Estimation of the local recreational value of the Hakgala Botanic Garden Sri Lanka

C T Jayaratne and UADP Gunawardene ,Unversity of Sri Jayewardenapura Nugegoda,Sri Lanka

Abstract

The Botanical garden at Hakgala

is one of the oldest ex-situ

conservation areas in Sri

Lanka. It is a unique

environmental asset, nationally

as well as globally. An economic

study was carried out in the

Hakgala Botanic Garden to

estimate its local recreational

value. The economic approach

used to estimate the

recreational value was the

travel cost method. The travel

cost approach is a way to value

unpriced goods. The surrounding

areas were divided into

concentric zones of increasing

distance, which represented

increasing levels of travel

cost. A survey of users was

conducted at the garden to

determine the zone of origin,

visitation rates, travel costs

and various socio economic

characteristics. The data

generated were used to regress

visitation rates, the total

travel cost and urban population

fraction of each zone. With

respect to the multiple trips

cost component to visit Hakgala

was differentiated based on

distances. Demand curve based on

visitation rates were

constructed using these data to

estimate the consumer surplus

from the site. Estimated minimum

total cost experienced by the

visitors

at the current entrance fee (Rs.

200) was Rs. 6,943,520. When

this amount is subtracted from

the total consumer surplus

(total welfare) of Rs.

228,493,714 the estimated

consumer surplus is Rs.

221,550,194. This figure can be

used to demonstrate the

contribution of a botanic garden

to the economy and to attract

more funds to develop

infrastructural facilities

inside the garden from the

government allocations.

Introduction

Sri Lanka is one of the

economically poorest and

ecologically richest countries

in the world. It has been

designated as a biological hot

spot of global importance due to

its high biological richness and

endemicity. Biodiversity must

certainly have considerable

economic value. An important

aspect of biodiversity that goes

unrecognized in national

accounting is its aesthetic

value. The methodologies for

valuing biodiversity are still

evolving, but studies have been

made elsewhere in the world on

how biodiversity value can be

incorporated in to the process

of decision-making on investment

projects. The establishment and

management of ex-situ

conservation is carried out in

limited ways in Sri Lanka. Three

botanical gardens at

Peradeniya,Hakgala and

Henerathgoda, house around 5500

plant species of which 1967 are

2

endemic to Sri Lanka.

(Rathnayaka and Kariyawasam,

2002). Other than ex-situ

conservation of biodiversity

these botanical gardens have

provided and continue to provide

recreation and eco touristic

services to Sri Lankan and

foreign visitors.

The Botanical garden at Hakgala

is one of the oldest ex-situ

conservation areas in Sri Lanka.

It is a unique environmental

asset, nationally as well as

globally, due to its

conservation, recreation,

historical, cultural and

educational and other existence

values.

The economic value of something

is measured by the summation of

many individual’s willingness to

pay (WTP). It reflects

individual’s preferences for the

good in question. So, economic

valuation in the environmental

context is about ‘measuring the

preferences’ of people for an

environmental good or against an

environmental bad. Valuation is

therefore preferences held by

people. The resulting valuations

are in money terms because of

the way in which preference

elevations sought i.e. by asking

what people are willing to pay.

Or by inferring their WTP

through other means. Moreover,

the use of money as the

measuring rod permits the

comparison that is required

between ‘environmental values’

3

and ‘development values’

(Pearce,1993).

Many people believe that there

are intrinsic values in

environmental assets. They are

of values of themselves and are

not of human beings, values that

exist not just because

individual human beings have

preferences for them. There is

no reason to reject the idea of

intrinsic values because the

idea of measuring preference is

adopted. What are being assessed

are two different things; the

value of preferences of people

for or against environmental

change (economic values) and the

value that intrinsically resides

‘in’ environmental assets

(intrinsic values).Economic

valuation is essentially about

discovering the demand curve for

environmental goods and services

the values which human beings

place on the environment. The

use of money as the measuring

rod is for

convenience. It happens to be

one of the limited number of

ways in which people use to

measure economic value or their

willingness to pay

(Hufschmidt,1990).

Once it is accepted that both

forms of value exist, the issue

becomes one which value should

inform and guide the process of

making public choices. The

answer is that since both values

are ‘legitimate,’ both are

relevant to decision making.

4

Making decisions on the basis of

economic value alone neither

describes real world decision

making, nor would it be

appropriate given that

governments and other agents

involved in the development

process have multiple goals. But

one difference between the

economic and intrinsic value

approach is that economic values

can, in practice, be measured

while intrinsic values cannot

(Hufschmidt,1990 and

Kulla,1995).

The practical problem with

economic valuation is one

deriving credible estimates of

that value in contexts where

there is either no apparent

market or very imperfect

markets. If it is possible to

derive such values, then it may

well be that some measures of

individuals preference will, in

any event, capture at least part

of what might be called

intrinsic value. This will be so

if the people expressing values

for the environmental change in

question themselves posses some

concept of the intrinsic value

of things. They may be partly

valuing ‘on behalf’ of the

environment as an entity itself

(Freeman, 1993).

Many of the environmental assets

that people generally feel are

very important are in the

developing word. Notable

examples include the tropical

rain forests, ecologically

5

precious wetlands, and many of

the world’s endangered species.

Many people believe that these

environmental assets have

intrinsic value. They may

express that view by speaking of

the immorality of activities

that degrade these resources,

and of the ‘rights’ to existence

of trees and animal species

(Pearce,1993).

Such discussions are important,

but at the practical level the

‘development and environment

debate is frequently about the

very high value placed on

development in a context of

malnourishment and

underemployment. The environment

will often be viewed as a luxury

to be afforded later, not now

while the struggle for

development is under way

Bringing discussions of rights

and intrinsic values into the

policy dialogue can be

counterproductive in such

context: honoring them is

perceived as forgoing the

benefits of development

(Sherman,1990).

If on the other hand,

conservation and the sustainable

use of resources can be shown to

be of economic value, then the

dialogue of developer and

conservationist may be viewed

differently, not as one

necessary opposites, but of

potential complements

6

(Hufschmidt,1990 and

Perman,1996).

Total Economic Value

Conceptually, total economic

value (TEV) of an environmental

resource consists of its use

value (UV) and non use value

(NUV). A use value is much as it

sounds usual value arising from

an actual use made of a given

resource. This might be the use

of a forest for timber, or of a

wetland for recreation or

fishing and so on. Use values

are further divided into direct

use values (DUV), which refer to

actual uses such as fishing,

timber extraction etc.

Indirect use values (IUV), which

refer to the benefits deriving

from ecosystem functions such as

a forest’s function in

protecting the watershed; and

option values (OV),which is a

value approximating an

individual’s willingness to pay

to safeguard an asset for the

option of using it at a future

date. This is like an insurance

value (Pearce and Moran),1994.

Non use vales (NUV) are slightly

more problematic in definition

and estimation, but are usually

divided between a bequest values

(BV) individual from the

knowledge that others might

benefit from a resource in

future. The latter are unrelated

to current use values, or

option values, deriving simply

from the existence of any

7

particular asset. An

individual’s concern to protect,

for example, the blue whale

although he or she has never

seen one and is never likely to,

could be an example of existence

value(Randal and Stoll, 1983

cited in Pearce and

Morgan,1994). Thus the total

economic value is,

TEV=UV+NUV=(DUV+IUV+OV)+(XV+BV)

Anthropocentric view of

biological resources offers a

convenient ‘window’ for economic

analysis over alternative value

paradigms such as ‘intrinsic

value’. Values in themselves

and, nominally anyway, unrelated

to human use. Intrinsic values

are relevant to conservation

decisions, but they are

generally not measurable. As

such they do not help to define

action in the context where

choices have to be made against

the backdrop of scare

conservation funds. Economic

value does not capture, nor is

it designated to capture

intrinsic value (Pearce,1994).

However, it is tempting to think

that economist have captured all

there is to know about economic

value in the concept of TEV. But

this is obviously not correct.

First they are not calming to

have captured all values, merely

economic values. Second, many

ecologists say that total

economic value is still not the

whole economic story. There

are some underlying functions of

8

ecological systems that are

prior to the ecological

functions (watershed protection

and so on) (Pearce,1994).Turner

(1992) calls them ‘primary

values’ (PV) ,. TEV may fail to

encapsulate the total secondary

value (TSV) provided by an

ecosystem. Because in practice

some of the functions and

processors are difficult to

analyze (scientifically) as well

as to value in monitory terms.

In addition (TEV) fails to

capture the (PV) of ecosystems,

indeed this or ‘glue’ value

notion is very difficult to

measure in direct value terms

since it is a non- preference,

but still instrumental, type of

value (Barbier, 1993).

It is believed that this primary

and secondary ecosystem value

classification goes some way

towards satisfying many

scientists’ concerns about the

‘partial’ nature of the

conventional economic valuation

approach (Ehrlich,1992 and

Barbier,1993).

More formally.

Each ecosystem provides a source

or stock of primary value i.e.

Total Primary Value (TPV) or

‘glue’ value of the ecosystem.

The existence of a ‘ healthy’

ecosystem (i.e. one that is

stable and/or resilient)

provides a range of services

that is known as Total Secondary

9

Value (TSV). Total Ecosystem

value s (TV).

TV = TPV+TSV;

TSV=TEV (Total Economic Value);

TEV= UV (use value) +NUV (non-

use value);

What is clear is that the

components of the TEV (use and

non use values) cannot simply be

aggregated. There are often

tradeoffs between different

types of use value and between

direct and indirect use values.

Smith (1992) has also pointed

out that the partitioning of use

and non use values may be

problematic, if it is the case

that use values may well depend

on the level of services

attributed to non-use values.

The TEV approach has to be used

with care and with a full

awareness of its limitations

(Barbier,1993).

Zonal travel cost model

In actual practice, the travel

cost approach is site specific

and measures the benefits from

one particular site and not from

recreation in general (Freeman,

1979). The recreation site

is identified, and the

surrounding area is divided into

concentric zones of increasing

distance, which represents

increasing levels of travel

cost. A survey of users is

conducted at the recreation site

to determine zone of origin,

visitation rates, travel costs,

10

and various socio economic

characteristics. The information

from this sample of visitors is

then analyzed, and the data

generated are used to regress

visitation rates on travel cost

and various socioeconomic

variables.

Q1=f(TC<X1…….Xn)

Where Q1 is the demand curve is

(number of visitors from zone i

per 1000 population in the zone

i), TC is travel cost, and X1………

Xn are number of socioeconomic

variables including income,

level of education, urban

population percentage and other

appropriate variables.

This regression will test the

hypothesis that travel costs do

in fact have an impact on

visitation rates. The inclusion

of other variables helps to

include the effects of non

travel cost related components

of total visitation rates.

The first step leads to the

creation of a so called “whole

experience” demand curve based

on visitation rates, not the

actual days spent at the site.

To estimate the consumer

surplus, or benefits, from the

site, this demand curve can be

used to estimate actual numbers

of visitors and how the numbers

would change with increases in

admission price-in-effect,

creating a classic demand curve.

The base information about total

visitation from all travel cost

11

zones define s one point on

the demand curve for the

recreation site under study

(Freeman, 1979). I.E. it defines

the point of intersection of the

present nominal or zero price

line with the true economic

demand curve. In figure 2.5 this

would be point A if the

admission charge were zero.

M

B

1.00

O

A

Demand curve for outdoor

recreation

(Source: Hufschmidt,1990

and pearce, 1993)

The remainder of the demand

curve is derived by assuming

that visitors would respond in

the same way to increases in

admission costs as to equal

increases in travel costs. For

each incremental increase in

admission cost, the expected

visitation rate from each origin

zone is calculated.

These values are assumed across

all travel origin zones to find

the predicted number of

visitors at the new admission

price. A $ 1 increase in

admission charges until the

entire demand curve, AM, is

traced. The area under the curve

is an estimate, therefore of the

12

total consumer’s surplus enjoyed

by present users of the

recreation site, assuming an

original access price of zero.

2.3.4 Assumptions in Travel Cost

Method

To use the travel cost approach,

a number of assumptions must be

made about individual behavior

and about the variables measured

(Sinden and Worrel, 1979). They

are as follows:

1. The consumer’s surplus of

the marginal user is zero

2. Travel cost is a reliable

proxy for price. This in

turn, rests on assumptions

that the disutility of

overcoming distance derives

monitory costs alone.

3. People in all distance

zones would consume the

same quantities of the

activity at given monitory

costs. That is the demand

curves for all distance

zones have the same

slopes .

The discussion of the

theoretical concept of the

travel cost approach is in

recreation analysis, but on

the valuation of an

unpriced good. A

recreational good is just a

one of a number of goods in

this category (Hufschmidt,

1990).

METHODOLOGY

13

Method of estimating

recreational value

Even though visitors who came to

the recreation site pay a

nominal entrance fee, value

placed by visitors on the

recreational site may be higher

or lower than the fee. An

approximate value can be

estimated considering the total

cost of the visitor for both

travel and opportunity cost of

time. This reflects the value of

scenic beauty of the site. This

approach is used in technique

called travel cost method

(Hotelling,1949 cited in

Claswon,1959). Main objective of

the study was to assess the

recreational value of the

Hakgala Botanic Garden. Zonal

travel cost was used to assess

the recreational value. As

Hufscmidt (1990) says travel

cost approach is the best method

to value unpriced goods like

recreation. The zonal travel

cost is applied by collecting

information on the number of

visits to the site from

distances. Because the travel

time and cost will improve with

distance, this information

allows the researcher to

calculate the number of visits

‘purchased’ at different

‘prices’. This information was

used to construct the demand

function for site, and estimate

the consumer surplus, or

economic benefits, for the

recreational services of site.

14

Process of data

collection

The data for the study were

collected from both primary and

secondary sources. Following

paragraphs give a detail

description about sources and

techniques of data collection.

Primary data collection

Survey technique was used to

find out consumer’s hypothetical

valuation of the site. A

Survey technique was undertaken

with the aid of a questionnaire,

amongst total adult visitors who

are employed. Only one person

was interviewed in a group.

Random sampling technique was

used. I.e. every other person

was interviewed who are going

out of the garden. 210

respondents were interviewed

from 8.00 a.m. to 5.00 p.m.

during 10th Thursday, 11th Friday

and 12 th Saturday in April and

18th Friday, 19th Saturday and 20th

Sunday in July 2003.The month of

April comes within the season

and July is off season. Survey

was conducted in Sinhala and

English medium.

Questionnaire is attached to

appendix 4. It included 20

questions. Question 1-4 included

socio economic characteristics

such as home town of the

visitor, occupation, monthly

income, age, education and

15

members in the group. It also

included questions on whether

respondent had visited this

place before, whether he/she had

a special interest to visit

Hakgala Botanic Garden. Those

two had no interest were

excluded (10 questionnaires).

Cheshire and Stabler (1976)

states meanderers, who derive

utility from journey, should be

excluded because including them

may overestimate he benefits.

Question 7 was whether the

visitor was a member of any

organization related to nature.

Question 9-14 included details

about travel costs such as total

distance traveled up to Hakgala,

mode of transport, cost per

kilometer/hire cost/travel

expenditure to find out round

trip travel cost, whether that

was the only place visited,

other places visited during the

trip, relevant distances to each

place from the starting point up

to the end of the trip, time

spent to reach the garden, time

spent at the garden, time to

reach the next place and other

positive expenditure due to the

trip. Question 15 was about the

interesting places inside the

garden and question 16 asked

whether the visit is worth for

money. Question 17 was about the

maximum amount a visitor was

willing to pay as the entrance

fee. Question 18 was about the

visitor’s attitude on the

existing facilities. Question 19

was on the visitor’s suggestions

to improve the qualities of the

16

garden. Question 20 asked the

maximum amount the visitor was

willing to pay after improving

the qualities of the garden.

Secondary data

collection

Secondary data was manly

obtained from the rerecords

maintained by the garden. It was

about the total number of

visitors annually, from 1997-

2002 and monthly visitors during

the year 1997- 2002.

Administration reports of the

Department of Agriculture from

1999-2002 was used to get

information about income

collected by the garden from

sale of plants, entrance fees

and other sources which is

credited to the treasury. It

also provided information about

the funds received by the garden

from various sources as

recurrent, capital, Farmer’s

Trust fund and Botanic Garden’s

Trust Fund.

Statistical abstracts of the

Department of Census and

Statistics was used to obtain

data such as total population in

each district, total urban

population in Sri Lanka and in

Colombo, Gampaha, Kandy,

Kurunegala, Kaluthara,Galle,

Badulla and Nuwara Eliya

districts for year 2002.

Zoning

17

In the usual practice of travel

cost study, the surrounding area

is divided in to concentric

zones of increasing distance,

which represents increasing

level of travel cost

(Freeman,1979). However these

zones may be concentric zones

radiating from site, or they

might be ‘local government

administrative districts’. Zonal

models may include travel costs

and socio economic variables

averaged for zones (Lansdell and

Gangadharan,2001).

Zoning was done by allocating

the visitors under the

respective districts where the

visit was originated. Travel

distances were obtained from a

road map published by the Survey

Department. Since the travel

distances to places visited or

to be visited and total travel

cost incurred was obtained in

the questionnaire, total travel

cost was apportioned according

to the distance in the case of

hired and own vehicles and

direct ravel expenses to places

were taken on the case of public

transport. Thereby travel cost

component relevant to visit

Hakgala Botanic Garden was

separately calculated. Data

entering and the above

calculations were done using a

excel spread sheet.

Obtaining visitor rates

for each zone

18

According to Hanley and Spash

(1993) Population levels of

zones must be included in zonal

models. Visitation rate is the

number of visitors from a

particular zone per 10000

population in that zone

(Hufschnidt,1990).

Using the information on the

number of sampled visitors from

each zone, total number of

visitors to the garden for a

year was calculated since the

garden does not keep records of

the origin of the visitors.

Number of sampled visitors in

the each zone, total number of

visitors to the garden for a

year was calculated since the

garden does not keep records of

the origin of the visitors.

Number of sampled visitors in

the each zone, sample size,

annual number of visitors in

each zone and population in the

each zone was used to calculate

the visitation rate per 1000

population in each zone using

equation 1.

Visits/1000/year=(vi/n)N*1000

…………(1)

P i

Vi = visits from ith zone

n = Sample size

N = Total number of visitors per

year

Pi = Population in the ith zone

Obtaining total travel

cost

19

Smith, Desvousges and Mc Givney

(1983) found that relevant price

of a visit to a site was the sum

of money travel cost and a

proportion of the total time per

visit (round trip travel time

and time spent on site). This

proportionately factor depend

upon the wage rate attached to

the money and time. In other

words, the total travel cost was

considered to comprise cost of

traveling and the opportunity

cost of time of traveling.

Total travel cost = Travel cost +Opportunity

cost of time ……………………(2)

Cost of traveling was considered

as direct expenses incurred by

visitors in getting to and from

the site for fuel and fairs.

This was obtained by deriving an

average travel cost figure for

each zone per person. Entrance

fee was included in the average

travel cost per zone.

Opportunity cost of traveling

was considered as value of time

spent on the round trip and

value of time spent at the

garden.

Opportunity round time

Cost = Trip + spent*value of time

Of travel at

Time time garden

…………….(3)

.

20

Round trip travel time and

time spent at the garden was

obtained by calculating the

average figure for each zone per

person.

Cesario (1976) says one third of

the wage rate should be attached

to money and time. Therefore,

one third of the wage was taken

as the rate to calculate the

value of time. The value of time

was calculated using following

formulae.

Value of time Rs/hour

= (MI /20) *1/3

8

MI = Average

monthly income

per person for

each zone

20= Average

number of

working days

per month

08 = Average

number of

working hours

per day

Estimation of urban

population fraction

Since the education level

influence the visitation rate

(Abeygunawardhana and

Kodituwakku,1993) the regional

education index has been

calculated by Marasinghe (2001).

Since the urban population

21

places higher values for natural

resources (Ekanayake and

Abegunawaredena, 1994) the

percentage urban population also

has been calculated by

Marasinghe (2001) which reflects

the regional income also

(Gunathilaka and Vieth, 1998).

It has been noted by Marasinghe

(2001) that percentage urban

population shows higher

correlation with visitation rate

than the regional education

index. So the regional education

index has been dropped from his

model. Therefore in this study

urban population fraction was

used instead of urban population

percentage for accuracy in

subsequent transformations.

Based on data published by the

Department of Census and

Statistics, urban population for

each district was obtained and

total urban population in Sri

Lanka was calculated for 2002.

Based on that, considering urban

population in districts of

Colombo, Kurunegala, Kandy,

Badulla, Nuwara Eliya, Gampaha,

Galle, and Kalutara urban

population fractions for each

above stated districts were

calculated.

Regression Analysis

According to Hufschmidt (1990)

are used to regress visitation

rates on travel cost and the

22

various socio economic

variables.

Qi = f(TC < X1,………………….Xn)

Where Qi is the visitation rate

(number of visitors from zone i

per 1000 population in zone i),

TC is travel cost, and X1…………….Xn

are a number of socioeconomic

variables including income,

level of education, urban

population fraction and other

appropriate variables.

This regression will test the

hypothesis that travel costs do

in fact have an impact on

visitation rates. The inclusion

of other variables helps to

include the effects of non

travel cost related components

of total visitation rates.

Computer simulated statistical

system MINITAB 12 for windows

was used in this study to

estimate multiple linear

regression functions. Multiple

linear regression model is

represented by the following

equation;

Y = β0+β1x1+β2X2+…………………….+βKXK +€

………………………………(5)

Where y is the dependent

variable, X1,X2……..XK are

independent variables. βo,β1,

………..βk are the co efficients,

and € is the error variable.

In the regression analysis

carried out in this study,

Visitation Rate (VR) for each

zone (visits/1000/year) was

considered as the dependent

variable. Sum of the value of

23

travel time and cost (TTC) for

each zone, average annual house

hold income from each zone (I)

according to the sample and

urban population fraction (UF)

in each zone was considered as

independent variables.

According to the questionnaire

survey, there were respondents

from 18 districts. They were

Colombo, Kurunegala, Gampaha,

Kandy, Kalutara, Badulla, Nuwara

Eliya, Galle,

Hambanthota, Kegalle, Matale,

Ampara, Puttlam, Polonnaruwa,

Jaffna, Rathnapura. Anuradhapura

and Monaragala. However

respondents from only 8 zones

(Colombo,

Kurunegala,Gampaha,Kandy,

Kalutara, Badulla, Nuwara Eliya

and Galle) had come from all the

three modes (own, public and

hired). It was assumed in this

study that modes own, public and

hired represented high, low and

middle income categories.

Therefore it was justifiable to

derive an average travel cost

figure for each zone by

averaging travel cost figures

represented by all three modes

together instead of using a

weighted average.

Due to the above stated reason

only 8 zones represented all

three modes were used to obtain

the regression function.

Necessary transformations such

as log, square, square root was

done to dependent as well as

independent variables in order

24

to obtain a higher co- efficient

of determination (R2). There is

a quantitative test to evaluate

the models. Best model was

selected by considering the R2

value and residual distribution.

Construction of the

demand curve

As Hufsmidt (1990) states, so

called “whole experience” demand

curve should be derived based on

visitation rates, to estimate

the consumer surplus, or

benefits, from the site. This

demand curve can be used to

estimate actual numbers of

visitors and how the numbers

would change with increases in

admission price.

The base information about total

visitation from all travel cost

zones defines one point on the

demand curve for the recreation

site under study (Freeman,

1979). I.e. it defines the point

of intersection of the present

nominal or zero price line with

the true economic demand curve.

If the visitation rates of the

garden users can be shown as a

function of ‘price’ paid for

which the travel cost is proxy,

the relationship can be taken a

‘demand curve’ for recreational

value at Hakgala Botanic

Gardens.

Zonal visitation rate per

thousand populations with

respect to travel costs and

urban population fraction was

25

used to estimate the regression

equation to derive the demand

curve. Zonal visitation rate per

thousand populations was

calculated for 0,20,200 and

increasing entrance fee in

rupees of interval of 200.

Actual numbers of visitors were

calculated by multiplying the

visitation rate by zonal

population in thousands for each

entrance fee. Entrance fee was

increased in the calculations

until zero number of visitors

was obtained. Total number of

visitors for each entrance fee

was calculated and this value

was plotted against respective

entrance fee to derive the

demand curve. Area under the

demand curve was calculated to

obtain the value of recreation

per year or ‘consumer surplus’

of the garden at zero entrance

fee. The area under this curve

was calculated assuming that the

demand curve is linear between

any two points. In absence of an

entrance fee, the area under

that demand curve is considered

as the consumer’s surplus and

that is equal to the

recreational value. In the real

scenario there is an entrance

fee of Rs. 20 and hence area

under the demand curve is not

equal to the recreational value

or consumer’s surplus. According

to the figure 3.1 consumer

surplus is the area under the

demand curve above the price

line. To obtain the actual

consumer surplus, calculated

value assuming zero entrance fee

26

was deducted from the nominal

value of the garden per year at

the entrance fee of Rs. 20

Nominal value was obtained by

multiplying the total number of

visitors at Rs. 20. by Rs. 20.

Final figure arrived was the

recreational value of the garden

per year.

Demand curve for recreational site

Source: (Hufschmidt, 1990)

RESULTS

Initially the visitor

perception on the benefits of

the Hakgala Botanic Garden,

weakness of Hakgala Botanic

Garden are provided in tabular

and graphical analysis. Secondly

the recreational value of

Hakgala Botanic are provided in

tabular and graphical analysis.

Secondly the recreational value

of Hakgala Botanic Garden is

estimated using the travel cost

method.

Visitor perception

27

Price

Number of visitorsEntrance Fee

Consumer surplus

Visitor perception was gathered

from the Questions 15-

20.Questionnarie is attached to

Appendix 3. This section

provides data obtained from the

questionnaire which was analyzed

qualitatively. Question number

15 was whether the visit to

Hakgala Botanic garden is worth

for money they spent as the

entrance fee. Among the total

sample of 200, many visitors

(87%,174) said current entrance

fee is worth. However, (13%, 26)

said that what they pay as

entrance fee is not worth since

they did not get much

satisfaction.

Attitude on entrance fee

26, 13%

174, 87%

worthnot worth

Figure 4.1 : Attitude on

entrance fee

Question number 15.1 asked

whether the respondent thought

visit is worthy more than what

he/she had paid, what was the

new entrance fee that he/she was

willing to pay. From the sample

of 200, 75 respondents agreed to

pay more. While 13 agreed to pay

25 rupees, 15 were willing to

pay 30 rupees, 3 agreed to pay

35 rupees, 30 respondents agreed

to pay 50 rupees and only 3 were

willing to pay 100 rupees.

28

W illingness to pay

13 15

3

11

30

305101520253035

25 30 35 40 50 100m axim um am ount w illing to pay

numbe

r of res

pond

ents

Figure 4.2 : Willingness to pay

Question 16 asked whether the

respondent was satisfied with

the existing facilities for

visitors. 59% of the visitors

(119) were satisfied with the

existing facilities provided by

the garden whereas 41% (81) were

not satisfied with the existing

facilities.

Level of satisfaction on facilities am ong visitors

81, 41%

119, 59%

not satisfiedsatisfied

Figure 4.3: Level of

satisfaction on facilities among

visitors

Question 18.1 asked if some

improvement is done, whether

they were willing to pay a

higher amount. Majority of

visitors agreed to pay higher

amount than existing entrance

fee if the facilities are

improved. 145 of visitors (72%)

agreed to pay a higher amount,

while 55 (28%) disagreed.

29

Num ber of Respondents willing to pay more after im proved facilities

145, 72%

55, 28%agreeddisagreed

Figure 4.4. : Number of respondents willing to pay more after improved facilities.

Question 19 asked what was the

increased entrance fee they

would like to pay after

improvements to facilities made.

This was an open ended question.

Table 4.1 represents number of

respondents and respective

amounts they were willing to

pay.

Table 4.1 Willingness to pay after improved facilities

Willingness Number of

to pay Respondents

25 19

30 30

35 3

40 14

45 1

50 50

60 4

70 3

75 2

100 13

150 2

200 4

Following graph shows

willingness to pay as new

entrance fee after facilities at

the garden are improved vs.

respective number of respondents

under each entrance fee.

30

W illingness to pay after im proved facilities

1930

314

1

50

4 3 213

2 40102030405060

Num ber of Respondents

Figure 4.5: Willingness to pay

after improved facilities

Question 14 asked what were the

interesting things they have

seen in the garden. Most

favorite site of the respondents

was rose garden. Other than that

glass house, other flower beds,

large trees, fernery, landscape

and dalia garden were the other

preferred sites by the

respondents.

Preffered sites at the garden

020406080

Site

Number of respondents

Figure 4.6: Preferred sites at

the garden

Question number 7 asked whether

respondent was a member of any

organization or society related

to nature. Majority of

respondents, 155 (77%) were not

members in any organization

related to nature. 45 out of

2000 (23%) were members in

organizations related to nature.

31

W hether respondents had m em bership in an organisation related to nature

yes, 45, 23%

no, 155, 77%

yesno

Figure 4.7: Whether respondent

had membership in an

organization related to nature

166 questionnaires were filled

in sinhala medium and 34

questionnaires were filled in

English medium.

Medium of Response

Sinhala, 166, 83%

English, 34, 17%

SinhalaEnglish

Figure 4.8 : Medium of response

Visit Data

Based on the analysis of

secondary data during past 6

years (1997-2002) it was found

that visits peaked during April

and August. Following graph

represents average annual visits

by local adults during the 12

months of the year according to

the visitor figures during past

6 years.

Average num ber of local adult visitors during (1997-2002)

010002000300040005000

M onth

Number of visitors

32

Figure 4.9 : Average number of

monthly local adult visitor

during (1997-2002)

Following graph represents the

total local adult visits during

1997 to 2002. During the year

1997, 303,065 local adult

visitors had visit Hakgala.

During 1998 it was 327,104, and

in 1999 it was 314,817. During

the year 2000, 326,560 local

adult visitors had visited,

whereas in 2001, it declined to

297,562 and in year 2002 it was

only 297,442 local adults

visited Hakgala.

Total local adult visitors during 1997-2002

280000290000300000310000320000330000340000

1997 1998 1999 2000 2001 2002

Figure 4.10: Total local adult visits during (1997-2002)

Many respondents (133) had visited Hakgala before whereas 67 respondents had not.

Previousely visited or not

not visited, 67, 34%

visited, 133, 66%

not visitedvisited

Figure 4.11 : Previously visitedor not

Among 200 respondents, 83 (42%)

had sole purpose to visit

Hakgala garden, while 117 (58%)

had intention to visit other

places as well.

33

Types of visit

Single purpose trips,

83, 42%m ulti prpose trips, 117,

58%

Single purpose tripsm ulti prpose trips

Figure 4.12 : Type of visit

Respondents were categorized

into three modes of transport.

They are own, hired, and public

vehicles. Amongst the 200

respondents 58 (29%) had come by

own vehicles, 86 (43%) by hired

vehicles and 56 (28%) by public

transport.

Mode of transport

Public, 56, 28%

hired, 86, 43%

own, 58, 29%

Publichiredown

Figure 4.13 : Mode of transport

Socio economic data

Sample of 200 respondents

represented 18 districts.

Following graph shows the origin

of the visit. 65 respondents

came from Colombo, 12 from

kurunegala, 4 from Hambanthota,

15 from Kandy, 17 from Badulla,

18 from Nuwara Eliya, 32 from

Gampaha, 2 from Kegalle, 8 from

Galle, 9 from Kalutara, 1 from

Matale, 1 from Ampara, 2 from

Puttalam, 3 from Pollonnaruwa, 2

from Jaffna, 4 from Rathnapura,

34

3 from Anuradhapura and 2 from

Monaragala.

Zone of Origine

010203040506070

Zone of Origine

Figure 4.14: Zone of origin

Question number 2 asked what the

respondent’s monthly income was.

Using those figures average

monthly income per person was

calculated for each zone as

presented in Table 4.2. and

figure 4.15.

Table 4.2. Average monthly

income per person in each zone

Zone oforigin

Income/person/month (Rs.)

Colombo 12990

Kurunegala 6777

Hambanthota

5193

Kandy 7005

Badulla 4646

NuwaraEliya

6082

Gampaha 10670

Kegalle 6150

Galle 7005

Kalutara 8328

Matale 5632

Ampara 6418

Puttlam 7433

Polonnaruwa

6857

Jaffna 6418

Rathnapura 5649

Anuradhapura

7763

Monaragala 4839

35

Incom e/person/month (Rs.)

02000400060008000100001200014000

Colom

boKurunegala

Hambanthot

Kandy

Badulla

Nuwara Eliya

Gampaha

Kegalle

Galle

Kalutara

Matale

Ampara

Puttlam

Polonnaruwa Jaffna

Rathnapura

Anuradhapur

Monaragala

zone/district

average monthly

income

Figure 4.15 : Average monthly

income per person in each zone

Among 200 respondents 8 (4%)

were upper executives, while 34

(17%) were middle managers, 93

(46.5%) of them were

teachers/clerks and related

employees, 20 (10%) were minor

employee/laborer/office

attendants, 13 (6.5%) were

engaged in self employment in

major scale and 32 (16%) were

engaged in self employment in

minor scale.

Em ploym ent status of visitors

051015202530354045

uppe

rex

ecuti

ve

midd

lema

nage

rs

teac

her/c

lerk/

relat

ed

drive

r/offic

eatten

dant/

mino

rem

ploy

ee

self

employ

ment

(majo

r sca

le)

self

employ

ment

(mino

r sca

le)

nature of em ploym ent

visito

rs %

Figure 4.16 : Employment status of the visitors

Many visitors were less than 30

years (90,45%). Whereas 65

(32.5%) visitors were 31-40

years old. 24 (12%) belonged to

the age class 41-50, while 15

(7.5%) belonged to age class 51-

60 and only 6 (3%) were more

than 60 years old.

With respect to education status

of the visitors 2 (1%)

respondents had only passed

grade 8, while 38 (19%) had

passed only O/L, 104 (52%) had

passed A/L and 31 (15.5 %) were

graduates whereas 10 (5%) were

post graduates and 15 (7.5%)

were professionally qualified.

36

Educational status of visitors

0102030405060

Passedgrade 8

passed O/L Passed A/L Graduate postgraduate

pofessional

educational status

visits %

Figure 4.17: Education status ofthe visitors

Many visitors were less than 30

years (90,45 %). Whereas 65

(32.5%) visitors were 31-40

years old. 24 (12%) belonged to

the age class 41-50, while 15

(7.5%) belonged to age class 51-

60 and only 6 (3%) were more

than 60 years old.

Age distribution of visitors

01020304050

18-30 31-40 41-50 51-60 60<age class (years)

visitors %

Figure 4.18: Age distribution of

visitors

Estimation of visitation

rates

Visitation rates are annual

visits per 1000 population of

each zone were calculated using

the formula number 1 in section

3.4. Table 4.3 represents the

visitation rates of each zone.

37

Table 4.3: Visitation rates of

each zone

Zone/district

Wage rate

Travel cost (Rs)

Colombo 27.06 502

Kurunegala 14.12 238

Hambanthota 10.82 30

Kandy 14.59 206

Badulla 9.68 131

Nuwara Eliya 12.67 50

Gampaha 22.23 338

Kegalle 12.81 147

Galle 14.59 776

Kalutara 17.35 719

Matale 11.73 146

Ampara 13.37 91

Puttlam 15.49 285

Polonnaruwa 14.29 148

Jaffna 13.37 1275

Rathnapura 11.77 125

Anuradhapura 16.17 422

Monaragala 10.08 78

Estimation of wage rates

and travel costs

Based on the data obtained from

the sample survey, the average

zonal per individual wage rate

per hour was calculated for each

zone by using formula number 4.

Using the information collected

in the sample survey average

travel cost per zone was

calculated which is relevant to

return trip to Hakgala garden,

Following table represents wage

38

rates and respective travel

costs of each zone.

Table 4.4: Wage rate and Travel

cost per each zone

Zone/district

Wage rate

Travel cost(Rs)

Colombo 27.06 502

Kurunegala 14.12 238

Hambanthota 10.82 30

Kandy 14.59 206

Badulla 9.68 131

Nuwara Eliya 12.67 50

Gampaha 22.23 338

Kegalle 12.81 147

Galle 14.59 776

Kalutara 17.35 719

Matale 11.73 146

Ampara 13.37 91

Puttlam 15.49 285

Polonnaruwa 14.29 148

Jaffna 13.37 1275

Rathnapura 11.77 125

Anuradhapura 16.17 422

Monaragala 10.08 78

Estimation of total

travel costs

According to formula 2 in

section 3.5 total travel cost is

the sum of travel cost and

opportunity cost of time per

39

person. According to formula 3

and 4 it is the sum of time

spent at the garden and round

trip travel time valued at third

of average monthly income per

person for each zone. According

to the questionnaire survey,

there were respondents from 18

districts (figure 4.14). They

were Colombo, Kurunegala,

Gampaha, Kandy, Badulla,

Kandy.Kaluthara, Badulla, Nuwara

Eliya,Galle, Hambanthota,

Kegalle, Matale,Ampara,Puttlam,

Polonnaruwa, Jaffna, Rathnapura,

Anuradhapura and Monaragala.

However, respondents from only 8

zones (Colombo,

Kurunegala,Gampaha,Kandy,Kalutar

a,Badulla,Nuwara Eliya and

Galle) had come from all three

modes( own, public and hired).

It was assumed in this study

that three modes (own,public and

hired) represented high, low and

middle income categories of the

society. Therefore it was

justifiable to derive an average

travel cost figure for each zone

by averaging travel cost figures

represented by all three modes

together instead of using a

weighted average. Therefore in

further analysis only these

zones will be dealt with. As a

result in calculation of total

travel cost only those 8 zones

were considered.

Table 4.5 represented calculated

total travel cost to the Hakgala

Botanic Garden from selected 8

zones.

40

41

Table 4.5: Total travel costs to Hakgala botanic garden from different zones

ZoneTravel cost

Time at Garden Round trip wage

opportunity Total

      travel time rate Cost travel

            cost

Colombo 502.34 1.64 6.75 27.06 227.08 729.42

Kurunegala 238.41 1.67 4.57 14.12 88.08 326.48

Kandy 205.81 1.6 3.11 14.59 68.7 274.51

Badulla 131.07 2.06 1.64 9.68 35.83 166.9

Nuwarael;iya 50.02 1.92 0.18 12.67 26.55 76.56

Gampaha 337.78 1.63 5.71 22.23 163.15 500.93

Galle 775.59 2.31 10.64 13.97 180.98 956.57

Kaluthara 718.62 1.75 7.14 17.35 154.29 872.9

Regression equations estimated

using all the above stated

variables. In all those

equations income appeared to be

insignificant at 95% probability

level. I.e. P value was higher

than 0.05. Therefore income was

not considered in the subsequent

estimations. Equations obtained

without any transformations had

low co-eficient of determination

(R2). Therefore transformation

(log, square, square root) were

done in order to obtain a

higher (R2). Following equation

was selected as the best model

since it has the highest

adjusted (R2) and a scattered

residual distribution with no

pattern.

LogVR=2.49-.0516

LOGttc+1.20UF………………………………(6)

R-Sq = 86.4% R-Sq (adj) =

81.0%

In the estimated equation total

travel cost is negatively

correlated with visitation rate

and urban population fraction is

negatively co- related with

visitation rate. All the

variables in the equation are

significant at 95% probability

level. I.e. P value <0.05.

Construction of the demand

curve

According to equation (5),

dependent variable is the log

visitation rate (Log VR). In

order to do subsequent

calculations visitation rate

(VR) had to be calculated using

Log VR. However, theoretically

there is no point where Log VR

and VR becomes zero

simultaneously. Therefore, this

equation had to be neglected.

This illustrated in figure 4.20

Figure 4.20 : Relationship of

log VR vs. VR

following model represented the

highest R2 and it was selected to

construct the demand curve. It

has a residual distribution

which is scattered and with no

pattern.

VR= 28.9-1.35sqr ttc +69.1 SQR

UF……………………….(7)

R-Sq=81.1% R-Sq (adj) =

73.6%

VR

Log VR

In the estimated regression

equation (6), square root of

total travel cost is negatively

correlated with Visitation Rate

(VR) and has a positive

relationship to square root of

urban population fraction (UF).

All variables in the equations

are significant at 95%

probability level. I.e. P value

< 0.05.

The average total cost per

person per visit, urban

population fraction for each

zone from Table 4.4 were

substituted in equation (7) To

obtain visits per 1000

population per year for each

zone (VR) at increasing entrance

fee. Population in thousands for

each zone was obtained from the

statistical abstracts published

by the Department of Census and

Statistics. It was used to

calculate the number of visitors

per year for each zone at

various levels of entrance fee

are provided in Table 4.7. Table

4.8 shows total number of

visitors under increasing

entrance fee.

Table 4.7 Visitors per year at various levels of increasing entrance fee.

District UF Population/ TTCTotal number of visitors (Q) under increasing entrance fee(Rs.)  

    1000   0 20 200 400 600 800 1000

Colombo 0.5469 2234.18 729 709 729 929 1129 1329 1529 1729

        (178737) (165249) (97301) (86805) (77392) (68784) (60800)

Kurunegala 0.0239 1451.936 326 306 326 526 726 926 1126 1326

        (22882) (21779) (12215) (4356) (44556) (4756) (4956)

Kandy 0.1233 1272.888 275 255 275 475 675 875 1075 1275

        (40227) (39172) (30216) (23023) (16837) (11327) (6309)

Badulla 0.0684 774.598 167 147 167 367 567 767 967 1167

        (23706) (22871) (16351) (11484) (7424) (3866) (661)

Nuwara Eliya 0.0615 699.46 77 57 77 277 477 677 877 1077

        (25071) (23914) (16485) (11577) (7631) (4237) (1212)

Gampaha 0.1459 2066.481 501 481 501 701 901 1101 1301 1501

        (53080) (51821) (40401) (30525) (21696) (13639) (6182)

Galle 0.1116 991.221 957 937 957 1157 1357 1557 1757 1957

        (10566) (10131) (6011) (2233) 0 0 0

Kalutara 0.1063 1060.648 873 853 873 1073 1273 1383 1529 1729

        (12726) (12238) (7642) (3458) (1296) 0 0

Figures in brackets indicate respective number of visitors under each total travel cost with increasing entrance fee.

contd……….Table 4.7 Visitors per year at various levels of increasingentrance fee.

       

DistrictTotal number of visitors (Q) under increasing entrance fee (Rs.)  

  1200 1400 1600 1800 2000 2200 2400 2600 2800 3000  

Colombo 1929 2129 2329 2529 2729 2929 3129 3329 3529 3729

 (5332

3) (46268)(3956

9)(3317

8)(2705

9)(2117

4)(1550

4)(1002

3)(471

5) 0

Kurunegala 1526 1726 1926 2126 2326 2526 2726 2926 3126 3326

  0 0 0 0 0 0 0 0 0 0

Kandy 1475 1675 1875 2075 2275 2475 2675 2875 3075 3275

 (1672

) 0 0 0 0 0 0 0 0 0

Badulla 1367 1567 1767 1967 2167 2367 2567 2767 2967 3167

  0 0 0 0 0 0 0 0 0 0

Nuwara Eliya 1277 1477 1677 1877 2077 2277 2477 2677 2877 3077

  0 0 0 0 0 0 0 0 0 0

Gampaha 1701 1901 2101 2301 2501 2701 2901 3101 3301 3501

  0 0 0 0 0 0 0 0 0 0

Galle 2157 2357 2557 2757 2957 3157 3357 3557 3757 3957

  0 0 0 0 0 0 0 0 0 0

Kalutara 1929 2129 2329 2529 2729 2929 3129 3329 3529 3729

  0 0 0 0 0 0 0 0 0 0

Figures in brackets indicate respective number of visitors under each total travel cost with increasing entrance fee.

Table 4.8: Total number of visitors under increasing entrance fee

DistrictTotal number of visitors under increasing entrance fee      

  0 20 200 400 600 800 1000 1200 1400

Colombo 178737 165249 97301 86805 77392 68784 60800 53323 46268

Kurunegala 22882 21779 12215 4356 0 0 0 0 0

Kandy 40227 39172 30216 23023 16837 11327 6309 1672 0

Badulla 23706 22871 16351 11484 7424 3866 661 0 0

Nuwara Eliya 25071 23914 16485 11577 7631 4237 1212 0 0

Gampaha 53080 51821 40401 30525 21696 13639 6182 0 0

Galle 10566 10131 6011 2233 0 0 0 0 0

Kalutara 12726 12238 7642 3458 1296 0 0 0 0

Total 366996 347176 226623 173461 132276 101853 75164 54995 46268

Contd……..Table 4.8: Total number of visitors under increasing entrance fee

DistrictTotal number of visitors under increasing entrance fee      

  1600 1800 2000 2200 2400 2600 2800 3000

Colombo 39569 33178 27059 21174 15504 10023 4715 0

Kurunegala 0 0 0 0 0 0 0 0

Kandy 0 0 0 0 0 0 0 0

Badulla 0 0 0 0 0 0 0 0

Nuwara Eliya 0 0 0 0 0 0 0 0

Gampaha 0 0 0 0 0 0 0 0

Galle 0 0 0 0 0 0 0 0

Kalutara 0 0 0 0 0 0 0 0

Total 39569 33178 27059 21174 15504 10023 4715 0

Information from Table 4.8 was

used to estimate a demand curve

for recreational benefits

provided by Hakgala botanic

garden. It was obtained by

plotting varying entrance fee

vs. total visitors per year from

each zone.

0200400600800100012001400160018002000

- 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000

Total visitorrs/year

Increasing entrance fee (Rs.)

Figure 4.22: User demand curve for recreational benefits provided by Hakgala botanic garden.

The area under the demand curve

is the recreational value of the

Hakgala Botanic Garden based on

travel cost approach. The area

under the demand curve gives

total consumer surplus/total

welfare enjoyed by the users of

the garden assuming original

access price of zero. The area

under the demand curve was

calculated using simple

approximation

illustrated in figure 4.23 and

Table 4.9. This approximation

assumes that demand curve is

linear between any two points.

0200400600800100012001400160018002000

- 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000

Total visitorrs/year

Increasing entrance fee (Rs.)

Figure 4.23 : Graphical

explanation of area under the

demand curve

Table 4.9: Calculation of total consumer surplus

Section

Entry Total

Delta Q

Delta P

Delta Pfor

Area triangle Area Total

Section

Entry Total

DeltaQ

Delta P

Delta Pfor

Area triangle Area Total

  Feevisits  

for Trangle

rectangle  

rectangle area

0 036699

6 0 0 0 0 0 0

1 2034717

6 19820 20 0 198199 0 198199

2 20022662

312055

2 180 200 10849722241104

9 13260771

3 40017346

1 53162 200 200 5316249106324

98 15948747

4 60013227

6 41185 200 400 4118462164738

46 20592308

5 80010185

3 30424 200 600 3042361182541

65 21296526

61000 75164 26689 200 800 2668898

21351181 24020078

71200 54995 20169 200 1000 2016884

20168836 22185720

81400 46268 8726 200 1200 872646

10471754 11344400

91600 39569 6699 200 1400 669885

9378395 10048280

180 102259

  Feevisits  

for Trangle

rectangle  

rectangle area

0 036699

6 0 0 0 0 0 0

Estimated minimum total cost

experienced by the visitors at

the current entrance fee (Rs.

20.00) was Rs. 6,943,520.00.

When this amount was subtracted

from the total consumer surplus

(total welfare) of Rs.

228,493,714 the estimated

consumer surplus is Rs.

221,550,194 per year.

DISCUSSION

The present study attempted to

assess the recreational value of

the Hakgala Botanic Garden.

Objectives of this chapter are

to discuss the issues involved

with survey, methodology,

research barriers and importance

of the study in terms of

implications of policy. There

were some problems inherent to

the adopted methodology, but

some difficulties were case

specific.

Survey

Lack of market prices or

incomplete information may make

it impossible to use the market

and surrogate market techniques.

This is often the case where

goods never enter the market and

surrogate market techniques.

This is often the case where

goods never enter the market

like recreation. If market

prices or surrogate market

prices cannot be obtained, it

may be possible to question

people directly how they would

react to a given situation as in

this case. Based on their

answers, the value of a good can

be determined and then

extrapolated to determine the

aggregate effect on every one

affected. These survey based

approaches have been largely

developed in industrialized

countries and are the subject of

considerable academic debate.

Although their usefulness in

developing countries is limited,

careful done they can yield

useful information. In fact,

this method is one of the few

ways to place monitory estimates

on certain intangible effects

(Sherman,1990).

Remuneration of data

In this study, survey was

carried out to collect primary

data. Personnel interviews were

conducted with respondents

during the period of April 10 th

Thursday, 11th Friday, 12th

Saturday and July 18th Friday 19th

Saturday and 20th Sunday in the

year 2003. During the season

(April) there was large number

of visitors, which made it easy

to do the survey, especially in

the week ends. Even in July (off

season) there were quite a lot

of visitors. Based on the

quantitative analysis of

secondary data during past six

years (1997-2002) it was found

that visits peaked during April

and August (figure 4.9). This

may be mainly because these two

months are considered as the

“season” at Hakgala. It could

have been better if the

interview was conducted during

all the 7 days of the week.

However, it was difficult to

carry out the survey during all

the seven days of the week due

to financial and time constrains

of the author.

Average length of the interview

was approximately about five

minutes which made many visitors

willing to answer. Yet some were

reluctant to answer mainly due

to linguistic barrier.

Questionnaire was conducted in

Sinhala and English medium.

However, some visitors could not

communicate in either language

but in Tamil.

Respondents were selected

randomly, i.e. every other

person who was going out of the

garden was interviewed. Sample

size was restricted to 210 local

adult respondents. Children were

excluded since it is a well

organized norm that their

decisions do not carry a

significant weight. Foreigners

had to be excluded since it was

difficult to differentiate their

travel cost component to Hakgala

round trip. Most of them had

visited many other South Asian

countries linked to a travel

package and therefore they had

paid for the whole journey.

Similarly meanderers i.e. those

who derive utility from

traveling were ignored from the

sample since Hufschmidt, (1990)

reveals inclusion of them may

lead to overestimation of

benefits of recreation.

Meanderers were differentiated

from pure visitors by question

number 6 of the questionnaire,

which asked whether the

respondent had a special

interest to visit botanic

garden. 10 questionnaires had to

be rejected due to this reason.

As Sherman, (1993) states, this

survey based approach create

substantial conceptual and

operational difficulties. When

considering the survey, it was

very difficult to obtain the

realistic income of the

respondents since the main

objective of the study was

stated as estimating the

recreational value of the garden

using ‘travel cost.’ To get real

income figure, detail

explanation of the methodology

was required. Despite of the

effort, some respondents did not

understand the real scenario and

they neglected answering. In

such cases income had to be

predicted according to the

occupation. Similar difficulties

had to undergo in order to find

age, education level and

occupation.

Multiple visits

It was difficult to obtain the

exact travel expenditure

incurred to Hakgala trip when

respondent had multiple visits.

Most of the visitors that had

come from their own vehicle had

pumped ‘full tank’ by incurring

a certain cost. Therefore, they

could not differentiate exact

travel cost to Hakgala. In this

case cost per kilometer was used

to get the travel cost figure.

When visitors had hired a

vehicle, for multiple trips,

similar difficulties had to be

faced with. In such

circumstances traveling

expenditure had to be

apportioned according to the

distance they traveled to reach

each and every destination as

stated in Smith and Kopp (1980)

and Sturgess (1999). However,

shoeckl (1993) has allocated

travel costs according to the

time spent at the Site and

Bennet (1995) had divided the

total cost of the trip according

to visitor’s stated relative

importance of different

destinations visited and Hai and

Thanh (1993) allocated 30% of

the total cost to each

destination visited.

Question number 12 was extremely

difficult in terms of obtaining

realistic answers. It included

questions like;

b) Distance from the previous

place to this place.

c) Travel expenses incurred to

visit the previous place.

d) Travel expenses incurred to

visit the garden from that

place.

e). Distance from garden to

next place.

f) Travel expenses from the

garden to next place.

In situations where it was

difficult to obtain the most

accurate answer, road map

published by the Survey

Department had to be used to

differentiate distances to each

and every place in order to

allocate costs to such places.

It was very difficult to obtain

a clear answer on other

expenditure in the specific trip

to Hakgala (Question 14) as

well. The answer expected was

incremental expenditure in

addition to their normal

expenditure on meals,

accommodation etc. Since most of

the trips were multi purpose

trips, respondents could not

give an exact answer for other

expenses for specific Hakgala

trip.

Visitor perceptions

According to the questionnaire

survey most interesting place of

the garden was the rose garden.

In addition, glass house,

fernery, dalia garden, landscape

and other flower beds were

highly appreciated by the

respondents.

Many visitors (174,87%) thought

that this visit is worth for

money and few respondents

(26.13%) had the perception that

what they have paid is not

worth.

Many visitors were satisfied

with the existing facilities

(119,59%) and some were not

(81,41%). According to the views

of the visitors dissatisfaction

was due to the following

reasons.

There is no properly named

paths in the garden.

Although there is a map at

the entrance, it does not

provide clear directions

for the observer to

identify the places inside

the garden. There is no

published leaflet for the

convenience of the visitors

to identify the places.

There is not enough taps

inside the garden for the

visitor use and drinking

purpose. Most of the

visitors complained that

numbers of toilets are also

not enough.

Rainy season prevails

throughout the year at

Hakgala. Therefore there

should be substantial

number of huts for the

visitors to stay when it is

raining. According to the

visitor perception existing

numbers of huts are not

substantial for them to

rest.

There are not enough

garbage bins inside the

garden as well. This leads

to haphazard disposal of

polythene and other waste

material by visitors.

Maintenance of the garden

is also not so favorable.

In some places it is

clearly visible that long

grasses have not been

cleared for a long time.

According to the

administration of the park

this is due to inadequate

workers to keep the garden

clean.

Some visitors complained

for having not enough

regulations to control the

visitor behavior. It was

visible during the period

of survey that some people

came to the garden with

bottles of liquor. This may

be a major disturbance to

the normal visitors.

Most of the visitors (145,72%)

were willing to pay a higher

amount after these problems

are solved. Only 55 (28%) out

of 200 respondents were

disagreed to pay more even

after facilities are improved.

According to the curator of

the garden, lack of finance is

a major constrain to proper

management of the garden. He

further said low worker

efficiency has lead to the

poor maintenance of the

garden. He further said low

worker efficiency has lead o

the poor maintenance of the

garden. Lack of security is

another problem faced by the

administration. Police

officers are working inside

the garden to look after its

condition only during the

season. (April and August).

Curator also stated that a

restaurant may not be

profitable inside the garden

since higher number of

visitors cannot be seen during

every month of the tear/ He

further mentioned that, higher

noise, misbehavior, littering

and stealing of plants are

some of the serious problems

faced y the administration.

Methodological issues

This section discusses the

issues related to the

methodology. Some issues were

case specific where as some

issues were inherent to adopted

methodology.

Zonation

Zonal travel cost method was

used to measure the recreational

benefits of the Hakgala Botanic

Garden. According to travel cost

method, the recreation site is

identified and the surrounding

area is divided into concentric

zones of increasing distance,

which represents increasing

levels of travel costs

(Hufscmidt,1990). However, in

this study administrative

districts had to be used instead

of concentric zones radiating

from the site. In some

international travel cost

studies, as Lansdell and

Gangadharan (2001)has used

administrative districts other

than concentric zones. Since

administrative districts were

used other than concentric

zones, there may be a bias due

to identification of two

separate districts at equal

distances ( in this case zones)

which is located in north and

south from Hakgala, which would

otherwise come under one

concentric zone.

Multiple Trips

With respect to the destinations

traveled by visitors, unlike

other studies carried out in Sri

Lanka as presented in table 2.3,

in this study multiple

destination trips were not

excluded and instead the cost

component relevant to visit

Hakgala was considered in the

present study.

Time Cost

Cesario (1976) reviewed a number

of travel time and

transportation cost studies in

an effort to determine a shadow

price for time. His conclusion

suggested that the value of time

with respect to non work travel

should be between one- quarter

and one half of the wage rate.

However according to Freeman

(1993) it has long been

recognized that the time spent

in travel to a site should be

included as a component of

travel cost for purposes of

estimating the demand for

visits, but it has not been

clear what price of time should

be used to convert the time cost

of travel to its monetary

equivalent. After reviewing

evidence from transportation and

urban commuting studies Cesario

(1976) concluded that the

scarcity value of time was

approximately one- third of the

average wage rate. In the

calculation of opportunity cost

of travel, in order to calculate

the value of time instead of

taking the full wage rate one

third of wage rate was used in

this study.

Assumptions in travel

cost method

One of the assumptions in travel

cost method is that people in

different zones take the same

quantity of recreation at the

same monitory cost

(Hufschmidt,1990). This

assumption was criticized by

Seckler (1966), who argued that

the demand curves of users from

different zones might not be

comparable if there were

systematic variations of income

and utility functions between

zones. However, no identified

taste differences could be

identified taste differences

could be identified among the

different districts in Sri Lanka

which justifies the claim of

Seckler. However no attempt was

made to identify any minor taste

differences which are possible

among groups of people.

Another assumption in travel

cost method is that, travel cost

is a reliable proxy for price

(Hufschmidt, 1990). It assumes

that when traveling from home to

a recreational place only cost

that will be incurred is travel

cost. However, according to

Winpenny (1999) in a country

like Sri Lanka, traveling in an

own vehicle is a source of

prestige and not a cost. Hence

it can be considered as a

benefit to the traveler.

A basic assumption in the

Claswan (1976) method is that,

visitors will react in the same

way to increases in entrance

feee and a rise in travel cost.

However if a visitor travels to

two similar sites where the

nearby site has a much higher

entrance fee and distant site

both costs become equal, visitor

may prefer to visit the distant

site.

Factors affecting

visitation rates

According to Hanley and Spash

(1993) population levels of

zones must be included in zonal

models. Visitation rate is the

number of visitors from a

particular zone per 10000

population in that zone

(Hufschmidt, 1990). Using the

information on the number of

sampled visitors from each zone,

total number of visitors to the

garden for a year was calculated

since the garden does not keep

records of the origin of the

visitors. Number of sampled

visitors in each zone,sample

size, annual number of visitors

in each zone and population in

the each zone using equation 1

as stated in chapter 3 section

3.4. Highest visitation rate was

recorded from Colombo (45.25).

This may be due to the high

buying power of the people in

Colombo due to high per capita

income per month that is Rs.

12,990 (Anonymous,2002).

Regression analysis

It has been noted by Marasinghe

(2001) that percentage urban

population shows higher

correlation with visitation rate

than the regional education

index. So the regional education

index has been dropped from this

model. Therefore in the present

study urban population fraction

was used instead of urban

population percentage for

accuracy in subsequent

transformations.

According to Hufschmidt (1990)

data generated are used to

regress visitation rates on

travel cost and the variouse

socio economic variables.

Visitation rate was regressed

with total travel cost

(TTC),average income per zone

(I) and urban population

fraction (UF). In the regression

equations estimated using all

the above stated variables

income appeared to be

insignificant at 95% probability

level. I.e. P value was higher

than 0.05. This could be avoided

if much larger sample was taken

instead of 200. Due to this

reason, income was not

considered in the subsequent

regression analysis. However

income has an indirect effect in

calculating the opportunity cost

of time. Finally, Visitation

Rate was regressed with total

travel cost (TTC), and Urban

population Fraction (UF).

Travel Cost

Many travel cost studies carried

out out side Sri Lnka argue that

the costs used in a travel cost

model should be consumers

perceived costs rather than the

actual costs./ (Seller,Stoll and

Chavas, 1985) and Beal and Ward

(2000)). These studies have

incurred cost of petrol plus

insurance, depreciation and

maintenance cost must be

included to cost of petrol.

However, in reality it is a

cumbersome task.

According to the questionnaire

survey, there were respondents

from 18 districts (figure 4.14).

They were Colombo,

Kurunegala,Gampaha,Kandy,Kalutar

a,Badulla,Nuwara Eliya, Galle,

Hambanthota,Kegalle,

Matale,Ampara,

Puttlam,Polonnaruwa,Jaffna,

Rathnapura, Anuradhapura and

Monaragala. However respondents

from only 8 zones

(Colombo,Kurunegala,Gampaha,Kand

y,Kaluthara,Badulla,Nuwara Eliya

and Galle)had come from all

three modes(own, public and

hired). It was assumed in this

study that modes of own, public

and hired represented high, low

and middle income categories.

Therefore it was justifiable to

derive an average travel cost

figure for each zone by

averaging travel cost figures

represented by all three modes

together instead of using a

weighted average. Therefore in

regression analisisonly zones

which represented all three

modes were considered. These 8

zones represented 176

respondents out of 200 (88%).

Other 24 respondents from other

zones had to be excludedwhich

was only 12%since the zones they

were originated did not

represent all three modes. In

most of other studies, carried

out in Sri Lanka, e.g. Silva

(1996), De Silva(1996),

Weerakoon (2000), Sooriyabandara

(2002), Rathnayaka (2000) and

Marasinghe (20001)had also used

to regress only selected number

of zones. This problem could

have been avoided if much larger

sample size was used which

represent all three modes for

all the zones.

Functional forms

There are number of functional

forms that are consistent with

economic theory. The linear form

is the most commonly estimated

(Ward and Beal,2000). However,

there are many examples of other

functional forms being used.

Almost all the Sri Lankan

studies based on travel cost

method has used linear form.

Choosing a linear form implies

that as travel cost increase

visits per year decrease by a

constant amount. The double log

form is commonly used as it

accounts for extreme

values( Ward and Beal 2000).

Beal (1995)chose to use the

double log form. Ward abd Beal

(2000) used reciprocal form for

their study to estimate

recreational value in Kakadu

islands.

Conclusion

The Biotanic Garden at Hakgala

one of the oldest ex-situ

conservation areas in Sri Lanka.

It is a unique environmental

asset, nationally as well as

globally, due to its

conservation, recreation,

historical,cultural and

educational and other values.

The objectie of the study was to

accesses the local recreational

value of the Hakgala botanic

garden. The economic approach

used to estimate the

recreational value was the zonal

travel cost method. It has been

widely used to value recreation

benefits.

A survey of 200 respondents was

conducted at the Hakgala garden

to collect primary data.

Personnel interviews were

conducted to collect primary

data.

Secondry data was mainly

obtained from records maintained

by the garden. It was about the

total number of visitors

annually, from 1997-2002 and

monthly visitors during the

years 1997-2002. Administration

reports of the Department of

Agriculture from 1999-2002 was

used to get information about

the income collected by the

garden. Statistical abstracts of

the Department of Census and

Statistics was used to obtain

data such as total population in

each district, total urban

population in Sri Lanka and

urban population in Sri Lanka

and urban population in selected

districts. These data was

obtained for year 2002.

With respect to multiple trips,

cost component to visit Hakgala

was differentiated based on

distances to particular

destinations travelled. Zoning

was done by allocating the

visitors under the respective

districts where the visit was

originated. Number of sampled

visitors in each zone, sample

size, annual number of visitors

in each zone and population in

each zone was used to calculate

the visitation rate per 1000

population in each zone. Total

travel cost was considered to

comprise cost of travelling and

the opportunity cost of time of

travelling.

Eight districts namely Colombo,

Kurunegala, Gampaha, Kalutara,

Nuwara Eliya, Badulla, Galle and

Kalutara were selected as zones

of increasing distance, which

represented increasing levels of

travel cost. The data generated

were used to regress visitation

rates, the total travel cost and

urban population fraction of

each zone. This regression was

used to test the hypothesis that

travel costs do infact have an

impact on visitation rates.

Necessary transformations such

as log, square, square root was

done to dependent as well as

independent variables in order

to obtain a higher co-efficient

of determination (R2). Residual

distribution was obtained by

plotting standard vs. fitted

values. Best model was selected

by considering the R2 value and

residual distribution.

Demand curve based on visitation

rates, was constructed using

these data to estimate the

consumer surplus, or benefits,

from the site. Estimated minimum

total cost experienced by the

visitors at the current entrance

fee (Rs.20.00) was Rs.

6,943,520. When this amount is

subtracted from the total

consumer surplus of Rs.

228,493,714 the estimated

consumer surplus was Rs.

221,550,194 which represents the

local recreational value of

Hakgala Botanic garden per year.

This figure can be used to

attract more funds to develop

infrastructural facilities

inside the garden from the

government allocations. This

figure is also helpful to

demonstrate the contribution of

a botanic garden to the economy.