5
0 0 0 2.5) ממוצע______ (כמה לילות 6
'בבית מלון וכו, היכן אתם מתאכסנים או תתאכסנו בביקור זה אצל ידידים. 10
11.6 12.5ידידים או משפחה 1
44.2 45.8צימרים 2
37.2 25.0בית הארחה 3
9.3 10.4בית מלון 4
18.6 2.1בונגלו , אוהלים 5
2.3 4.2: __________________ פרט, אחר 6
52.8 56.0 50.0 35.3לא מתאכסנים
? מאיזה מקום יצאתם לטיול היום. 11
71.2 72.1 54.9 38.5) 12- עבור ל(מהבית 1
28.8 27.9 45.1 61.5) 13- עבור ל(ממקום האכסון 2
)אל תכלול את זמן השהיה ארוחות: למראיין(כמה זמן ארכה הנסיעה מהבית עד לאתר הראשון שביקרתם היום . 12
12.6 14.6 3.4- פחות מחצי שעה 1
9.1 12.4 6.4- חצי שעה עד שעה 2
29.3 32.0 25.5 8.4שעה עד שעתיים 3
11.1 9.6 15.2 20.4שעתיים עד שלוש שעות 4
6.6 3.4 2.9 22.6שלוש עד ארבע שעות 5
2.0 - 0.5 5.8ארבע עד חמש שעות 6
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0.5 - 0.5 3.1למעלה מחמש שעות 7
28.8 27.9 45.6 61.2השאלה לא רלבנטית
אל תכלול את זמן השהיה: למראיין( כמה זמן ארכה הנסיעה ממקום האכסון עד לאתר הראשון שביקרתם היום . 13
)באתרים או זמן באתרים או זמן ארוחות
20.2 17.3 30.9 28.8פחות מחצי שעה 1
6.6 7.8 9.8 19.5חצי שעה עד שעה 2
1.5 2.8 3.9 10.6שעה עד שעתיים 3
- - - 0.4שעתיים עד שלוש שעות 4
0.5 - - 0.4שלוש עד ארבע שעות 5
- - - -ארבע עד חמש שעות 6
- - - 0.4למעלה מחמש שעות 7
71.2 72.1 55.4 39.8השאלה לא רלבנטית
)אל תכלול את זמן השהיה באתרים או זמן ארוחות: למראיין: (כמה זמן ארכה הנסיעה מהבית עד מקום האכסון בו לנתם. 14
- 1.7- - פחות מחצי שעה 1
0.5 0.6- - חצי שעה עד שעה 2
2.0 4.5 10.3 8.4שעה עד שעתיים 3
12.1 10.2 17.2 20.4שעתיים עד שלוש שעות 4
10.6 9.0 10.3 22.6שלוש עד ארבע שעות 5
3.0 0.6 6.4 5.8ארבע עד מחמש שעות 6
0.5 0.6 1.0 3.1למעלה מחמש שעות 7
71.2 72.9 54.9 39.8השאלה לא רלבנטית
?כמה זמן אתם מתכוונים להיות באתר זה . 15
4.1 11.6 1.5 3.1פחות משעה 1
28.9 44.5 25.0 27.6שעתיים -שעה 2
34.5 37.0 32.4 31.1ארבע שעות -שלוש 3
19.6 5.8 11.8 15.1שש שעות -חמש 4
11.3 1.2 20.6 18.2יותר מחמש שעות 5
1.0 - 3.4 1.8יומיים 6
0.5 - 2.9 2.2שלושה עד ארבעה ימים 7
- -2.5 0.9חמישה ימים ויותר 8
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?מהם שני הדברים העיקריים שעשיתם או שתעשו היום באתר . 16
31.8 44.4 15.6 34.4בילוי ללא ארוחה ) שחיה במים (1
13.1 - 17.7 25.4פיקניק + שחיה ( פיקניק (2
2.0 - 10.9 6.9(בפרחים וכו , כולל הסתכלות בציפורים(בילוי בטבע ללא ארוחה 3
ספורט+ שחיה
43.4 36.5 39.1 31.2 פיקניק (מ"ק 3-פחות מ(הליכה ברגל להנאה 4
9.7 19.1 16.7 2.1 אחר ( מ"ק 3-יותר מ(הליכה ברגל כספורט 5
משחקי ספורט 6
: ____________________________________פרט, אחר 7
אנחנו רוצים לשאול אותך כמה שאלות על בקורים שלך באזור הגליל. כידוע לך האתר הוא חלק מאזור הגליל העליון
,האזור אינו כולל את החרמון. אזור הגליל העליון כולל את האתרים השונים מראש פינה עד מטולה: למראיין. (העליון
).סביב הכנרת, רמת הגולן
?באיזה אתרים נוספים בגליל העליון ביקרתם בביקור הנוכחי. 17
59.6 59.8 57.8 37.3ביקרנו רק במקום שאנו נמצאים בו כעת 0
40.4 40.2 42.2 62.7כתוב את השם של האתר : למראיין: (בקרנו במקומות נוספים 1
( או סמן אם מזכיר את האתר
21.2 19.4 15.7 19.3בניאס 2
11.2 1.4 9.8 10.8חורשת טל 3
11.2 8.3 1.5 3.1נחל עיון 4
23.7 8.3 12.7 20.2תל דן 5
2.5 - 1.0 2.2ברעם 6
2.5 4.1 - 1.3תל חצור 7
8.7 11.1 1.5 5.8פסל האריה , חי- תל, ב ית השומר 8
6.2 - 2.9 0.9בית אוסישקין 9
11.2 19.4 1.5 7.6שמורת החולה 10
13.7 12.5 20.6 21.5רמת הגולן 11
5.0 29.1 1.0 6.3חרמון 12
8.7 1.4 13.7 24.8כנרת 13
16.2 9.7 1.0 1.8מטולה 14
8.7 9.7 1.0 6.8כפר בלום , קייקים 15
3.7 1.3 0.5 1.8צפת , מרון 16
- - -0.5פארק ירדן 17
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? מה הסיבה העיקרית בגללה החלטתם לצאת לאזור . 18
27.4 20.1 15.7 19.4היינו מעונינים במקום יפה מחוץ לעיר כדי לטייל או לערוך פיקניק 1
29.4 40.2 35.3 30.4באנו בעיקר בגלל הנוף המיוחד של האזור והאתרים המיוחדים באזור 2
17.3 5.6 14.2 13.2חיפשנו מקום על יד מים 3
1.0 2.2 0.5 1.3אקלים מיוחד 4
- 1.1 1.0 2.2מבנה טופוגרפי מיוחד 5
5.1 2.8 1.5 1.3היינו מעונינים במקום שקט 6
6.6 10.1 13.2 5.3)________________ כתוב את הסיבה: למראיין: (פרט, אחר 7
8.1 10.1 13.2 15.0) כולל מים(שתי סיבות 8
5.1 7.8 5.0 11.9) ללא מים(שתי סיבות 9
?האם אכלתם ארוחה במסעדה בטיול הנוכחי או אתם מתכוונים לאכול. 19
19.4 23.6 28.7 35.7אכלנו לפחות ארוחה אחת , כן 1
16.8 27.5 25.7 15.4אבל אנו מתכוונים לאכול , לא 2
63.8 48.9 45.5 48.9לא אכלנו ואין לנו תוכנית לאכול 3
רשום את: למראיין(אנחנו רוצים לדעת כמה כסף אתה מעריך שהוצאתם במסגרת הטיול עבורך ועבור משפחתך . 20
הזמין את המלון לכמה, למשל, פרט למקרים בהם התחייב להוצאה, התייחס להוצאות שבצעו בפועל. התשובה בשקלים
).ימים
45.6 30.1 95.8 97.6) ממוצע עבור משפחה(ח "ש_ כמה הוצאתם עבור כניסה לפארקים ולמוזיאונים 1
33.5 57.0 218.5 273.0) ממוצע עבור משפחה(ח "ש__ כמה הוצאתם עבור מסעדות ומזנונים 2
104.4 108.4 627.1 843.3) ממוצע עבור משפחה(ח "ש_____________ כמה הוצאתם עבור לינה 3
החודשים האחרונים בנוסף 12-כלומר ב- האם אתה ומשפחתך טיילתם כבר באזור הגליל העליון בשנה האחרונה . 21
?לפעם הזאת
19.5 21.5 24.1 45.5לא ביקרנו בשנה האחרונה 0
80.5 78.5 75.9 54.5, כן 1
: כמה פעמים בקירוב-
14.9 23.4 16.7 15.1פעם אחת 2
30.8 24.0 31.8 24.7פעמיים או שלוש 3
34.9 30.9 26.8 14.6ארבע פעמים ויותר 4
19.5 21.7 24.7 45.7השאלה לא רלבנטית
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:השנים האחרונות 5- האם אתה ומשפחתך ביקרתם באזור ב . - 22
5.7 4.5 2.0 7.8) 24עבור לשאלה (השנים האחרונות 5-- לא ביקרנו ב 0
כן 1
:כמה פעמים בקירוב-
4.6 4.0 3.0 5.9פעם אחת 2
5.7 6.8 10.6 20.1פעמיים או שלוש 3
3.1 5.7 8.1 12.8ארבע פעמים ויותר 4
80.9 79.0 76.3 53.4השאלה לא רלבנטית
:י המרואיין"שאל את כל מי שביקר באזור וסמן בעיגול את כל התשובות המוזכרות ע: למראיין. (23
?כ לבקר באזור הגליל העליון"באיזו עונה של השנה אתה נוהג בד
1.6 2.3 0.5 1.9בחורף 1
21.8 25.1 9.5 10.2באביב 2
0.5 1.8 15.1 2.4בסתיו 3
17.5 5.4 9.5 44.7בקיץ 4
27.3 26.9 29.1 18.9בכל עונות השנה 5
- -29.1 16.0אביב וסתיו 6
- - 4.5 1.9קיץ ועוד עונה אחרת 7
31.1 38.3 2.5 3.9אין נוהג קבוע לביקורים באזור 0
?האם תבוא פחות לאזור , 25%- ומשך הנסיעה יתארך ב, אם מערכת הכבישים באזור תהיה עמוסה יותר. 24
37.3 27.0 40.2 33.9כן 1
62.7 73.0 59.8 66.1לא 2
. אמוד את המרחק לחבורה הקרובה לפני שתשאל ורשום את מספר המטרים: למראיין. 25
)99רשום , אם לא רואים אנשים
? האם זה מפריע לכם. מטרים יושבת חבורה אחרת של נופשים_______ במרחק
79.5 81.1 90.4 85.0) עבור לשאלות החולה (לא מפריע 1
15.9 13.6 8.7 13.6מפריע במקצת , כן 2
4.6 5.3 1.5 1.4) 26עבור לשאלה (מפריע מאד , כן 3
?מה מפריע לכם. 26
צפיפות 1
הרעש 2
ריחות, מנגל, עשן 3
לכלוך 4
Page
בשטח. הפארק יתבסס על הצפת שטחי הכבול במים ובניית אגמים מלאכותיים. באזור צפון החולה מתוכנן פארק חדש
אזור אכסון משולב, שייט על אגם, מוסים'פארק ספארי המשלב נופי ביצה עם חיות כמו ג, הפארק מתוכננים פארק ציפורים
. מים ועוד
? האם אתה צופה שאתה ומשפחתך תבקרו בפרויקט. 27
88.2 87.0 81.9 91.8כן , בוודאות 1
11.3 11.9 16.1 7.8לא בטוח / לא יודע 2
0.5 1.1 2.0 0.5) 28עבור לשאלה (לא 3
:רצונך לבקר בפרויקט החולה החדש-מה הסיבות לאי. 28
אין טעם 1
התנגדות עקרונית לפרויקט 2
חושש מהצפיפות 3
)עבור לשאלות רקע אישי: למראיין)
תאמר לי איזה שתיים מהפעילויות הבאות הכי מושכות אותך לפארק. אקריא בפנייך את הפעילויות המתוכננות בפארק. 29
:המתוכנן
42.7 49.4 33.7 29.6פארק ציפורים ועופות מים 1
47.9 43.6 43.2 41.7פארק ספארי 2
33.3 41.8 47.3 48.6שייט על אגם 3
15.1 7.5 14.1 17.9בריכות שחיה 4
6.2 13.9 9.5 8.3פיקניק 5
16.1 16.9 13.5 14.0דייג 6
15.6 19.8 30.6 25.6מסלולי רכיבה עם סוסים 7
5.2 - 2.0- אכילה במסעדה 8
?ח עבור בלוי יום שלם באתר כולל שתי הפעילויות שבחרת"ש 30האם אתה מוכן לשלם . 30
לא . 6 31.8 35.2 26.7 35.8כן . 1
ח"ש 20ח האם תהיה מוכן לשלם "ש 40 האם תהיה מוכן לשלם
לא. 7 15.4 22.7 19.0 16.5כן . 2
30.3 18.8 23.1 22.9כן . 8לא . 3
ח"ש 10 ח האם תהיה מוכן לשלם "ש 50האם תהיה מוכן לשלם
) 31עבור לשאלה (לא . 9 3.6 14.8 17.4 17.0כן . 4
15.4 7.4 13.6 6.4כן . 10לא . 5
האם אתה בכלל מוכן לשלם . 31
3.1 1.3 - 0.9לא . 0
0.6 - - 0.5כן . 1
Page
96.3 98.7 99.3 98.6השאלה לא רלבנטית
.אני רוצה להדגיש ששמך אינו נרשם על השאלון. הרשה לי לשאול אותך מספר קטן של שאלות אישיות, לפני שנסיים
)הצע לו שתי קבוצות גיל שנראות סבירות: למראיין? (לאיזה מקבוצות הגיל הבאות אתה שייך. 32
1.0 4.0 5.6 1.4 20עד 1
2 20-29 23.4 28.3 23.9 26.3
3 30-49 67.0 58.6 61.9 64.4
4 50-64 6.0 7.6 8.0 7.2
1.0 2.3 - 2.3ויותר 65 5
?מה גיל המבוגרים בקבוצה. 33
)סמן בעיגול את כל קבוצות הגיל שלפחות אחד מהאנשים בקבוצה נמצא בה, אפיין את הגילאים, נא: למראיין(
1 18-20 2.2 7.4 0.6 2.1
2 20-29 20.3 29.9 30.5 29.2
3 30-49 70.0 60.3 70.1 69.7
4 50-64 9.3 10.8 12.4 9.7
3.6 2.2 2.0 3.5ויותר 65 5
סמן בעיגול את כל קבוצות הגיל שלפחות אחד מהאנשים, אפיין את הגילאים, נא: למראיין? (מה גיל הילדים בקבוצה. 34
(בקבוצה נמצא בהן
29.7 36.7 39.7 50.7 6- למטה מ 1
2 6-13 47.6 45.6 29.3 41.5
3 14-18 15.4 17.2 9.6 7.6
? ________________________________מהי תעסוקתך. 35
(.דאג להתאים את הסימון לתעסוקה, רשום תשובת הנחקר ומיד לאחר מכן סמל: למראיין(
, מהנדס, רופא: כגון(בעלי מקצוע מדעיים ואקדמיים 0
19.1 21.3 17.1 16.1) מורה תיכון בעל השכלה אקדמית, מרצה באוניברסיטה
: טכניים ודומיהם כגון, בעלי מקצועות חופשיים אחרים 1
14.4 19.5 21.1 16.1) הנדסאי, טכנאי, אחות, ס יסודי"מורה בבי
5.2 4.9 7.0 7.3מנהלים 2
8.2 10.4 13.1 11.5עובדי פקידות ודומיהם 3
Page
5.2 3.0 8.0 3.2סוכנים וזבנים , עובדי מכירות 4
2.1 1.2 4.0 5.5עובדי שירותים 5
4.1 3.7 0.5 2.8עובדי חקלאות 6
5.7 4.9 4.0 6.9בבנייה ובתחבורה , במחצבים, עובדים מקצועיים בתעשייה 7
3.1 3.0 2.0 2.8עובדים אחרים בתעשייה בבנייה ובתחבורה ופועלים פשוטים 8
11.9 7.9 7.5 6.0סטודנטים 9
5.7 9.8 6.5 6.0אנשי צבא 10
4.6 4.3 3.0 8.7מחפש עבודה , גמלאי עקרת בית 11
10.8 6.1 6.0 7.3:____________________________ פרט, אחר 12
:שם הארץ, באיזו ארץ נולדת. 36
75.6 71.0 77.2 71.6ישראל 1
16.1 21.0 13.2 14.2(אוסטרליה, דרום אפריקה(ארצות דוברות אנגלית , אמריקה, אירופה 2
7.8 8.0 9.6 10.1( כולל טורקיה(אפריקה , אסיה 3
?כמה שנים למדת. 37
- - - -לא למד כלל 1
0.5- - - שנים 4למד עד וכולל 2
1.6 1.7 2.0 1.4שנים 5-8למד 3
33.2 32.4 41.6 40.8שנים 9-10למד 4
28.0 25.0 26.9 23.4השכלה על תיכונית או אוניברסיטאית בלי תואר אקדמי 6
34.2 38.1 26.9 30.7) קיבל תואר אקדמי(השכלה אוניברסיטאית מלאה 7
. ח"ש 5,300- כ ) שכר ברוטו לחודש- (ההכנסה הממוצעת למשק בית מכל המקורות הינה כיום . 38
:הינה) ברוטו(אם הכנסת משק הבית שלכם
פחות מהממוצע ) א
-- האם הרבה פחות מהממוצה
10.9 8.2 14.2 5.9כן 1
12.5 7.6 11.6 19.8לא 2
25.0 31.6 21.1 30.5בערך בסביבת סכום זה 3
מעל הממוצע) ב
האם הרבה מעל הממוצע
25.0 28.1 24.2- לא 4
26.6 24.6 28.9 43.9כן 5
:האם אתה בעל רכב כגון מכונית פרטית או טנדר. 39
Page
87.5 80.8 81.0 82.0כן 1
9.9 5.6 5.1 4.6, לא 2
האם עומד לרשותך רכב לשימושך הפרטי-
2.6 8.5 11.3 10.6כן 3
- 5.1 2.6 2.8לא 0
4 4אין נתונים ) ממוצע) (כולל עצמך(כמה בני משפחה גרים אתך . 40
: מין: סמן מבלי להקריא: למראיין. 41
69.6 63.3 56.3 66.5זכר . 1
30.4 36.7 43.7 33.5נקבה . 2
תודה רבה על עזרתך
:______________ שם המראיין: _______ שעת סיום הראיון. 42
Page
APPENDIX B
LIST OF VARIABLES
Income - a variable with 5 classes relating the household’s income level to the national average
income. (much higher than average level = 5, much lower than average = 1). The classes can be
compared to the households with incomes in the following brackets: 81-100%, 61-80%,...., 1-20%.
Family size - number of family members living in the same household.
Distance - a variable with 4 classes ranking the distance traveled from home to Upper Galilee
(Distance = 1 if respondent traveled 0 - 49 km, Distance = 2, 3 or 4 if respondent traveled 50-99, 100-
149, or more than 150 km respectively).
Type of activities - A dummy variable describing the respondent’s activities while visiting the site
where interviewed -- sports, swimming, hiking, picnic and other. The variable receives the value 1 if
the visitor participated in it, and 0 otherwise. Similar variables apply to the preferred activities in the
new park -- swimming, horse riding, bird watching, boating, safari, fishing and picnic. The variable
receives the value 0 if the respondent does not prefer the activity, and the value 1 if the respondent
prefers it.
Past visits- a variable with 3 class levels relating to the respondent’s past visits (Pastvisit = 0 if the
respondent has not visited in the last five years, Pastvisit = 1 if respondent has visited in the last five
years, but not the last year, Pastvisit = 2 if respondent has visited in the last year).
Group size - number of visitor’s group members (adults and kids).
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APPENDIX C
LOGISTIC REGRESSION
C.1. Theoretical Background - Logistic Regression
In analyzing logistic regression, the equation describing the probability function has the following
structure:
p x = eβ0 βx
1eβ0βx (1)
where (x) denotes the probability of willing to pay a certain value or higher values as entrance fee
for given values of the explanatory variables xi. In the first stage we estimate the coefficients using
maximum likelihood procedures.
Let us define the logit transformation as
g x =logp x
1 p x =β0βx (2)
The ratio p x
1− p x is defined as the odds that an individual will pay the specified sum of money or
a higher sum.
The odds ratio, ρ , is defined as the ratio of the odds for x =1 to the odds for x =0:
ρ=p 1/1− p 1p 0 /1− p 0
(3)
The odds ratio is calculated using the results of the logistic regression for the specific explanatory
variable. Substituting (1) into (3) we get
ρ=e β
When the independent variable is binary, the odds ratio measures how much more likely it is
for a person to be willing to pay when x =1 than to be willing to pay if x = 0 (e.g., if x = 1 means
one wants to participate in safari, and x = 0 means one does not, the odds ratio will measure how
Page
much more likely it is that one is more willing to pay in the first case) . The advantage if the odds
ratio is that it is independent of other explanatory variables. When the parameter estimate is positive,
ρ is larger than 1, which means that the odds when x = 1 are higher than the odds when x = 0. When
the parameter estimate is negative, ρ is smaller than 1, which means that the odds are smaller when
x = 1.The larger values mean that the variables are more effective.
C.2 Technical Details on the Logistic Regression
The data were run using the logistic procedure in SAS version 6. The results reported were reached
using stepwise regression with a backward procedure. The detailed results of the logistic regression
analyzing WTP for NIS 20, 30, 40 and 50 are reported in Table C.1.
Table C.1 shows that income has a positive effect on WTP in three out of four runs. An increase in
income as reflected in one’s moving from one quintile to another (see Appendix B) will increase the
odds of paying the specified sum or a higher value by 22-43%. This result is reasonable and was
found in previous studies (Enis et al., 1974), since recreation is a normal good. Family size affects
negatively, which means that large families find it difficult to pay the large sums for the new park.
An increase of one member of the family decreases the likelihood of willingness to pay a certain
value or higher by 0.12 - 0.19%. Another variable which affects positively is distance. An increase in
1 km will increase the odds by 0.4%, which means that the further away one resides the more is one
to be willing to pay high sums vs. not willing. Three activities affect WTP: safari affects positively,
whereas swimming and horse riding affect negatively. This shows that visitors are willing to pay
high sums as entrance fee only for activities which are unique, while activities which are available at
alternative sites (i.e., swimming and horse riding) have a negative effect on WTP.
Table C.1. Logistic Model for Predicting WTP in Hula Projects
Variables Parameter estimate P >chi-square Odds ratio
Page
WTP = 20InterceptSwimmingHorsesDistanceN = 752-2LOG L
WTP = 30InterceptIncomeFamily sizeDistanceN = 752-2LOG L
WTP = 40InterceptSafariIncomeFamily sizeDistanceN = 752-2LOG L
WTP = 50InterceptIncomeFamily sizeN = 754-2LOG L
1.7488-0.7035-0.6153 0.0062
Intercept only 542.9Intercept and covariates 524.3
0.2102 0.1524-0.1212 0.0036
Intercept only 981.9Intercept and covariates 968.0
-1.6513 0.3982 0.2643-0.1539 0.0037
Intercept only 937.2Intercept and covariates 900.8
-2.4939 0.3765-0.1912
Intercept only 589.6Intercept and covariates 569.3
0.00010.01480.01350.0047
0.0003
0.51080.01250.02850.0106
0.010
0.00010.01400.00010.01520.0113
0.0001
0.00010.00010.0306
0.0001
5.7480.4950.5401.006
1.2341.1650.8801.004
0.1921.4891.3030.8581.004
0.0831.4570.826
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APPENDIX D
MATHEMATICAL APPENDIX
We calculate the present value of the revenues and the net benefits under the following assumptions
and symbols:
TR - present value of total revenues
TRt - total revenues in year t (entrance fee multiplied by number of visitors)
TB - present value of total benefits
TBt - total benefits in year t
NB - present value of net benefits
NBt - net benefits in year t
A - the percentage increase in visits due to change in population
B - the percentage increase in visits due to change in income
Due to our assumptions the following holds:
TRt = TRo [ (1 + A) (1 + B) ]t
TBt = TBo [ (1 + A) (1 + B) ]t
NBt = NBo [ (1 + A) (1 + B) ]t
Under these assumptions we calculate (assuming that r is the interest rate):
the present value of the expected revenues:
TR = TRt/(1+r)t
the present value of the expected (social) total benefits:
TB = TBt/(1+r)t
the present value of the expected (social) net benefits:
NB = NBt/(1+r)t
Page
UNIVERSITY OF HAIFA Natural Resources &Environmental Research Center
אוניברסיטת חיפה המרכז לחקר משאבי טבע וסביבה
TEL-HAI חי-מרכז להשכלה תלRODMAN REGIONAL COLLEGE רודמן. ומ. ש ג"ע
ט"נב)פיתוח משאבי נופש בטבע (:בפרויקט שטחי יבוש החולה
ניתוח כלכלי של תועלות צפויות
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חוקרים
ר מירה ברון"ד, והפקולטה להנדסת תעשייה וניהול, אוניברסיטת חיפה, המרכז לחקר משאבי טבע וסביבה
מכון טכנולוגי לישראל- טכניון ר נטליה זייצב"ד
גליל, חי-אוניברסיטת חיפה ושלוחת המחקר במכללת תל, המרכז לחקר משאבי טבע וסביבהעליון
פרופסור מרדכי שכטראוניברסיטת חיפה, והחוג לכלכלה, המרכז לחקר משאבי טבע וסביבה
עוזרי מחקר
( B.A)וצבי אשר ( M.A)שגיא נבו אוניברסיטת חיפה, המרכז לחקר משאבי טבע וסביבה
מוגש למנהלת פרויקט החולה(ל"מיג)מרכז ידע גליל עליון
1997ספטמבר
Page
הבעת תודה
:י מינהלת פרויקט החולה"המחקר מומן ע
,משרד התיירות, משרד הפנים, משרד החקלאות, נציבות המים, מינהל מקרקעי ישראל, קרן קיימת לישראל
.מבואות חמה, מרום הגליל, גליל עליון: מועצות איזוריות. החברה הממשלתית לתיירות
.מיכאל נודלמן שהשתתף איתנו בשלבים הראשונים של המחקר' תודתנו לפרופ
:הצוות מודה לאישים ולגופים הבאים אשר סייעו בביצוע העבודה
ר ועדת המחקרים"יו, מר עמוס הרפז
מתאם המחקרים בחולה , משה גופן' פרופ
מר גיורא שחם מנהל הפרויקט
רשות שמורות הטבע, דינה וינשטיין' גב
רשות שמורות הטבע , , אביבה לאונוב' גב
העמותה לקידום ופיתוח תיירות באצבע הגליל, מר משה עטייה
רשות הגנים הלאומיים, מר אמיתי רותם
מועצה אזורית גולן, מר אבי שרון
ולמועצה אזורית גולן שאפשרו לנו לערוך את הסקרים, לרשות הגנים הלאומיים, תודתנו לרשות שמורות הטבע
.ולמנהלי האתרים ולעובדים על העזרה הרבה, באתרי הגליל העליון
Page
תקציר
.מטרת המחקר היא הערכה כלכלית של כדאיות פרויקט החולה מבחינה ציבורית ומנקודת מבטם של היזמים
:המחקר עוסק בבעיות הבאות
,מהו הביקוש הפוטנציאלי לנופש בפארק החולה-
,מה הן פעילויות הנופש האטרקטיביות למבקרים הפוטנציאליים-
.מה היא התועלת הכלכלית הצפויה מפרויקט החולה מנקודת מבטם של היזמים ומבחינה חברתית-
הסקרים והשאלון. 1
נעשו מדגמי מבקרים בעונות שונות. ח מביא את תוצאות סקרים אשר בוצעו בפארקים שונים בגליל העליון"הדו
נחל, חורשת טל, שמורת החולה, דן-תל, האתרים אשר נכללו בסקרים הם בניאס. 1996עד אביב 1995במהלך קיץ
. עיון ופארק הירדן
על סמך מדגם ארצי או על סמך סקר, אך נמצא בתכנון, ניתן לבצע חיזוי של הביקוש לפארק שעדיין לא קיים
עקב התקציב המוגבל שעמד לרשותנו החלטנו לבצע סקר מבקרים של פארקים הקיימים בגליל. באתרים קיימים
-הכולל שבעה תת, הגודל האפקטיבי של המדגם הכללי. הסקרים נערכו בכל עונות השנה, כפי שנאמר לעיל. העליון
. תצפיות 800הוא , מדגמים
:להלן קבוצות השאלות אשר נכללו בשאלונים
,שאלות היפותטיות לגבי פרויקט החולה החדש-
',וכו, הפעילויות, ההוצאות, זמן השהייה, מספר הביקורים הקודמים: שימוש הנופשים בפארקים הקיימים-
,שאלות לגבי המרחק בין אזור המגורים לפארק-
,שאלות הקשורות לכושר נשיאה חברתי-
.חברתיים-מאפיינים דמוגרפיים וכלכליים-
הערכת מספר המבקרים באתרי נופש בגליל העליון. 2
נאמד( שנה בה בוצעו הסקרים באתרים אלה )1995מספר המבקרים הישראלים באתרי נופש בגליל העליון בשנת
. מבקרים 700,000- ב
:יש להדגיש כמה נקודות לגבי מספר זה
Page
ישנה נטייה אצל המבקרים לטייל יותר מפעם אחת. מספר זה הוא בעצם מספר הביקורים ולא מספר המבקרים( א
.באזור ולכן אותו מבקר נמנה יותר מפעם אחת
,אומדן זה יכול להיות גדול ממספר המבקרים האמיתי גם משום שקיים מעבר של מבקרים מאתר אחד לאחר( ב
.והמבקרים נמנים בכל פארק בו הם משלמים דמי כניסה
(אומנם גדול)מכיוון שהאומדן מייצג מבקרים רק בחלק , יתכן ואומדן זה קטן ממספר המבקרים הכולל באזור( ג
.ויש המבקרים באזור מבלי לבקר באתרים בתשלום, של האתרים באזור
.ישראלים-המספר אינו כולל את התיירים הלא( ד
התנהגות הנופשים באזור הגליל העליון. 3
אצל רוב הנשאלים ביקור. ניתוח התנהגות הנופשים באזור הראה כי קיים ביקוש רב לאתרי נופש בגליל העליון
מהנשאלים ביקרו בגליל 95%לפי תוצאות הסקרים . אלא תופעה חוזרת, בגליל העליון לא היה חוויה חד פעמית
החודשים 12מהנשאלים ביקרו באזור במהלך 72%. העליון במהלך חמש השנים האחרונות בנוסף לביקור הנוכחי
(.הגליל העליון)אך מספר הביקורים החוזרים משתנה לפי המרחק בין אזור המגורים לבין אזור הנופש , האחרונים
החודשים 12ואחוז המבקרים אשר בקרו באזור במהלך , עלויות הנסיעה גבוהות יותר, ככל שמרחק זה גדול יותר
מספר המבקרים אשר ביקרו במהלך חמש השנים האחרונות בלתי תלוי במרחק, לעומת זאת. האחרונים קטן יותר
הביקורים החוזרים. מבקרים את האתרים ביתר תדירות, הנסיעה המבקרים הגרים קרוב יותר לאזור הנופש
.מאפשרים לצפות כי פוטנציאל אתרי הנופש באזור הוא גבוה ביותר
אך, הליכה ברגל מאד אטרקטיבית בעונות הקרות: מצאנו שסוג פעילויות הנופש בו עוסקים המבקרים תלוי בעונה
מבקרים בוחרים את האתר לפי, כמו כן. עונתית-שחייה אטרקטיבית בעונות החמות רק פיקניק הנו חוויה על
.פעילויות הנופש האפשריות באתר
בחורף ובאביב רוב: אחוז המבקרים אשר מבלים בגליל העליון יותר מיום אחד תלוי בעונה. זמן השהייה
ואילו בקיץ ובסתיו רוב המבקרים באים לשהייה ממושכת יותר של כמה, באים רק ליום אחד( 70%- כ)המבקרים
מחצית. לאור תוצאות אלה ברור כי מספר הלינות באזור הינו גם כן תופעה עונתית(. בהתאמה 51%- ו 64%) ימים
שליש(. אוהלים ובונגלו, צימרים)המבקרים הנשארים ללון באזור מעדיפים להתאכסן במתקנים הפחות יקרים
.מכל המבקרים הלנים באזור נשארים בבתי מלון ובבתי הארחה
זמן השהייה ובמאפיינים, הוצאות לינה של משפחה המבקרת באזור תלויות בסוג מקום הלינה . הוצאות לינה
ההוצאה השנתית הממוצעת של משפחה ללינה לפי הסקר. בקיץ הוצאות הלינה הגבוהות ביותר. כלכליים-חברתיים
.ח"ש 633היא
(המידע המעודכן ביותר אותו ניתן היה לקבל ) 1993לפי המידע שסופק על ידי עמותת התיירות בגליל העליון משנת
בעובדה זו ובשינוים עונתיים של מספר הלינות יש. בלבד 26%תפוסת מקומות לינה בכל סוגי האכסון היא
.להתחשב בתכנון הקמת מתקני לינה חדשים באזור הגליל העליון
Page
הוצאה זו. ניתן לראות השפעות עונתיות על גודל ההוצאה המשפחתית במסעדות באזור . ביקורים במסעדות
.גם אחוז המבקרים במסעדות גבוה יותר בקיץ ובסתיו, גבוהה יותר בקיץ ובסתיו
במחקר נמדד כושר הנשיאה החברתי על ידי אומדן של המרחק המינימלי בין הקבוצה( כושר הנשיאה החברתי
התצפיות מראות כי הצפיפות מקובלת על המבקרים לפחות באתרים. המרואיינת לבין הקבוצה הקרובה אליה
-10מהמרואיינים המרחק היה פחות מ 61%ולגבי , מטר -5מהמרואיינים המרחק היה פחות מ 23%לגבי : שנסקרו
,ההפרעה הייתה קטנה 12%- ל, מהנשאלים נוכחות קרובה של מבקרים אחרים לא הוותה הפרעה 84%לגבי . מטר
.צפיפות הפריעה מאד 3%- ורק ל
התוצאות מראות כי התגובה. ניתחנו את הסיבות להפרעה הנגרמת על ידי צפיפות תוך שימוש בניתוח לוגיסטי
בפעילות. ככל שהכנסה גבוהה יותר גדל הסיכוי שצפיפות תפריע. לצפיפות תלויה ברמת ההכנסה ובפעילויות הנופש
. הפיקניק אנשים סובלניים הרבה יותר לצפיפות מאשר בפעילות ספורטיבית
לכן יש להקים באתר בחלקים שונים מקומות. מתוצאות המחקר עולה כי צפוי עומס עונתי בפארק החולה החדש
.המיועדים לפעילויות נופש שונות וזאת על מנת למנוע צפיפות יתר
.תועלת כלכלית של פרויקט החולה. 4
חיזוי הביקורים העתידיים בפרויקט החולה מבוסס על שאלות היפותטיות לגבי. ביקוש הנופשים לפארק החדש
. מהנשאלים הביעו רצון כזה 87%. הרצון לבקר
Contingent- השתמשנו בשיטת ה, על מנת לאמוד את הביקוש לפרויקט החולה בתנאי שהכניסה הנה בתשלום
Valuation Method .נשאלו המבקרים על גובה דמי הכניסה המרביים שהם מוכנים לשלם ,לפי שיטה זו(WTP.)
זהו גם ממוצע)ח ויותר "ש 30השיבו כי הם מוכנים לשלם דמי כניסה בגובה ( 63.5%)כשני שליש מהנשאלים
כאשר דמי הכניסה גבוהים. מבקרים בשנה 381,000במקרה זה מספר המבקרים הצפוי הוא (. הערכים שהתקבלו
כאשר דמי הכניסה(. מבקרים בהתאמה 78,000או 188,000)מספר המבקרים הולך וקטן ( ח"ש 50או 40)יותר
(.מבקרים בהתאמה 593,000או 587,000, 523,000)מספר המבקרים הולך וגדל ( ח"ש 3או 10, 20)נמוכים יותר
.יש להדגיש כי רק אחוז אחד מהנשאלים מסרבים לשלם סכום חיובי כלשהו כדמי כניסה לפארק
כל המרואיינים נשאלו לגבי שתי פעילויות המועדפות עליהם בפארק. פעילויות מועדפות בפרויקט החולה החדש
,ביקורים בספארי(. המראיין הקריא לנשאלים את רשימת הפעילויות המתוכננות בפארק החולה החדש)החדש
פעילויות הקיימות באתרי נופש אחרים. ושייט על אגם התקבלו כאטרקטיביים ביותר בפארק החדש" צאפארי"
אנו יכולים לסכם כי מבקרים מחפשים אטרקציות(. שחיה ודייג, כמו פיקניק)בגליל העליון לא הוזכרו כמועדפות
.ייחודיות שאינן קיימות באתרים אחרים
(.דמי כניסה ממשיים)עלינו להבחין בין התועלת הכוללת של הנופשים לבין פדיון היזמים . פדיון ותועלת כלכלית
ישנה חשיבות גדולה לתועלת הכוללת מנקודת. את התועלת הכוללת ניתן למדוד כרצון לשלם עבור פעילות הנופש
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בהנחה שדמי הכניסה הינם נתונים אנו. אך היזמים מעונינים אך ורק בפדיון התלוי בדמי כניסה, מבט חברתית
(דמי כניסה)פדיון היזמים שווה למכפלת המחיר . מעריכים את מספר המבקרים תוך שימוש בעקומת הביקוש
.ח לשנה"מיליון ש 11.4הפדיון הכולל הצפוי הוא , ח"ש 30כאשר דמי הכניסה הינם (. מספר המבקרים)בכמות
.ח לשנה"מיליון ש 14.1הצפויה היא ( פדיון היזמים ועודף הצרכן)התועלת החברתית הכוללת
הערך: ח הערך הנוכחי של פדיון היזמים משתנה"ש -30 באם דמי הכניסה הם בסך שנה 25 פדיון היזמים במשך
ובהנחה שהעלייה השנתית( לשנה 5%)המתקבל בהנחה שהריבית נמוכה , ח"מיליון ש 324הנוכחי המרבי הינו
(לשנה 10%)מתקבל בריבית גבוהה , ח"מיליון ש 123, הערך הנוכחי המינימלי. לשנה 6%- במספר המבקרים היא ב
פדיון היזמים גדל עם עליית מספר המבקרים ועם ירידה בשער, כלומר. לשנה 2%- ובעלייה במספר המבקרים ב
. הרבית
שנה משתנה בטווח 25 הערך הנוכחי של התועלת החברתית מקיומו של הפארק במשך התועלת הכוללת החברתית
.ח בהתאם לעלייה הצפויה במספר המבקרים ובהתאם לשער הרבית"מליון ש 400 - 152
. העלייה הצפויה במספר המבקרים תלויה בהנחות לגבי העלייה בביקורים לאורך זמןמספר המבקרים באתר
אלף 682 - 464מספר המבקרים הצפוי בעוד עשר שנים ינוע בתחום 2-6%- בהנחה של גידול שנתי בביקורים ב
.אלף מבקרים 1,635 - 625שנה ינוע בתחום 25ובעוד , מבקרים
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