148

CHAPTER 5

DATA ANALYSIS AND INTERPRETATION

5.1 Introduction ........................................................................................................... 153

5.2 Demographics of Respondents ............................................................................. 153

5.2.1 Educational Status .......................................................................................... 153

5.2.2 Occupational Status ....................................................................................... 154

5.2.3 Income Status ................................................................................................. 155

5.2.4 Age Group ...................................................................................................... 155

5.2.5 Duration of Residence.................................................................................... 156

5.3 Preservation of Customs and Traditions ............................................................... 157

5.3.1 Cross Tabulation: Tradition and Number of Years of Residence .................. 158

5.3.2 Cross Tabulation: Tradition and Age ............................................................. 160

5.3.3 Comparative Contribution to Preservation of Traditions............................... 162

5.4 Growth of Infrastructure and Tourism .................................................................. 164

5.4.1 Comparative Contribution towards Infrastructure Growth ............................ 165

5.5 Local Income and Tourism ................................................................................... 167

5.5.1 Comparative Contribution towards Local Income ......................................... 169

5.6 Quality of Life and Tourism ................................................................................. 171

5.6.1 Comparative contribution to quality of life. .................................................. 172

5.7 Knowledge and Skill through Tourism ................................................................. 173

5.7.1 Comparative Contribution to Knowledge and Skill Acquisition ................... 175

5.8 Culture and Tourism Development ....................................................................... 175

5.8.1 Comparative Contribution towards Cultural Development ........................... 177

149

5.9 Crime and Tourism ............................................................................................... 179

5.9.1 Perception on Reduction of Crimes ............................................................... 181

5.10 Ecological Preservation and Tourism ................................................................. 182

5.10.1 Comparative Contribution to Ecology and Environment ............................ 183

5.11 Residents‟ Psychological Engagement in Tourism Development ...................... 185

5.11.1 Psychological Engagement with Tourism ................................................... 186

5.11.2 Correlation Analysis: Psychological Engagement with Tourism ................ 188

5.11.3 Regression Analysis: Psychological Engagement with Tourism................. 189

5.12. Resident Participation in Kumbalangi Tourism Project .................................... 189

5.12.1 Resident Participation in Planning ............................................................... 190

5.12.2 Resident Participation in Implementation .................................................... 192

5.12.3 Comparison of Participation between Planning and Implementation .......... 193

5.12.4 Hypothesis Testing: Relationship between Planning and Implementation.. 194

5.13 Hypothesis Testing: Impact of Participation on Perception ............................... 196

5.13.1 Correlation Analysis: Participation and Perception ..................................... 196

5.13.2 Regression Analysis: Relationship between Participation and Implementation

................................................................................................................................. 197

5.13.3 Relationship between Participation and Perception: Conceptual Model ..... 201

5.14 Influence of Demographic Variables on Perception ........................................... 202

5.14. 1 Influence of Gender on Perception ............................................................. 203

5.14.2 Influence of Age on Perception ................................................................... 205

5.14.3 Influence of Income on Perception .............................................................. 207

5.14.4 Influence of Education on Perception .......................................................... 210

150

5.14.5 Influence of Occupation on Perception........................................................ 213

5.14. 6 Influence of Duration of Stay on Perception .............................................. 215

5.15 Rural Tourism Influence on Development Management .................................... 217

5.16 Summary ............................................................................................................. 219

Endnotes and References ............................................................................................ 221

List of Tables

Table 5. 1 Educational status of respondents .................................................................. 153

Table 5. 2. Occupational status of respondents............................................................... 154

Table 5. 3 Income of the respondents ............................................................................. 155

Table 5. 4 Age group of respondents ............................................................................. 155

Table 5. 5 Years of residence of respondents ................................................................. 156

Table 5. 6 Preservation of traditions ............................................................................... 157

Table 5. 7 Relationship between tradition and years of stay .......................................... 159

Table 5. 8 Relationship between tradition and age ......................................................... 160

Table 5. 9 Comparative contributions to preservation of traditions ............................... 162

Table 5. 11 Infrastructure developments and tourism .................................................... 164

Table 5. 12 Relative contribution towards infrastructure growth ................................... 166

Table 5. 14 Growth of local income ............................................................................... 168

Table 5. 15 Comparative contribution to local income ................................................... 169

Table 5. 17 Quality of life due to tourism ....................................................................... 171

Table 5. 18 Comparative contribution of quality of life factors ..................................... 172

Table 5. 19 Knowledge enhancement through tourism .................................................. 174

Table 5. 20 Relative contribution to knowledge and skill .............................................. 175

Table 5. 21 Contribution to cultural development .......................................................... 176

Table 5. 22 Relative contribution towards culture ......................................................... 177

Table 5. 24 Growth of Tourism and Crimes ................................................................... 180

Table 5. 25 Perception on reduction of crimes ............................................................... 181

151

Table 5. 27 Preservation of ecology and environment ................................................... 182

Table 5. 28 Preservation of ecology and environment ................................................... 182

Table 5. 29 Relative contributions to ecology and environment .................................... 183

Table 5. 31 Psychological engagement with tourism ..................................................... 185

Table 5. 32 Outlook towards tourism development ........................................................ 186

Table 5. 34 Correlation Analysis: Attitude factors ......................................................... 188

Table 5. 35 Regression Analysis: Psychological engagement factors ............................ 189

Table 5. 36 Resident participation in tourism planning .................................................. 190

Table 5. 37 Correlation Analysis – CV Model ............................................................... 191

Table 5. 38 Resident participation in implementation .................................................... 192

Table 5. 39 Correlation Analysis- Participation in Implementation ............................... 193

Table 5. 40 Comparison of participation between planning and implementation .......... 194

Table 5. 41 Correlation between participation and perception factors ........................... 197

Table 5. 42 Descriptive statistics of variables ................................................................ 198

Table 5. 43 Regression Analysis Values......................................................................... 199

Table 5. 45 Genderwise Group Statistics ........................................................................ 203

Table 5. 46 T-test results: Gender and perception .......................................................... 204

Table 5. 47 ANOVA results: Age and perception on DMV ........................................... 205

Table 5. 48 Tukey B and Scheffe results for age and local income ................................ 206

Table 5. 49 Tukey B and Scheffe results for age and ecology & environment .............. 207

Table 5. 50 ANOVA results: Income and perception on DMV .................................... 208

Table 5. 51 Tukey B and Scheffe results: Income and implementation ......................... 209

Table 5. 52 ANOVA results: Education and perception on DMV ................................. 210

Table 5. 53Tukey B and Scheffe results: Education and implementation ...................... 211

Table 5. 54 Tukey B and Scheffe results: Education and ecology & environment ........ 211

Table 5. 55 Tukey B and Scheffe results: Education and knowledge ............................ 212

Table 5. 56 ANOVA results: Occupation and perception on DMV .............................. 213

Table 5. 57 Tukey B and Scheffe results: Occupation and local income ....................... 214

Table 5. 58 Tukey B and Scheffe results: Occupation and quality of life ...................... 215

Table 5. 59ANOVA results: Duration stay and perception on DMV ............................. 216

Table 5. 60 Tourism impact on development ................................................................. 217

152

List of Figures

Figure 5. 1. Comparative contributions to preservation of traditions ............................. 163

Figure 5. 2. Relative contribution to infrastructure growth ............................................ 166

Figure 5. 3. Comparative contribution to local income .................................................. 170

Figure 5. 4. Relative contribution towards culture ......................................................... 178

Figure 5. 5. Perception on different types of crimes ....................................................... 181

Figure 5. 6. Relative contributions to ecology and environment .................................... 184

Figure 5. 7. Psychological engagement with tourism development ............................... 187

Figure 5. 8. Relationship between participation and perception ..................................... 202

Figure 5. 9. Relationship between participation and perception ..................................... 218

153

CHAPTER 5

DATA ANALYSIS AND INTERPRETATION

5.1 Introduction

This chapter analyses the situation existing in Kumbalangi village, after the

implementation of the endogenous rural tourism project. Data were collected with

the intention to evaluate the development management of the village through the

rural tourism project. Primary means of data collection was questionnaire survey.

Focus group interviews and participant observations were also conducted for

strengthening the research. Kumbalangi is the first village in India to complete the

implementation of the endogenous tourism project.

5.2 Demographics of Respondents

The participants for this study were identified from the voters list prepared by the

district election commission. Therefore all the respondents were adults and above

eighteen years of age. The updated list prepared by the authorities in 2008 was

taken for the study. The respondents were identified using stratified random

sampling. The tables and graphs below explain the socio-economic status of the

respondents. Socio-economic status of respondents are analysed under 5 headings.

5.2.1 Educational Status

Table 5. 1 Educational status of respondents

10th and

Below

HSS or

Equivalent

Bachelor

Degree

P G and

Above

Total

360 93 61 16 530

68% 18% 11% 3% 100%

154

It is clear from the above table that majority of the respondents have their

education up to matriculation or below. The adult population in Kumbalangi have

only minimum education because in the past most of the villagers were engaged

in fishing, agriculture and allied activities. People had to go to either Alappuzha

or Cochin for higher studies. In order to travel to either place people had to

depend solely on ferries. The availability of ferries was also limited in the past.

Even today there is no higher educational institution in the island village. But at

present Kumbalangi is well connected to mainland with the construction of

bridges. This would certainly improve the possibility for higher education for

younger generation in the island.

5.2.2 Occupational Status

Table 5. 2. Occupational status of respondents

Frequency Percentage Education 22 4

Home Making 214 40

Daily Wages 251 47

Salaried 43 8

Total 530 100.0

The table above explain that the majority population in Kumbalangi village is

without regular employment. Only 8% of the respondents fall in the salaried class.

Majority of the population are daily workers. Their employment is often seasonal

and therefore they are either under employed or unemployed for many days in a

155

year. The women are primarily engaged in homemaking without any source of

regular income.

5.2.3 Income Status

Table 5. 3 Income of the respondents

Income Level Frequency Percentage

Less than 2000 226 43

2000-4000 160 30

4001- 6000 68 13

6001 – 8000 15 3

8001 – 12000 6 1

Not declared 55 10

Total 530 100

The table above clearly demonstrate the income level of the respondents. More

than 70% of the people say that their income level is below Rs4000/- per month.

One of the major reasons for lower income is the lack of availability of

continuous jobs. Another important reason is the small size and fragmentation of

agricultural land holdings. Most of the farmers in the region have only less than

half an acre of land.

5.2.4 Age Group

Table 5. 4 Age group of respondents

Age Group Frequency Percentage

Below 22 30 6

22- 35 91 17

36-50 209 39

51- 65 141 27

Above 65 59 11

Total 530 100

156

Most of the respondents belonged to 36- 50 age group. This is the group that can

actively contribute to tourism development in the region. Since respondents were

identified from the voters list none of the respondents are below 18 years of age.

5.2.5 Duration of Residence

Table 5. 5 Years of residence of respondents

Unlike in many peripheral areas attached to townships, even today the vast

majority of the inhabitants of Kumbalangi are natives. The presence of migrant

population at present is very low. This is an advantage for the island to develop its

own indigenous tourism products. The destination can certainly offer unpolluted

culture and traditions of a typical island village community in Kerala. One of the

reasons behind the presence of low migrant population in the region was the issue

of connectivity to the mainland. The construction of bridges as well as the

growth of tourism in the region will certainly bring the area to the limelight and

the in-migration is likely to be high in future.

Years of stay Frequency Percentage

10 and Below 84 16

11 to 25 123 23

26 to 50 209 39

Above 50 114 22

Total 530 100

157

5.3 Preservation of Customs and Traditions

One of the major reasons behind objections to tourism development in rural

regions is the fear of either undervaluing the traditions and practices or their

commercialisation and commoditisation for the purpose of tourism. In many rural

tourism areas, the host community faces the threat of emulating the customs and

practices of tourists. All these happen when people fail to assign importance to

their own traditions.

Eight questions were asked to collect the perception of people regarding the

preservation of traditions. Responses were collected on a five point scale from

very important to no answer. The composite score of all the eight questions is

taken to present the table and the graph.

Table 5. 6 Preservation of traditions

Statistics Responses Frequency %

Mean 4.15 Very Important 117 22.2

Median 4 Important 358 67.8

Mode 4 Not Important 20 3.8

Std. D .466 Do not Know 33 6.3

Minimum 2.25

Maximum 5 Total 528 100

158

The table above show that the attitude of people towards the preservation of

traditions and practices is very positive. Only 10% of respondents were either

neutral or negative. Most of the respondents said that traditions are important. In

many rural tourism destinations there are temptations for residents to imitate

tourists‟ behaviour and under estimate their own rich traditions.

To further under the nature of responses we look into the composite mode and

median for traditions. The mode and median are four and the mean value is 4.15

out of five, with a standard deviation of .466. That means lions majority of the

respondents is positively disposed to maintain their traditions and culture.

Kumbalangi implements endogenous rural tourism project for its development. In

order to develop unique and authentic, nature based tourism projects with

community participation, faithful preservation of the traditions and culture of the

place is absolutely necessity. The questionnaire sought responses on preservation

of religious festivals, dress patterns, life styles, food habits, occupations and

culture.

5.3.1 Cross Tabulation: Tradition and Number of Years of Residence

In order to find out the relationship between the residents‟ perceptions on

preservation of traditions and the number of years of stay both cross tabulation

and chi-square tests were done.

159

Since the value of chi-square is 2.48 and therefore not significant at 0.05 level.

Therefore we conclude that duration of residency and one‟s willingness to follow

local traditions and customs are not significantly related.

Even the migrant population is aware of, and is interested in the preservation of

traditions and practices that are unique to Kumbalangi. This is exceptionally

advantageous for the island to develop tourism. Partially this can be ascribed to

the successful implementation of the training programmes as part of the UNDP

project. More than 5000 people were trained under the project. When we look

into the cross tabulation table, it is interesting to notice that even among the

people who have come to Kumbalangi within the last ten year period, almost 90%

support preservation of traditions of the region.

24 54 23 16 117 19.7% 24.7% 20.0% 22.2% 22.2%

86 145 80 47 358 70.5% 66.2% 69.6% 65.3% 67.8%

8 12 7 6 33 6.6% 5.5% 6.1% 8.3% 6.3%

4 8 5 3 20 3.3% 3.7% 4.3% 4.2% 3.8% 122 219 115 72 528

100.0% 100.0% 100.0% 100.0% 100.0%

Count % within stay Count % within stay Count % within stay Count % within stay Count % within stay

Very Important

Important

Don't Know

Not important

Tradition

Total

50 and Above 25-50 10-25 below 10 Stay

Total

Table 5. 7 Relationship between tradition and years of stay

Chi-Square Test Result

2.480 9 .981 Pearson Chi-Square Value df

Asymp. Sig. (2-sided)

160

5.3.2 Cross Tabulation: Tradition and Age

The data was further analysed to find out whether there existed any relationship

between age and preservation of tradition.

Chi-square test was also done to ascertain the relationship

Since the chi square value is significant, we accept the alternate hypothesis. There

is relationship between age and preservation of traditions. From the table it is

clear that around 90% of youngsters and elderly people alike are interested in

preserving traditions and practice. There is significant difference between the age

group 22-35 and others. Almost 20% of the people in this age group are not much

concerned about traditions.

In order to ascertain the relationship between tradition and age the data is further

tested using the ANOVA. The results are given below.

Chi-Square Tests

41.124 12 .000Pearson Chi-SquareValue df

Asy mp. Sig.

(2-sided)

12 17 50 31 7 117 41.4% 19.1% 23.9% 22.1% 11.5% 22.2%

15 55 151 93 44 358 51.7% 61.8% 72.2% 66.4% 72.1% 67.8%

0 14 6 9 4 33 .0% 15.7% 2.9% 6.4% 6.6% 6.3%

2 3 2 7 6 20 6.9% 3.4% 1.0% 5.0% 9.8% 3.8%

29 89 209 140 61 528 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Count % within Age Count % within Age Count % within Age Count % within Age Count % within Age

Very Important

Important

Don't Know

Not important

Tradition

Total

Below 22 22-35 36-50 51- 65 Above 65 Age

Total

Table 5. 8 Relationship between tradition and age

161

Tradition

Sum of

Squares

DF Mean

Square

F Sig

Between

groups

Within

groups

Total

501.684

101115.376

10617.061

4

523

527

125.421

19.341

6.485 .000

The P-value of ANOVA (p-value < 0.05) indicates that there is significant

difference between the age groups with regard to their perceptions. Since both

chi-square and ANOVA results spoke of significant changes in perceptions

between age groups, Tukey HSD test was further administered. This was done to

find out the variation in the mean values of among different age groups Tukey

HSD test was conducted. The table below shows pair-wise comparison of the age

groups.

Comparison of mean values makes it clear that there are two groups based on

their perceptions on preserving traditions and culture. The respondents above 65

Tradition

Tukey HSD a

61 30.4754

89 31.9663 31.9663

140 32.5786

209 33.4545

29 33.7586 .282 .126

Age Above 65

22-35

51- 65

36-50 Below 22

Sig.

N 1 2

Subset for alpha = .05

Means for groups in homogeneous subsets are displayed.

Uses Harmonic Mean Sample Size = 67.531. a.

162

years of age and those between 22 and 35 belong to one group and others another

group. However, the perception regarding the preservation of traditions among the

age group above 65, significantly differ from other age groups. Based on a

smaller mean value it is clear that unlike the usual, the older generation is less

obstinate in the preservation of traditions. The perception of the age group

between 22 and 35 is significantly closer to the older generation. This is probably

because the youth in those ages are in the strains of finding adequate livelihood

for their family and therefore less concerned about traditions and culture.

5.3.3 Comparative Contribution to Preservation of Traditions

In order to find out the relative importance of different traditions based on the

perception of people in the region a descriptive statistics is also done.

Table 5. 9 Comparative contributions to preservation of traditions

N Mean Std. Deviation

Parish Festivals 528 4.20 .647

Temple Festivals 514 4.04 .614

Mosque Festivals 514 3.90 .659

Cultural practices 516 4.21 .475

Dress habits 525 4.19 .498

Food habits 525 4.20 .498

Life style 514 4.21 .475

Traditional Occupations 520 4.23 .479

163

Figure 5. 1. Comparative contributions to preservation of traditions

From the table and graph above it is clear that there is no significant perception

difference among the residents regarding the preservation of any tradition. People

consider all the aspects of traditions and customs very important. In general

people assign lesser importance to the preservation of religious festivals. The

standard deviations are also higher in the case of all religious festivals. The higher

mean rate for Christian and Hindu festivals is probably because the sample size

contained almost equal number of people from those religions. Hence the

respondents from the religion said the preservation of festivals of their religion is

very important while those of others are not. The residents in the island also

3.65

3.75

3.85

3.95

4.05

4.15

4.25Parish Festivals

Temple Festivals

Mosque Festivals

Cultural practices

Dress habits

Food habits

Life style

TraditionalOccupations

164

primarily belong to Christian and Hindu religions. The mean value for

preservation of Muslim festivals is the lowest because the number of residents is

small.

5.4 Growth of Infrastructure and Tourism

Another major analysis in the study was to find out the impact of tourism in the

growth of infrastructure in the area. There were eleven questions on infrastructure

development. They included questions on roads, public transportation, bridges,

housing conditions, shopping facilities, electricity, internet facilities etc. The

values given below are based on the composite score.

Table 5. 10 Infrastructure developments and tourism

Statistics Response Frequency %

Mean 4.18 No Difference 10 1.9

Median 4.00 Improved 414 78.1

Mode 4.00 Significantly Improved 106 20.0

S D .43 Total 530 100

The perception of the people is generally positive about infrastructure

development in the village. The mean value is 4.18. The composite highest and

the lowest mean values were 4.82 and 2.82. The standard deviation is only .43.

The median and mode scores are also high. All these figure point to the fact that

people are positive about the contribution of tourism to infrastructure

development. Only an insignificant 1.9% of the people said that there is no

difference in infrastructure development. The remaining 98% of the population is

of the opinion that tourism resulted in the development of infrastructure. None of

165

the respondents said that tourism has worsened the availability of infrastructure in

the village. This is quite beneficial to Kumbalangi Village. In places where

enclave tourism is promoted in the rural areas, residents suffer from the lack of

availability of infrastructure facilities. Very often they are deprived of many of

the facilities they enjoyed even before the arrival of tourism.

As a part the endogenous tourism project from UNDP and Government of India

together spent, funds worth 50 lakhs rupees were for infrastructure development.

Most part of the funds was spent for public and household waste management.

Every house in the village was provided with a biogas plant to effectively manage

domestic bio-waste. There were also significant additions to roads and bridges.

The response of the people certainly approves off effective spending of available

resources.

5.4.1 Comparative Contribution towards Infrastructure Growth

Rural tourism models do not make large amount of infrastructure for tourism

alone. Therefore in Kumbalangi Panchayath there are not many infrastructure

investments made for tourism. At the same time rural tourism models must be

able to make investment in the region that would make the life of the people in the

destination more healthy and comfortable. Therefore, efforts were made to

understand the level of investments due to tourism that would raise the standard

of living of the general public in Kumbalangi Panchayath. The table below

compares the resident perception towards infrastructure.

166

Table 5. 11 Relative contribution towards infrastructure growth

Min Max Mean

Std.

Deviation

Cleanliness in restaurants 2 5 3.88 0.46

Accommodation facilities 3 5 3.81 0.46

Public transportation 2 5 3.76 0.54

Bridges 2 5 3.74 0.54

Other public transportation ( like taxi) 2 5 3.72 0.53

Business avenues 2 5 3.71 0.51

Availability of electricity 1 5 3.65 0.58

Road construction 1 5 3.59 0.66

Availability of clean drinking water 2 5 3.56 0.61

Availability of internet and phone 2 5 3.56 0.56

Quality of food in restaurants 1 5 3.55 0.78

Figure 5. 2. Relative contribution to infrastructure growth

3.3 3.4 3.5 3.6 3.7 3.8 3.9

Clean tea shops & restaurants

Accommodation facilities

Public transportation (Bus…)

Bridges

Other public transportation (Taxi)

Business avenues

Electricity

Road

Clean drinking water

Internet and phone

Quality of food in restaurants

3.88

3.81

3.76

3.74

3.72

3.71

3.65

3.59

3.56

3.56

3.55

167

From the table and graph it is clear that mean values of all the eleven factors

understudy are above three. This means people generally agree that there is

significant infrastructure growth as a result of tourism. It is really interesting to

note that the highest mean value is for the cleanliness of restaurants and the

lowest is for the quality of food.

Proper education and training is required to enhance the quality of food in tea

shops and small restaurants. The cleanliness and the quality of food and beverages

in the region are particularly significant to the development of tourism in

Kumbalangi, especially in the absence of any upper-class branded restaurants.

Tourists have to solely depend on the available small local restaurants. Studies

have revealed the fact that in general 10 to15 percentage of tourist spending is on

food and beverages1. Moreover Kumbalangi is projecting itself as one of the rural

tourism models. In rural tourism models contribution to local economy happens

primarily through local cuisines and beverages2. Unless the region is able to offer

quality food in a clean environment, tourists will be hesitant to come to the place.

Immediate attention to ensure quality of services is a must for the future tourism

development of the region.

5.5 Local Income and Tourism

Endogenous rural tourism was implemented in Kumbalangi village in order to

enhance the local income in a significant way. Economic gain being one of

important paradigms of development management effort was made to analyse the

contribution of tourism in enhancing the local income in Kumbalangi. Therefore

in the pilot test an effort was made to collect quantitative data regarding income.

But the effort was not successful because the ordinary residents of the place do

168

not keep exact accounts of their income and expenditure. Even those households

who are directly engaged in tourism related activities were not keeping accounts

relating to income from tourism, because tourism is not their major activity and

moreover, the rural less educated population in India has not yet started keeping

accounts of their income and expenditure. But all of them were able to judge the

impact of tourism on local income. Therefore in the final data collection the

perception of the residents was collected to gauge the contribution of tourism to

local income.

Table 5. 12 Growth of local income

Statistics Response Frequency %

Mean 3.54 Significantly improved 27 5

Median 3.54 Somewhat improved 203 38

Mode 3.54 No difference 246 47

Std. D .261 Worsened 54 10

Total 530 100

From the table above it is clear that the respondents are evenly divided regarding

the contribution of tourism towards local income. Only less than 50% of people

feel the positive impact of contribution of tourism. When we look into the

statistics too, we see that the mean, median, and mode are equally smaller values.

However, they indicate that respondents in general agree that tourism contributes

to local income.

Tourism in Kumbalangi is still in its infancy. Though there is lot of hype being

created about the possibilities of tourism, many of the expectations are yet to be

materialised. 10% of the people feel that tourism has only reduced their income

169

directly or indirectly. In connection with the Kumbalangi Tourism Village project,

there were efforts to implement many eco-friendly practices like minimising the

use of plastics, cultivation of paddy without chemical fertilisers and pesticides etc.

Some of these practices have negatively affected the income of the few. Unless

tourism is able to supplement the loss of their income in the near future, those

people could be sceptical about tourism impact and in the long run they could be

against tourism promotion in the region.

5.5.1 Comparative Contribution towards Local Income

The data is analysed to find out the relative contribution of the seven variables

under study. Table below gives a comparison of the perception of people

regarding the economic value of different resources available to them.

Table 5. 13 Comparative contribution to local income

Min Max Mean SD

Income from ordinary works through

tourism

1 5 2.22 0.923

Overall income of the people 2 5 2.89 0.793

Sale of goods and services 1 5 3.13 0.681

The quantity of sales in shops 2 5 3.47 0.545

Price of land and real estate 1 5 3.65 0.581

Employment opportunities 1 5 3.69 0.593

Income from artistic performances 2 5 4.65 0.488

170

Figure 5. 3. Comparative contribution to local income

From the above table and graph it is clear that income from tourism for ordinary

workers is the lowest. Highest income is earned from artistic performance. Artists

receive higher earnings from tourism because as a part of the endogenous tourism

project, efforts were made to restore and promote traditional art forms of

Kumbalangi. Presentation of different art forms is a good means to generate

income from tourists. The Kalagram (art school), which is part of the tourism

project, was meant for the development and preservation of indigenous art forms,

is not yet complete.

The respondents perceive generation of additional income from additional job

opportunities. The rise of price in the real estate need not be always positive at

least for those in the lower economic strata. Higher real estate cost will gradually

result in the migration of people from the place and to the place. Large scale

migration will make it very difficult even to define local people.

0.1 1.1 2.1 3.1 4.1 5.1

Income from ordinary works through tourism

Overall income of the people

Sale of goods and services

The quantity of sales in shops

Price of land and real estate

Employment opportunities

Income from artistic performances

2.22

2.89

3.13

3.47

3.65

3.69

4.65

171

Many respondents perceived increase in the sales of shops. Every year there are

exhibitions conducted in the island with a view to show case the village and to

ensure adequate market for different curios prepared in the village. In connection

with the exhibitions there are also food stalls that sell indigenous cuisines to

tourists. All these have resulted in the increase of sales in the shops. However,

when we look into the table we see that the mean value for sales is not very high

and the standard deviation is high. Based on the table given above it could be

rightly concluded that in general the respondents agree that there is moderate

increase in local income in the village due to tourism development.

5.6 Quality of Life and Tourism

Improved quality of life is intimately connected with the development

management of any region. Quality of life is dependent on various factors. In the

questionnaire sixteen factors were studied under quality of life. The summery of

the perception based on the composite score on all the sixteen factors under study.

Table 5. 14 Quality of life due to tourism

Statistics Responses Frequency %

Minimum 2.50 No Difference 36 6.8

Maximum 3.94 Improved 487 91.9

Mean 3.09 Significantly Improved 7 1.3

S D .224 Total 530 100.0

Majority of the people are clearly positive about the impact of tourism on quality

of life. However the contribution of tourism towards quality of life is not very

significant. There is no overall negative response in this case. The lowest score

being 2.5 out of five indicates that they are more or less neutral about the

172

contribution of tourism. The mean value indicates positive perception. However

the score is low. Data was further analysed to examine the relative contribution.

5.6.1 Comparative contribution to quality of life.

One of the primary objectives behind the implementation of the tourism project in

Kumbalangi was to enhance the quality of life. The table below gives the details.

Table 5. 15 Comparative contribution of quality of life factors

Min Max Mean S D

General well-being 1 5 2.79 .766

Public security 1 5 2.93 .652

Reduction in disturbances from public noise 1 5 3.13 .723

Reduction in spitting in public places 1 5 3.16 .718

Cultural centres like clubs 1 5 3.16 .889

Play grounds 1 5 3.33 .661

Pride in being a person from Kumbalangi 1 5 3.51 .560

Reduction in littering 1 5 3.58 .647

Recreational facilities (theatres, cinemas etc.) 2 5 3.69 .515

Ability to interact with strangers 1 5 3.80 .485

Residents' concern for material gains 1 5 3.82 .470

Cleanliness of public places 1 5 3.87 .474

Cleanliness of premises of food service areas 3 5 3.93 .368

Health consciousness 3 5 3.93 .403

Reduction in public smoking 2 5 3.97 .397

Mutual confidence among people 2 5 3.99 .498

173

From the above table it is clear that the overall perception about quality of life is

not very high. The mean value for general well-being is the lowest among the

variables with 2.79 and it has one on the highest standard deviations. However,

even the smallest mean value is above 2.5 which suggest positive contribution of

tourism to quality of life. Highest mean value among the variables is for mutual

confidence among people. Probably the democratic process of decision making in

connection with tourism development gave the residents different forums for

mutual interaction and discussion. These forums directly and indirectly promote

social capital which again stimulates the development management of the region.

Moreover, in future the democratic process of decision making could be further

strengthened which will lead to increased participation in the tourism

development.

5.7 Knowledge and Skill through Tourism

One of the important aspects of development management is knowledge

acquisition and empowerment of residents. Through tourism development the host

community is often enriched by knowledge about other cultures and practices.

Knowledge acquisition of residents is assessed using three variables. The general

influence of tourism on knowledge and skill enhancement is presented below.

174

Table 5. 16 Knowledge enhancement through tourism

Statistics Response Frequency %

Minimum 2.67 Worsen 11 2.1

Maximum 5 No Difference 283 53.4

Mean 3.25 Improved 220 41.5

Std. D .449 Significantly Improved 16 3.0

Total 530 100.0

It is clear from the table that people are not very positive about knowledge

gaining through tourism. There are many reasons for lack knowledge

improvement through tourism. Kumbalangi is not yet able attract large number of

tourists. Another important reason is the lack of possibility for ordinary residents

to interact with tourists. Most of the residents are having less education. Therefore

their possibility to interact with the tourists is also low. However, 45% of the

residents have expressed favourable perception regarding knowledge acquisition.

The lowest composite mean value signify positive contribution of tourism towards

knowledge. Some of the residents especially those who provide direct service to

tourists like the homestay owners and taxi drivers certainly have plenty of

opportunities to interact with tourists. That is the reason why the highest

composite mean is five. The composite mean value of 3.25 denotes the positive

impact of tourism on knowledge enhancement. Knowledge and skill

enhancement of people certainly augments the development management of the

village.

175

5.7.1 Comparative Contribution to Knowledge and Skill Acquisition

There were three questions to evaluate the knowledge acquisition of residents.

They were asked to respond to the question on a five point scale. The table gives

the details.

Table 5. 17 Relative contribution to knowledge and skill

Mean S D

Ability to interact with strangers 2.880 .8282

Opportunity for learning 3.216 .8275

Multi linguistic skills 3.273 .5056

The mean values indicate that general perception of people is positively oriented.

The least mean value is regarding the ability to interact with strangers. As already

stated the tourism development in Kumbalangi is still in its infancy. The number

of tourists visiting the place is still small. Therefore the residents do not have

many chances to interact with strangers. The highest mean value is regarding the

acquisition of multi-linguistic skills. The development of tourism in the place led

to conscious efforts among many villagers to develop their foreign language

skills. Since the overall perception of residents is positively oriented, as the

tourism in Kumbalangi matures there will be significant value addition to their

knowledge and skills.

5.8 Culture and Tourism Development

One of the possible dangers of tourism development especially in rural areas is

the negative visitor influence on the community. In such cases the host

community will imitate the behaviour and lifestyles of the tourists. When the host

176

community fails to preserve its culture, it is counter to organic growth and

development management of the region. Hence the cultural impact of tourism is

also was included in the study.

Table 5. 18 Contribution to cultural development

Statistics Responses Frequency % Minimum 2.75 Significantly Improved 11 2

Maximum 4.92 Somewhat Improved 315 59

Mean 3.67 No Difference 190 36

Std. D .287 Worsen 14 3

Total 530 100

Residents are generally positive about the influence of tourism on their culture.

Majority of the people said that tourism positively affects their culture. 2% have

said that there is significant improvement in the cultural expressions and 59%

people agree that there is moderate positive influence on culture. Only an

insignificant minority of respondents expressed their negative perception.

We can also see that the composite mean value also is high with 3.67 and a small

standard deviation of .278. Even the composite minimum score too indicate

positive contribution of tourism. From the development management perspective

culture has a significant role in determining the organic growth of a region. In

Kumbalangi tourism is perceived by residents as something that contribute to the

organic growth and development of their cultural expressions. The focus of

residents in preserving their traditions together with the organic growth of their

177

culture gives abundant opportunity for the development management of

Kumbalangi village.

5.8.1 Comparative Contribution towards Cultural Development

The questionnaire contains twelve factors under cultural development. Culture is

a generic term that explains the fundamental social fabric of a region and is

inclusive of large number of factors. The twelve factors in this study are selected

after the focus group interactions and personal observations in the village under

study.

Table 5. 19 Relative contribution towards culture

Min Max Mean SD

Attitude towards work 3 5 4 0.383

Relationship between generations 2 5 3.94 0.512

Maintenance of moral uprightness 2 5 3.92 0.439

Sexual morality 2 5 3.87 0.447

Preservation of the culture 2 5 3.86 0.513

Politeness and good manners 2 5 3.85 0.468

Conservation of heritage buildings 2 5 3.73 0.646

Tolerance towards different cultures 1 5 3.68 0.756

Religiosity 2 5 3.59 0.56

Celebration of religious festivals 1 5 3.5 0.587

Honesty 1 5 2.23 1.072

Relationship between neighbours 1 5 2.22 1.072

178

Figure 5. 4. Relative contribution towards culture

The table and graph above communicates clearly that tourism is helpful in the

development of culture of Kumbalangi. The respondents are negative about their

perceptions only regarding two factors, namely, honesty and relationship with

neighbours. One of the very good impacts of tourism is the changing positive

outlook towards tourism. Tourism has given opportunity for employment for

many residents, especially the women. Most probably this has also resulted in the

improvement of sexual morality in the society.

The mean value for relationship between neighbours indicates negative perception

of residents. This is probably because of economic reasons. Tourism has resulted

in creating two classes of residents – the beneficiaries of tourism and others. Not

all the residents are able to get employment or economic benefit out of tourism.

Some of the residents have benefited from tourism while many others are just

2 2.5 3 3.5 4 4.5 5

Attitude to work

Relationship between generations

Moral uprightness

Sexual morality

Preservation of the culture

Politeness and good manners

Conservation of heritage

Tolerance to other cultures

Religiosity

Religious festivals

Honesty

Relationship between neighbours

4

3.94

3.92

3.87

3.86

3.85

3.73

3.68

3.59

3.5

2.23

2.22

179

spectators of tourism. Those who do not reap any economic or social benefit out

of tourism may turn antagonistic it in the long run. Therefore some institutional

mechanisms should be executed to ensure the flow of tourism benefits to the

general public also through some form of taxation.

The data also indicate that there is growing dishonesty among people due to

tourism. In general people of Kerala understate their economic gains therefore in

the case of gains from tourism too. Tourism development has brought in increased

interactions between residents. However the relationship between them

deteriorated. Therefore it is quite likely that those beneficiaries of tourism do not

share accurate account of monetary gains. This is probably why the respondents

said that there is growing dishonesty among people due to tourism.

One of the significant achievements of tourism is the positive change in the

attitude towards work. This has the highest mean with the lowest standard

deviation. The homestays and the increased job opportunities for women in the

tourism field have helped in the development of constructive attitudes towards

tourism related jobs.

5.9 Crime and Tourism

Increase of crime in a locality retards the development management of the region.

Very often in connection with tourism there are increased crimes and violence3.

Therefore the influence of tourism on crime is examined in this research. It

examines six types of crimes. The decision to study six types of crimes was made

based on the focus group interactions with relevant resident groups. The

following table demonstrate, the perception of people regarding crime rates. The

180

perception regarding the growth or decrease of different crimes are summarised

below.

Table 5. 20 Growth of Tourism and Crimes

Statistics Responses Frequency %

Minimum 1.33 Increased 26 4.9

Maximum 4.67 No Change 263 49.6

Mean 2.75 Decreased 233 44

Std. D .676 Significantly

Decreased

8 1.5

Total 530 100

From the table above it is very difficult to conclude the impact of tourism on

crime because the responses of residents regarding crime are almost evenly

divided. When 44% of the respondents perceive that there is decrease in crime,

another 50% perceive that there is no difference. Yet another 5% respondents say

that there is increase. The composite mean value also is low and has a wide range

of 3.34. The standard deviation is also high. All these figures point to the fact that

many respondents believe that there is increase of crime in the village due to

tourism. However, there are also many respondents who perceive reduction of

crimes due to tourism. Globally, one of the most important forms of crime in

connection with tourism is drug abuse. Chester Nelson Mitchel wrote that tourism

“…would permit creation of tourist Mecca‟s catering to all drug tastes and

appetites in a reasonably safe, understanding atmosphere”.4 Therefore further

analysis was done to understand the growth of different forms of crimes including

drug abuse and alcoholism.

181

5.9.1 Perception on Reduction of Crimes

The following table gives the perception of residents towards different forms of

crimes after the introduction of tourism in the village. The residents were asked to

respond from significantly increased (=1) to significantly decreased (=5).

Therefore higher values in the table and graph indicate decrease in crime and

lower values indicate increase in crime rate.

Table 5. 21 Perception on reduction of crimes

Min Max Mean SD

Vandalism 1 5 3.90 .950

Drug abuse 3 5 3.45 .532

Alcoholism 3 5 3.26 .487

Gambling 1 5 2.52 1.128

Individual crime 1 5 2.31 1.047

Organised crime 1 5 2.13 .996

Figure 5. 5. Perception on different types of crimes

From the data presented above we see that tourism influences differently on

different forms crimes. From the mean values we understand that there is increase

in both organised and individual crimes, while other forms of crimes are lower.

2.00 2.50 3.00 3.50 4.00 4.50 5.00

Vandalism

Drug abuse

Alcoholism

Gambling

Individual crime

Organised crime

182

Kumbalangi is a village in the suburbs of fort Kochi. In Fort Kochi which is very

near to Kumbalangi village there are many criminal groups that recruit youngsters

for organized crimes. Many unemployed youth are tempted to join these groups

for money. This could be the reason why respondents perceived increased

individual and organised crimes. However, the residents perceive that the tourism

development has significantly brought down the use of alcohol and drug abuse.

5.10 Ecological Preservation and Tourism

Very often tourism is said to be a smokeless industry and therefore non-polluting.

But this is not fully true. Unless tourism is planned and implemented, it can be

detrimental to the preservation of ecology and environment of the destination.

Preservation of environment and ecology is important to the village life in

Kumbalangi. Development management also aims at preserving the quality of

ecology and environment. Hence the impact of tourism on ecology and

environment is examined in this study.

Table 5. 22 Preservation of ecology and environment

Statistics Response Frequency %

Minimum 2.29 Significantly

improved

12 2.3

Maximum 5 Somewhat

Improved

300 56.6

Mean 3.39 No Difference 87 16.4

Std. D .392 Worsen 131 24.7

Total 530 100

From the above table it is clear that almost 60% of the population is of the opinion

that tourism has contributed positively to the preservation of ecology and

183

environment. Only 25% people expressed negative views on protection of

ecology and environment. The composite mean value is 3.39 and the standard

deviation is .392. The mean value indicate that the overall perception of

respondents is positive regarding the preservation of ecology and environment. As

part of the tourism project the residents were given special training on

preservation of ecology and environment. The responses show that the training

has constructively contributed to the protection of environment.

At present tourism in Kumbalangi is its infancy. There are only few tourists

visiting the island. When the tourism in the region grows, there could be increased

threat to the ecology and environment of the place. Therefore adequate pro-active

steps must be implemented to prevent the possible damages to environment.

5.10.1 Comparative Contribution to Ecology and Environment

The influence of tourism on ecology and environment was studied under six

variables. In order to assess the relative contribution of each of the factors the

mean values, minimum, and maximum values were calculated. The results are

presented below.

Table 5. 24 Relative contributions to ecology and environment

Min Max Mean S D

Preservation of ecology and

environment

2 5 3.91 .411

Domestic waste management 2 5 3.91 .411

Prawns 1 5 3.90 .457

Public waste management 2 5 3.87 .415

Agriculture 1 5 3.87 .434

Fishes 1 5 3.13 .830

Lobster 1 5 2.11 .885

184

Figure 5. 6. Relative contributions to ecology and environment

From the graph and table it is clear that people are generally happy with the

preservation of ecology and environment of the Village. In all the different

aspects- except growing of lobster- the mean values are higher than 3. When we

look at the responses, we see that no one has given lowest value for waste

management and environmental protection efforts. The people are not very happy

with the situations in farming. The villagers undertake three types of farming,

namely fish farming, prawn farming and agriculture farming. All these three has

lowest mean values, lowest minimum values and highest standard deviations.

According to the response of the people now there is deterioration of quality and

extend of farming.

As a part of the UNDP tourism project all the houses were provided with biogas

plants for domestic waste management. Public waste bins were also provided in

many places in the Panchayath as a part of the scheme. Moreover there were

programmes to educate and train public regarding the need for preservation of

environment for healthy living. The use of plastic is considerably decreasing. In

3.91

3.91

3.90

3.87

3.87

3.13

2.11

2.00 2.50 3.00 3.50 4.00 4.50 5.00

Preservation of ecology and…

Domestic waste management

Prawns

Public waste management

Agriculture

Fishes

Lobster

185

the island there is a general practice of erecting small fencing walls around each

one‟s property. Traditionally this was done using only plastic. Due to consistent

education and follow up, people have started using biodegradable materials for

fencing. As a part of tourism project many trees were also planted on both sides

of many roads. Signage boards were installed in many places in the Panchayath

with a view to educating the public regarding the importance of maintaining the

unique environment of Kumbalangi. People generally are aware of the need for

maintaining a clean environment to promote tourism in the region and are willing

to cooperate with the local authorities.

5.11 Residents’ Psychological Engagement in Tourism Development

As already stated in the methodology chapter the Civic Voluntarism Model

suggests that there is direct relationship between residents‟ psychological

engagement and their participation. Four questions were asked to draw

information regarding residents‟ psychological engagement towards the

implementation of the tourism project. Their responses were collected on a five

point scale from strongly agree (=5) to strongly disagree (=1). The summery

results are presented below.

Table 5. 25 Psychological engagement with tourism

Statistics Responses Frequency %

Minimum 1.75 Disagree 4 .8

Maximum 4.25 No Opinion 106 20.0

Mean 2.93 Agree 411 77.5

Std. D .404 Strongly Agree 9 1.7

Total 530 100.0

186

The cumulative percentage reveals that almost 80 % of the residents have positive

outlook towards tourism. Only very insignificant number of respondents has

given total negative disposition towards tourism development. However, when

look into the composite mean value it is 2.93 which is not a high score. The mean

value is brought down by the 20% of the respondents who did not give their

opinion. This group of respondents are probably closely observing the

development of tourism. To ensure sustainable development of tourism in

Kumbalangi it is important to productively influence them. In order to better

understand the reason for low composite mean a detailed analysis each factor is

done below.

5.11.1 Psychological Engagement with Tourism

Residents‟ outlook towards the tourism project was analysed using four questions.

Questions were asked to know their attitude to tourism related decision making

process and the general impact of tourism in the region.

Table 5. 26 Outlook towards tourism development

Mean

Mode S D

Tourism decision making is always democratic 2.70 2 .972

Tourism is favourable to the culture of Kumbalangi 3.66 4 .996

Tourism is advantageous to the poor 3.65 4 .714

Willing to receive tourists at home if available 3.52 4 .691

187

Figure 5. 7. Psychological engagement with tourism development

From the table and graph it is clear that residents in general have positive outlook

towards tourism development in the village. They have very strong positive

opinion regarding the general outcome of the project. The mode of all the

questions except the one regarding style of decision making is four out of five.

This means that large number of respondents have given the rating four out five.

The median also is very near to four. The standard deviation is also low. This

shows that majority of the respondents have favourable disposition to the effect of

tourism. However, the residents‟ outlook towards the decision making process is

not very positive.

Development management always stress democratic decision making in

developmental projects. Tourism project implemented by Government of India in

Kumbalangi visualises democratic decision making in all its details. However, the

response of residents does not give a colourful picture regarding decision making

process. Therefore beyond the wishful thinking and policy making proper

2.7

3.66

3.65

3.52

0.5 1 1.5 2 2.5 3 3.5 4

Tourism decision making is alwaysdemocratic

Tourism is favourable to the culture ofKumbalangi

Tourism is advantageous to the poor

willing to receive tourists at home ifavailable

188

machineries must be set up to ensure participation of residents in the planning and

implementation of developmental projects.

5.11.2 Correlation Analysis: Psychological Engagement with Tourism

Analysis was done to find out the existing correlation between the four factors

under study.

Table 5. 27 Correlation Analysis: Attitude factors

1 2 3 4

1. Decision making –Consultation 1

2. Tourism destroys culture -.130**

1

3. Tourism is for the rich -.246**

.098* 1

4. Willing to receive tourists at home -.276**

.130**

.622**

1

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

From the table it is clear that there exist very strong correlation between four

factors under study. It should also be noted that the perception of residents about

the tourism decision making process is negatively affecting their psychological

engagement. In other words, lower scores to decision making process results in

higher scores to other factors. This means that the respondents who are positively

disposed to tourism are unhappy with the tourism decision making process. The

respondents are really looking for more involvement and participation in tourism

decision making.

189

5.11.3 Regression Analysis: Psychological Engagement with Tourism

Regression analysis is further done to confirm the significance of negative

correlation found between attitude towards tourism decision making process and

other factors influencing the attitude.

Table 5. 28 Regression Analysis: Psychological engagement factors

Dependent Variable R2 β (Beta) ϝ ƥ

Tourism Decisions Democratic .095 -.092 17.683 0.000

Perception regarding tourism decision making was the dependent variable and

other factors of psychological engagement - which were already mentioned above

- were the independent variables. Regression analysis too confirms that there exist

negative relationship between the perception to tourism decision making process

and other psychological engagement factors. The R2 value speaks about the

strength of the model. 9.5% of the outlook towards tourism decision making

process is determined by other psychological engagement factors. The beta value

signifies the direction and proportion of the influence. The negative beta value

proves the assumption that those who are positively disposed to tourism have

negative disposition towards the process of decision making. The F value and

significance confirm that the relationship is significant at 0.05 level and not just

accidental.

5.12. Resident Participation in Kumbalangi Tourism Project

Participation of the residents is an important component of development

management. In this research two levels of participation of the people were

studied. At the first level the participation of the people in the planning process

190

and at the second level their participation in the implementation of the project

were studied.

5.12.1 Resident Participation in Planning

Resident participation in planning was enquired in five different areas. They

included both public and private projects. Each factor under study is analysed

later. The table below gives a summary perspective regarding participation in

planning.

Table 5. 29 Resident participation in tourism planning

Frequency Percentage

Rarely 448 84.5

Occasionally 42 7.9

Usually 31 5.8

Always 9 1.7

Total 530 100.0

From the table it is very evident that practically everyone got involved with

planning session in some form or at some level. However, the vast majority of the

general public was not actively involved in the planning and decision making

process regarding tourism. It is evident from the figures above that only less than

20% people only ordinarily participated in the tourism planning. Kumbalangi is

village tourism model and not a mass tourism destination. Therefore long term

success and sustainability of tourism in the region is certainly dependent on public

participation. It is noteworthy that none of the respondents said that they never

participated in the project planning.

191

The Civic Voluntarism (CV) Model was also utilised to analyse the resident

participation in planning tourism projects. The correlation between CV Model

factors and participation variables were examined. The following table gives the

details.

Table 5. 30 Correlation Analysis – CV Model

CVM Factors Variables Studied

Correlation

Coefficients

(participation

planning)

Belongingness to recruiting

networks

Duration of residence .090*

Psychological engagement Psychological engagement .053

Resources

Income of the family .127**

Educational status -.024

Occupation .039

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

As per the theory resident participation is directly related to CVM factors. The

table above suggests that belongingness and income of the family are strongly

correlated to level of participation in planning. However, correlation coefficients

of psychological engagement, educational status and occupation do not suggest

strong correlation. This means that in Kumbalangi tourism project, residents with

higher income participated in the planning stage more significantly than lower

income group. Similarly those with longer residence participated in the planning

stage more than those with lower duration of residence.

192

5.12.2 Resident Participation in Implementation

Participation of residents in the implementation of the project was also analysed.

The purpose was to understand participation of people at different levels and also

to see how participation at different levels affects their perception

Table 5. 31 Resident participation in implementation

The table above tell us that more than 10% of the residents more or less

participated in the implementation. However, 80% of residents participated only

rarely in the implementation of the project. It is notable that no respondents

reported that they never participated in the implementation.

The projects listed in the questionnaire included both public and private projects.

The public projects were road construction and maintenance, Park construction

and beautification, setting up of Kalagram in the Panchayath. Of these the

construction of Kalagram is still pending. Major roads in the Panchayath were

improved with the construction of drainages on both sides, putting waste baskets

in junctions, planting of different varieties of trees by the side etc. A small park

was constructed at the entrance of the village by the sides of the bridge connecting

the village to Kochi, undoubtedly an ideal location for the village.

Frequency Percentage

Rarely 463 87.4

Occasionally 31 5.8

Usually 15 2.8

Always 21 4.0

Total 530 100.0

193

Participation in implementation also was analysed using the CV Model.

Correlation analysis between CVM factors and participation in implementation is

given below.

Table 5. 32 Correlation Analysis- Participation in Implementation

CVM Factors Variables Studied

Correlation

Coefficients

(participation

Implementation)

Belongingness to recruiting

networks

Duration of residence .006

Psychological engagement Psychological engagement .090*

Resources

Income of the family .- 213**

Educational status -.371**

Occupation .251**

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

From the table above it is clear that there is significant correlation between CVM

factors and participation in implementation. However, the correlation coefficient

of belongingness to recruiting networks is not found significant. It is also

interesting to note that the contribution to implementing the project is inversely

related to income and educational status of the residents. The data is further

analysed below to examine the relation between participation in planning and

implementation.

5.12.3 Comparison of Participation between Planning and Implementation

A detailed analysis of the data was conducted to evaluate level of participation in

each project. The table below gives a comparison of mean values and standard

deviations between participation in planning and implementation.

194

Table 5. 33 Comparison of participation between planning and implementation

Mean SD

Participation in

Planning

Construction of the Park 1.25 .69

Implementation of Home-stays 1.27 .72

Road construction and maintenance 1.39 .88

Construction of Kalagram (Art School) 1.27 .74

Setting up water related recreations 1.22 .69

Participation in

Implementation

Construction of the Park 1.22 .78

Implementation of Home- stays 1.40 1.02

Road construction and maintenance 1.27 .85

Construction of Kalagram (Art School) 1.23 .76

Setting up water related recreations 3.53 .99

Participation in implementation has higher mean in two cases – implementation of

homestays and implementation of water related recreation avenues. The

participation in the implementation of homestays for tourists to stay is high

because, they are independently done by individual family members. At present

there are 16 registered homestays. Naturally those who plan to establish

homestays will work with dedication for successful setting up of the house.

Participation in the water related recreation is high probably because the residents

knew how to organise water related recreation avenues. Again arranging small

boats or kayak is the task of one person or one family. The other three projects in

the list can be implemented only through public participation.

5.12.4 Hypothesis Testing: Relationship between Planning and Implementation

The proposed hypothesis is:

Participation in planning directly influences participation in implementation.

195

The hypothesis is in agreement with the Leader- participation model proposed by

Vroom and Yetton. In order test the hypothesis at first correlation between the

variables were identified. The correlation coefficient between the variables is

0.729, which is significant at 0.05 level. Therefore in order to ascertain the

validity of the correlation coefficient, regression analysis was also conducted. The

prediction variable is participation in planning. The relevant values are reported in

the table below.

Dependent Variables R2 β (Beta) Ϝ Ƥ(sig)

Participation in Implementation .531 .729 537.296 0.000

The R2 value says that 53% of participation in implementation is related to

participation in planning. The beta value speaks about the proportion of change

that takes place to participation in implementation with a unit change in

participation in planning. The beta value predicts that a unit change in

participation in planning will directly (because the beta value is positive) affect

.729 changes in the participation in implementation. The F and P values state the

significance of the R2

values. They say that the influence of participation in

planning on participation in implementation is significant and not accidental.

Based on the findings stated above, the study accepts the hypothesis that

participation in planning directly influences participation in implementation and

rejects the null hypothesis. The results of the study confirm the findings of the

Leader-participation model. When people are given a role in decision making

there is greater participation in the implementation.

196

5.13 Hypothesis Testing: Impact of Participation on Perception

The research attempted to explore the impacts of the level of participation on

residents‟ perceptions on the tourism project. The proposed hypothesis was:

Resident participation in planning and implementation directly influences the

resident perception on the impact of tourism.

For this initially correlation between participation and different perception

variables were analysed. After doing the correlation analysis stepwise multiple

regressions analysis was also done to see the impact of participation -both

planning and implementation- on perception.

5.13.1 Correlation Analysis: Participation and Perception

In order to ascertain the relationship between participation and perception at first

two tailed Pearson correlation analysis was done. The correlation analysis showed

that there is stronger correlation between participation in implementation and

perceptions than between participation in planning and perceptions. Participation

in implementation certainly gives more involvement than participation in

planning. Therefore it can be rightly concluded that the intensity of participation

influences the perception. There is an exception observed in the case of

perception on crime. The details are given in the table below.

197

Table 5. 34 Correlation between participation and perception factors

Correlations

1 2 3 4 5 6 7 8 9

1. Planning 1

2. Implementation .708**

1

3. Ecology &Environment .114* .121

** 1

4. Culture .334**

.427**

.432**

1

5. Infrastructure .132**

.153**

.340**

.468**

1

6. Income .120**

.185**

.412**

.479**

.635**

1

7. Quality of Life .126**

.129**

.433**

.512**

.473**

.492**

1

8. Knowledge .122**

.248**

.598**

.368**

.324**

.324**

.236**

1

9. Crime .336**

.300**

.290**

.453**

.049 .081 .253**

.143**

1

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

From the above table it is clear that all the correlation coefficient values except

correlation between ecology and planning are significant at 0.01. The values

indicate significant positive correlation between predictive variables and

dependent variables. Form values given in the table it is clear that there exist

strong correlation between independent variables too.

5.13.2 Regression Analysis: Relationship between Participation and Implementation

In order to establish the influence of predictive variables – participation in

planning and implementation - on independent variables a series of stepwise

multiple regression analyses were also conducted. The multiple regression

formula used is

Yn = a + B1x1 +B2x2 +.... Bnxn + ε

198

The X1 and X2 are the predictive variables in the study. The multiple regression

analysis was performed also with the intention to test the hypothetical model

proposed in the research methodology chapter. As the first step the descriptive are

given below.

Table 5. 35 Descriptive statistics of variables

Mean

Std.

Deviation

Participation in Planning 1.2698 .63619

Participation in Implementation 1.7355 .66409

Ecological & Environmental Effect 3.5330 .30381

Culture of the Village 3.5324 .29325

Infrastructure 3.7271 .33291

Local Income 3.5811 .25924

Quality of Life of Residents 3.3065 .23476

Knowledge of Residents 3.1194 .55571

Crime 2.9275 .54473

From the stepwise multiple regression analysis R2,

β, F-values and P-values are

reported below in tabular form. R2 gives the significance of the model proposed.

β explains the relationship between Y variable and X variable. In this case the β

explains the relationship between participation (prediction variable = X ) and

perception (dependent variable = Y). F and P explain the same thing. They

explain the significance of β values.

199

Table 5. 36 Regression Analysis Values

Dependent Variables R2 β (Beta) Ϝ Ƥ(sig)

Ecological & Environmental Effect .014 .119 7.550 0.006

Culture of the Village .193 .439 125.832 0.000

Infrastructure .038 .196 21.123 0.000

Local Income .051 .227 28.584 0.000

Quality of Life of Residents .031 .176 16.952 0.000

Knowledge of Residents .044 .214 25.186 0.000

Crime .121 .350 73.362 0.000

Stepwise multiple regression method is considered the most parsimonious model.

Each predictive variable is entered in a sequence and the value is accessed. The

advantage of stepwise method is that the relative value of each variable in the

model can be evaluated. The insignificant variables are removed from the model.

Thus stepwise multiple regression analysis helps to ensure the smallest possible

set of predictor variables for a model. The values and significance of the removed

variables are also generated by SPSS for the judgement and evaluation of the

researcher. In this study when analysis was done in all the multiple regression

analysis participation in planning was removed from the model. Moreover in all

the cases participation in planning was not found significant in the model at 0.05

200

level (P>0.05). Therefore the values given above give the significance of

participation in implementation in the model.

While doing the analysis multicollinearity of predictive variables were also

analysed. Tolerance is 1- R2. It is generally accepted that a tolerance of less than

0.20 or 0.10 and/or a VIF of 5 or 10 and above indicates a multicollinearity

problem5. In the analysis the tolerance was close to one and hence quite within

acceptable limits. Again this study utilises the R2 because it gives more accurate

measure of relationship between predictor variables and criterion variables than R

values. The adjusted R2 was not considered because the study utilised only two

predictive variables. Adjusted R2 is often used when there are many predictive

variables. Again in the analysis the difference between R2 and adjusted R

2 was

very low.

The value given in the table must be evaluated together with the correlation table.

According to correlation analysis there was strong correlation between predictive

variables and criterion variables. But the multiple regression analysis table gives

more important and clearer insights regarding the proposed model. It is very

obvious that resident participation in implementation significantly influences their

perceptions about the impact of the project. Whereas a peripheral participation in

the planning process is not able to significantly influence the participant

perception. The R2 values are explaining the correlation between the prediction

variables and criterion variable. The R2 values are not very high. The highest R

2

value is observed in the case of perception regarding the influence on culture of

the place. 19% of the perception on preservation on culture and 12% of perception

201

on crime is influenced by participation in the implementation of the project. The

finding is very important for the practitioners.

The beta values measure the strength of influence of predictive variable on

criterion variable. It is referring to the slope of Y. Higher the beta value greater

the influence of predictive variable on dependent variable. From the table above

we see that change in the participation in implementation will bring in significant

changes in the perceptions of people. The highest change will be regarding the

perceptions related to cultural impacts and crime impacts of tourism.

F and P values are testing the significance of R values or R2 values. In other

words these are values that test the significance of the whole regression model. In

our case we could see that F and P values are very significant in all the models.

Since F and P values are significant at 0.05 level, in all the cases tested above it

can be rightly assumed that there exists linier relationship between predictive

variables and criterion variables. In other words the alternate hypothesis is

accepted and null hypothesis is rejected.

5.13.3 Relationship between Participation and Perception: Conceptual Model

The findings based on correlation and multiple regression analyses it is very clear

that there exists strong relationship between participation in implementation and

perception. Though according to the values of correlation analysis, participation

in planning also correlates significantly with the perceptions of residents, the

regression analysis do not suggest any significant relationship between the two.

The hypotheses proposed to explain the relationship between participation and

perception was: Resident participation in planning and implementation directly

influences the resident perception on the impact of tourism. On the basis of

202

findings of the study the first hypothesis is modified. Resident participation in

implementation directly influences the resident perception on the impact of

tourism. Resident participation in planning process is excluded from the proposed

model. The proposed new model is give below.

Figure 5. 8. Relationship between participation and perception

The above alternate model is proposed to explain the relationship between

participation and resident perception on the impact of tourism.

5.14 Influence of Demographic Variables on Perception

Demographic variables are often found significantly affecting the perception of

people. In this study the influence of gender, age, income, occupation, and level

of education on perception are analysed in detail.

203

5.14. 1 Influence of Gender on Perception

Independent Sample T-test was used to analyse the difference in responses

between male and female. Perception differences among both genders in the case

of nine factors are analysed. As the first step mean values of the factors were

calculated.

Table 5. 37 Genderwise Group Statistics

Variables Sex N Mean S D

Planning Male 219 1.2767 .59905

Female 277 1.2643 .70159

Implementation Male 223 1.7552 .74384

Female 264 1.7189 .64762

Infrastructure Male 245 3.7071 .34226

Female 285 3.7443 .32429

Local Income Male 245 3.5867 .26347

Female 285 3.5763 .25591

Quality of Life Male 245 3.2985 .23941

Female 285 3.3134 .23089

Ecology &

Environment

Male 232 3.5283 .32572

Female 259 3.5372 .30696

Culture Male 231 3.5400 .33503

Female 253 3.5254 .27924

Knowledge Male 237 3.1153 .63321

Female 260 3.1231 .51513

Crime Male 232 2.9957 .52862

Female 276 2.8702 .57345

204

From the above table we observe that there are differences in the mean values

between male and female. Therefore t-test was conducted to find out the

significance in the differences between mean values. The table below gives t-

value, values for degree of freedom and significance.

Table 5. 38 T-test results: Gender and perception

t-test for Equality of Means

T df

Sig.

(2-tailed)

Planning .209 494 .834

Implementation .574 485 .566

Infrastructure -1.284 528 .200

Local Income .462 528 .644

Quality of Life -.731 528 .465

Ecology & Environment -.312 489 .755

Culture .525 482 .600

Knowledge -.150 495 .881

Crime 2.546 506 .011

From the table above it is clear that there exists no perception difference between

male and female except regarding crime. T-test reveals that the difference in the

mean values in the case of crime is significant at 0.05 level. From the mean given

in table it is clear that females are more concerned about the increase of crime due

to tourism. (In the questionnaire significant reduction in crime = 5 and significant

increase in crime = 1)

205

5.14.2 Influence of Age on Perception

Since there were more than two factors in the age groups, ANOVA test is done.

After doing ANOVA the relevant values – sum of squares, degree of freedom,

mean square, f-value and significance- are presented in tabular format.

Table 5. 39 ANOVA results: Age and perception on DMV

Variables Sum of

Squares df

Mean

Square F Sig.

Planning 1.273 4 .318 .783 .537

Implementation 4.781 4 1.195 2.548 .039

Infrastructure 1.434 4 .359 3.292 .011

Local Income .953 4 .238 3.615 .006

Quality of Life .825 4 .206 3.823 .004

Ecology & Environment 1.881 4 .470 4.868 .001

Culture 1.610 4 .403 4.394 .002

Knowledge 5.747 4 1.437 4.485 .001

Crime 4.834 4 1.209 3.996 .003

The results of ANOVA show that the differences in the mean values between

different age groups are significant at 0.05 level except in the case of participation

in planning. Therefore further analysis was done to find out the differing age

groups for each variable using Tukey‟s B and Scheffe tests. These tests further

reaffirmed that there exist significant differences among different age groups

regarding perception on local income and impact on ecology & environment. The

results of both tests showed the same differences among groups. The mean values

are given in groups in the tables below.

206

Table 5. 40 Tukey B and Scheffe results for age and local income

Local Income

Age N

Subset for alpha =

0.05

1 2

Tukey B

&

Scheffe a

Below 22 29 3.4481

51- 65 141 3.5481 3.5481

Above 65 61 3.5906

36-50 209 3.5975

22-35 90 3.6310

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 67.692.

From the above table it is clear that those below twenty years of age have the least

mean value. Another group that goes with this youngest group is those between

fifty one and sixty five. In the case both these groups tourism might bring

minimum economic benefits. Most of the respondents between 18 and 22 are in

academics and they have little for tourism. Many of those between 51 and 65 are

probably not being employed by anyone. Tourism also is not offering them

significant employment opportunities. However, it should be noted that mean

values are still more than three out of five. That means in general people agree

that tourism is able to generate income for the locality.

207

Table 5. 41 Tukey B and Scheffe results for age and ecology & environment

Ecology & Environment

Age N

Subset for alpha = 0.05

1 2

Tukey B

&

Scheffea

Below 22 29 3.4236

51- 65 134 3.4840

36-50 197 3.5279 3.5279

Above 65 58 3.5591 3.5591

22-35 73 3.6595

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 64.134.

It is interesting to note that respondents below 22 years and between 55 and 65

have similarity of perceptions regarding ecology and environment. Those in the

said age groups are most conservative about the income generation through

tourism. In the correlation analysis conducted above, strong direct relationship

was observed between income and ecology & environment. Therefore most

probably the opinions of those age groups are influenced by the income factor.

Regarding tourism influence on ecology & environment the respondents in

general are positive. The lowest mean value is 3.4 out of five.

5.14.3 Influence of Income on Perception

To find out the influence of income of the people on their responses, ANOVA

was conducted. The table is given below.

208

Table 5. 42 ANOVA results: Income and perception on DMV

Sum of

Squares Df

Mean

Square F Sig.

Planning 4.483 5 .897 2.332 .041

Implementation 15.884 5 3.177 7.278 .000

Infrastructure 1.317 5 .263 2.222 .051

Local Income .916 5 .183 2.544 .027

Quality of Life 1.193 5 .239 4.326 .001

Ecology &

Environment

.824 5 .165 1.640 .148

Culture .993 5 .199 2.128 .061

Knowledge 4.162 5 .832 2.570 .026

Crime 2.920 5 .584 2.014 .075

The ANOVA results show that there are significant differences in the mean values

between different income groups regarding participation in planning, and

implementation, quality of life, and knowledge. The F values are significant at

0.05 level in the case of these four variables. However, further analysis using

Tukey B and Scheffe methods revealed that the mean differences among different

income group are significant only in the case of participation in implementation.

The test results are given below for participation implementation.

209

Table 5. 43 Tukey B and Scheffe results: Income and implementation

Implementation

Income of the

family N

Subset for alpha =

0.05

1 2

Tukey Ba

Above 120000 8 2.1250

2000 - 4000 160 2.1563

Below 2000 226 2.1814

4001- 6000 68 2.3529

6001-8000 10 2.9000

8001-12000 15 3.0000

Scheffea

Above 120000 8 2.1250

2000 - 4000 160 2.1563

Below 2000 226 2.1814

4001- 6000 68 2.3529 2.3529

6001-8000 10 2.9000

8001-12000 15 3.0000

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 18.925.

From the mean values it is clear that higher income group participated more in the

implementation stage. Participation from the higher income group in the

implementation is found more, probably because of their involvement in setting

up homestays and water related recreation avenues. The advantages of the rich are

evident in both these cases. There are at present sixteen registered homestays in

the island. The rich has the possibilities to spend money for setting up water

related recreation avenues too.

210

5.14.4 Influence of Education on Perception

Usually education is one of the important factors significantly influencing the

perception of people. Therefore analysis was done to see how significantly

education influenced the perception of people regarding tourism impacts.

ANOVA was used in this study to test the influence of education on perception.

Table 5. 44 ANOVA results: Education and perception on DMV

Sum of

Squares df

Mean

Square F Sig.

Planning 2.828 3 .943 2.319 .075

Implementation 6.646 3 2.215 4.721 .003

Infrastructure 1.936 3 .645 5.918 .001

Local Income 1.035 3 .345 5.251 .001

Quality of Life .532 3 .177 3.231 .022

Ecology & Environment 1.179 3 .393 4.011 .008

Culture 1.776 3 .592 6.431 .000

Knowledge 7.963 3 2.654 8.550 .000

Crime 3.885 3 1.295 4.321 .005

The ANOVA values above say that education significantly differentiates the

perception of people regarding all variables except participation in planning (P>

0.05). Therefore Scheffe and Tukey B tests were conducted to find out the

differing groups in each case. When this analysis was done no group differences

were noticed in the case of participation in planning, infrastructure, local income,

quality of life, and crime. However, significant group differences were observed

in the case of participation in implementation, ecology & environment, and

knowledge. Relevant tables are presented below.

211

Table 5. 45Tukey B and Scheffe results: Education and implementation

Implementation

Education N

Subset for alpha =

0.05

1 2

Tukey B

&

Scheffea

HSS 93 2.1075

10th

and Below 353 2.2153 2.2153

Bachelor Level 61 2.4754

Masters Level 17 2.5294

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 45.044.

The results of both Tukey B and Scheffe tests were the same. Those with higher

secondary level of education have lower level of participation in the

implementation of the tourism project. This is probably because majority of those

having HSS level of education are still studying. Therefore they have less time to

participate in the implementation of tourism related projects. On the other hand

majority of respondents in other groups have already completed their studies.

Therefore they would be available to take part in implementing tourism projects.

Table 5. 46 Tukey B and Scheffe results: Education and ecology & environment

Ecology & Environment

Education N

Subset for alpha =

0.05

1 2

Tukey B

&

Scheffea

Masters Level 14 3.4082

10th

and Below 329 3.5076 3.5076

Bachelor Level 59 3.5835 3.5835

HSS 83 3.6179

a. Uses Harmonic Mean Sample Size = 38.660.

212

The results of both Tukey B and Scheffe were the same. From the analysis it is

clear that those with Masters level education are not as positive as the other

groups in the case of tourism impacts on ecology and environment. It is

interesting note that close to them come the lowest educated group. Probably they

are not very positive because they are the people who work and live in the island

and have information from their direct personal experience like less fish or

prawns resources.

Difference was also found significant in the case of acquiring knowledge through

tourism. The average mean value for all groups is above three out of five. It

means that there is a general agreement about gaining of knowledge through

tourism. Respondents with lowest level of education had the lowest average

mean. Results of Tukey B and Scheffe tests were the same.

Table 5. 47 Tukey B and Scheffe results: Education and knowledge

Knowledge

Education N

Subset for alpha = 0.05

1 2

Tukey B

&

Scheffea

10th

and Below 342 3.0458

Masters Level 14 3.2143 3.2143

Some College 79 3.2152 3.2152

Bachelor Level 59 3.4181

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 38.476.

213

Those with lowest level of education have lowest mean value. Majority of the

respondents in this group had only very little formal education – mostly

elementary school level. Therefore their ability to absorb knowledge also will be

limited. However, even that group has an average mean value above three out of

five.

5.14.5 Influence of Occupation on Perception

Occupation of the people is another factor found significantly affecting the

perception of people. There were eight occupational categories in the

questionnaire. But they were regrouped into four for the convenience of analysis.

To understand the influence of occupation on perception ANOVA was used.

Table 5. 48 ANOVA results: Occupation and perception on DMV

Sum of

Squares df

Mean

Square F Sig.

Planning .546 3 .182 .451 .716

Implementation 3.039 3 1.013 2.190 .088

Infrastructure .861 3 .287 2.434 .064

Local Income .949 3 .316 4.454 .004

Quality of Life 2.145 3 .715 13.018 .000

Ecology & Environment .936 3 .312 3.187 .024

Culture 1.370 3 .457 4.840 .003

Knowledge 1.906 3 .635 1.945 .122

Crime 2.924 3 .975 3.236 .022

214

The ANOVA results show that there are significant differences in the perceptions

between people in different occupations. The mean differences are significant at

0.05 level, in the case of local income, quality of life, ecology & environment,

culture, and crime. However based on Tukey B and Scheffe tests differences in

perceptions are observed only in the case of local income and quality of life.

Table 5. 49 Tukey B and Scheffe results: Occupation and local income

Local Income

Occupation N

Subset for alpha =

0.05

1 2

Tukey B

&

Scheffea

Education 22 3.4206

Daily Wages 200 3.5606

Salaried 43 3.5656

Home

Making

214

3.6178

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 51.031.

The results of both Tukey B and Scheffe were the same. Those still attending

academic institutions are a different group as per both tests. The mean score is

lowest for those in the academics. Those in the education cannot give their

services to tourism and earn income from it. Probably that is the reason why they

have the lowest average mean value. However, it is to be noted that even in their

case the average mean value is above 3.4 out of five.

215

Table 5. 50 Tukey B and Scheffe results: Occupation and quality of life

Quality of Life

Occupation N

Subset for alpha = 0.05

1 2 3

Tukey Ba Education 22 3.1493

Daily Wages 200 3.2555

Salaried 43 3.2898 3.2898

Home Making 214 3.3772

Scheffea Education 22 3.1493

Daily Wages 200 3.2555 3.2555

Salaried 43 3.2898

Home Making 214 3.3772

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 51.031.

According to Tukey B based on their responses people could be divided into three

categories. Scheffe divides them into two groups. Lowest mean value regarding

the perception of quality of life is among those who attend the school. The highest

mean value is found in the case of home makers. In fact tourism has given jobs

for many unemployed women in the village. They run teashops, conduct food

fests, participate in the artistic performances for tourists etc. Therefore tourism

was able to enhance the quality of life of villagers, especially the women.

5.14. 6 Influence of Duration of Stay on Perception

In many research studies, the number of years of stay is found significantly

influencing the perception of residents towards tourism. In many rural regions, the

traditional settlers object tourism development, because of the fear of damaging

216

their culture and peaceful existence. In this research ANOVA was conducted to

evaluate the influence of number years stay on perception of people.

Table 5. 51ANOVA results: Duration stay and perception on DMV

Sum of

Squares df

Mean

Square F Sig.

Planning 3.122 3 1.041 2.584 .053

Implementation 2.500 3 .833 1.761 .154

Infrastructure 1.322 3 .441 4.037 .007

Local Income .505 3 .168 2.521 .057

Quality of Life .489 3 .163 2.987 .031

Ecology & Environment .161 3 .054 .537 .657

Culture .207 3 .069 .732 .533

Knowledge 3.801 3 1.267 3.915 .009

Crime 3.073 3 1.024 3.355 .019

From the table above it is clear that number of years of stay do not significantly

differentiate the perceptions of people. Only two differences are found significant

at 0.05 level – perceptions on infrastructure and quality of life.

Tukey B and Scheffe tests were further conducted to find out the groups with

significant differences in perception. The test results did not differentiate people

based on number of years of stay. In the case of infrastructure the difference

between mean values ranged between 3.66 and 3.82 and in the case of quality of

life it ranged from 3.2 to 3.3. Hence all of them were placed as one group. In

other words, in Kumbalangi, there are no perceptual differences between people

based on the number of years of stay in the village.

217

5.15 Rural Tourism Influence on Development Management

Tourism in Kumbalangi is a catalyst to the development of the region. The rural

tourism model helps the region to maintain its integrity while moving towards

development. The rural tourism model being experimented in Kumbalangi is

called endogenous tourism. “Endogenous tourism development is based mainly

on local and/ or national sources while exogenous is based primarily on foreign or

transnational capital.”6 Development management also focuses on integrated

development of the region and therefore socio-cultural and environmental aspects

of development are considered equally important to economic development. The

following table facilitates a comparison of the impact of different development

management variables used in this study. The table explains the relative influence

of tourism on different development management variables under study. All the

values are the result of grouping of all the factors under one variable.

Table 5. 52 Tourism impact on development

Minimum Maximum Mean

Std.

Deviation

Planning 1.00 5.00 1.27 .65768

Implementation 1.00 5.00 1.74 .69284

Crime 1.67 4.50 2.93 .55642

Knowledge 2.00 5.00 3.12 .57390

Quality of life 2.64 4.14 3.31 .23476

Culture 2.58 4.92 3.53 .30690

Ecology & Environment 2.57 4.71 3.53 .31567

Income 2.68 4.68 3.58 .25924

Infrastructure 2.83 4.94 3.73 .33291

218

Figure 5. 9. Relationship between participation and perception

The table and graph give us information regarding the impact of tourism on

different development management variables. Participation in planning has the

lowest mean value and infrastructure development has the highest mean value.

When we look at the table we also see that the standard deviation is also one of

the lowest for infrastructure. Participation in planning and implementation have

the highest standard deviations too. The lowest standard deviation is found for

quality of life. The mean value also is comparatively on the higher side. Tourism

development in Kumbalangi has resulted in creating additional income without

damages to ecology and environment. Tourism impact on culture also is

considered positive.

Resident participation is found very low both in the planning phase and

implementation phase. Based on the model proposed above, participation in

implementation has significant positive influence on perceptions of people.

1.27

1.74

2.93

3.12

3.31

3.53

3.53

3.58

3.73

1.00 1.50 2.00 2.50 3.00 3.50 4.00

Planning

Implementation

Crime

Knowledge

Quality of life

Culture

Ecology & Environment

Income

Infrastructure

219

Several studies have already proved the importance of positive residents‟

perception in the implementation of tourism projects. The attitude and perception

of the host community directly influences the experience of guests too.

5.16 Summary

There are two approaches in analysing and examining tourism impacts. One is the

scientific monitoring of the actual changes in the host area. It involves the

collection of historic data and compares it with the current data after the

implementation of tourism. The other is to evaluate what the residents perceive to

be the case7. The second approach tries to collect the perception of residents

regarding different aspects of tourism. This research follows the second approach

in collecting and analysing data.

Kumbalangi was the first endogenous tourism project India, to complete its

implementation. The Government of India communication clearly outlined the

purpose of the project. „Endogenous Tourism is a new approach in tourism that

aims at maximizing local control and benefits. It tries to maximise economic

benefits to the residents and enhance their quality of life with minimum cost to the

community. Therefore rural life experience itself is presented as the tourism

product.‟8 The study indicates that the broad objectives of the project are

successfully accomplished to certain level. The study has also found that

endogenous rural tourism model implemented in Kumbalangi is a successful

model of rural development management too.

However, the project implemented in Kumbalangi needs to enhance the

participation and involvement of residents. From the model presented in this

220

chapter it is clear that resident participation especially in the implementation of

the project significantly influences the generation of positive perception about the

project. Long term success of any development project is highly linked to the

participation of residents.

221

Endnotes and References

1 Pan Gs .P. (2002). Private sector tourism spending, Legislative Reference Bureau, State

capital, Honolulu, Hawai, Report # 5

2 Clark G. & Chabrel M. (2007). Measuring integrated rural tourism, Tourism

Geographies, 9 (4), p. 371-386

3 Ryan C. Crime, Violence, Terrorism and Tourism: An Accidental or Intrinsic

Relationship? Tourism and Recreation Studies Unit, Nottingham Business School, UK

4 Chester N. M. (1990). The Drug Solution-Regulating Drugs According to Principles of

Efficiency, Justice and Democracy, Carlton University Press, p 255

5 Garson D. (2010 Spring). Multiple Regression, Retrieved February 2010, from

http://faculty.chass.ncsu.edu/garson/PA765/regress.htm

6 Apostolopoulos, Y., & Sonmez, S.F. (1999), From farmers and shepherds to

shopkeepers and hoteliers: Constituency-differentiated experiences of endogenous

tourism in the Greek island of Zakynthos. International Journal of Tourism Research, 1,

p. 413-427

7 Lu C.J. & Var T. (1986). Resident attitudes towards tourism impacts in Hawaii. Annals

of Tourism Research, 13(2), p.17 -37

8 Endogenous Tourism for Rural Livelihoods. (2007). Government of India. Retrieved

August 25, 2009, from: http://data.undp.org.in/facts heets/hd-rl/jan08/ETP.pdf