chapter 4 data analysis -...

CHAPTER 4DATA ANALYSIS


4.1 Introduction

4.2 Data Presentation

Sr. Section Number Title of Section1 I Government and Tourism2 II Demographic Profile of Stakeholders3 III Tourist Descriptive Analysis4 IV Hoteliers Descriptive Analysis5 V Tour Operators Descriptive Analysis6 VI Comparative Analysis7 VII Selected Intellectuals Descriptive

Analysis8 VIII SWOT Analysis9 IX Analysis of Tourist Amenities10 X Exploration of New Destinations11 XI Hypotheses Testing12 XII Cluster Analysis

Data Analysis

Shivaji University, Kolhapur 137


4.1 Introduction:

The present chapter articulates presentation and analysis of the data. This is an effort

to suffice the objectives set for this research and to test the hypotheses.

For geared up situation the hypotheses and objectives of research are reproduced

here.

Following hypotheses have been set to test

1. Lack of promotion of tourism destinations hinders development of tourism sector

in Satara District.

2. Availability of infrastructural facilities and tourism development are correlated.

3. Government proposes planning to develop places of tourist interest but the gap

exists in planning and implementation, which leads to failure in attracting

tourists.

Present study purports following objectives

1. To analyze efforts of State Government towards development of tourism industry

in Satara District

2. To study the problems in existing tourism base in Satara District

3. To prepare SWOT matrix on the basis of infrastructural facilities and

environmental aspects prevailing for tourism in Satara District

4. To find out prospects for tourism and explore tourist destinations in Satara

District.

Data Analysis


4.2 Data Presentation:

Data is presented into 12 sections. Each section is narrating details of entire data, data

of all respondent viz. Government, Tourist, Hotelier, Tour Operator and NGOs/Social

Activist. These 12 sections are titled and presented in following manner.

Section I Government and Tourism

Section II Demographic Profile of Stakeholders

Section III Tourist Descriptive Analysis

Section IV Hoteliers Descriptive Analysis

Section V Tour Operators Descriptive Analysis

Section VI Comparative Analysis

Section VII Selected Intellectuals Descriptive Analysis

Section VIII SWOT Analysis

Section IX Analysis of Tourist Amenities

Section X Exploration of New Destinations

Section XI Hypotheses Testing

Section XII Cluster Analysis

Data Analysis


Section I

4.2.1 Government and Tourism:

Government of India Government of Maharashtra and local bodies is putting efforts in

the promotion of tourism. Government is assigned the funds for the tourism

development of Satara. The detail analysis is as follows

Distribution of Tourism Development Funds on the Basis of Infrastructure

Government sanctioned funds to the respective district for the development of tourist

destination. Funds to be utilized to improve basic and tourist infrastructure at tourist

destinations in Satara reflects in following table.

Table 4.2.1.1Tourism Development Funds Budgeted and Actually Spent on Basic Infrastructureand Tourist Infrastructure in Satara District since 1999-2011.

(Figures in Rs. Lakhs)

Sr. Basic and Tourist InfrastructureAmountbudgeted

Amountspent

Gap %

Basic Infrastructure1. Construction of Road (wp)* 200.65 151.68 48.97 24.412. Drinking Water 5 5 0 0.003. Footpath or Pathway, Stair Case,

Railing, Fixing Paving Block,Entrance, Fencing (Wp)*

122.8 103.91 18.89 15.38

4. Repair and Maintenance (wp)* 84.66 50.15 34.51 40.765. Surrounding Development,

Landscaping or Survey5.74 5.5 0.24 4.18

6. Toilets and Bathrooms (wp)* 16.99 16.4 0.59 3.477. Total 435.84 332.64 103.2 23.68

Tourist Infrastructure1. Arrangement of SPV Solar System 3.25 2.95 0.3 9.232. Canteen , Tiffin Shade 6.42 6.42 0 0.003. Construction of Hall or Multipurpose

Hall, Entertainment Hall/WaitingRoom (wp)*

19.79 19.77 0.02 0.10

4. Construction of Smarak 13.7 12.73 0.97 7.085. Garden for Children(wp)* 14.59 0 14.59 100.006. Office 8.21 8.21 0 0.007. Parking Place 9.91 9.91 0 0.008. Provision of Other Facility 5 2.07 2.93 58.609. Rest House (wp)* 50 41.18 8.82 17.64

Total 130.87 103.24 27.63 21.11Grand Total 566.71 435.88 130.83 23.09

Source: (District Planning Department, Satara, translated and compiled by researcher)*(wp) - work is progress

Data Analysis


Table 4.2.1.1 depicts that Satara district officials have spent the funds for tourism

development at different location under the different heads as per sanctioned budget.

However, it has observed that there is marginal gap between amount budgeted and

actual spending. Some of the work is still pending and the amount is yet to be spent

which was shown with (wp)*. Budget was sanctioned for development of Garden but

it was not utilized. Whereas 58.60% gap was found under the head of provision of

other facility but this heading does not give clear idea about nature of other facility,

40.76% gap found at repair and maintenance. 24.41% gap is found on construction of

road and the work in progress. 17.64% gap at rest house projects entire funds were not

utilized as the work in progress, 15.38% on footpath and staircase, railing etc.

However, very meager gap was found in different heads like 9.23% SPV solar system,

7.08% construction of Smarak, 4.18% Surrounding development and landscaping,

3.47% toilets and bathrooms and 0.10% construction of multipurpose hall. The

infrastructure like construction of office, parking place, canteen and Tiffin shade, and

drinking water gap between budgeted amount and actual amount spent was zero.

It is concluded that tourism development funds in Satara were underutilized or cost

overrun. As per the budget control system, actual expenditure exceeds the budget that

would be unfavorable condition and vice versa. In this most of the tourism

infrastructure heads budgeted amount exceeds the expenditure so it shows favourable

situation. However, allowable variance is 5% plus and minus and sometimes based on

nature of product and policy. Nearly 10% plus and /or minus variance is accepted

under the condition of allowable variance for unpredictable expenses. However, in

case of Satara in most of the tourism infrastructure this percentage is higher especially

in case of provision of other facility, road, rest house, repair, and maintenance.

Data Analysis


Total Amount Spent on Infrastructure

Following table shows the tourism development funds actually spent on basic and

tourist infrastructure at Satara since financial year 1999 to 2011. The total of amount

of basic and tourist infrastructure in previous table has taken out and presented for the

sake of lucidity.

Table 4.2.1.2Actual amount spent on basic and tourist infrastructure in Satara District since 1999 to2011

Sr. Nature of Infrastructure Amount (in Rs. lakhs) Percentage1. Basic Infrastructure 332.64 76.312. Tourist Infrastructure 103.24 23.69Total 435.88 100

Source: (District Planning Department, Satara, documents translated and compiled byresearcher)

Table 4.2.1.2 depicts that 76.31% of tourism funds spent on basic infrastructure and

only 23.69% spent on tourist infrastructure. It can be concluded that Satara district

still lags in the development of basic infrastructure. It is quite essential to provide

basic infrastructure so as at least to reach out to the development of tourist

destination.

Distribution of Tourism Development Funds on the Basis of Taluka

Following table shows the budget sanctioned and actual spending on different tourist

destinations talukawise in the year 1999 to 2011. In Satara district, 11 Talukas viz.

Satara, Karad, Phaltan, Wai, Mahabaleshwar, Koregaon, Jaoli, Maan, Khatav

Khandala and Patan where the funds are sanctioned and spent to make available

facilities for tourist that depict in the following table.

Data Analysis


Table 4.2.1.3Talukawise Distribution of Funds for Tourism Development in Satara District

(Rs. in lakhs)Sr. Taluka Destination

DevelopmentBudgeted Amount Actual

ExpenditureFacilities MadeAvailable for Tourist

1. Satara Thoseghar, 22.11+17.00* 22.08+17.00 Road, Public Toiletries,Maintenance OfSurroundings,Renovation

Sajjangarh 32.39 26.85(WP)

Yawateshwar 11.24 10.7Dhawadshi 15 14.47Kas 25.00* 15.8

Total 122.74 106.9(87.48%)

2. Karad Agashiv 40 35.69 Road, Renovation

Pal 40.00* 39.08

Total80

74.77(93.46%)

3. Phalatan Santoshgad10.66

10.42(WP)(97.74%)

Road

4. Wai MenawaliVagheshwarTemple

5.56 5.25(WP)Road, Renovation AndMaintenance

NanaPhadniswada 5.56 5.29(WP)

Narsinh Mandir,Dhom 19.1 3.32(WP)

Total 30.22 13.86 (45.86%)5. Mahabal

eshwarPratapgarh

47.99+25.00*9.73(WP)+24.80

Road, Boating, SafetyWall, Fortification,Repair And Renovation

Tapola 18 18Total 90.99 52.53 (57.73%)

6. Koregaon 47.17 37.15 Rest House, Road, SPVSolar System, Garden15.32 12.21(WP)

Total 62.49 49.36 (78.99%)7. Jaoli Bamnoli

7.787.78(100%)

Road. Rest House

8. Maan MaujeKharkhel(Santaji Ghorpade)

9.99.90(100%)

Road, Smarak

9. Khatav Aundh75.11+166.40*

74.72+163.52

Rest House, Road,Waiting Room, Repair,Renovation AndMaintenancMuseum,Tiffney Shade,

Mayani 4.62 4.62Katgun 25.49 22.91Vadgaon 36.96 35.07

Data Analysis


Mauje Bhosare 30.23 14.12(WP) Toiletries,Multipurpose Hall,Smarak, Garden,Canteen

Total 338.81314.96(92.96%)

10. Khandala Naygao3.7

3.35(90.54%)

Road, Smarak

11. Patan Ramghal 16.74 16.74 Road, Repair AndMaintenance, SafetyRailingShri Shkeshtra

Valmiki 6.97 6.57

Ozarde7.41 7.41

Marul Haveli

31.59+2.95

9.34(WP)+2.48

BahuteshwarMandir

3.17+25*

3.00+24.82

MurumKhodi 2.18 2.13Koyananagar 12.00* 11.91Banpuri 25.00* 24.69Dhareshwar 50.00* 34.88

Total 183.01 143.97(78.67%)

Source: (District Planning Department, Satara)Percentage figures in the bracket drawn on total sanctioned amount to the respectivedestinations.* Shows the funds available from regional tourism development package from state ofMaharashtra.WP- indicates work in progress.

Table 4.2.1.3 inferred that funds have been distributed among 11 Talukas of Satara

district for the year 1999 to 2011. Among these Khatav, taluka has received highest

share of Rs. 338.81 lakhs to undertake projects like construction of rest house, road,

waiting room, repair, renovation and maintenance, museum, Tiffney shade, toiletries,

multipurpose hall, smarak, garden, canteen. Out of these Aundh Museum has received

Rs. 75.11 lakhs of local level of tourism development funds and Rs. 166.40 lakhs

from regional tourism development funds of Government of Maharashtra. Rs. 36.96

lakhs allotted to Vadgaon for Jairamswami Temple, Rs. 30.23 lakhs to Mauje Bhosare

for Prataprao Gujar smarak, Rs. 25.49 lakhs to Katgun the birthplace of Mahatma

Phule and Rs. 4.62 lakhs to Mayani bird Sanctuary. However, Rs. 314.96 lakhs

means 92.96% of actual money spent of sanctioned amount

Data Analysis


Patan taluka has received Rs. 183.01 lakhs as tourism development funds to undertake

projects such as construction of roads, repair and maintenance, safety railing. Out of

these Rs. 50.00 lakhs for Dhareshwar along with this Rs. 25.00, lakhs allotted through

regional tourism development funds. Rs. 3.17 lakhs for Koynanagar from local

tourism development funds, Rs. 6.97 lakh to Shri Skshetra Valmiki, Rs. 25.00 lakhs to

Banpuri, Rs. 12.00 lakhs to Koyananagar. Tourism budget sanctioned to Marul

Haveli’s Bahuteshwar Temple was Rs. 31.59 and Rs. 2.95 lakhs. Rs.16.74 lakhs to

Ramghal, Rs. 7.41 lakhs to Ozarde Waterfall and Rs. 2.18 Banpuri Naikeba temple.

However, total actual spending is Rs. 78.67 lakhs from sanctioned amount which is

21.33% lesser than budgeted. It is because of some work is in progress.

Rs. 122.74 lakhs sanctioned to Satara Taluka from tourism development funds to

undertake projects such as construction of roads, public toiletries, maintenance of

surroundings, renovation. Out of these Rs. 22.11 lakhs sanctioned to Thoseghar from

local tourism budget and Rs. 17.00 lakhs from regional tourism development budget.

Sajjangarh received Rs. 32.39 lakhs; Kas received Rs. 25 lakhs from regional tourism

development funds, Rs. 15.00 lakhs to Dhawadshi, and Rs. 11.24 Yawateshwar.

However, 87.48% of total actual amount spent for Satara Taluka, which are 12.52%

lesser than sanctioned funds. It is because of some work is in progress.

For Mahabaleshwar Tourism development funds sanctioned of Rs. 90.99 lakhs to

construct road, boating, safety wall, fortification, repair and renovation. Out of these

Rs. 47.99 lakhs allotted to Pratapgarh from local tourism development funds and Rs.

25.00 lakhs from regional tourism development funds. Rs. 18.00 lakhs allotted to

Tapola. However, 57.73% of amount only spent for Mahabaleshwar Taluka, which is

42.27% amount, is yet to be spent as work is in progress.

Karad taluka received Rs. 80.00 lakhs for tourism development and has undertaken

projects such as construction of roads, renovation. Out of these Rs. 40.00 lakhs, each

to Agashiv caves and Pal. However, 93.46% amount spent for Karad Taluka which is

6.54% lesser than actual sanctioned amount.

Koregaon taluka has received budget of Rs. 62.49 lakhs for tourism development

from local tourism development funds to conduct number of projects such as

construction of rest house, road, SPV solar system, garden. Out of these Rs. 47.17

lakhs allotted to Chavaneshwar temple Karanjkhop and Rs. 15.32 lakhs to Kalyangarh

Data Analysis


Nandgiri temple. However, 78.99% total actual amount spent at Koregaon, which is

21.01% lesser than sanctioned budget. However, Nandgiri project is yet to be

completed.

Wai taluka received Rs. 30.22 lakhs for tourism development to undertake projects

such as construction of roads, renovation, and maintenance. Out of these Rs. 5.56

lakhs allotted for Vageshwari temple Menwali, Rs. 5.56 lakhs for Nana Phadnis Wada

Rs. 19.10 lakhs to Narsinh Temple Dhom. 45.86% total amount spent for Wai Taluka

which is 54.14% lesser than actual allotted funds. However, all projects are in

progress.

Phaltan taluka received only Rs. 10.66 lakhs to Santoshgad for tourism development

and has undertaken construction of road. 97.74% of amount spent for Phaltan Taluka

and the project is in progress.

Rs. 9.90 lakhs budget allotted to Maan taluka Mauje Kharkhel, Santaji Ghorpade

Smarak from local tourism development funds to construct road and Smarak. The

Maan taluka has utilized entire budget sanctioned for the tourism development.

Rs. 7.78 allotted from local tourism development funds to Bamnoli taluka Jaoali to

undertake projects such as construction of road and rest house. The entire budget has

utilized for the development of Bamnoli.

Khandal taluka received least share of local tourism development funds i.e. Rs. 3.70

lakhs to Naygao, a birth place of Savitribai Phule to undertake construction of road

and Smarak. Khandal taluka utilized only 90.54% of sanctioned tourism budget which

is 9.46% lesser than actual sanctioned funds.

The table reveals that Jaoli, Maan taluka utilized entire sanctioned budget, followed

by 97.74% of utilization in Phaltan, 92.96% in Khatav, 90.54% in Khandala, 87.48%

in Satara, 78.67% in Patan, 78.99% in Koregaon, 57.73% in Mahabaleshwar, 46% in

Karad and 45.86% in Wai. The work in taluka viz. Patan, Khatav, Koregaon,

Mahabaleshwar, Wai, Phaltan and Satara is in progress.

It is concluded that Patan and Khatav taluka have larger share of tourism development

funds. It is observed that more than merit of tourist destination, local political leaders

makes large difference in utilizing funds. Satara being district Head Quarter and

having many places worth seeing has not allotted enough funds, which may show

lack of political will. It was also found that though sanctioned amount was not

Data Analysis


sufficient to develop destination yet much of the amount was not utilized and so

returned back.

Distribution of Funds on the Basis of Nature of Destination

Following table shows allotment and expenditure of tourism budget for the year 1999-

2000 to 2010-11as per nature of different tourist destinations in Satara district.

Generally, tourism budget sanctioned for the development of worth seeing destination

that may attract large tourist flow viz. Historical Monuments, Forts, Temples, Caves,

Pilgrimage Centre, Museum, Waterfall, Lake/Reservoir, Smarak and Sanctuary. This

distribution is discourse in following table.

Table 4.2.1.4Allotment and Expenditure of Tourism Budget as Per Nature of Destination

(Rs. in lakhs)

Sr. Type of DestinationBudget

Sanctioned

% allottedfrom totalamount

Actualamount spent

% ofsanctioned

amountspent

1. Historical Monuments 149.36 15.74 107.19(WP)* 71.77

2. Forts 57.82 6.09 47.57(WP)* 82.273. Temples 70.45 7.43 31.09(WP)* 44.134. Caves 71.55 7.54 47.90(WP)* 66.955. Pilgrimage Centre 143.5 15.13 134.39 93.656. Museum 241.51 25.46 238.24 98.657. Waterfall 58.52 6.17 58.4 99.798. Lake/Reservoir/Nature 43 4.53 41.58 96.79. Smarak 30.23 3.19 14.42 47.710. Sanctuary 82.79 8.73 67.32 81.31

Total 948.73 100 788.1 83.07Source: Figures taken from District Planning Department, Satara andorganized/compiled by researcher into nature/type of tourist destination*WP- work in progress

Table 4.2.1.4 inferred that 25.46% amount sanctioned to Museum, 15.74% to

historical monuments, 15.13% to pilgrimage centers, 8.73% to Sanctuary, 7.54% to

Caves, 7.43% to temples. Very meager amount is sanctioned for Waterfall i.e. 6.17%,

6.09% to forts, 4.53% to Lakes, reservoir/nature and 3.19 % to Smarak.

Data Analysis


Actual total amount spent is 83.07% of total allotted tourism budget on tourism

development on various types of destinations in Satara district. On individual heads

it was found that 99.79% of sanctioned amount was spent on waterfall,

98.65 on Museum, 96.70% on lakes, and 93.65% on pilgrimage, 82.27% on forts and

71.77% on historical monuments. Temples, Forts, Smaraks have been sanctioned

lesser amount. However, much lesser amount is spent i.e. 44.13 % on Temples,

66.95% on Caves and 47.70% on Smarak. The work is in progress at Forts, temples,

caves and historical monuments. Governments focus is mainly on museum, historical

monuments, and pilgrimage centers in allotment of tourism funds.

Allotments of Tourism Development Funds under ‘C’ Class to Satara District.

Following table shows Tourism Development Funds allotment and actual expenditure

since 1999-2000 to 2010-2011 at Satara district under ‘C’ class, column number 7

shows percentage of change from previous year.

Table 4.2.1.5Year-wise Funds Allotment and Actual Expenditure on Tourism Development from1999 to 2011.

(Figures are in rupees lakhs)Sr.

Year FundsAllotted For

TourismDevelopmentIn Year (Rs.

In Lakhs)

%Growth

Expenditure

%Growth

Gap %Chan

ge

1 2 3 4 5 6 7

1 1999-2000 15.00 - 15.00 - - -2 2000-2001 17.00 13.33 16.80 12 0.20 -3 2001-2002 - - - - - -4 2002-2003 - - - - - -5 2003-2004 18.03 - 18.03 INF* - -6 2004-2005 - - - - - -7 2005-2006 25.45 - 24.39 INF* 1.06 -8 2006-2007 83.50 228.09 77.96 219.63 5.54 4489 2007-2008 30.00 -64.07 30.00 -61.51 0.00 0.0010 2008-2009 125.94 319.8 120.22 300.73 5.72 419.811 2009-2010

114.06 -9.43 66.41 44.75 47.65733.0

412 2010-2011 110.00 -3.56 68.83 3.64 41.17 13.60

Total 488.95 387.81 101.14Source: District Planning Department, Satara* INF-infinite

Data Analysis


Table 4.2.1.5 depicts the allocation of funds from the district authority for the

development of tourism places of ‘C’ class from 1999 to 2011.

Except the year 2001-2002, 2002-2003 and 2004-2005 the funds has been allocated

for the development of tourism places.

Column number 6 titled gap depicts figures, which are drawn from column number 2

minus column 4 shows the difference between allotted funds and actual expenditure.

In 2001-2002, 2002-2003 and 2004-2005 the fund allotment is zero thus next year

change in % of the growth is not shown.

There is no uniformity in allocation of funds and actual expenditure.

In 1999-2000, there was no gap between budget sanctioned and actual amount spent,

in 2000-2001 there was marginal gap of Rs. 0.20 lakhs and 2001-2002, 2002-2003

there was no budget. In 2003-2004, entire budget was spent, 2004-2005 there was no

budget. In 2005-2006, the gap was Rs. 1.06 lakhs, which increase to greater extent i.e.

Rs. 5.54 lakhs in 2006-2007. In 2007-2008, entire budget was spent. Since 2008 to

2011, there was a gap of Rs. 5.72 lakhs, Rs. 47.65 lakhs, and Rs.41.17 lakhs

respectively.

The allotment of funds for tourism development has risen substantially from 2008-

2009. Until date, government has spent almost 80% of sanctioned amount for the

tourism development.

Both budget allotment and actual expenditure is increasing at greater space since 1999

to 2011.

In 2009-10 and 2010-11 gap is higher i.e. 47.65% and 41.17% respectively. In those

years’ Government spent only 60.36 % of sanctioned amount on tourism

development. This leads to find out the reason behind less spending as compare to

budget.

It has observed that there is no consistency in the sanctioning of funds for tourism

development. Irrespective of lesser amount, sanctioned local bodies could not spend

the same amount and refund is reported of more than 40% of the sanctioned amount.

This draws attention on Government’s planning and implementation.

Data Analysis


Allotment of Regional Tourism Development Funds to Satara District

Following table shows the distribution of allotted funds and actual expenditure for

Satara district tourism development. The funds have been allotted to respective

destinations since 1999 and/or to 2011. However the status for the development is

equally important to expect the potential of tourism that depict in the following

table.

Table 4.2.1.6Distribution of Funds Available Under Regional Tourism Development since 2004-5and/or to 2010-11

(Figures are in rupees lakhs)

SrName of Tourist

DestinationAllotted

fundsActualSpent

SurplusStatus of

Development

1 Pal, Karad 40.00 39.08 0.92 3 Jobs Completed2 Dhareshwar(Diwashi),

Tal Patan 12.00 11.91 0.09 3 Jobs Completed

3 Valmiki PaneriSurroundings Tal. Patan

25.00 24.69 0.31 2 Jobs Completed

4 Koyna Wild LifeSanctuary

50.00 34.88 15.12

3J 3 Jobs Completed,Construction of Suspension

bridge at Ozarde Falldropped because of

permission regretted due totech problem. Thus surpluswith interest deposited into

government Treasury.5 Pratapgarh Tal.

Mahabalshwar25.00 24.80 0.20 3 Jobs Completed

6 Thoseghar Tal. Satara 17.00 17.00 0.00 4 Jobs Completed7 Kas Lake Surroundings

Tal. Satara25.00 15.80 9.20

2JobsUncompleted. Surplusamount deposited to

government by SataraNagarparishad

8 KoynanagarSurroundings Tal. Patan

25.00 24.82 0.18 2 Jobs Completed

9 Aundh Tal. KhatavConstruction of safetywall at Aundh to YamaiDevi Temple Ghat

28.40 26.53 1.87surplus deposited to

Government

10 AundhMuseumRenovation anddevelopment ofsurroundings

100.00 100.00 - 9 Jobs Completed

Data Analysis


Total ( 1 to 10)Amount Received in2004-2005

347.40 319.51 27.89

11 Bhavani Museum,Aundh renovation likefixing poly carbonatesheet, colouring ofnames at porch, fixingof MRP Domb onbuilding, making corehall for strong room,painting of Entrance

5.24 5.10 0.14

12 Repair of statue atsurrounding of BhavaniMuseum, fixing of newgate, fixing of pavingblock, grill, breaking ofold store building,painting of varandha,making of Guardroomfor pay and parking

6.15 6.05 0.10

All jobs are completed andsurplus amount returned to

government.

13 Tar road at parkingarea, windows atCanteen and Tiffinshade, making of letterat Entrance, soil andgrill for garden,leveling of ground,shifting of scrap,removal of unnecessaryconstruction.

7.23 7.23 0.00

14 Construction of waitingroom for tourist atBhavani museum porch

11.24 10.95 0.29

15 Tar road of parking areaat Bhavani Museum,Aundh, windows atcanteen and tiffinshade, soil and grill forgarden, leveling ofground, shifting ofscrap and removal ofunnecessaryconstruction

6.14 6.09 0.05

16 Fixing of two electricalmotor pump andpipeline at BhavaniMuseum area.

2.00 1.57 0.43

Data Analysis


Total(11-16)Amount Received in 2007-2008

38.00 36.99 1.01

Total amount received fromMaharashtra tourismDepartment.

385.40 356.50 28.90

Source: District Planning Department, Satara

Table 4.2.1.6 shows that Satara district received Rs. 385.40 lakhs for tourism

development, Out of this Rs. 347.40 received in 2004-2005 and Rs. 38.00 lakhs in

2007-8. There is gap in budgeted amount and actual expenditure. The total amount

has been distributed to Aundh Museum in Khatav taluka until 2010-11 is Rs. 166.40

lakhs. Patan Rs.112.00 for Valmiki.Dhareshwar and Ozarde(Waterfall). Rs. 40 lakhs

are sanctioned to Karad, for Pal pilgrimage centre. In Satara, taluka for the

development of Thoseghar and Kas Rs. 42 lakh has been sanctioned. Rs. 25 lakhs to

Mahabaleshwar for Pratapgarh (Fort). Same jobs undertaken for the tourism

development at Bhavani Museum Aundh are shown twice. It is observed that tourism

needs are not met yet under number of heads, the said amount is not used, and surplus

amount is returned. It can be inferred that concerned department is unable to design

and implement right tourism development policy for the district. There are no special

funds available for tourism development like Kokan development, Marathwada and

Vidharbh Development Package to Satara district in 2011.

It concludes that tourism development funds are regularly allotted to Satara district

thorugh Zilha Parishad under ‘C’ category being Satara as a district place. Funds are

usually spent on basic and tourist infrastructure of the destinations. It is found that

funds are not sanctioned by considering the need of destination but through influence

of political force. Without any marketing strategy or marketing planning funds

allotment is vain. Thus, need arises to make proper marketing planning to promote

destination like Satara. Identification of need of destination is vital for effective

marketing planning. Need of destination is determined by number of factors. But one

important is demographic profile of stakeholder viz. tourist, hoteliers, tour operators.

Researcher has insight into demographic profile of stakeholders of Satara district in

the next section.

Data Analysis


Section II

4.2.2 Demographic Profile of Stake Holders:

The section details the demographic profile of stakeholders i.e. tourist, hoteliers and

tour operators who put the effort directly and indirectly in the promotion of tourist

destination. The demographic profile of respective stakeholders presents in 3 parts as

demographic profile of tourist, demographic profile of hoteliers and demographic

profile of tour operators with their respective interpretation.

4.2.2.1 Demographic Profile of Tourist:

This part discusses the tourist profile of 326 samples who have visited the 10 well-

known destinations viz. Aundh, Mahabaleshwar, Panchgani, Pratapgarh, Wai,

Sajjangarh, Thoseghar, Kas, Ajinkyatara, and Koyna. The tourists’ origin of state,

gender, age group, and occupation reflected in tourist profile.

Distribution of Tourist’s Origin

Following table presents the distribution of sample tourists as per their origin of state.

Tourists are visiting to different locations of Satara viz. pilgrimage place like Aundh,

Wai. Hill stations like Mahabaleshwar and Panchgani, historical fort Pratapgarh,

Ajinkyatara, holy place Sajjangarh, Thoseghar, beautiful flora of Kas and nature

gifted location Koyna. They are from different origins of states like Uttar Pradesh

(UP), Andhra Pradesh (AP), Delhi, Gujarat, West Bengal (WB), Uttaranchal,

Himachal Pradesh (HP), Punjab, Orissa, Karnatak, Rajsthan, and Goa. Some of the

tourists are from other districts in Maharashtra viz. Pune, Mumbai and the like.

Researcher has broadly classified the samples into, within Maharashtra and Out of

Maharashtra. Further Maharashtra category is sub-classified into Maharashtra

excluding Satara district and only Satara district. The distribution of samples is as

follows.

Data Analysis


Table 4.2.2.1.1Distribution of Sample Tourists as Per Origin of State

(n=326)

Sr.

OriginofTouristSample

NameoTouristLocation

Out of Maharashtra Maharashtra

Tot

al

U.P

.

A.P

.

Del

hi

Guj

arat

W.B

.

Utt

aran

chal

H.P

.

Pun

jab

Ori

ssa

Kar

nata

k

Raj

stan

Goa M

ahar

asht

ra(E

xclu

ding

Sat

ara

and

Sur

roun

ding

)

Sat

ara

Dis

tric

t

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.

1. Aundh 27 3 30

2. Mahabaleshwar

1 1 1 1 24 2 30

3. Panchgani

4 1 4 1 24 1 35

4. Pratapgarh

1 3 1 2 121 1 30

5. Wai 2 2 30 3 376. Sajjanga

rh16 14 30

7. Thoseghar

33 33

8. Kas 1 1 1 1 26 30

9. Ajinkya-Tara

1 1 31 1 34

10. Koyna 1 29 7 37

Total 1 3 2 9 1 1 1 1 1 11 1 1 261 32 326

%

0.31

0.92

0.61

2.76

0.31

0.31

0.31

0.31

0.31

3.37

0.31

0.31

80.0

6 9.82

100

Source: Field Data

Table 4.2.2.1.1 reveals the prime focus of outside tourist seems to be national famous

tourist destinations viz. Mahabaleshwar, Panchgani, and Pratapgarh, which is a

Data Analysis


package tour as such. The tourist from other district in Maharashtra seems focused

more on Thoseghar, Ajinkytara fort, Wai, a famous museum of Aundh, and the like.

Only 10 % of sample tourists found to visit from other states i.e. out of Maharashtra

visit destinations within Satara district. Respondents who visited from other states

were from Uttar Pradesh, Andhra Pradesh, Delhi, Gujarat, West Bengal, Uttaranchal,

Himachal Pradesh, Punjab, Orissa, Karnataka, Rajasthan, and Goa.

However, most of the tourist’s flow (80.06%) is coming from Maharashtra excluding

Satara district, 9.82% from Satara district, (10%) from other states. From Maharashtra

majority of tourist flow is from Pune, Mumbai, Sangli, and Kolhapur and among

states Gujarat and Karnataka tourist flow is better compared to other states.

It is inferred that tourists who are visiting well-known hill stations Mahabaleshwar

they are likely to visit nearest tourist location viz. Panchgani, Pratapgarh and Wai.

The few tourists who visit Kas were mainly because the Kas site has entered into

world heritage site. Local tourists are equally visiting the destinations at percentage

of 9.82% of total samples.

Distribution of Tourist Genderwise

Following table reveals the distribution of sample tourists as per gender at different

destinations of Satara. Tourists visit aforesaid locations of Satara belongs to both

genders male and female that reflect in the following table. The percentages are

calculated on total frequency destination-wise.

Data Analysis


Table 4.2.2.1.2Distribution of Sample Tourists as Per Gender at different destinations of Satara

(n=326)

Sr.

GenderName of TouristLocation in SataraDistrict

Male Female Total

F. % F. % F. %

1. 2. 3. 4. 5. 6. 7.

1. Aundh 16 53.3 14 46.67 30 9.20

2. Mahabaleshwar 23 76.67 7 23.33 30 9.20

3. Panchgani 24 68.57 11 31.43 35 10.74

4. Pratapgarh 27 90.00 3 10.00 30 9.20

5. Wai 30 81.08 7 18.92 37 11.35

6. Sajjangarh 20 66.67 10 33.33 30 9.20

7. Thoseghar 29 87.88 4 12.12 33 10.12

8. Kas 21 70.00 9 30.00 30 9.20

9. Ajinkya-Tara 24 70.59 10 29.41 34 10.43

10. Koyna 32 86.49 5 13.51 37 11.35Total 246 75.46 80 24.54 326 100.00

Source: Field Data

Table 4.2.2.1.2 reveals that males are more than females who visit different locations

of Satara. Out of those Pratapgarh, Wai, Thoseghar and Koyna are more preferred

locations by males compared to females and females has given more preference to

visit Aundh rather than other locations of Satara.

75.46% are male tourist on the contrary female are only 24.54%. At Aundh

destination the gender ratio is nearly equal i.e. 53.33% and 46.67%, at

Mahabaleshwar male are highest i.e.76.67percentage as compared to 23.33% of

female, Panchgani male are 68.57 whereas females are 31.43%. Pratapgarh, Wai,

Sajjangarh, Thoseghar, Kas, Ajinkyatara, and Koyna have found to be male

dominated locations since more than 70% of male found visiting these locations.

These destinations are moreover hilly destinations and require some walking to reach

out.

Data Analysis


Distribution of Tourist Agewise

Following table presents distribution of sample tourists visited at different

destinations as per their age group. Tourists of different age groups visit Satara to see

the locations. Researcher has sought age groups in six intervals ranging from below

15 years, 15-25 to 55 and above with an interval of 10. This distribution reflects in the

following table. Since no sample interviewed to visit destination having age below 15

years hence the column did not included.

Table 4.2.2.1.3Distribution of Sample Tourists as Per Age Group at different destinations of Satara

(n=326)

Sr

Age Group

Name ofDestination

15-25 25-35 35-45 45-5555&above

Total

F % F % F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.1. Aundh 4 13.33 2 6.67 6 20 6 20 2 40 30 1002. Mahabalesh

war3 10 9 30 11 36.67 3 10 4

13.33

30 100

3. Panchgani 1 2.86 13 37.14 14 40 6 17.14 1 2.86 35 1004. Pratapgarh 2 6.67 16 53.33 9 30.00 2 6.67 1 3.33 30 1005. Wai 7 18.92 16 43.24 8 21.62 4 10.18 2 5.41 37 1006. Sajjangarh 6 20 6 20 9 30 6 20 3 10 30 1007. Thoseghar 7 21.21 14 42.42 9 27.27 2 6.06 1 3.0 33 1008. Kas 8 26.67 16 53.33 5 16.67 1 3.33 30 1009. Ajinkya-

Tara10 29.41 3. 8.82 10 29.41 6 17.65 5

14.71

34 100

10. Koyna 6 16.22 18 48.65 11 29.73 2 5.40 37 100Total

46 14.11 105 32.21103

31.60 42 12.88 30 9.20 326 100

Source: Field Data

Table 4.2.2.1.3 reveals that tourists are found in all age groups but more tourists found

to be in age group of 25-45, which amounts to 63.81% of total sample tourists.

32.21% of tourists found to be in age group of 25-35 whereas 31.60% of tourists from

age group of 35-45. The age group 15-25 more preferred to visit Thoseghar and

Ajinkytara and the percentage is 21.21and 29.41 respectively. The age group 55&

above has preferred Aundh destination to visit compared to other destinations of

Satara. The age group 45-55 has preferred equally all the destinations of Satara. The

Data Analysis


age group 25-35 has merely preferred all the destinations of Satara but Pratapgarh is

more preferred followed by other destinations like Koyna, Wai, and Thoseghar.

Distribution of Tourist as Per Occupation

Following table represents the distribution of tourist samples available in respective

tourist destinations of Satara as per their occupation. Tourists are of different

occupations. Researcher has categorized into 13 groups viz. unskilled worker,

unskilled worker, petty traders, shop owners, industrialists with no employees, with 1

to 9 employees, with 10+ employees, self employed professional, clerical salesman,

supervisory level, officer executive junior, middle/semi and students/housewife.

Student and housewife consider in one category since they are not earners. This

sample distribution depicts in following table.

Data Analysis


Table 4.2.2.1.4Distribution of Tourists Samples at respective tourist destination as Per Occupation

(n=326)

Tot

al

10 3.07

13 3.99

4 1.23

13 3.99

9 2.76

9 2.76

3 0.92

36 11.0

4

24 7.36

31 9.51

54 16.5

655 16

.87

65 19.9

4

326

10 Aun

dh

8 26.6

7

2 6.67

4 13.3

3

2 6.67

4 13.3

36 20

.00

4 13.3

3

30

9 Mah

abal

eshw

ar 2 6.67

5 16.6

7

2 6.67

2 6.67

1 3.33

3 10 1 3.33

2 6.67

4 13.3

35 16

.67

3 10 30

8 Panc

hga

ni

5 14.2

91 2.

86

4 11.4

3

1 2.86

4 11.4

36 17

.14

5 14.2

9

9 25.7

1

35

7 Prat

apg

arh

2 6.67

1 3.33

2 6.67

2 6.67

2 6.67

8 26.6

7

2 6.67

2 6.67

3 10 2 6.67

4 13.3

3

30

6 Wai

2 5.41

2 5.41

2 5.41

3 8.11

2 5.41

4 10.8

1

3 8.11

5 13.5

14 10

.81

10 27.0

3

37

5 Sajja

nga

rh

3 10 1 3.33

1 3.33

5 16.6

7

3 10 1 3.33

5 16.6

73 10 8 26

.67

30

4 Tho

segh

ar

3 9.09

4 12.1

212 36

.36

7 21.2

1

7 21.2

1

33

3 Kas

1 3.33

1 3.33

9 30 1 3.33

7 23.3

34 13

.33

5 16.6

7

2 6.67

30

2 Aji

nkya

-T

ara

1 2.94

1 2.94

1 2.94

1 2.94

4 11.7

615 44

.12

11 32.3

5

34

1 Koy

na 1 2.

701 2.

701 2.

701 2.

701 2.

70

2 5.41

8 21.6

2

5 13.5

17 18

.92

3 8.11

7 18.9

2

37

Sr.

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

Tot

al

F % F % F % F % F % F % F % F % F % F % F % F % F %

Nam

e of

Des

tinat

ion

Occ

upat

ion

Gro

up

Uns

kill

ed W

orke

r

Skill

ed W

orke

r

Petty

Tra

ders

Shop

Ow

ner

Indu

stri

alis

t w

ith

noE

mpl

oyee

s

With

1-9

Em

ploy

ees

wit

h 10

+ E

mpl

oyee

s

Self

E

mpl

oyed

Prof

essi

onal

Cle

rica

l/Sa

lesm

an

Supe

rvis

ory

Lev

el

Off

icer

/Exe

c Ju

nior

Off

ice

Exe

.M

iddl

e/Se

mi

Stud

ent/

Hou

sew

ife

Source: Field Data

Data Analysis


Table 4.2.2.1.4 reveals that there is relationship between occupation and tourism.

Salaried tourists are of higher category found to have more tourism as compared to

entrepreneurs and petty traders. Self-employed professionals are found to enjoy

tourism.

53.37% of total sample tourists are officers and executive (Junior and Senior),

students and housewives occupation category followed by 11.04% self-employed,

9.51% supervisory level and 7.36% clerical/salesmen, only 6.44% are industrialist.

2/3rd of total respondents of Aundh i.e. 66% are clerical/salesmen, supervisors,

officers/executives (Junior/Middle level), and housewife, followed by unskilled

workers 26.6%, and no self employed sample found as the location is mostly

preferred for pilgrimage. Except petty traders all respondents were of all categories in

almost equal number found visiting Mahabaleshwar since the hill station is preferred

by almost all the occupation category. 82% of sample respondents at Panchgani

belong to self employed, clerical/salesmen, supervisory level, officer/executives

(Junior/Middle/Semi) and students/housewife category. Except unskilled workers, all

respondents were of all categories in almost equal number in Pratapgarh since the fort

is preferred as a sight scene by Mahabaleshwar tourists. Except unskilled workers,

petty traders, clerical salesmen were found visiting Wai in almost equal number in

Wai where housewife were maximum (27%) since it is popular pilgrimage centre.

80.4% of tourist visiting Sajjangarh belongs to self employed, clerical/salesmen,

officer executives(Junior/Middle/Semi), students and housewife category. No

Unskilled and shop owners’ category of tourists found to visit Sajjangarh. Mostly

white-collar working class found in Thoseghar. So the waterfall is almost preferred by

white-collar working class of tourist category. Kas is more (30%) preferred by self

employed professionals, followed by 23.33% supervisory levels staff, 16.67% officers

of middle and semi category and lesser by industrialist and business group (higher

income group). At Ajinkyatara 44.12% of the respondents visited were of

officers/Executives middle/semi followed by 32.35% students/housewife category.

Data Analysis


At Koyna 59.42%, respondents belong to clerical/salesmen, officer executives junior

and student’s occupational category. Clerical/salesmen, junior executives, and student

mostly prefer the waterfall at Koyna.

4.2.2.2 Demographic Profile of Hoteliers:

There are various categories of hotels operating in Satara district. The researcher hasinterviewed 40 samples. This part discourse the categories, year of establishment andspeciality in food served.

Distribution of Hotels as Per Location

Following table presents the distribution of hoteliers respondents. Researcher has

selected 40 respondents from the important locations of Satara where hotel business is

operated in a great scale compared to other destination of Satara. The distribution is

shown in the following table.

Table 4.2.2.2.1Distribution of Hoteliers Samples

(n=40)

Sr.

Name ofLocation

Frequency Percentage

1. 2. 3.1 Satara 10 252 Wai 5 12.53 Koyna 5 12.54 Mahabaleshwar 10 255 Panchgani 10 25

Total 40 100Source: Field Data

Table 4.2.2.2.1 reveals that total hoteliers respondents are 40. Majority of the

respondents i.e. 25% are each from Mahabaleshwar, Panchgani, and Satara. The rest

of the respondents i.e. 12.5% are from Wai and Koyna each.

Data Analysis


Distribution of Hotels as Per Category and Establishment

Following table presents the hotelier respondents according to their category wise

establishment. (Percentages are worked out category wise).

Table 4.2.2.2.2Hoteliers Samples as per their Category and year of Establishment

(n=40)

Sr

Year ofEstablishmentCategory

1960-19701970-1980

1980-2000

2000&above Total

F % F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.1. Resort 1 20 0 0 3 60 1 20 5 1002. Star Graded 2 50 0 0 2 50 4 1003. Downtown 2 9.09 2 9.09 5 22.73 13 59.09 22 1004. Other 1 11.11 0.00 0.00 8 88.89 9 100

Total 6 15 2 5 8 20 24 60 40 100Source: Field Data

Table 4.2.2.2.2 depicts that majority i.e. 60% hotels are established after 2000 and

only 15% are prior to 1970 in Satara district. In Resort category majority (60%) of

resorts established during 1980-2000, 20% in each during ‘1960-1970’ and ‘2000 and

above’. 50% Star graded hotels established prior to 1970 and 50% after

2000. In Downtown category, most of the hotels i.e. 59.09% established after

2000 and 22.73% in 1980-2000 and rest of hotels established prior to 1980. In the

'other category' majority i.e. (88.89%) of hotels are established after 2000 and rest i.e.

11.11% prior to 1970.

Data Analysis


Distribution of Hotels as Per Spciality in Serving of Food

Following table presents hoteliers as per speciality in food. Availability food is

indispensable at tourist destination to attract and hold the tourist. The availability of

variety as vegetarian, non-vegetarian, Gujarathi Thali, Continental is depicted in the

following table.

Table 4.2.2.2.3Hoteliers as per their Specialty in Food

(n=40)

Sr. Name of Specialty F Percentage1. Vegetarian 7 24.142. Non-Vegetarian 0 0.003. Gujarati 0 0.004. Continental 0 0.005. Vegetarian and Non-vegetarian 22 75.86

Total 29 100.00Source: Field Data

Table 4.2.2.2.3 infers that in ‘speciality in food’ 75.86% hotels serves both vegetarian

and non-vegetarian food whereas rest 24.14% hotels serve pure vegetarian food.

4.2.2.3 Demographic Profile of Tour Operator:

This part depicts the tour operator’s profile on the basis of their type of formation and

establishment.

Distribution of Tour Operators as Per Their Forms of Organisation

Following table represents forms of tour operating organization, i.e. as per their

constitution, proprietary, partnership, private limited and others. The percentages are

worked out as per forms of organization.

Data Analysis


Table 4.2.2.3.1Forms of Organization

(n=10)

Sr.

Year ofEstablishment

Form ofOrganization P

rior

200

0

%

200-

2005

%

2005

-201

0

%

2010

-on

war

ds

%

Tot

al

1. Proprietary 1 11.11 5 55.56 2 22.22 1 11.11 92. Partnership 0 0 0 0 0 0 0 0 03. Pvt. Ltd 1 100 0 0 0 0 0 0 14. Other 0 0 0 0 0 0 0 0 0

Total 2 20 5 50 2 20 1 10 10Source: Field Data

Table 4.2.2.3.1 reveals that most of the organizations i.e. 90% are proprietary. Out of

them 66.67% organization established prior to 2005 and rest after 2005. There is no

any partnership firm and other type of forms of organization. Only 10% are private

limited who established prior to 2000.

It is found that tourists are visiting Satara mainly from the cities like Pune,

Mumbai, Sangli and Kohapur. People prefer all kinds of destinations with same

zeal and enthusiasm. Salaried people are more preferring Satara. Both male and

female are equally found at Satara and especially they belong to 25 to 45 age-

groups. Hotels of all categories are available in Satara and both type of food is

served. However, tour operators are enough in quantity but they are arranges tours to

take away the local people outside and not to bring the outsiders to Satara. Therefore

there is needed to find out the problems and prospects of tourism sector. So researcher

has studied and analyzed the stakeholders independently in the proceeding sections to

know their niceties. Thus, the first important stakeholder of the tourism sector is

Tourist; researcher has put the effort to know tourist’s niceties in next section tourist

descriptive analysis.

Data Analysis


Section III

4.2.3 Tourist Descriptive Analysis:

Structured schedule is executed on 326 tourist at ten different places of Satara viz.

Aundh, Mahabaleshwar, Panchgani, Pratapgarh, Wai, Sajjangarh, Thoseghar, Kas,

Ajinkyatara and Koyna were interviewed. This section orate tourists’ perceptions on

15 tourism of products, destination awareness, perception on motivators to tourism,

promotion of tourism, potential to Satara, tourism pattern, pricing of tourism,

satisfaction and importance of tourism services and amenities. The majority of

responses were collected on 5-point likert scales. The said data is analyzed with

statistical tools viz. mean, rank, standard deviations, Spearman’s rank correlation, and

percentages. These detailed analyses are as follows

Perception of Tourist on Attraction of Tourism Product

Distribution of Tourist Genderwise

Following table depicts the perception of sample tourists on attraction of tourist

location in Satara as per their gender. Nature of different tourism products attracts

tourists of both genders male and female. Researcher has considered 15 tourism

products viz. Adventure, Flora, Fauna/Wild Life Sanctuary, Waterfall, Ghats, Hill

Stations, Lake/Reservoir, Scenery Beauty, Valleys, Pilgrimage, Temples, Museum,

Historical Monuments, Forts, and Windmills to know the tourist perception on their

attractions.

Data Analysis


Table 4.2.3.1Perception of Sample Tourists on Attraction of Tourists Locations as Per Gender

(n=326)

Sr

Gender

Nature ofProducts

Male Female Total

Mean Rank SD MeanRank

SD MeanRank

SD

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.1. Adventure 3.58 13 0.81 3.58 13 0.81 3.58 13 0.81

2. Flora 3.84 9 0.70 3.84 8 0.70 3.84 9 0.70

3.Fauna / Wild LifeSanctuary

3.72 10 0.78 3.72 10 0.78 3.72 10 0.78

4. Waterfall 4.08 3 0.66 4.08 3 0.66 4.08 3 0.66

5. Ghats 3.87 7 0.79 3.87 7 0.79 3.87 7 0.796. Hill Station 4.37 1 0.75 4.37 1 0.76 4.37 1 0.757. Lake/Reservoir 3.90 6 0.79 3.90 6 0.79 3.90 6 0.79

8. Scenery beauty 4.21 2 0.75 4.21 2 0.76 4.21 2 0.75

9. Valleys 3.67 11 0.83 3.67 11 0.83 3.67 11 83

10. Pilgrimage 3.85 8 0.98 3.83 9 0.98 3.85 8 0.98

11. Temples 3.96 5 0.82 3.94 5 0.82 36 5 02

12. Museum 3.53 14 0.89 3.51 14 0.89 3.53 14 0.89

13.HistoricalMonuments

3.67 11 0.87 3.67 11 0.87 3.67 11 0.87

14. Forts 3.97 4 0.80 3.97 4 0.80 3.97 4 0.80

15. Windmills 3.26 15 0.92 3.26 15 0.92 3.26 15 0.92

Correlation Coefficient .996**

Sig. (2-tailed) .000Source: Field Data**. Correlation is significant at the 0.01 level (2-tailed).

Table 4.2.3.1 reveals that the tourists perception about the tourist location at Satara.

Tourism products like hill station, scenic beauty, waterfall and forts attracts them

more compared to windmill, museum, adventure, valleys and historical

monuments.

Gender wise there is no difference in perception of tourism product.

To investigate into the depth of analysis researcher has calculated Spearman’s

rank correlation coefficient of perception of male and female for tourism products.

The score is 0.996, with ‘P’ value 0.000, which is significant at 0.01 levels (2-tailed).

Data Analysis


Distribution of Tourist Agewise:Following table reveals the perception of sample tourist on attraction of tourists’location as per their age. Tourist of different age groups carries different perceptionon tourism products. The researcher has considered previously mentioned 15 tourismproducts for the same. There are 5 age groups viz. 15-25, 25-35, 35-45, 45-55 and 55and above that considered to check the different perception on tourism products.These data collected through 5-point likert scale and analyzed with different statisticaltools as above-mentioned table. The distribution of total sample tourist as per the agegroup is presented in following table.Table 4.2.3.2Perception of Sample Tourists on Attraction of Tourists Locations Age wise

Sr.

Age Group

Name ofProduct

15-25 25-35 35-45 45-55 55&above

Mea

n

Ran

k

SD Mea

n

Ran

k

SD Mea

n

Ran

k

SD Mea

n

Ran

k

SD Mea

n

Ran

k

SD

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.1. Adventure 3.58 13 0.8 3.58 13 0.81 3.58 13 0.8 3.58 13 0.81 4 13 0.812. Flora 3.82 9 0.7 3.82 9 0.72 3.83 9 0.7 3.84 9 0.7 4 8 0.73. Fauna / Wild

LifeSanctuary

3.72 0 0.8 3.72 10 0.78 3.72 10 0.8 3.72 10 0.78 4 10 0.78

4. Waterfall 4.09 3 0.7 4.09 3 0.68 4.08 3 0.7 4.08 3 0.66 4 3 0.665. Ghats 3.87 7 0.8 3.87 7 0.79 3.87 7 0.8 3.87 7 0.79 4 7 0.796. Hill Station 4.33 1 0.8 4.34 1 0.76 4.37 1 0.8 4.37 1 0.75 4 1 0.767. Lake/Reservoi

r3.89 6 0.8 3.89 6 0.81 3.9 6 0.8 3.9 6 0.79 4 6 0.79

8. Scenerybeauty

4.16 2 0.8 4.16 2 0.75 4.2 2 0.8 4.21 2 0.75 4 2 0.76

9. Valleys 3.67 11 0.8 3.67 11 0.83 3.67 11 0.8 3.67 11 0.83 4 11 0.8310. Pilgrimage 3.83 8 1 3.84 8 0.98 3.84 8 1 3.85 8 0.98 4 8 0.9811. Temples 3.94 5 0.8 3.96 5 0.82 .96 0.8 3.96 5 0.82 4 5 0.8212. Museum 3.51 4 .9 3.52 14 0.9 3.52 4 0.9 3.53 14 0.89 4 14 0.8913. Historical

Monuments3.67 11 0.9 3.67 1 0.87 3.67 1 0.9 3.67 1 0.87 4 11 0.87

14. Forts 3.97 4 0.8 3.97 4 0.83 3.97 4 0.8 3.97 4 0.8 4 4 0.815. Windmills 3.26 5 0.9 3.26 15 0.92 3.26 15 0.9 3.26 15 0.92 3 15 0.92Correlation Coefficient age group 15-25 and 25-35 1.000**Sig.(2-tailed) 0.00Correlation Coefficient age group 15-25 and 35-45 1.000**Sig.(2-tailed) 0.00Correlation Coefficient age group 15-25 and 45-55 1.000**Sig.(2-tailed) 0.00Correlation Coefficient age group 15-25 and 55 and above .999**Sig.(2-tailed) .000

Source: Field Data**. Correlation is significant at the 0.01 level (2-tailed).

Data Analysis


From the 4.2.3.2 table inferred that tourism product such as hill station, scenic beauty,

waterfall and forts attract more to the tourists irrespective of their age group. The

tourism products viz. windmill, museum, adventure, valley, and historical monuments

attract lesser to the tourists irrespective of their age group.

The Spearman’s rank correlation coefficient of perception for tourism products across

different age group is 0.999, with ‘P’ value 0.00, which is significant at 0.01 levels (2-

tailed).

Motivators to TourismFollowing table shows the opinion of sample tourist on motivators to tourism. Peoplego for tourism for different purposes. It is observed that different situations motivatepeople for tourism. Researcher has considered 10 situations that motivates fortourism as motivators’ viz. Availability of Financial Resources like Money, Leisure toreduce the stress, Propensity to Pleasure, More Occasions for Special Gatherings,Influence of Western Culture, Promotion in employment, Cost Effective TransportSystem, Time Saving Transport System, Sponsorship from Employer, Changes inDomestic Culture and asked to the total sample of tourists to assign the ranks for thesame from 1 to 10 on priority basis. This data is observed with concentratedfrequencies area that is put forward in table below.

Table 4.2.3.3Opinion of Sample Tourists on Motivators to Tourism

(n=326)

Sr.

Rank Frequency

Name of Motivator1 2 3 4 5 6 7 8 9 10

Total

1 2 3 4 5 6 7 8 9 10 11 121. Availability of Financial

Resources Like Money31 12 68 29 5 4 2 1 1 14 167

2. Leisure to Reduce The Stress 97 100 32 3 3 3 1 1 0 2 2423. Propensity to Pleasure 140 85 37 9 2 1 0 0 1 1 2764. More Occasions for Special

Gatherings26 19 21 29 9 6 7 6 3 1 127

5. Influence of Western Culture 3 9 6 10 21 6 6 10 3 5 796. Promotion in Employment 1 2 2 3 6 11 7 6 11 7 567. Cost Effective Transport

System3 4 5 4 14 19 17 3 2 0 71

8. Time Saving Transport System 0 1 7 9 11 7 9 18 5 2 69

9. Sponsorship from Employer 1 4 0 7 3 4 7 1 1 0 8

10. Change in Domestic Culture 15 9 12 12 11 7 6 5 2 8 87

Source: Field Data

Data Analysis


Table 4.2.3.3 reveals that money, leisure, pleasure and gatherings motivates mainly to

the tourist for tourism in Satara.

Table orate that prime motivators to tourism are propensity to pleasure, leisure to

reduce the stress and availability of financial resources like money as the frequency of

respondents is concentrated in this area. The rest factors do not carry much

importance in tourism. Thus, these three main factors need to focus in designing

tourism-marketing strategies followed by ‘more occasions for gathering’.

Distribution of Tourist as Per Travel Package

Following table depicts the distribution of respondents based on travel package

obtained in respective destinations of Satara. People visit to different tourist

destinations through tourism packages, which are generally organized by tour

operators. Researcher is interested to know preference of tourist who visits previously

mentioned locations of Satara through tour packages. Due to dichotomous nature of

question, the collected data has been analyzed using percentages. The opinion of

sample tourists is open in following table.

Table 4.2.3.4Distribution on the Basis of Travel Package Obtained by Tourist Samples fromdifferent places of Satara

(n=326)

Sr.

Opinion

Name of PlacesYes % No %

1. 2. 3. 4. 5.1. Aundh - - 30 1002. Mahabaleshwar - - 30 1003. Panchgani - - 35 1004. Pratapgarh - - 30 1005. Wai - - 37 1006. Sajjangarh - - 30 1007. Thoseghar - - 33 1008. Kas - - 30 1009. Ajinkya-Tara 17 50 34 10010. Koyna - - 37 100

Total 17 5.21 326 100Source: Field Data

Table 4.2.3.4 reveals tourists have least preference for travel package to visit Satara.

Data Analysis


5.21% of the tourists have enjoyed tourism through travel package to visit Ajinkyatara

locations of Satara. Further, these tourists have travelled to Kas, Sajjangarh, and

Thoesghar. Majority of tourists ie 94.79% have not traveled by package tour to visit

the destinations in Satara. Thus, tourists are more preferring independent tour plan

rather than travel package. It has also not observed in Satara district that tourist visit

destinations through travel packages. The observations may be because of less

number of samples of tour operator specifically out of Satara or it might be that tour

operator outside Satara and Maharashtra did not offer any tourism product of Satara.

Tourist Travel Pattern

Following table shows the distribution of travel pattern of sample tourists of

different places of Satara. Tourist travel alone, with family and may be in-group.

The table below narrates the description of travel pattern of total tourist samples. The

collected data is analyzed with the help of percentage.

Table 4.2.3.5Distribution of Travel Pattern of Sample Tourists of different places

(n=326)

Sr.

Travel Pattern

Name of Places

Alone Family Group

TotalF % F % F %

1. 2. 3. 4. 5. 6. 7. 8.

1. Aundh 2 6.67 18 60 10 33.33 302. Mahabaleshwar 0 0 22 73.33 8 26.67 303. Panchgani 2 5.71 27 77.14 6 17.14 354. Pratapgarh 0 0 13 43.33 17 56.67 305. Wai 2 5.41 18 48.65 17 45.95 376. Sajjangarh 0 0 20 66.67 10 33.33 307. Thoseghar 0 0 13 39.39 20 60.61 338. Kas 1 3.33 26 86.67 3 10.00 309. Ajinkya-Tara 0 0 4 11.76 30 88.24 3410. Koyna 0 0 19 51.35 18 48.65 37

Total 7 2.15 180 55.21 139 42.64 326Source: Field Data

Data Analysis


Table 4.2.3.5 inferred those tourists prefer to visit Satara with family and group.

Tourist products like forts and waterfall are more likely to visit with groups and

pilgrimage, hill stations and scenic beauty is preferred to visit with family.

Visiting tourist destinations with family and group is more preferred than individual

visits since 55.21% respondents found visited destinations with family followed by

group 42.64% and alone (individual) visits 2.15%. The tourists who have visited

Aundh out of which 60% tourist visited with family and 33.335 visited with group.

The tourists who visited hill stations Mahabaleshwar, out of which 73.33% visited

with family and 26.67% with groups. Tourist who visited Panchgani, out of that

77.14% visited with family and very few i.e. 17.14 visited with group. Tourist who

visited Sajjangarh, out of which 66.67% visited with family and 33.33% visited with

groups. Tourist who visited Kas preferred mainly go with their family and the

percentage is 86.67%. Tourists who visited Ajinkyatara a well-known fort of Satara,

out of that majority visited with group and the percentage is 88. 24% and very few

11.76% visited with family.

Distribution of Tourist as Per their Group Size

Following table shows the distribution of sample tourists visited different destinations

as per their group size. Tourists are likely to enjoy some of the destinations with

group. Researcher is interested to know the size of group with which tourist visited

Satara to see the different locations as Aundh, Mahabaleshwar, Panchgani,

Pratapgarh, Wai, Sajjangarh, Thoseghar, Kas, Ajinkyatar and Koyna. Previous table

evident that tourist travels in-group. The percentages are used for analysis of data and

calculated row-wise. The data is presented in following table. (Figures in bracket are

the percentages drawn on total tourist who visited different destinations of Satara with

group).

Data Analysis


Table 4.2.3.6Distribution of sample Tourists of different destinations as per their Group Size

(n=139)

Source: Field Data

Table 4.2.3.6 depicts that more groups visits found at Ajinkyatara, Thoseghar, Koyna

and Pratapgarh compared to other destinations of Satara.

Majority 53.2% of tourists visited of which group size was below 10, 28.1% tourists

group size was in between 10-20, 12.9% tourists’ group size was 30-40,

2.88% tourists’ group size was 20-30 and 50 & above each. At Aundh almost all

the tourists who visited with group, their group size is 0-10, at Mahabaleshwar

62.5% tourists’ group size is up to 20. At Panchgani (83.33%), tourist’s group size is

up to 20. At Pratapgarh 94% tourists group size is up to 20, Wai (82%) up to 20,

Sajjangarh almost all up to 20, Thoseghar(90%) up to 20, Kas almost all up to 20,

Ajinkytara majority(56.67%) up to 20 and Koyna 94.4% tourists up to 20 group size.

Thus, almost all the destinations tourist has visited with group size is merely about 20.

The possibility group size is in between 0-20 to visit different locations of Satara.

Sr

Group Size

Name ofPlaces

0-10 10-20 20-30 30-4040-50

50&above

Total

F % F % F % F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.1. Aundh 10 100 10(7.19) 1002. Mahabales

hwar4 50 1 12.5 337.5 8(5.76) 100

3. Panchgani 2 33.33 3 50 116.7 6(4.32) 1004. Pratapgarh 11 65 5 29 1 5.9 17(12.23) 1005. Wai 6 35 8 47 2 12 1 5.9 17(12.23) 1006. Sajjangarh 3 30 7 70 10(7.19) 1007. Thoseghar 14 70 6 30 20(14.39) 1008. Kas 2 66.7 1 33.3 3(2.16) 1009. Ajinkya-

Tara13 43.33 17 56.67 30(21.58) 100

10. Koyna 9 50 8 44.4 1 5.56 18(12.95) 10011. Total 74 53.2 39 28.1 4 2.88 18 12.9 4 2.88 139(100) 100

Data Analysis


Distribution of Tourist as Per Purpose of Visit

Following table presents distribution of sample tourists according to their purpose of

visit to the respective destinations of Satara. Tourist may visit destinations with

different purposes i.e. business/conference, enjoying adventure, only for leisure,

religious cause, may be merely enjoying destinations and the recent trend like health

treatment and the like.

Table 4.2.3.7Distributions of Sample Tourists According to their Purpose of Visit

(n=326)

Sr.Purpose of Visit

TotalF. %

1. 2. 3.1. Business/Conference 5 1.532. Culture/Heritage Monuments 2 0.613. Adventure 6 1.844. Leisure 89 27.305. Religion/Pilgrimage 49 15.036. Health Treatment 2 0.617. Friends /Relatives 24 7.368. Tourism 149 45.71


Table 4.2.3.7 reveals that Satara destination is more preferred for tourism purpose and

leisure.

Sample tourist visited Satara district for many purposes out of which 45.71% samples

visited purely with purpose of tourism at different locations of Satara, followed by

27.30% samples visited for merely leisure, 15.03% for religion/pilgrimage, 7.36%

accompanying friends and relatives, 1.84% for enjoying adventure, 1.53% for

business/conference and 0.61% each for culture/heritage monuments and for health

treatment.

Distribution of Tourist as Per Mode of Travel

Following table reveals the sample tourists mode of travel to visit the different

destinations of Satara. Tourists have many options to travel like bus, train, plane,

personal car, and two-wheeler and like. The effort has been made in following table to

Data Analysis


reveal travel mode of total sample tourist who visited the previously mentioned

locations. Percentages are calculated on tourist-visited destination wise.

Table 4.2.3.8Sample Tourists Mode of Travel to Visit the Destination

(n=326)

Source: Field Data* Rent a Vehicle

Table 4.2.3.8 inferred that personal car is more preferred to visit Satara.

68.4% of sample tourists have used personal car to visit different destinations

of Satara. 11.35% tourists use bus as travel mode, 10.14% sample tourist used rental

vehicle, 6.13% samples travelled by Two Wheeler. Train is a made of travel used

by 3.37 % of sample tourist. Personal car as a mode of travel used by tourist at Aundh

86.67%, Koyna 83.78%, Mahabaleshwar 83.33%, Thoseghar 81.82%, and Sajjangarh

73.33%, and Kas 73.33%, Panchgani 62.86% and Wai 48.65%.

However, for Ajinkytara 50% tourists have used rental vehicle and 23.53% have used

personal car. Bus as a mode of transport used at Wai by 35.14% samples, followed by

Ajinkyatara by 20.59%, Pratapgarh 20%, Panchgani 17.14%, 6.06% Thoseghar,

3.33% Mahabaleshwar, 3.33% Kas and 2.7% at Koyna. Very few tourists have used

train as a mode of travel to Kas 16.67%, 14.29% Panchgani, and 3.33% Pratapgarh.

No sample has found who used plane since the facility is not convenient. Two-

Sr.

TouristMode

Name ofPlaces

Bus Train Personal CarTwo

WheelerOther(Pl.Specify)*

Total

F % F % F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.1. Aundh 26 86.67 4 13.33 30 1002. Mahabalesh

war1 3.33 25 83.33 4 13.33 30 100

3. Panchgani 6 17.14 5 14.29 22 62.86 2 5.71 35 1004. Pratapgarh 6 20 1 3.33 22 73.33 1 3.33 30 1005. Wai 13 35.14 18 48.65 3 8.11 3 8.11 37 1006. Sajjangarh 22 73.33 6 20 2 6.67 30 107. Thoseghar 2 6.06 27 81.82 4 12.12 33 1008. Kas 1 3.33 5 16.67 22 73.33 2 6.67 30 1009. Ajinkya-

Tara7 20.59 8 23.53 2 5.88 17 50 34 100

10. Koyna 1 2.7 31 83.78 3 8.11 2 5.41 37 100Total 37 11.35 11 3.37 223 68.4 20 6.13 35 10.74 326 100

Data Analysis


wheeler as a mode of travel used by tourist at Sajjangarh 20%, 13.33% Aundh, 8.11%

Wai, 5.88% Koyna, 5.88% Ajinkyatara and 5.71% Panchgani. Rental vehicles is used

for travel at Mahabaleshwar by13.33percentage, at Thoseghar by12.12percentage

samples, 6.67% samples at Sajjangarh, 6.67% samples at Kas, 5.41% Koyna and

Pratapgarh is visited by 3.33% samples.

Distribution of Tourist as Per Length of Stay

Following table shows the distribution of sample tourists’ length of stay at respective

destinations of Satara. People prefer staying at tourist destinations for leisure, comfort

and enough enjoyment. Satara district have few tourist places that do have good

staying arrangements made available preferentially. Few other tourist destinations do

not have staying arrangements at all. Looking towards different forts in Maharashtra

the staying arrangement is not in existing. At few forts scanty arrangements are found

e.g. Fort Panhala (Kolhapur district), the entire chain of forts are worth seen.

Following table traces the length of stay of sample tourist at different destinations.

Tourist stayed different destinations of Satara overnight, day visit and more than two

visits. Parentages are calculated on samples destination wise.

Table 4.2.3.9Sample Tourists Length of Stay at Destination

(n=326)

Source: Field Data

Sr.

Length of Stay

Name of Places

Overnight Day VisitMore ThanTwo Days

Total

F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9.1. Aundh 30 100 30 1002. Mahabaleshwar 5 16.67 12 40 13 43.33 30 1003. Panchgani 4 11.43 11 31.43 20 57.14 35 1004. Pratapgarh 30 100 30 1005. Wai 4 10.81 21 56.76 12 32.43 37 1006. Sajjangarh 7 23.33 19 63.33 4 13.33 30 1007. Thoseghar 13 39.39 20 60.61 33 1008. Kas 15 50 15 50 30 1009. Ajinkya-Tara 17 50 8 23.53 9 26.47 34 10010. Koyna 9 24.32 24 64.86 4 10.81 37 100

Total 74 22.7 190 58.28 2 9.02 26 100

Data Analysis


Table 4.2.3.9 depicts that Day visits are more prefer to visit Satara. Destinations like

Aundh, Pratapgarh, Wai, Sajjangarh, Thoseghar, Kas and Koyna are more preferred

for day visit whereas hill stations like Mahabaleshwar and Panchgani prefer to visit

for staying.

58.28% of total sample tourists have made day visit, 22.7% of total sample tourists

stayed overnight, and 19.02% of total sample tourist stayed more than two days at

destinations of Satara.

57.14% samples tourist who visited Panchgani and 43.33% who visited

Mahabaleshwar stayed for more than two days. 50% samples tourist who visited Kas

preferred to stay overnight and 50% made day visit. Majority of sample tourist who

visited Aundh, Pratapgarh, Wai, Sajjangarh, Thoseghar, and Koyna had day visit. It

could be concluded that majority of destinations of Satara are more preferred for day

visit.

Tourist’s Average Spending

Following table shows the distribution of sample tourists as per their average

spending at respective destinations of Satara. The places like Mahabaleshwar,

Panchgani, Wai, Sajjangarh, and Koyna have developed arrangement of lodging.

Other tourist places of interest do not have professionally managed lodging and

boarding arrangements includes Aundh, Pratapgarh, Thoseghar, Kas, and the like.

Data Analysis


Table 4.2.3.10Sample Tourists Average Spending per person at Destination

(n=326)

Source: Field Data

Table 4.2.3.10 reveals that destinations Mahabaleshwar, Panchgani, Pratapgarh,

Ajinkytara, and Koyna are visited by tourists’ spending across all groups. Tourists

visited above destinations are preferably found spending in upper spending group i.e.

Rs. 1500-2000 and Rs. 2000 and above per day per person.

Destinations Sajjangarh and Koyna seems to be cost economy since 63.33% of

samples of Sajjangarh and 64.88% of samples at Koyna opine spending less than Rs.

500 per day.

In all 88.95% of sample, tourists’ spending was up to Rs. 1500 per day per person.

Majority i.e. 45.71% sample tourists who visited Panchgani have spent between Rs

1000-1500. Majority 63.33% sample tourists who visited Sajjangarh have spent less

than Rs. 500. 63.64% of sample tourists who visited Thoseghar their spending was

Rs. 500-1000. 93.33% sample tourist who visited Kas their average spending was in

between Rs.500 to Rs.1000. 64.86% sample tourist who visited Koyna have spent less

Sr.

AverageSpending

Nae ofPlaces

< Rs. 500Rs. 500-1000

Rs. 1000-1500

Rs. 1500-2000

Rs.2000&above

Total

F % F % F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.1. Aundh 10 33.33 16 53.33 4 13.33 30 1002. Mahabalesh

war3 10 12 40 12 10 2 6.67 1 1.33 30 100

3. Panchgani 3 8.57 14 40 16 45.71 1 2.86 1 2.86 35 1004. Pratapgarh 4 13.33 17 56.67 3 10 5 16.67 1 3.33 30 1005. Wai 11 29.73 19 51.35 6 16.22 1 2.7 37 1006. Sajjangarh 19 63.33 3 10 4 13.33 4 13.33 30 1007. Thoseghar 10 30.3 21 63.64 2 6.06 33 1008. Kas 1 3.33 28 93.33 1 3.33 30 100

9. Ajinkya-Tara

12 35.29 5 14.71 17 50 34 100

10. Koyna 24 64.86 4 10.81 7 18.92 1 2.7 1 2.7 37 100Total

97 29.75139

42.64 54 16.56 11 3.37 25 7.67 326 100

Data Analysis


than Rs. 500. It could be inferred that the Satara destinations can come up as budget

tourist destination.

Sample tourist visited Ajinkyatara, out of which 50% of samples average spending

was Rs2000 and above (as tourists had preferred package tour). Rs 2000 and above

average spending was found with other few sample tourist may be due to their

distance or their long stay.

Percentage of Expenses on Major Items

The major heads of expenses at tourist destinations are accommodation,

transportation, food; shopping and entertainment. Following table presents the

distribution of sample tourists as per their daily expenses for major items.

Table 4.2.3.11Sample Tourists Daily Expenses for Major Items at Destination

(n=326)

Sr

PercentageRange

Major Items

5-15 15-25 25-35 35-45 45-55 55& above Total

F % F % F % F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.1. Accommodati

on3 4.69 13 20.31 24 37.50 14 21.54 8 12.50 3 4.62 65 19.94

2. Food 10 10.99 34 37.36 27 30.77 13 14.29 1 0.85 6 5.13 91 27.91

3. Transportation4 2.00 9 4.50 21 10.50 22 11.00 16 8.00 129 64.18

201

61.66

4. Entertainment 15 51.72 5 17.24 6 20.69 2 6.90 1 3.45 0.00 29 8.90

5. Shopping 13 68.42 5 26.32 1 5.26 0.00 0.00 0.00 19 5.83

Source: Field Data

Table 4.2.3.11 infers that major chunk of budget is spent on transportation while

amounts to nearly 55% of budget opined by 64% of samples. Around 25-35% of

budget spends on accommodation and food opined by 37.5% and 30.77% of samples

respectively. After transportation, food and accommodation are the major areas of

concerned. 30.77% and 20.31% of sample tourist opined to spend around 15-25% of

budget on food and accommodation respectively. Spending on entertainment and

shopping is on last priority on which 5 to 15% of budget is spent.

Data Analysis


Staying Arrangement by TouristFor tourist destination, attract tourist to stay. At the destination, different staying

arrangements are available viz. Star Hotel, Budget Hotel, Friends and Relatives. Few

tourists might return without staying as well. Following table presents the distribution

of sample tourists’ staying arrangement at different locations of Satara.

Table 4.2.3.12Distribution of Sample tourist’ Staying Arrangement at Destination

(n=326)

Source: Field Data*Note: the variable not applicable is also housed in ‘other’ category of stayingarrangement.

Table 4.2.3.12 reveals that Budget hotels are more preferred by respondents to stay.

Majority 52.76% of total sample tourist did not stayed at destination. 22.7% tourists

made staying arrangement at budget hotel, 10.43% tourists preferred star hotel and

14.11% preferred to stay at friends/relatives place.

Budget hotels are more preferred to stay at Mahabaleshwar, Panchgani, Pratapgarh

(Mahabaleshwar stay), Wai, Kas (Satara stay), and Koyna. Star hotel is preferred to

Sr.

Name of StayingArrangement

Name ofPlaces

Star HotelBudgetHotel

Friends/Relatives

NotApplicable

Total

F % F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.1. Aundh 30 100 30 1002. Mahabaleshwar 2 6.67 11 36.67 5 16.67 12 40 30 1003. Panchgani

411.4

314 40 4 11.43 13 37.14 35 100

4. Pratapgarh 3 10 10 33.33 1 3.33 16 53.33 30 1005. Wai

410.8

19 24.32 9 24.32 15 40.54 37 100

6. Sajjangarh4

13.33

1 3.33 1 3.33 24 80.00 30 100

7. Thoseghar 2 6.06 4 12.12 27 81.82 33 1008. Kas 14 46.67 3 10 13 43.33 30 1009. Ajinkya-Tara 17 50 13 38.24 4 11.76 34 10010. Koyna 13 35.14 6 16.22 18 48.65 37 100Total

3410.4

374 22.7 46 14.11 172 52.76 326 100

Data Analysis


stay by 50% of sample tourist who visited Ajinkyatara and they came through the

package tour to see other destinations of Satara. In Sajjangaarh staying arrangement

is available at free of cost. 38.24% of sample tourists who visited Ajinkytara have

made staying arrangement at their friends and relatives house. 24.32% of sample

tourists who visited Wai have made staying arrangement at their friends and relatives

house. Also 16.67% of sample tourists who visited Mahabaleshwar, 16.22% of

sample tourist who visited Koyna, 11.43% of sample tourists who visited Panchgani,

10% of sample tourists who visited Kas and 3.33% of sample tourists who visited

Pratapgarh (Mahabaleshwar) and Sajjangarh each have made staying arrangement at

friends and relatives house.

Type of Visit by Tourist

Following table depicts the account of first time visitors and repeat visitors in the

respective places of Satara. It is observed that both types of visitors are found in the

tourist flow i.e. first time visitor and repeat visitors. The frequency of tourists’ visit

depends mainly on the destinations worth seeing quality and their satisfaction.

Researcher wants to know the percentages of fresh visitors and repeat visitors to see

the previously mentioned places of Satara. The distribution of total sample tourists is

presented in the following table.

Table 4.2.3.13Type of Visit to the Destination by Tourists

(n=326)

Source: Field Data

Sr

Type of VisitName of Places

First Visit Repeat Visit Total

F % F % F %

1. 2. 3. 4. 5. 6. 7.1. Aundh 6 20 24 80 30 1002. Mahabaleshwar 10 33.33 20 66.67 30 1003. Panchgani 16 45.71 19 54.29 35 1004. Pratapgarh 21 70 9 30 30 1005. Wai 12 32.43 25 67.57 37 1006. Sajjangarh 6 20 24 80 30 1007. Thoseghar 27 81.82 6 18.18 33 1008. Kas 28 93.33 2 6.67 30 1009. Ajinkya-Tara 25 73.53 9 26.47 34 10010. Koyna 23 62.16 14 37.84 37 100

Total 174 53.37 152 46.63 326 100

Data Analysis


Table 4.2.3.13 inferred that fresh visitors are found at the places like Kas (93.33),

Thoseghar (81.82%), Ajinkytara (73.53%), and Pratapgarh (70%). The destinations

like Aundh (80%) that is famous for Yamai pilgrimage and Sajjangarh(80%) a holy

place, Wai which famous for Ganpati temple and a historical place attracts tourist for

repeat visit.. Mahableshwar and Panchgani known hill stations also attracts tourist for

repeat visit. Koyna attracts first time visitors due to its gorgeous nature. Mostly all

destinations at Satara found attracting tourists for repeat visit.

Frequency of Repeat Visit by TouristFollowing table shows the frequency of repeat visit to the different locations of Satara

by sample tourists. It is quiet likely that tourist visited the destination may visit couple

of times. This table is an effort to assess these visits. Percentages are calculated on

152 samples that have made repeat visit to either of the destination. But from column

Number 2 to 9 where percentages are calculated as per destination.

Table 4.2.3.14Frequency of Repeat Visit to the Destination by Tourists

(n=152)

Source: Field Data

Table 4.2.3.14 reveals that all destinations are visited by 46.62% of total sample

tourist. Out of these, 152 samples have made repeat visit to the respective

Sr.

Number ofRepeat Visit

Name of Places

0-5 5-10 10-1515&

aboveTotal

F % F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.1. Aundh 041.67 2 8.33 10 41.67 2 8.33 24 15.792. Mahabaleshwar 14 70 4 20 1 5 1 5 20 13.163. Panchgani 8 42.11 6 31.58 5 26.32 19 12.504. Pratapgarh 3 33.33 1 11.11 2 22.22 3 33.33 9 5.925. Wai 10 40 8 32 5 20 2 8 25 16.456. Sajjangarh 8 33.33 6 25 3 12.5 7 29.17 24 15.797. Thoseghar 3 50 3 50 6 3.958. Kas 2 100 2 1.329. Ajinkya-Tara 9 100 9 5.9210. Koyna 12 85.71 2 14.29 14 9.21

Total 79 51.97 32 21.05 26 17.11 15 9.87 152 100

Data Analysis


destinations. The most frequently visited destinations is Aundh, Sajjangarh 15.79% of

samples each out of repeat visited tourist have visited these destination. Kas,

Ajinkytara, and Thoseghar are the least repeat visited destinations. Wai stood first

with 16.45% of tourist visited frequently. Hill stations i.e. Mahabaleshwar, Panchgani

do found visited by 13.16% and 12.50% samples respectively. It can be said that

pilgrimages remain more attraction for repeat visit followed by hill stations.

Pricing Perception by Tourist

Following table presents pricing perception on different items in different

locations of Satara. The tourist samples that have stayed at respective locations have

interviewed to seek their perception on pricing of food and drinks, accommodation,

transport, packaged tours, information material and shopping items. The respondents

who stayed are 119 in numbers. These respondents were asked to rate their perception

on five point likert scale 1 for highly unreasonable, 2 for unreasonable, 3 for neither

reasonable more unreasonable, 4 for reasonable and 5 for highly reasonable. These

responses are purely based on actual availed items at respective places.

Table 4.2.3.15Sample Tourists Perception on Pricing at Destination

(n=119)

Source: Field Data

Sr

PricingPerception

Name of Places Foo

d an

dD

rink

s

Acc

omm

odat

ion

Tra

nspo

rt

Pac

kage

dT

ours

Info

rmat

ion

Mat

eria

l

Sho

ppin

gIt

ems

1. 2. 3. 4. 5. 6. 7.1. Aundh2. Mahabaleshwar 2.58 2.69 3 3 1.863. Panchgani 3.38 3.14 3.42 2 2.67 2.364. Pratapgarh5. Wai 3.54 3.5 3.25 3.1 2.82 3.5

6. Sajjangarh 3.94 3.41 4 4.33 3.567. Thoseghar 3.88 3.46 3.44 3 3 38. Kas 3.93 3.5 3.43 3 3.14 3.389. Ajinkya-Tara10. Koyna 4.08 4.08 3.67

Total 3.58 3.35 3.47 2.89 3.2 2.85

Data Analysis


Table 4.2.3.15 reveals that packaged tours, information materials and shopping items

are not reasonable from the new point of samples as far as pricing is concerned.

Pricing of transportation is quite reasonable to Sajjangarh and somewhat reasonable

for rest of destinations except Mahabaleshwar. Destination Mahabaleshwar seems to

be costlier in all respect since the score for pricing was reasonability tends from 1.86

to 3 for respective items. Destination Koyna is the most reasonable on the part of food

and accommodation.

Following table presents the perception of pricing by sample tourists who did not stay

at respective locations of Satara. The variables food and drinks, information material

and shopping items are only considered for non-resident tourists.

Table 4.2.3.16Perception of pricing by tourists who did not stay at Destination

(n=190)

Source: Field DataTable 4.2.3.16 reveals that destination Mahabaleshwar is still costlier for non residenttourist for food, information material and shopping items. Samples are foundreasonable prices of food and information material at destination Pratapgarh and Wai.Prices of food seem to be more reasonable at Thoseghar, Kas, and Wai since the meanreasonability is 4 and nearby.

Sr.

Prcing Perception

Name of Places

Foodand

Drinks

InformationalMaterial

ShoppingItems

1. 2. 3. 4.1. Aundh 3.33 3 3.332. Mahabaleshwar 1.88 2 2.253. Panchgani 3.45 3.1 34. Pratapgarh 3.76 3.63 3.65. Wai 3.82 3.33 3.536. Sajjangarh7. Thoseghar 48. Kas 4 3.5 3.369. Ajinkya-Tara10. Koyna 3.4 3 3

Total 3.59 3.43 3.35

Data Analysis


Section IV

4.2.4 Hoteliers Descriptive Analysis:

This part deals with the status of 40 hoteliers of Satara district. Data orate on purpose

of lodging occupancy, tourists’ origin who stayed, services offered, preference of

customers for hotel services, size of business, awareness, promotion tool, tourist

season, media effectiveness, awareness of destination, perception on tourism services

and amenities available in district, potential to tourism and like. Responses were

collected on 5-point scale. Data analyzed with different statistical tools percentages,

mean, rank, standard deviation, rank correlation etc.

Lodging OccupancyFollowing table shows opinion of hoteliers on percentage of lodging occupancy as per

the purpose of tourist visit at Satara. People sought in the hotel for business/office

purpose, tourism, and other. The percentage of occupancy for each purpose from the

range of 0-20 to 80-100 at the interval of 20 highlight the size of business of each

reason. The data depicts the percentage interval of lodging occupancy in Satara.

Table 4.2.4.1Lodging Occupancy in Sample Hotels

(n=40)

Sr.

Purpose ofVisit

Percentage ofOccupancy

Business/office Tourist Other

F % F % F %

1 2 3 4 5 6 71. 0-20 26 65 1 2.5 32 802. 20-40 5 12.5 6 15 7 17.53. 40-60 4 10 2 5 1 2.54. 60-80 5 12.5 8 20 05. 80-100 0 0 23 57.5 0

Total 40 100 40 100 40 100Source: Field Data

Table 4.2.4.1 reveals that occupancy of tourism lodging is more as compared to other

type of occupancy.

Data Analysis


Tourism occupancy is in the range of 80-100 opined by 57.5% hoteliers, business

occupancy is below 20 percentages opined by 65% hoteliers, and ‘other purpose’

lodging occupancy is below 20% opined by 80% of sample hoteliers.

Following table shows the opinion of hoteliers on percentage of lodging occupancy of

tourist from different locations. Tourist came from different areas some are from

Satara district, other district, and some times out of Maharashtra and may be from

foreign countries. Lodging occupancy is in percentage range of each area reflecting in

the following table.

Table 4.2.4.2Lodging Occupancy of Tourist from Different Locations

(n=40)

Sr.

Area

OccupancyPercentage

Sat

ara

dist

rict

%

Oth

er d

istr

ict

of M

ahar

asht

ra

%

Out

of

Mah

aras

htra

%

For

eign

%1. 2. 3. 4. 5. 6. 7. 8. 9.

1. 0-20 36 90 2 5 11 27.5 40 1002. 20-40 2 5 4 10 15 37.5 0 03. 40-60 2 5 17 42.5 8 20 0 04. 60-80 0 0 11 27.5 3 7.5 0 05. 80-100 0 0 6 15 3 7.5 0 0

Total 40 100 40 100 40 100 40 100Source: Field Data

Table 4.2.4.2 reveals that occupancy lodging of tourist is more from other district of

Maharashtra followed by rest of other states.

Lodging occupancy from ‘Satara district’, ranges up to is 20% opined by 90% hotel

owners whereas 40-60% lodging occupancy received from tourist from other district

of Maharashtra opined by 42.5% hoteliers and from rest of states in India the

occupancy receives below 40%. Foreign tourists’ occupancy is also less than 20%

opined by all hoteliers.

Data Analysis


Tourist Preference for Hotel Services

Following table presents opinion of hoteliers on tourist preference for hotel services in

Satara hotel offered many services for tourist but tourist preference depicts in

following table.

Table 4.2.4.3Preference of Hotel Services by Tourists

(n=40)

Sr.Name of Services F Percentage

1. 2. 3.1 Air/Rail Ticket Booking 11 27.52 Hotel Booking 40 1003 Local Transport Vehicle 28 704 Tour Guide 23 57.55 Package Tour 12 306 Entertainment 12 307 Any Other* 1 2.5

Total 40 100Source: Field Data*Any other’ services are not specified by hotelier

Table 4.2.4.3 depicts that ‘Hotel Booking’ is the priority of tourist according to the

hotel owners. Next priority is arrangements of ‘Local Transport Vehicle’ preferred by

70%, of samples. ‘Tour Guide’ preferred by 57.5% of sample. ‘Package Tour’ and

‘Entertainment’ and Air/Rail ticket booking preferred by around 30% of samples.

Data Analysis


Size of Tourist Hanled by Hotels

Following table discourse number of tourist handled in a year by sample hoteliers inSatara.Table 4.2.4.4Number of Tourist Handled yearly by Sample Hotels

(n=40)

Sr.Number of

TouristF Percentage

Estimated Number ofTourist*

1. 2. 3. 4.1 0-5000 11 27.5 275002 5000-10000 10 25 750003 10000-15000 5 12.5 625004 15000-20000 4 10 700005 20000-25000 5 12.5 1125006 25000-30000 2 5 550007 30000& above 3 7.5 97500Total 40 100 500000

Source: Field Data*Figures are calculated by taking average of number of tourist column

multiplied by frequency i.e. Average of column No. 1 * 2

Table 4.2.4.4 depicts that 27.5% of hotels yearly handle ‘0-5000’ tourists whereas

25% handle ‘5000-10000’ and 12.5% each hotel handles ‘10000-15000’ and ‘20000-

25000’ tourist. ‘15000-20000’ tourists are yearly handled by 10% hotel owners,

‘30000 and above’ tourist handled by 7.5 % and only 5% hotel owner handle ‘25000-

30000’ tourist. Thus, it infers that 15000 tourists are yearly handled by 60% of

respondents and more than 25000 tourists by 12.5% respondents. Estimated amount

of tourist handled by hotelier in Satara counts to five lakhs.

Tourism Season as per Hoteliers’ Opinion

Table depicts opinion of sample hotel owners on tourism season like ‘peak season’,

‘off season’ and ‘special season’ in Satara. The following table depicts the

months/occasions of tourism seasons in Satara district.

Data Analysis


Table 4.2.4.5Opinion of Sample Hotel Owners on Tourism Season in Satara

(n=40)

Sr

Tourism Season

Month /occasions ofSeason

Peak Off Special

F % F % F %

1. 2. 3. 4. 5. 6. 7.1. April-May, Sept-Oct 5 12.52. June and July(Weekend,

vacations, rainy season)25 62.5

3. Aug-Sept 4 104. Feb- June 6 155. Working and Fasting Days 28 706. Aug-Diwali 2 57. Jan – March 4 108. June-Sept 5 12.59. Rainy Season 1 2.510. April-May 6 1511. Christmas and Diwali 33 82.512. Aug-Oct 1 2.5

Total 40 100 40 100 40 100Source: Field Data

Table 4.2.4.5 discourse that June and July are favourable months in peak season i.e.

occasions of rain, vacations, weekend whereas working and fasting occasions are off-

season and Christmas and Diwali occasions are the special season.

62.5% respondents said that ‘peak season’ is weekend, vacations and rainy season and

very few i.e. 15% sample hoteliers said that Feb and June are months of the peak

season. For ‘Off season’ majority i.e. 70% sample hoteliers opines working and

fasting days are the occasions of off-season. Very few i.e. 5% sample hoteliers opines

August-Diwali are the month and occasions of off-season. For ‘Special season’

majority i.e. 82.5% sample hoteliers felt that Christmas and Diwali are the special

occasions and very few i.e. 2.5% said that August to October are the months of

special season. From this table it could be conclude that difference in the opinion of

sample hoteliers may be due to their destinations speciality.

Data Analysis


Offerings by Hoteliers

Following table presents the services offered by hoteliers in Satara. There are variousservices offered to the tourist by hotel owners is depicted in the following table.

Table 4.2.4.6Services Offered by Hotelier

(n=40)

Sr.Name of Services F Percentage

1. 2. 3.1 Lodging 40 1002 Communication 40 1003 Parking 35 87.54 Generator 39 97.55 Dinning 29 72.56 Conference Hall 20 507 Aqua-guard 35 87.58 Garden 23 57.59 Rental car 30 75

10 Sight Scene 25 62.511 Permit room 14 3512 Waiting room 32 8013 Entertainment 29 72.514 Doctor on call 37 92.515 Swimming Pool 10 2516 Internet 26 6517 Indoor game 13 32.518 Laundry 37 92.519 Gymnasium 13 32.520 Driver room 23 57.521 Sight scene information/guidelines 32 8022 Guide for sight scenes 27 67.523 Room Service 39 97.524 Cleanliness and Maintenance 40 100

25 Other(if any)* 7 17.5Source: Field Data

* Sona and Steam Bath, Health Resort, Spa, Wi-Fi, Maharashtra Thali,Children Park, Security.

Data Analysis


Table 4.2.4.6 depicts that cleanliness and maintenance, communication, and lodging

are the main thirst fulfilled by all sample hotels in Satara district and also services of

generator, doctor on call, laundry and room services.

97.5% respondents provide generator and room service, 92.5% laundry and doctor on

call, 87.5% sample hotels provide Acquaguard and parking facility, 80% facilitate

waiting room and sightseeing guidelines, 75% provides rental car, 72.5% each extend

entertainment and dining. 65% of hoteliers provide internet and 62.5% arranges sight

scene. Very few of them offer swimming pool i.e. 25%, 35% sample hotels have

permit room, 32.5% sample hotels have gymnasium and indoor games.

Promotion Technique Adopted

Following table reveals the opinion of hoteliers on promotion techniques adopted.

Table 4.2.4.7Promotion Techniques Adopted by Hotelier

(n=40)

Sr.Name of Technique F Percentage

1. 2. 3.1. Advertisement 29 72.52. Personal Selling(Agents/PROs) 14 35

3. Sales Promotion( discounts/Foodfestivals/ Special offers)

9 22.5

4. Publicity 8 205. Public Relation 19 47.56. Other(if any)* 4 10

Source: Field Data* Word of mouth and Hoardings

Table 4.2.4.7 infers that advertisement is the main tool adopted by respondents.

72.5% respondent uses advertisement as a tool of promotion technique, 47.5% use

public relation, 35% hotels do personal selling (agents/PROs), 22.5% go for sales

promotion and 20% relies on publicity. It means that all the promotion techniques are

adopted by hotels in Satara but there is no uniformity. Most of them use more than

one technique and some of them use all. Thus, advertisement is most preferred by

hoteliers of Satara, followed by public relation.

Data Analysis


Time Slab for Promotional Activities

Following table discourse, the responses of hoteliers on time slab for promotional

activities. The timing of promotion is reveals in the following table

Table 4.2.4.8Time Slab for Promotional Activities by Hoteliers

(n=40)

Sr.Time Slab for Promotion F Percentage

1. 2. 3.1 All around the year 29 72.52 During the tourism season 8 20

3 Before the season(Please specify the month and duration)* 3 7.54 Other# 2 5

Total 40 100Source: Field Data* 15 days before, Diwali, summer vacation and 31st December# No Need of promotion

Table 4.2.4.8 reveals that majority of hoteliers i.e. 72.5% do promotional activities

throughout the year, 20% do during the tourism season, 7.5% do before the season

and 5% do not feel the need of promotion. The established oldest hotel of Satara do

not feel the need of promotion.

Data Analysis


Section V

4.2.5 Tour Operators Descriptive Analysis:

This part contains the analysis of 10 tour operators who do the business to take the

tourist from Satara and who bring the tourist to Satara. Out of them 5 are from Satara,

2 from Mahabaleshwar, 2 from Kolhapur and one from Mumbai. To probe into

problems and prospects of tourism sector in Satara, researcher has serene the opinion

of Tour operators through the independent schedule, as they being stakeholder of

tourism sector. It orate size of business in percentage, perception on tourism products

that attract tourist, available tourist services and amenities, preference of promotional

techniques, its effectiveness, destination awareness, tour package, tourist preference

towards services, potential to tourism and like. The data collected on 5-point scale and

somewhere through dichotomous question and open ended questions. Responses

collected through open-ended questions are presented in readable format. The

collected data has been analyzed and presented with its inferences, which are as

follows.

Geographical Distribution of Tour Operators BusinessFollowing table shows the percentage of business of tour operators received from

different geographies. Geographies are composed as Satara, Maharashtra (excluding

Satara), out of Maharashtra and Foreign.

Table 4.2.5.1Tour Operators Receives Business from tourists of Different Geographies

(n=10)

Source: Field Data

Sr.Tour Operator’sBusiness Location

SataraMaharashtra(ExcludingSatara)

Out ofMaharashtra

Foreign

1. Satara 70 302. Satara 75 253. Satara 10 40 48 24. Satara 1005. Satara 1006. Mahabaleshwar 60 407. Mahabaleshwar 5 70 258. Kolhapur 40 309. Kolhapur 85 510. Mumbai 100

Data Analysis


Table 4.2.5.1 depicts that Satara sample tour operator receives majority business from

Satara. Mahabaleshwar sample tour operator receives business from Maharashtra and

out of Maharashtra. Kolhapur sample tour operator receives business from Satara and

Maharashtra (excluding Satara).

Tourist Purpose as Per Tour Operators’ OpinionFollowing table shows the opinions of tour operators on tourist objectives to visit

Satara. Tour operators have responded to different tourist objects viz. business,

adventure, leisure, pilgrimage, culture and other to visit Satara and registered their

response in percentage figures since the questions was open ended.

Table 4.2.5.2Opinion of Tour Operators on Tourist Objects to Visit Satara

(n=10)

Sr.

Tourist Objects

Tour Operator’sBusiness Location B

usin

ess

Adv

entu

re

Lei

sure

Pil

grim

age

Cul

ture

Oth

ers

1. Satara 5 80 10 2 32. Satara 99 13. Satara 50 304. Satara 5 30 40 20 55. Satara 70 10 206. Mahabaleshwar 1007. Mahabaleshwar 1008. Kolhapur 5 5 30 40 209. Kolhapur 20 50 3010. Mumbai 40 60

Source: Field Data

Table 4.2.5.2 depicts majority of total sample of tour operator opines that that leisure

is the main object of tourist to visit Satara. Tourist also visits to Satara for pilgrimage

opined by sample tour operator of Satara and Kolhapur as both are organizes the

pilgrimage tour packages for Satara and other services like business, adventure,

culture are ignored by total sample tour operators as their interest is only with routine

packages.

Data Analysis


Perception of Tour Opeators on Tourist Season

Following table reveals the Perception of tour operators on tourist peak season, off-

season and special season for Satara. Data have collected through open-ended

question and presented in original form.

Table 4.2.5.3Perception of Tour Operators on Tourist Season at Satara

(n=10)

Sr.

Tourist Season

Tour Operator’sBusiness Location

Peak SeasonOff

SeasonSpecialSeason

1. Satara Aug-Sept Nov-March2. Satara April-May3. Satara Sept-Oct4. Satara April-May Aug ,Sept5.

SataraApril-May-June, Sept-

Oct6. Mahabaleshwar May-June Rainy7.

MahabaleshwarDiwali And March To

June8. Kolhapur Nov-Dec June-July April9.

Kolhapur Oct-NovMarch-

AprilSchools

10.Mumbai Aug-Sept

KasFlowering

Source: Field Data

Table 4.2.5.3 shows that majority of sample tour operators have their peak season

from April to June and off-season from June to July at Satara. From Mid Aug to mid

Sept is the special season for them at Satara.

Data Analysis


Tourist Origin According to Tour Operator

Following table shows the origin of tourist who are the customers of tour operator.

Table 4.2.5.4Origins of Tourists Who are the Customer of Tour Operator

(n=10)

Sr. Name of Town F %1 Pune 4 402 Mumbai and Surrounding 6 603 Satara Interiors 2 204 Sangli 2 205 Kolhapur 3 306 Bangalore 1 107 Gujarat 1 108 Surat 1 109 Hydrabad 1 1010 Hubali, Belgaon 1 10

Source: Field Data

Table 4.2.5.4 reveals the majority i.e. 60% tour operators’ perception, about the origin

of tourist traffic for their business is Mumbai and surrounding. 40% felt Pune, 50%

getting the business from out of Maharashtra as 10% each from Bangalore, Gujarat,

Surat, Hydrabad, Karnataka (Hubali and Belgaon), 30% from Kolhapur, and 20%

each from Sangli and Satara interiors. Thus, most of the business comes from

Maharashtra and very meager comes from out of Maharashtra. It can be inferred that

tour operators’ business activity is limited to Maharashtra.

Major Thirst of Tourist According to Tour Operator

Following table shows the opinion of respondents about the thirst of tourist services.

It is the experience of tour operators that tourist demands served services from tour

operators. The services are taken on rank as follows.

Data Analysis


Table 4.2.5.5Tour operator’s Opinion on Major Thirst of Tourist Services

(n=10)

Sr.Rank Frequency

Name of Services1 2 3 4 5

1 Air and Rail ticket booking 2 3 1 0 02 Hotel Booking 5 2 2 0 03 Local Transport Vehicle 0 5 3 1 04 Tour Guide 0 0 2 4 05 Package Tour 3 0 0 1 36 Entertainment 0 0 0 0 1

Source: Field Data

Table 4.2.5.5 orates on six thirsts areas of tourist services in the view of tour operator.

Most of the tour operators’ opines that major thirst is hotel booking and local

transport vehicle since the frequency is more concentrated to first priority

followed by package tour and ‘air and rail ticket booking’. No single tour operator

feels entertainment services can be major thirst of tourist.

Tourist Handled by Tour Operator

Following table presents the opinion of tour operators on average tourist handled by

them in a year.

Table 4.2.5.6Average Tourist Handled in a year by Tour Operators

(n=10)

Sr. Number of Tourist F %1. 100-1000 4 402. 1000-10000 4 403. 10000 and above 2 20


Table 4.2.5.6 reveals that 60% of tour operators have handled more than 1000

tourists. 40% tour operators handled up to 1000 tourists, and 40% have handled 1000-

10000 tourists and 20% have handled more than 10000 tourists in a year.

Data Analysis


Tour Packages by Tour Operator

Following table presents the tour package offered by tour operators for Satara

destination. The data is qualitative in nature.

Table 4.2.5.7Tour Package Offered by Tour Operator for Satara

Sr. Name of Package1. Kas-Thoseghar-Sajjangarh2. Sajjangarh--Chaphal-Gondawale-Ajinkya Fort and Kas-Bamnoli-Satara3. 11Maruti( God Hanuman), Gondawale-Sajjangarh-Chaphal,Mahabaleshwar-

Panchgani-Pratapgarh4. Mahabaleshawar-Panchgani; Wai; Kaas; Audh; Koynanagar5. Kas-Thoseghar-Sajjangarh, Aundh Museum6. Mahabaleshwar and Panchgani7. Mahabaleshwar Sight Scene 11 Points and 7 Points Two Packages, Panchgani

Darshan, Pratapgarh, Mini Kashmir-Tapola,Watersport, TriveniSangam,Bamnoli Point and Shooting Point

8. Mahabaleshwar, 11 Maruti9. 11 Maruti, Aundh, Chaphal School Trip10. Thoseghar-Sajjangarh-Satara-Kas- Bamnoli- Ajinkya Tara-SataraSource: Field Data

Table 4.2.5.7 reveals that various options for the tourist who wish to visit Satara. It

has observed that majority of them offer ‘11 Maruti’ Tour package and ‘Kas-

Thoseghar- Sajjangarh’ tour package. Recently the Mumbai tour operators have

started offering ‘Kas-Thoseghar-Sajjangarh’ and ‘Thoseghar-Sajjangarh-Satara-Kas-

Bamnoli- Ajinkya Tara-Satara’ packages.

Promotion Slab for Tour Operator

Following table depicts Promotional activities are undertaken by tour operators.

Researcher assessed opinion of tour operators as to when the promotion activities are

undertaken.

Data Analysis


Table 4.2.5.8Time Slab for Promotion Activities by Tour Operator

(n=10)

Sr. Time Period F %1 All Around the Year 5 502 During Tourism Season 2 203 Before the Season 0 004 Other* 3 30

Total 10 100Source: Field Data*Other means no need to promote the business.

Table 4.2.5.8 depicts that 50% of the tour operators’ conduct promotional activities

‘all around the year’, whereas 30% respondents do not find any need to promote the

business and 20% tour operators conduct promotional activities ‘during tourist

season’. It infers that 80% tour operators do not take any promotional measures

during tourism season. 30% tour operators do not find any need because they do their

business through franchise.

Data Analysis


Section VI

4.2.6 Comparative Analysis:

This part narrates the comparative opinions of stakeholder viz. tourist, hoteliers and

tour operators. Many questions were asked to all stakeholders for an effort to assess

perceptual differences. The comparative analysis were held on destination awareness,

opinions on its worth seeing, promotion of Satara, media effectiveness, media

preference, potential to Satara, tourism services and amenities available in Satara. The

responses are collected on 5-point scale and analyzed by tools using mean, standard

deviation and rank is calculated for analyzing the data that is presented in followed

tables. A percentage is also used as per the requirement of data. Each table describes

the opinion of each stakeholder and comparative opinions analyzed at the end of all

individual opinions. Obtained figures, information from officials and observation is

considered for discussion. Being tourist as target customer his opinion is compared

with others.

4.2.6.1 Awareness of Destination:

This part depicts the awareness of stakeholder viz. tourist, hoteliers, and tour

operators of different destinations of Satara. There are numbers of worth seeing

tourist destinations in Satara. Researcher has taken 38 tourist destinations of Satara to

test viz. Thoseghar, Sajjangarh, shri Shkestra Mahuli, Kas, Dhawadshi, Yawateshwar,

Agashiv, Pal, Santoshgad, Nana Phadniswada, Narsinhmandir(Dhom), Pratapgarh,

Tapola, Chavaneshwar, Kalyangad, Bamnoli, Mauje Kharkhel, Aundh, Mayani,

Katgun, Jairamswami Vadgaon, Mauje Bhosare, Naygaon, Ramghal, Ozarde and

Marul Haveli to know its awareness by visited tourists. The destinations viz.

Mahabaleshwar and Panchgani has not been added. Researcher has also probe into the

opinions of sample tourists on worth seeing-visited destinations of Satara. The data is

to be collected through dichotomous type of questions . The collected responses were

analyzed with the percentage method.

Data Analysis


Awareness by Tourist

Following table represents the awareness of different tourist destinations of Satara by

sample tourist. The photographs taken by researcher has attached for more

clarification and to get an idea of destinations.

Table 4.2.6.1.1Awareness of Sample Tourist of Different Tourist Destinations in Satara

(n=326)

Sr.

Opinion

Name of Places

Visited DestinationOpinion About its Worth

seeing

Yes % No % Yes %No

%

1. 2. 3. 4. 5. 6. 7. 8. 9.1. Thoseghar 156 47.9 170 52.15 153 100 0 0.002. Sajjangad 191 58.6 135 41.41 191 97.45 5 2.553. Shri Shkestra

Mahuli51 15.6 275 84.36 47 95.92 2 4.08

4. Kas 141 43.3 185 56.75 139 97.20 4 2.805. Dhawadshi 11 3.37 315 96.63 7 53.85 6 46.156. Yavateshwar 52 16 274 84.05 47 100 0 0.007. Agashiv 18 5.52 308 94.48 18 66.67 9 33.338. Pal 39 12 287 88.04 31 100 0 0.009. Santoshgad 2 0.61 324 99.39 2 20.00 8 80.0010. Nana Phadniswada 37 11.3 289 88.65 30 88.24 4 11.7611. Narsinha

Mandir(Dhom)33 10.1 293 89.88 30 100 0 0.00

12. Pratapgarh 203 62.3 123 37.73 203 97.60 5 2.4013. Tapola 125 38.3 201 61.66 121 100 0 0.0014. Chavneshwar 36 11 290 88.96 36 97.30 1 2.7015. Kalayangad 4 1.23 322 98.77 3 100 0 0.0016. Bamnoli 48 14.7 278 85.28 48 100 0 0.0017. Mauje Kharkhel

(SantajiGhorpadeSamadhi)

23 7.06 303 92.94 13 68.42 6 31.58

18. Aundh81 24.8 245 75.15 87 87.00

13

13.00

19. Mayani 43 13.2 283 86.81 30 83.33 6 16.6720. Katgun 14 4.29 312 95.71 8 88.89 1 11.1121. Jairamswami,

Vadgaon4 1.23 22 98.77 3 100 0 0.00

22. MaujeBhosare,(PratapraoGujar Smarak)

4 1.23 322 98.77 4 80.00 1 20.00

Data Analysis


23. Naygao( SavitribaiPhule Birthplace)

17 5.21 309 94.79 16 84.21 3 15.79

24. Ramghal 9 2.76 317 97.24 6 85.71 1 14.2925. Ozarde Panchdhara

Waterfall65 19.9 261 80.06 54 100 0 0.00

26. Marul Haveli 10 3.07 316 96.93 20 83.33 4 16.6727. Koyananagar

Dam/Nehrugarden92 28.2 234 71.78 78 95.12 4 4.88

28. Banpuri, Naikeba 25 7.67 301 92.33 22 91.67 2 8.3329. Valmiki 13 3.99 313 96.01 13 81.25 3 18.7530. Dhareshwar 16 4.91 310 95.09 16 100 0 0.0031. Koyna 92 28.2 234 71.78 71 89.87 8 10.1332. Vasota 40 12.3 286 87.73 24 88.89 3 11.1133. Pateshwar 20 6.13 306 3.87 30 93.75 2 6.2534. Gondawale 63 19.3 263 80.67 51 92.73 4 7.2735. Natraj Mandir 46 14.1 280 85.89 41 85.42 7 14.5836. Shivaji Museuem 31 9.51 295 90.49 24 85.71 4 14.2937. Petri 24 7.36 302 92.64 25 78.13 7 21.8838. Shikhar Shingnapur 57 17.5 269 82.52 46 100 0 0.00Source: Field Data

Table 4.2.6.1.1 depicts that Pratapgarh and Sajjangarh is mainly seen by tourists.

Out of 38 destinations only 8 destinations viz. Pratapgarh (62.3), Sajjangarh (58.6%),

Thoseghar (47.9%), Kas (43.3%), Tapola (38.3%), Aundh (24.8%), and Koyna/

Koynanagar (28.2%) are visited by tourists and almost all the tourists felt these

locations are worth seeing. Tourists overlook rests 30 destinations and awareness

percentage is in between 2 to 20% only. However, the sample tourists who have

visited these destinations feel worth seeing perception about these destinations, which

accounts to 80 to 100%. Therefore, it is inferred that only the tourists visit few known

destinations and most of the destinations are aware nor they are visited by the tourists.

It shows that destinations are not properly popularized to attract tourists.

Data Analysis


Awareness by Hotels

As like tourists researcher has also asked the same questions to sample hoteliers.

Following table shows the sample hoteliers opinion on visited destination in Satara

Table 4.2.6.1.2Sample Hoteliers Visited the Tourist Destinations in Satara

(n=40)

Sr

Opinion

Name of TouristPlaces in Satara

District

Visited DestinationOpinion about its worth

seeing

Yes % No %Yes

% No %

1. 2. 3. 4. 5. 6. 7. 8. 9.1. Thoseghar 23 57.5 17 42.5 23 100 0 02. Sajjangad 23 57.5 17 42.5 23 100 0 03. Shri Shkestra

Mahuli16 40 24 60 15 93.75 1 6.25

4. Kas 22 55 18 45 22 100 0 05. Dhawadshi 10 25 30 75 9 90 1 106. Yavateshwar 15 37.5 25 62.5 15 100 0 07. Agashiv 8 32 80 8 100 0 08. Pal 12 30 28 70 11 92.67 1 8.339. Santoshgad 3 7.5 37 92.5 3 100 0 010. Nana Phadniswada 8 20 32 80 8 100 0 011. Narsinha mandir

(Dhom)8 20 32 80 8 100 0 0

12. Pratapgad 7 17.5 33 82.5 7 100 0 013. Tapola 35 87.5 5 12.5 35 100 0 014. Chavneshwar 31 77.5 9 22.5 31 100 0 015. Kalayangad 4 10 36 90 4 100 0 016. Bamnoli 4 10 36 90 4 100 0 017. Mauje Kharkhel(

Santaji Ghorpade)18 45 22 55 18 100 0 0

18. Aundh 4 10 36 90 4 100 0 019. Mayani 20 50 20 50 20 100 0 020. Katgun 8 20 22 55 8 100 0 021. Jairamswami,

Vadgaon5 12.5 35 87.5 5 100 0 0

22. MaujeBhosare,(PratapraoGujar smarak)

5 12.5 35 87.5 5 100 0 0


3 7.5 37 92.5 3 100 0 0

Data Analysis


Source: Field Data

Table 4.2.6.1.2 depicts that out of 38 destinations hoteliers have seen very few

destinations as Tapola by 87.5%, Shikhar Shingnapur by 80%, 77.5% hoteliers have

seen Chavaneshwar, 65% Banpuri(Naikeba), 57.5% each Thoseghar and Sajjangarh,

55% Kas and 50% Mayni. Hoteliers do not often see rest 30 destinations. Gondawale

and Natraj mandir 42.5%, 40% each have visited Vasota and Marul haveli, Mauje

Karkhel 45%, 40% Skshetra Mauli and 37.5% Yawateshwar. Majority of hoteliers

does not know rests of the destinations. Those who have visited they feel all are worth

seeing but according to few hoteliers’ 8.33% sample hoteliers feel ‘Pal’ and 6.25%

thinks ‘Skshetra Mahuli’ and 10% think ‘Dhawadshi’ are not worth seeing. Thus,

excluding these three destinations, most of the destinations are worth seeing for tourist

and these are not seen by most of the hotel owners so need to be aware of the same.

Thus, it concludes that there is lack of awareness among the hoteliers about the

destinations available in Satara.

24. Ramghal 7 17.5 33 82.5 7 100 0 025. Ozarde Panchdhara

Waterfall7 17.5 33 82.5 7 100 0 0

26. Marul Haveli 16 40 24 60 16 100 0 027. Koyananagar

dam/Nehrugarden7 17.5 33 82.5 7 100 0 0

28. Banpuri, Naikeba 26 65 14 35 26 100 0 029. Dhareshwar 8 20 32 80 8 100 0 030. Valmiki 5 12.5 35 87.5 5 100 0 031. Koyna 7 17.5 33 82.5 7 100 0 032. Vasota 16 40 24 60 16 100 0 033. Pateshwar 5 12.5 35 87.5 5 100 0 034. Gondawale 17 42.5 23 57.5 17 100 0 035. Natraj Mandir 17 42.5 23 57.5 17 100 0 036. Shivaji Museuem 14 35 26 65 14 100 0 037. Petri 9 22.5 31 77.5 9 100 0 038. Shikhar Shingnapur 32 80 8 20 32 100 0 0

Data Analysis


Awareness by Tour Operators

Unlike tourists and hoteliers even tour operators are also interviewed on same

variables. Following table talks about the sample tour operators visited locations in

Satara.

Table 4.2.6.1.3Sample Tour Operators visited the Tourist locations in Satara

(n=10)

Sr.

Name of TouristPlaces in Satara

District

Seen DestinationOpinion about Worth

seeing

Yes % No % Yes % No %

1. 2. 3. 4. 5. 6. 7. 8. 9.1. Thoseghar 9 90 1 10 9 100

2. Sajjangad 9 90 1 10 9 1003. Shri Shkestra

Mahuli5 50 5 50 5 83.33 1 16.7

4. Kas 9 90 1 10 9 1005. Dhawadshi 1 10 9 90 1 50 1 506. Yavateshwar 6 60 4 40 6 100

7. Agashiv 0 0 10 100 0 100

8. Pal 2 20 8 80 2 1009. Santoshgad 0 0 0 100 010. Nana Phadniswada 4 40 6 0 4 66.67 2 33.3

11. Narsinhamandir(Dhom)

2 20 8 0 2 .67 1 33.3

12. Pratapgarh 4 40 6 0 4 80 1 20

13. Tapola 9 90 1 10 9 10014. Chavneshwar 7 70 3 30 7 10015. Kalayangad 1 10 9 90 1 100

16. Bamnoli1

10

9 90 1 100

17. Mauje Kharkhel(Santaji Ghorpade)

7 70 3 30 7 100

18. Aundh 0 0 10 100 0 10019. Mayani 9 90 1 10 9 10020. Katgun 4 40 6 60 4 10021. Jairamswami,

Vadgaon0 0 10 100 0 100

Data Analysis


22. MaujeBhosare,(PratapraoGujar smarak)

1 0 9 90 1 100


0 0 10 100 0 100

24. Ramghal 0 0 10 100 0 100

25. Ozarde PanchdharaWaterfall

2 20 8 80 2 100

26. Marul Haveli 6 60 4 40 6 10027. Koyananagar

dam/Nehrugarden0 0 0 100 0 100

28. Banpuri, Naikeba6

60

4 40 6 100

29. Dhareshwar 2 20 8 80 2 10030. Valmiki 2 20 8 80 2 100

31. Koyna 1 10 9 90 1 100

32. Vasota 7 70 3 30 7 87.5 1 12.5

33. Pateshwar 7 70 3 30 7 87.5 1 12.5

34. Gondawale 5 50 5 50 5 100

35. Natraj Mandir 7 70 3 30 7 100

36. Shivaji Museuem 5 50 5 50 5 100

37. Petri 5 50 5 50 5 100

38. Shikhar Shingnapur 6 60 4 40 6 85.7 1 14.3Source: Field Data

Table 4.2.6.1.3 depicts that most of tour operators i.e. 90% visit Thoseghar,

Sajjangarh, Kas, Tapola, Mayni, followed by 70% tour operators visited to

Chavaneshwar, Mauje Kharkhel, Vasota, Natraj mandir. 60% visit to Banpuri,

Marul Haveli and Yewateshwar. Whereas locations like Agashiv, Santoshgarh,

Aundh, Jairamswami (Vadgaon), Naygaon, Ramghal, Koynanagar dam has not

seen at all by these tour operators, followed by 90% tour operator did not visited

locations like Dhawadshi, Kalyangarh, Bamnoli, Mauje Bhosare and Koyna while

80% did not visits Valmiki, Dhareshwar, Ozarde, Narsinh Mandir and Pal. Nana

Phadniswada, Pratapgarh and destination Katgun were not visited by 60% of tour

operators. It infers that more than 50% of locations as mentioned above were not

visited by tour operator since they were not aware of them. Those who have visited

locations feel the locations are worth seeing.

Data Analysis


Data depicts that Pratapgarh and Sajjangarh the well-known destinations only were

seen by majority of tourist.Whereas Tapola, Shikhar Shingnapur, Chavaneshwar,

Banpuri (Nikeba), Thoseghar, and Sajjangarh destinations are seen by majority of

sample hotel owners. Thoseghar, Sajjangarh, Kas, Mayani,Tapola, Chavaneshwar,

Vasota, Pateshwar, Natraj Mandir,Aundh,Marul Haweli,Shikhar Shingnapur

destinations are seen by majority of tour operators. It infers that stakeholders had not

seen most of the destinations and they are not aware of these destinations. There was

no single stakeholder who has not seen all the destinations nor had noticed all of

them. Tour operators knew more destinations compared to hoteliers or tourist.

It is observed that tourist are interested to visit other destinations of Satara, hoteliers

are not taking initiative to make them aware unless tourist show their interest. Tour

operators emphasizes on traditional tour packages like 11 Maruti, Sajjangarh and

shows more interest to promote only few destinations which are popular like Kas,

Thoseghar and Sajjangarh. There is lack of communication of destinations by

hoteliers and tour operators to tourist. Researcher has also observed most of the

destinations were neither seen nor they were aware by government officials who

sanctioned and implemented tourist development plans. Thus, it infers that most of the

destinations of Satara are unexploited to be developed district as a tourist destination.

Data Analysis


4.2.6.2 Effectiveness of Media in Promotion of Tourism:

This part talks on the perception of all the stakeholders on media effectiveness in

promotion of tourism. There are 11 Medias options considered to know its

effectiveness by stakeholders. Media plays important role in the promotion of

destinations. These responses are mirrored in the following table with its respective

mean, standard deviation, and rank with spearman’s correlation score.

Media Effectiveness as Per Tourist

Following table presents opinion of sample tourists on effectiveness of media in the

promotion of tourism. It reflects the Medias preference by sample tourist to know the

respective destinations of Satara.

Table 4.2.6.2.1Opinion of Sample Tourists on Effectiveness of Media in Promotion of Tourism

(n=326)

Sr.

Gender

Media

Male Female Total

Mean S.D. Rank Mean S.D. Rank Mean S.D. Rank

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.1. Newspaper

Advertisement3.95 0.65 6 3.95 0.66 6 3.95 0.65 6

2. Television Advertisement 4.01 0.72 3 4.01 0.72 3 4.01 0.72 33. Magazine Advertisement 3.78 0.78 8 3.76 0.78 8 3.78 0.78 84. Information aterials(Brochures,

Guides, Souvenirs, Folders,Handbooks)

3.98 0.95 4 3.97 0.96 4 3.98 0.95 4

5. Posters 3.55 0.81 9 3.55 0.81 9 3.55 0.81 96. Website/Internet Ad 4.31 0.85 2 4.31 0.85 2 4.31 0.85 27. Motivation by Tour

Operators3.85 1.00 7 3.86 1.00 7 3.85 1.00 7

8. Word-of-Mouth 4.46 0.70 1 4.47 0.70 1 4.46 0.70 19. Newspaper Articles

Related to Tourism3.97 0.88 5 3.97 0.88 4 3.97 0.88 5

10. Publication of in HouseLetters

3.54 0.71 10 3.54 0.71 10 3.54 0.71 10

11. Yellow Pages 2.55 0.85 11 2.55 0.85 11 2.55 0.85 11Correlation Coefficient male and female .991**


Data Analysis


Table 4.2.6..2.1 depicts that Word of Mouth (WOM), Website/Internet advertisement,

and Television are most preferred media in the promotion of tourism and yellow

pages, publication of in house letters and a poster are the least preferred by

respondents

Word of Mouth (WOM), Website/Internet advertisement and Television carries mean

score more than 4 and received rank 1st, 2nd and 3rd respectively. Media like yellow

pages, publication of in house letters, and a poster whose mean score is below 4 and

received ranks are 11, 10 and 9 respectively.

The Spearman’s rank correlation coefficient of perception of male and female on

effectiveness of media for tourism is 0.991 with ‘P’ value 0.00, which is significant at

0.01 levels (2-tailed). This signifies perception of effectiveness of media in promotion

of tourism is uniform in male and female.

Media Effectiveness as Per Hoteliers

Following table presents opinion of sample hoteliers on effectiveness of media for

promotion. For effective communication, media weightage according to the

respondents is reveal in the following table.

Table 4.2.6.2.2Opinion of Sample Hoteliers on Effectiveness of Media for Promotion

(n=40)

Source: Field Data3

Sr.Media Mean SD Rank

1. 2. 3. 4.1. Newspaper Advertisement 3.04 3.04 92. Television Advertisement 3.42 3.42 53. Magazine Advertisement 3.19 3.19 84. Information Materials(Brochures, Guides,

Souvenirs, Folders, Handbooks)4.00 4.00 3

5. Posters 3.81 3.81 46. Website/Internet Ad 3.13 3.13 107. Motivation by Tour Operators 4.51 4.51 28. Word-of-Mouth 4.00 4.00 69. Newspaper Articles Related to Tourism 4.65 4.65 110. Publication of in House Letters 3.56 3.56 711. Yellow Pages 2.91 2.91 11

Data Analysis


Table 4.2.6.2.2 depicts that media like ‘newspaper articles related to tourism’,

‘motivation by tour operators’ and ‘information materials’ are more effective for

promotion as they received rank first, second and third respectively and their mean

score is more than 4. The l The least effective media are ‘website/internet

advertisement’, ‘newspaper advertisement’ and ‘magazine advertisement’ as the mean

score is less than 4 and ranks are in bottom three i.e.10th, 9th and 8th respectively.

Less effective media are ‘website/internet advertisement’, ‘newspaper advertisement’

and ‘magazine advertisement’ as the mean score is less than 4 and ranks are in bottom

three i.e.10th, 9th and 8th respectively.

Media Effectiveness as Per Tour Operator

Following table shows the opinion of sample tour operators on effectiveness of media

for promotion.

Table 4.2.6.2.3Opinion of Sample Tour Operators on Effectiveness of Media for Promotion

(n=10)

Sr. Media Mean SD Rank1. Newspaper Advertisement 4.10 0.74 32. Television Advertisement 4.00 0.50 53. Magazine Advertisement 3.67 0.87 94. Information Materials(Brochures, Guides,

Souvenirs, Folders, Handbooks)4.33 0.71 4

5. Posters 4.25 0.89 76. Website/Internet Ad 4.78 0.44 27. Motivation by Tour Operators 4.50 0.53 58. Word-of-Mouth 4.60 0.52 19. Newspaper Articles Related to Tourism 4.25 0.71 710. Publication of in House Letters* 3.43 0.98 1011. Yellow Pages 2.83 1.17 11Correlation Coefficient .073Sig. (2-tailed) .831

Source: Field Data* Publication of in House Letters is the in-house publication of Chudhari Travels thatshares tourist experiences on traveled area.

Table 4.2.6.2.3 reveals that media of promotion like ‘Word of mouth’,

‘Website/internet advertisement’, ‘Newspaper advertisement’ and ‘Information

Data Analysis


material’ are more effective in the perception of tour operator , as they received

rank 1st,2nd,3rd and 4th respectively and their mean score is more than 4. ‘Yellow

pages’, ‘Publication of in house letters’, and ‘Magazine advertisement’ are the least

effective media according to the perception of tour operators as they received rank 11,

10 and 9 respectively and the mean score is less than 4.

To investigate into the depth of analysis researcher has tested with the help of

spearman’s rank correlation’ the perception of tour operator and hoteliers. The

correlation coefficient is .073, with ‘P’ value 0.831, which is insignificant at 0.05

levels (2-tailed). It reveals that there is no uniformity into the opinion of tour

operators and hoteliers regarding media preference for promotion.

Data reveals that Word of Mouth (WOM), Website/Internet advertisement, and

Television are effective tools in tourist point of view. Whereas hoteliers thinks

‘newspaper articles related to tourism’, ‘motivation by tour operators’ and

‘information materials’ as a effective tool. However, tour operators think ‘Word of

mouth ’, ‘Website/internet advertisement, Newspaper advertisement, and ‘Information

material’ are more effective tool for communication. Therefore, there is difference of

opinion on effectiveness of media. One should consider those media that target

customers feel effective. It infers that word of mouth; website and television would be

effective tool for tourism promotion.

4.2.6.3 Source Usage for Promotion:

This part deals the sources used by different stakeholders for promotion. Each

stakeholder has his or her own objectives as per the nature of business. However, for

the sake of promotion of tourism researcher intend to find out the gap between source

used by tourist to know the destination with efforts of hoteliers and tour operators for

the same. Four advertising media are considered to know their efforts.

Data Analysis


Media Preference by Hoteliers

Following table depicts the opinion of hoteliers on media preference for promotion.

For advertisement respondents preference to various media on priority basis is

discourse in the following table.

Table 4.2.6.3.1Media Preferred by Hotelier for Promotion

(n=40)

Sr.

Rank Frequency

Name of Media1 2 3 4 5 Total

1 2 3 4 5 6 71 TV 1 2 3 4 5 152 Newspaper 3 0 2 1 0 63 Website 5 5 1 0 0 114 Brochure 20 4 0 3 0 275 Other* 1 14 6 0 0 21

Source: Field Data* Visiting cards, hoardings, word of mouth and Tour operator

Table 4.2.6.3.1 reveals about the media preference by hoteliers. It has found that

brochure is most preferred, followed by website and other (Visiting cards, hoardings,

word of mouth and Tour operator).

Television as a media used for the promotion is rear by hotel owners.

Media Preference by Tour Operator

Following table depicts media preference by tour operator for the promotion of their

product. Preferences are taken on ranks.

Table 4.2.6.3.2Media Preference by Tour Operator for Promotion

(n=10)

Sr.Rank FrequencyMedia Preference

1 2 3 4 5 Total

1. TV 0 0 1 1 0 22. Newspaper 2 1 2 0 0 53. Website 5 2 1 0 0 84. Brochure 3 3 2 0 0 85. Other 1 1 0 0 0 2

Source: Field Data

Data Analysis


Table 4.2.6.3.2 depicts that for promotion tour operators prefers website andbrochures rather than other options like television, newspaper and ‘other’ since therank frequency is concentrated on these two media.

Actual Source Used by TouristFollowing table represents sources used by sample tourists to know the respectivelocations of Satara. The data is presented location wise.Table 4.2.6.3.3Sources Used by Sample Tourists to Know the Destination

(n=326)

Source: Field Data*Magazine

Sr

Name of Source

Name of Places

Tel

evis

ion

Ad

New

spap

er

Tra

vel G

uide

Tra

vel

Age

nt/T

our

oper

ator

Web

site

Pers

onal

Eff

ort

Frie

nds/

Rel

ati

ves

Oth

er(P

l.Sp

ecif

y)*

Tot

al

F % F % F % F % F % F % F % F % F %

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

1. Aundh4

13.3

3

26

86.6

7

30 100

2. Mahabaleshwar 1

3.33 10

33.3

3

6 20 13

43.3

3

30 100

3. Panchgani

1

2.86 8

22.8

6

24

68.5

7

2

5.71 35 100

4. Pratapgarh

1

3.33 4

13.3

3

3 10 11

36.6

7

11

36.6

7

30 100

5. Wai

4

10.8

1

7

18.9

2

7

18.9

2

19

51.3

5

37 100

6. Sajjangarh

1

3.33 3 10 1

3.33 11

36.6

7

9 30 5

16.6

7

30 100

7. Thoseghar

33 100

33 100

8. Kas

6 20 22

73.3

3

2

6.67 30 100

9. Ajinkya-Tara

1

2.94 17 50 1

2.94 15

44.1

2

34 100

10. Koyna

1 2.7 1 2.7 3

8.11 32

86.4

9

37 100

Total

1

0.31 4

1.23 1

0.31 27 8.28 30 9.2

50

15.3

4

204

62.5

8

9

2.76

326

100

Data Analysis


Table 4.2.6.3.3 inferred that respondents preferred to reliable source ‘friends and

relatives’ to know the destinations of Satara. It infers that local community plays

important role in the promotion of tourism.

62.58% of tourists have adopted source ‘friends and relatives’ to know the

destination, followed by 15.34% tourists used ‘personal effort’.

Friends and relatives have been used the major source of information by majority of

tourists. Destination Aundh is visited by 86.67%, Mahabaleshwar is visited by

43.33% of tourists with this source, 68.57% of tourists visited Panchgani, 36.67%

tourists visited Pratapgarh, 51.35% Wai, and the entire tourists visited Thoseghar

through the source of friends and relatives. Kas is known to 73.33% of tourists

through friends and 88.49% of tourists known Koyna through friends and relatives.

Ajinkyatara is visited by 50% of tourist with source of information tour operator and

travel agent. However, 36.67% of the tourists have used ‘personal effort’ to know the

destination Sajjangarh and Pratapgarh. Personal efforts made out of curiosity, sample

tourists have searched and collected information from all the possible sources and not

specific.

Data depicts that brochure is more preferred by hoteliers and very few go for website.

Whereas website is more preferred by tour operators and few go for brochure.

However, tourist widely uses ‘friends and relatives’ a reliable source to know the

destinations of Satara. It found the gap between target customer (tourist), service

providers (hoteliers and tour operators). Researcher has also noticed that government

is not taking effort to reach to tourist.

4.2.6.4 Potential of Tourism in Satara District:

This part contains perception of stakeholders on potential of tourism in Satara

District. It is observed that majority of the people have neither visited nor aware of

these worth seeing destinations. It is noticed that the tourist flow is intensifying

compared to earlier years. To know the opinion of tourist on potential to Satara seven

statements were developed. These statements assess the perception of stakeholders on

potential to attract tourists, use of package tour to attract tourists, adequacy of existing

Data Analysis


hotel facility and celebrity advertisement. These responses are analyzed with the help

of mean, standard deviation, rank, and spearman’s rank correlation.

Perception of Tourist on Potential

Following table shows the perception of sample tourists on potential of tourism in

Satara district. Researcher is also interested to know the perceptual gender difference

for the same. These details are mirrored in following table.

Table 4.2.6.4.1Perception of Sample Tourists on Potential of Tourism in Satara District

(n=326)

Sr.

Gender

Perception

Male Female TotalM

ean

SD Ran

k

Mea

n

S.D

Ran

k

Mea

n

S.D

Ran

k

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.1. Satara District has Potential to

Attract Tourist fromMaharashtra/India.

4.16 0.65 1 4.17 0.66 1 4.16 0.65 1

2. Few Destinations Only in SataraHave Potential to Attract ForeignTourist.

3.77 0.80 4 3.78 0.80 4 3.77 0.80 4

3. Satara District has Few Unexploitedbut Worth Seeing TouristDestination.

3.66 0.76 6 3.67 0.76 6 3.66 0.76 6

4. Package Tours Would be of GreatTourist Attraction for The Tourist inMaharashtra.

3.67 0.84 5 3.68 0.85 5 3.67 0.84 5

5. Package Tours Would be of GreatAttractions for the Tourist Outside ofMaharashtra.

3.84 0.80 3 3.84 0.81 3 3.84 0.80 3

6. Existing Hotel Facility is Adequatefor Tourist in Satara District.

3.660.

756 3.66 0.76 7 3.66 0.75 6

7. Advertisement by Celebrity WouldHelp Much to Attract Tourist toSatara.

3.85 0.85 2 3.86 0.84 2 3.85 0.85 2

Correlation Coefficient male and female .964**


Table 4.2.6.4.1 depicts that Satara has potential for tourism and there is no gender

difference in the perception.

All the seven statements show the mean score above three. Statement viz. Satara

district has potential to attract tourist from Maharashtra/India received first rank, as

Data Analysis


the mean score is highest (4.16). Followed by statement viz. advertisement by

celebrity would help much to attract tourist to Satara whose mean score is 3.85 and

received rank is 2nd and statement i.e. package tours would be of great attraction for

the tourist outside of Maharashtra received rank 3rd since the mean score is 3.84. It

focuses on potential of tourism in Satara.

The Spearman’s rank correlation of gender perception on potential of tourism is 0.964

with ‘P’ value 0.00, which is significant at 0.01 levels (2-tailed). Thus, there is

uniformity in the opinion of both male and female on potential of tourism in Satara to

attract the tourist.

Perception of HoteliersFollowing table presents the perception of hoteliers on potential of tourism in Satara.

Table 4.2.6.4.2Perception of Sample Hoteliers on Potential of Tourism in Satara District

(n=40)

Source: Field Data)

Table 4.2.6.4.2 represents perception of sample hotelier about the potential of tourism

with seven statements. The first rank received to the ‘Satara district has potential to

attract tourist from Maharashtra/India’ as the mean score is highest 4.48, 2nd rank

received to statement ‘existing hotel facility is adequate for tourist in Satara district’

as the means score is 4.08 and 3rd rank goes to ‘package tours would be of great

Sr.Statements of Perception Mean S.D Rank

1. 2. 3. 4.1. Satara District has Potential to Attract Tourist from

Maharashtra/India.4.48 0.55 1

2. Few Destinations Only in Satara Have Potential toAttract Foreign Tourist.

3.80 0.88 6

3. Satara District has Few Unexploited but WorthSeeing Tourist Destination.

3.98 0.73 4

4. Package Tours Would be of Great Tourist Attractionfor The Tourist in Maharashtra.

3.68 0.73 7

5. Package Tours Would be of Great Attractions for theTourist Outside of Maharashtra.

4.03 0.62 3

6. Existing Hotel Facility is Adequate for Tourist inSatara District.

4.08 0.89 2

7. Advertisement by Celebrity Would Help Much toAttract Tourist to Satara.

3.95 0.90 5

Data Analysis


attraction for the tourist outside of Maharashtra’ as the mean score is 4.03. So the

mean score of these three statements is more than 4. It infers that Satara has potential

to attract tourist. Thus, hotel facility and tour operator may help to increase tourism

development and tourist flow in Satara. The rest of the statements do not reflect the

confidence as the mean score is less than four i.e. neither agree nor disagree.

Perception of Tour Operators

Following table talks on perception of sample tour operators on potential of tourism in

Satara district.

Table 4.2.6.4.3Perception of Sample Tour Operators on Potential of Tourism in Satara District

(n=10)

Sr Perception about potential of tourism Mean SD Rank1. Satara District has Potential to Attract Tourist from

Maharashtra/India.4.3 0.48 1

2. Few Destinations Only in Satara Have Potential toAttract Foreign Tourist.

4 0.82 4

3. Satara District has Few Unexploited but Worth SeeingTourist Destination.

4.2 0.63 2

4. Package Tours Would be of Great Tourist Attractionfor The Tourist in Maharashtra.

3.8 0.79 6

5. Package Tours Would be of Great Attractions for theTourist Outside of Maharashtra.

4.1 0.88 3

6. Existing Hotel Facility is Adequate for Tourist inSatara District.

3.4 0.97 7

7. Advertisement by Celebrity Would Help Much toAttract Tourist to Satara.

4 0.94 4

Correlation Coefficient .090Sig. (2-tailed) .848Source: Field Data

Table 4.2.6.4.3 reveals that the four statements focuses on the potential of tourism as’

Satara District has Potential to Attract Tourist from Maharashtra/India’ that received

1st rank as the mean score is 4.3, ‘Satara District has Few Unexploited but Worth

Seeing Tourist Destination’ received second rank as the mean score is 4.2, ‘Package

Tours Would be of Great Attractions for the Tourist Outside of Maharashtra’ received

third rank as the mean score is 4.1 and ‘Advertisement by Celebrity Would Help

Much to Attract Tourist to Satara’ received fourth rank as the mean score is 4.

Data Analysis


To look into the depth of analysis researcher test the spearman’s rank correlation

between perceptions of tour operator with hotel owners on potential of tourism in

Satara. The correlation coefficient is 0.090 with ‘P’ value 0.848, which is insignificant

at 0.05 levels (2-tailed). This reveals that there is no uniformity into opinions among

tour operators and hoteliers.

Researcher is interested in first 3 ranked statements by tourist to infer the data. Data

focuses that all stakeholders strongly agreed with statement ‘Satara district has

potential to attract tourist from Maharashtra/India’ but there is difference of opinion

about other two statements that are ranked by tourist second and third.

Tourist strongly agreed on statement that ‘celebrity would help much to attract tourist

to Satara’ whereas hoteliers and tour operator do not agree since they ranked these

statement 5th and 4th respectively.

Tourist strongly agreed on statement ‘Package tour would be of great attraction for

the tourist outside of Maharashtra’ but tour operator and hotelier do not strongly agree

as they have given sixth and seventh rank respectively. It infers that all are carrying

similar perception that Satara district has potential to attract tourist from

Maharashtra/India.

4.2.6.5 Perception on Promotion of Tourism in Satara District:

This part deals with the perception of stakeholders on promotion of tourism in Satara

District. Promotion is important tool in marketing mix to deliver satisfaction to the

target customer. Different tools are used to promote tourism products like

advertisement, publicity, personal selling, and sales promotion. Researcher has

developed three statements viz. advertisement play important role in tourism, need of

promotion activities and lack of promotion hinder tourism development of Satara

District and collected the responses on 5 point scale as 1 for strongly disagree, 2 for

disagree, 3 for neither agree nor disagree, 4 for agree and 5 for strongly agree. Data

analyzed with Mean, Standard Deviation, rank and Spearman’s rank correlation. Each

stakeholder opinion described in following tables.

Data Analysis


Perception of Tourist

Following table shows the perception of sample tourists on promotion of tourism in

Satara district. It is observed that there is a lack of promotion in tourism sector of

Satara. To support the observation and to know its necessity the opinion of tourist

(Customer) on promotion of tourism in Satara is taken into granted. There may be

difference of opinions between male and female. Responses on the aforesaid

statements are existing in following table.

Table 4.2.6.5.1Perception of Sample Tourists on Promotion of Tourism in Satara District

(n=326)

Sr.

Name ofDestinationStatement ofPerception

Male Female Total

Mean S.D. Rank Mean S.D. Rank Mean S.D. Rank

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

1.AdvertisementPlay ImportantRole in Tourism

4.08 0.73 2 4.08 0.73 2 4.08 0.73 2

2.Need ofPromotionalActivities

4.19 0.74 1 4.19 0.74 1 4.19 0.74 1

3.

Lack ofPromotionHinder TourismDevelopment ofSatara District

4.02 0.89 3 4.01 0.89 3 4.02 0.89 3

Correlation Coefficient of male and female 1.000**

Sig. (2-tailed) 0.00

Source: Field Data**. Correlation is significant at the 0.01 level (2-tailed).

Table 4.2.6.5.1 infers that all three statements draw the attention on need of

promotion for tourism development in Satara district since the mean score is four.

Among the three statement the statement ‘need of promotional activities’ received 1st

rank due to its mean score is 4.19, ‘advertisement plays important role in

tourism’ received 2nd rank and has mean score 4.08 and the statement “lack of

promotion hinders tourism development of Satara district” received 3rd rank since

mean score is lesser compared to other two statements i.e. 4.02.

Data Analysis


The Spearman’s rank correlation between the opinions of male and female to the

perception on promotion of tourism in Satara is 1.000 with ‘P’ value 0.00, which is

significant at 0.01 levels (2-tailed). This reveals that there is uniformity into the

opinions of male and female.

Hoteliers Perception

Following table talks the perception of hoteliers on promotion of tourism in Satara

district.

Table 4.2.6.5.2Hoteliers’ Perception on Promotion of Tourism in Satara District

(n=40)

Source: Field Data

Table 4.2.6.5.2 infers that there is need of promotional activities for the tourism in

Satara district and advertisement will play important role for the same.

The statement ‘need of promotional activities’ received 1st rank as the mean score is

4.27 Followed by the statement ‘advertisement play important role in tourism’ with

the mean score is 4.02 received 2nd rank, ‘Lack of promotion hinders tourism

development of Satara district’ received 3rd rank and mean score is 3.95. The mean

score of a first two statements is more than 4. It signifies promotion is indispensable

to Satara tourism development.

Sr.Statement of Perception

Mean SD Rank

1. 2. 3. 4.1. Advertisement Play Important Role in

Tourism4.02 0.70 2

2. Need of Promotional Activities 4.27 0.85 13. Lack of Promotion Hinder Tourism

Development of Satara District3.95 0.68 3

Data Analysis


Tour Operators Perception

Following table reveals the perception of tour operators on promotion of tourism in

Satara district.

Table 4.2.6.5.3Tour Operators Perception on Promotion of Tourism in Satara District

(n=10)

Sr Statement of Perceptions Mean SD Rank1. Advertisement Play Important Role in

Tourism4.4 0.52 2

2. Need of Promotional Activities 4.8 0.42 13. Lack of Promotion Hinder Tourism

Development of Satara District4.3 0.95 3

Correlation Coefficient 1.000**

Significant(2-tailed) .00Source: Field Data

Table 4.2.6.5.3 infer that statement ‘need of promotional activities’ received rank 1st

as the mean score is 4.8 and statement ‘advertisement play important role in tourism’

received second rank as the mean score is 4.4 and 3rd rank received to the statement ‘

lack of promotion hinders tourism development of Satara district’ carries mean score

4.3. Thus it concludes that according to the perception of tour operators there is need

of promotion activities in Satara.

To investigate into the depth of analysis researcher has test the spearman’s rank

correlation between the perception of hoteliers and tour operators. The correlation

coefficient score is 1.000 with ‘P’ value 0.00, which is significant. It reveals uniform

opinions between tour operator and hotelier

It is notice that all stakeholders strongly agreed on three statements viz. ‘Need of

Promotional Activities’, ‘Advertisement Play Important Role in Tourism’ and ‘Lack

of Promotion Hinders Tourism Development of Satara District’. All are carrying

uniform opinion that Satara needs promotional activities. Lack of promotion hindered

tourism development and advertisement will be helpful to promote tourism.

Data Analysis


4.2.6.6 Perception of Stakeholders on Satisfaction towards the tourist Servicesand Amenities available in Satara:

This part depicts the perception of stakeholders on satisfaction of tourist services and

amenities available in Satara district. There are 33 tourist services and amenities are

considered to know their opinions. Researcher is intending to find out the gap

between perception of tourist with service provider hoteliers and tour operators. Data

is collected on 5-point likert scale and analyzed with mean, standard deviation, and

rank score. To probe into the depth of analysis researcher has calculated spearman’s

rank correlation between perceptions of tourist and other stakeholders i.e. hotelier and

tour operator.

Satisfaction Level of Stakeholders

Following table orate on sample units as tourists, hoteliers, tour operators’ opinion on

satisfaction of tourists’ services and amenities in Satara.

Table: 4.2.6.6.1Satisfaction of Tourism Stakeholders towards the Tourist Services and Amenities

Sr.

Stakeholders’Perception

Tourist Service andAmenities

Tourists’Satisfaction

Hoteliers’Satisfaction

Tour Operators’Satisfaction

MeanRank

S.D. MeanRank

S.D. MeanRank

S.D.

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

1.Air ConnectivityStatus

1.29 33 0.49 1.17 33 0.38 1.71 33 1.11

2. Rail ConnectivityStatus

1.96 32 0.76 2.20 32 0.91 2.90 15 0.99

3. Quality of the Roads 3.17 16 0.95 2.90 25 1.08 3.00 11 0.944. Quality of Way Side

Amenities Availableon This Road

3.30 14 0.80 3.40 16 0.98 2.80 18 1.40

5. Public ConveniencesAlong Roads/Streets

3.02 23 0.96 3.13 22 1.18 2.60 22 1.35

6. Sewage and DrainageSystem

3.11 20 0.94 3.00 24 1.13 2.11 31 0.78

7. Garbage Disposal 3.16 17 0.85 3.10 23 1.12 2.30 28 1.068. Condition of City

Roads2.79 29 1.09 2.90 25 1.13 2.20 29 1.14

9. Drinking WaterSupply

3.43 11 0.81 3.67 12 0.77 2.80 18 1.14

10. Condition of StreetLighting

3.40 12 0.86 3.40 16 1.01 2.90 15 1.20

Data Analysis


11. Traffic Management 2.92 28 1.12 2.90 25 1.30 2.20 29 0.9212. Condition of Traffic or

Transport Signage3.10 21 1.02 3.73 11 0.82 3.00 11 1.15

13. Availability ofCommercialTransportations

3.52 10 0.83 4.13 2 0.52 3.90 2 0.74

14. Behaviour of theDrivers of CommercialTransportations

3.75 6 0.71 4.13 2 0.40 3.80 3 0.79

15. Availability ofAuthorized TourOperators

2.99 24 0.87 3.58 13 0.75 3.40 10 0.97

16. Availability of Hotels 3.55 8 0.90 4.03 4 0.53 4.00 1 0.8217. Behaviour of Service

Staff at the Hotel3.67 7 0.74 3.83 8 0.90 3.60 6 0.70

18. Tariff Structure of theHotel Rooms

3.12 19 0.82 3.38 18 0.78 3.50 7 0.85

19. Hygiene at WaysideRestaurants andDhabas

3.16 18 0.97 4.03 4 0.80 3.44 8 0.88

20. Availability of PetrolPump

3.09 22 1.11 3.25 20 1.10 3.70 5 0.48

21. Behaviour of ServicePersonnel at WaysideRestaurants andDhabas

3.76 4 0.67 3.75 10 0.49 3.44 8 0.88

22. Levels of Road Taxeson Vehicles(Tax Rates)

2.78 30 0.94 3.14 21 0.72 2.67 21 1.32

23. Administration of theRoad Taxes

2.99 25 0.95 3.36 19 0.64 2.89 17 1.17

24. Public Utilities at theTourist Attraction

2.65 31 1.25 2.24 31 1.15 2.10 32 0.88

25. General CleanlinessTourist Attraction andArea Around it

3.25 15 0.97 2.85 28 1.00 2.50 24 0.97

26. Condition of SignageWithin the TouristAttraction

3.36 13 1.25 3.43 15 0.75 2.60 22 0.97

27. Parking Facility at theTourist Attraction

2.95 27 1.24 2.63 30 1.19 2.50 24 0.97

28. Availability of TrainedTourist Guides

2.98 26 1.10 3.46 14 1.02 2.40 27 1.35

29. Behaviour of theGuides at the TouristAttraction

3.53 9 0.75 3.94 7 0.61 3.00 11 1.22

30. Conservation ofHeritage Sites

3.76 3 0.85 2.76 29 1.02 2.50 24 0.97

31. Promptness at theTicketing Window ofthe Monument/TouristAttraction

4.19 1 0.65 4.00 6 0.55 3.00 11 0.87

Data Analysis


32. Power SupplySituation

3.75 5 0.66 3.78 9 0.77 2.80 18 1.03

33. Telephone/MobileServices

3.93 2 0.86 4.43 1 0.55 3.80 3 1.23

Correlation Coefficient Tourist and Hoteliers .358*

Sig. (2-tailed) .041

Correlation Coefficient Tourist and Tour operator .294

Sig. (2-tailed) .097

Correlation Coefficient Hoteliers and Tour operator .767**

Sig. (2-tailed) .000Source: Field Data*. Correlation is significant at the 0.05 level (2-tailed).**. Correlation is significant at the 0.01 level (2-tailed).

Table 4.2.6.6.1 depicts stakeholder viz. tourists, hoteliers, and tour operators’

satisfaction level towards 33 tourist services and amenities. Tourists are strongly

satisfied with promptness of ticketing window of the monuments/tourist attraction,

telephone/mobile services, conservation of heritage sites and behaviour of service

personnel at wayside restaurants and Dhabas. Whereas hoteliers are strongly satisfied

with the telephone and mobile services, hygiene at wayside restaurants and Dhabas,

availability of commercial transportation and behaviour of the drivers of commercial

transportation. Tour operators are strongly satisfied with the availability of hotels,

availability of commercial transportation, behaviour of commercial transportation and

telephone and mobile services since the mean score is more than 3

However tourists are strongly dissatisfied with the air and rail connectivity, public

utilities at the tourist attraction and levels of road taxes on vehicles. Hoteliers are

dissatisfied with air and rail connectivity, public utilities and parking facility at the

tourist attraction. Tour operators are dissatisfied with the air connectivity, public

utilities at the tourist attraction, sewage and drainage system, condition of city roads

and traffic management since the mean sore is less than 3

To probe into the depth of analysis researcher has calculated spearman’s rank

correlation between perception of stakeholders towards the satisfaction level of tourist

services and amenities. Spearman’s rank correlation coefficient score is 0.358, 0.294

and 0.767 respectively, with 041, .097 and 0.000 ‘P’ value respectively, which is

significant at (tourists and hotelier) 0.05 level and (hoteliers and tour operator) 0.01

levels (2-tailed). But the tour operators ‘P’ value is more i.e. 0.97 at 0.05 levels which

Data Analysis


is insignificant. Thus, perception of tourists and hoteliers has significant relation

whereas the tour operator does not. There is a gap between the perception of tourist

and tourist service provider (tour operator) and not the hoteliers

(T-Test)

The data of satisfaction towards 33 tourist services were obtained on 5 point scalewith median of 3 to see the overall distribution of stakeholders. One sample‘t’ test hasbeen used with test value ‘3’. Following table narrates the‘t’ test.

One-Sample Test

Sr.Satisfaction

Test Value = 3

t dfSig.(2-tailed)

MeanDifference

95% ConfidenceInterval of theDifferenceLower Upper

1 Tourist 2.026 32 .051 .19333 -.0010 .38772 Hoteliers 2.771 32 .009 .32212 .0853 .55893 Tour

Operators-.865 32 .393 -.08909 -.2989 .1207

The calculated ‘t’ is significant in case of hoteliers since the ‘p’ value is 0.009. The

same is insignificant in case of tour operators and the ‘t’ is on border since the ‘p’

value is .051 regarding tourist. Overall satisfaction count dwindles around mid point

i.e. test value 3 which is not much significant.

4.2.6.7 Perception of Stakeholders on importance towards the tourist Servicesand Amenities available in Satara:

This part depicts the perception of stakeholders on importance of tourist services and

amenities available in Satara district. There are 33 tourist services and amenities are

considered to know their opinions. Researcher is intending to find out the gap

between perception of tourist with hoteliers and as well with tour operators. Data is

collected on 5-point likert scale and simple statistical tools like mean, standard

One-Sample Statistics

Sr. Satisfaction N Mean Std. Deviation Std. Error Mean1 Tourist 33 3.1933 .54809 .095412 Hoteliers 33 3.3221 .66781 .116253 Tour Operators 33 2.9109 .59167 .10300

Data Analysis


deviation, and rank are used for analysis. To investigate in depth of analysis

researcher has calculated Spearman’s rank correlation between perceptions of tourist

and other stakeholders i.e. hotelier and tour operator.

Importance Level of Stakeholders

Following table shows the distribution of importance level of tourist services and

amenities in the view of three-sample unit viz. tourist, hoteliers and tour operators.

Table 4.2.6.7.1Distribution of Importance level of tourist services and Amenities in the view of threesample units viz. Tourists, Hoteliers, and Tour Operators

Sr.

Stakeholders’ Perception

Tourist Service andAmenities

Tourists’Perception

Hoteliers’Perception

Tour Operators’Perception

Mean

Rank

S.D.Mean

Rank

S.D.Mean

Rank

S.D.

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.1. Air Connectivity Status 2.83 33 1.30 3.18 33 1.39 2.6 33 1.432. Rail Connectivity Status 3.10 32 1.23 3.53 32 1.13 3.1 32 1.23. Quality of the Roads 4.45 8 0.56 4.40 6 0.55 4.6 3 0.524. Quality of Way Side

Amenities Available onThis Road

4.29 15 0.68 4.25 19 0.49 4.2 20 0.42

5. Public ConveniencesAlong Roads/Streets

4.2318

0.664.33

11

0.47

4.2 200.63

6. Sewage and DrainageSystem

4.2024

0.654.43

3 0.50 4.3 11 0.48

7. Garbage Disposal4.21

19

0.654.43

3 0.50 4.3 11 0.67

8. Condition of City Roads 4.39 13 0.57 4.48 2 0.51 4.6 3 0.79. Drinking Water Supply

4.44 9 0.56 4.43 3 0.50 4.8 10.42

10. Condition of StreetLighting

4.24 7 0.67 4.15 26 0.43 4.2 20 0.63

11. Traffic Management 4.42 11 0.61 4.25 19 0.49 3.9 30 1.112. Condition of Traffic or

Transport Signage4.47 7 0.58 4.28 17 0.45 4.5 5 0.53

13. Availability ofCommercialTransportations

4.32 14 0.59 4.30 16 0.56 4.2 20 0.42

14. Behaviour of the Driversof CommercialTransportations

4.16 26 0.69 4.35 10 0.48 4.5 5 0.53

15. Availability ofAuthorized TourOperators

3.14 31 1.24 4.05 29 0.45 4 29 0.82

16. Availability of Hotels 4.14 27 0.96 4.38 8 0.49 4.5 5 0.53

Data Analysis


17. Behaviour of ServiceStaff at the Hotel

4.2023

0.54 4.33 11 0.47 4.2 20 0.42

18. Tariff Structure of theHotel Rooms

4.16

25

0.52

4.21

24

0.52

4.220

0.42

19. Hygiene at WaysideRestaurants and Dhabas

4.26 16 0.52 4.40 6 0.50 4.3 11 0.48

20. Availability of PetrolPump

4.20 22 0.54 4.28 17 0.60 4.3 11 0.67

21. Behaviour of ServicePersonnel at WaysideRestaurants and Dhabas

4.21 21 0.57 4.15 26 0.43 4.2 20 1.03

22. Levels of Road Taxes onVehicles(Tax Rates)

3.97 30 0.64 3.94 31 0.47 4.3 11 0.67

23. Administration of theRoad Taxes

4.04 29 0.57 4.00 30 0.59 4.3 11 0.48

24. Public Utilities at theTourist Attraction

4.59 4 0.55 4.33 11 0.47 4.5 5 0.71

25. General CleanlinessTourist Attraction andArea Around it

4.60 2 0.57 4.33 11 0.47 4.3 11 0.67

26. Condition of SignageWithin the TouristAttraction

4.57 6 0.55 4.25 19 0.44 4.2 20 0.63

27. Parking Facility at theTourist Attraction

4.58 5 0.56 4.38 8 0.49 4.3 11 0.67

28. Availability of TrainedTourist Guides

4.21 20 0.91 4.23 23 0.58 4.3 11 0.48

29. Behaviour of the Guidesat the Tourist Attraction

4.09 28 0.77 4.24 22 0.61 4.2 20 0.44

30. Conservation of HeritageSites

4.60 2 0.58 4.20 25 0.55 4.5 5 0.53

31. Promptness at theTicketing Window of theMonument/TouristAttraction

4.39 12 0.59 4.11 28 0.52 3.9 30 0.74

32. Power Supply Situation 4.44 10 0.67 4.33 11 0.47 4.4 10 0.733. Telephone/Mobile

Services4.72 1 0.46 4.58 1 0.50 4.8 1 0.42

Correlation Coefficient Tourist and Hoteliers .479**

Sig. (2-tailed) .005Correlation Coefficient Tourist and Tour operator .565**

Sig. (2-tailed) .001Correlation Coefficient Hoteliers and Tour operator .642**


Data Analysis


Table 4.2.6.7.1 reveals that air and rail connectivity, availability of tour operators as if

services are least important in the view of all the stakeholders. However, about level

of road taxes on vehicles opinion of hoteliers and tourists are the same i.e. least

important. As per tour operators, opinion traffic management and promptness at the

ticketing window of the monument/tourist attraction are least important.

Administration of the road taxes is least important as hotelier’s opinion. All

stakeholders felt telephone and mobile is most important service. But conservation of

heritage, public utility and general cleanliness at tourist attraction are most important

as per tourist opinion. Hoteliers and tour operators felt most important civic amenities

viz. sewage and drainage system, garbage disposal, condition of city roads and

drinking water supply. Tour operators felt quality of roads is most important for

tourism development in Satara.

To look into the depth of analysis researcher has calculated Spearman’s rank

correlation between perception of stakeholders towards the importance level of tourist

services and amenities. Spearman’s rank correlation coefficient score is 0.479 and

0.565, 0.642 respectively, with .005, 0.001 and .000 ‘P’ value respectively, which is

significant at (tourists and hoteliers), (tourist and tour operators) and (hotelier and

tour operator) 0.01 levels (2-tailed) Thus, perception of stakeholders has significant

relation on importance of tourist services and amenities.

The data of satisfaction towards 33 tourist services were obtained on 5-point scale

with median 3 to see the overall distribution of stakeholders. One sample‘t’ test has

been used with test value ‘3’. Following table narrates the‘t’ test.

Sr.One-Sample Statistics

Importance N MeanStd.Deviation

Std. ErrorMean

1 Tourist 33 4.2079 .42315 .073662 Hoteliers 33 4.2276 .26655 .046403 Tour Operators 33 4.2340 .41730 .07264

Data Analysis


Sr.

One-Sample Test

Importance

Test Value = 3

t dfSig. (2-tailed)

MeanDifference

95% Confidence Intervalof the Difference

Lower Upper1 Tourist 16.398 32 .000 1.20788 1.0578 1.35792 Hoteliers 26.456 32 .000 1.22758 1.1331 1.32213 Tour

Operators16.988 32 .000 1.23401 1.0860 1.3820

The calculated‘t’ is significant in case of hoteliers and tour operators since the ‘p’

value is 0.00. Overall importance count dwindles around point i.e. test value 4 which

is significant.

To conclude, the satisfaction and importance towards tourist services and amenities

there found difference of opinion amongst stakeholders for satisfaction but uniformity

found in case of importance of these amenities.

Data Analysis


Section VII

4.2.7 Selected Intellectuals Descriptive Analysis:

This section depicts the opinion on proposed projects in the 15 prospective

destinations of Satara. The projects are perceived by researchers twenty respondents

interviewed for the same. It consist government officials, newspaper reporters,

editors, social activist and towering personality of Satara on feasibility of tourism.

The said responses collected on 5 point scale 1 for not at all feasible to 5 for highly

feasible. The data analyzed and presented with mean, rank, and standard deviation.

Intellectuals’ Opinion of Feasibility of Tourism Project

Following table shows the opinion of governmental officials, newspaper reporters andeditors, social activists, and towering personality on feasibility of tourismdevelopment project at Satara district.

Table 4.2.7.1Opinion of Selected Intellectuals on Proposed Projects

Sr.

Location Name of Project Mean Rank S.D.

1. Bamnoli

Houseboat – Tapola, Bamnoli 3.71 19 1.06

Water Sports 3.57 20 1.12Mountaineering Institute 3.73 18 1.27Health Resorts 2.76 23 1.61Summer camps 4.60 2 0.60

2. Kas

Kite Festival 4.9 8 1.29Flora and Fauna 4.55 4 0.60Dirt Biking 2.00 27 1.64Dirt Cycling 3.11 22 1.49

3. ThosegharHanging pool 4.00 15 0.46Bungee Jump 2.00 27 1.53

4. AjinkyafortRappelling and Caving 4.55 4 0.60Paragliding and Parasailing 4.45 7 0.94Light and Sound Show 4.47 6 0.70

5. SaddavaghapurDirt Biking 1.76 29 1.44Dirt Cycling 3.25 21 1.34

6. Chalkewadi Tents 4.11 14 0.46

Data Analysis


7. Koyna

Residential Schools like Panchgani 2.41 26 1.62

Health Resorts 4.17 10 0.38Village tourism 4.76 1 0.44Eco Tourism 4.19 8 0.51

8. Yarad Riverside Tourism 4.11 13 0.479. Valmiki Winter camp 2.56 25 1.72

10. BanpuriA plateau valley, nature, small

waterfalls, windmills andForest,

4.13 12 0.34

11. Karad Village Tourism 4.16 11 0.37

12.

Saap(Rahimatpur), NanaPhadniswada(Wai), Vathar(Nimbalkarvada),Jalmandir, Adalatvada,Rajwada,(satara

Historical Havelis 3.84 17 0.76

13. Yawateshwar Health and Mediation Centres 2.63 24 1.64

14.

Gondawale/Sajjangarh/Aundh/Pal/Chphal/Wai/Bawadhan/Banpuri/PusegaonMaharah/Mhaswad/

Pilgrimage Tourism 4.57 3 0.51

15.Agashiv caves,Karad

Mediation Camp 3.85 16 1.04

Source: Field Data

The table 4.2.7.1 depicts prospects of Satara district to be developed as a tourist

destination with the help of 22 projects out of 29 (consideration by researcher) at a 15

different locations of Satara. Table shows feasibility of 22 projects out of 29 in

different locations of Satara District since the mean score is higher than 3. Out of that

Village tourism (Koyna), Summer camp (Bamnoli), Pilgrimage tourism (Gondawale,

Sajjangarh, Aundh, Pal, Chaphal, Wai, Bawadhan, Banpuri, Pusegaon, Mhaswad)

reflect most feasible tourism projects as they received highest mean score and rank

first 4 respectively. However, seven projects shows less feasibility as their mean

score is less than 3. Dirt Biking (Saddavaghapur, Kas), Bungee jump(Thoseghar),

Data Analysis


residential school (Koyna) and Winter camp (Valmiki) like tourism projects shows

less feasibility in their respective locations since the ranks received are 29 to 25

respectively.

Since the local intellectuals responded favourable opinions on the project where mean

score is 4 and more. These locations can be come up as new tourist products. These

products may help capitalizing opportunity of product life cycle.

Data Analysis


Section VIII

4.2.8 SWOT Analysis:

The SWOT highlights the Strengths, Weaknesses, Opportunities, and Threats based

on infrastructural facilities and environmental aspects prevailing for tourism in Satara

District. The present work is based on researcher’s observation, interview, and

discussions with tourists, hoteliers, tour operators, NGOs, Government officials,

Social activist, and towering personalities of Satara.

SWOT Matrix

STRENGTHS WEAKENSSES

1. District Bounded With GorgeousNature.

2. Rich Historical Background.3. Geographical Diversity.4. National Highway.5. Better Transportation.6. Affordable Tourist Services.7. World Heritage Sites.8. Hill Station.9. Good Locations for Cinema

Shooting.10. Tourists Satisfaction towards

important services ‘promptness ofticketing window of themonument/tourist attraction’,Conservation of heritage site,‘telephone/mobile services’, and‘behaviour of service personnel atwayside restaurants and dhabas’ arestrengths of Satara.

1 Earthquake Prone Area.2 Absence ‘Sahyog’.3 Inconvenient Frequency Of Rail.4 Tourism Season Depends On Good

Rainfall And Climatic Condition.5 Dissatisfaction with important services

viz. ‘Condition of city roads’, ‘trafficmanagement’, ‘public utilities at touristattraction’ , ‘parking facility at thetourist attraction’, general cleanliness attourist attraction and area around’,‘quality of roads’ , ‘condition of trafficand transport signage’ are theweaknesses of Satara.

OPPORTUNITIES THREATS

1. Tourist flow is increasing.2. World Heritage.3. Emerging trend of Agro Tourism

and rural tourism.4. Bio Diversity Act.

1 Absence of political desire.2 Legal threats to implement the tourism

plan.3 Lack of coordination.4 Active Environmentalists.5 World Heritage Nature site and TigerConservation project will hinder theinfrastructural development.

Data Analysis


Strengths:

1. Habitant places in Satara district are bounded with gorgeous nature and ranges of

Sahyadri. A wide variety of beauty to see in Sahyadri ranges. Richest of its glory

and owing to flora and fauna, valleys, clouds, river, streams, variety of birds, water

reservoir Koyna and backflow, more than 10 lakes like Kas, Mayani,Venna etc.

More than 10 dams like Koyna, Dhom, Kanher, Urmodi, Veer, Balkwadi, Tarli,

Marathwadi, etc. Satara District is gifted with two Popular Hill Station viz

Mahabaleshwar and Panchagani. Budhist caves like Agashiv caves, Shirwal, and

many other caves like Ramghal, Morghal, Lahore, Rajapuri, Yarphal, Yeradwadi,

Helwak, Chaphal, etc. Satvahankalin or Hemandpati Tempels at Parli, Asle,

Dandeghar, Nagewadi, Vaduth, Khinai, Deur, Kikali, Mhavashi, Marul Haveli,

Bhaule, Aswali, Kanheri, Lohom, Vadagaon, Gursale, Ambheri, Khatav,

Nagnathwadi, Katharkhatav, Mhaswad, Nigadi, Chimangaon, Bhogaon, Kole,

Bawadhan etc., more than 25 Shivkalin forts54 Pratapgarh, Sajjangarh, Ajinkya

Tara, Vasantgarh, Sadashivgarh, Santoshgarh, Varugadh, Vasota, Pandavgarh,

Vairatgarh, Bhairavgarh, Dathegarh etc. Havelis55 and palaces at Satara, Saap near

Rahimatpur, Phltan, Vathar etc. Koyna Wild Life Sanctuary, Sayahadri Tiger

Project, and Koyna Power Project.

2. Quadrilateral national highway number 4 (proposed to be 6 lane) with service road

passes 120 Kilometers through Satara district and connects Mumbai (capital of

Maharashtra) via Pune in the north and Kolhapur ( a holy, heritage destination) in

South heading to Bangalore (Capital of Karnataka). Almost entire existing tourist

destinations are connected through state highway and within distance of 50 to 100

Km. from head quarter Satara.

3. Tourist related services are affordable and reasonable in Satara. Satara is ‘C’ grade

town.

4. Geographical Structure of Satara district is very diverse where almost one third of

its area is covered by Sahyadri ranges, which are hilly having forest, and declared

as eco sensitive zone. One third of its land is fertile which is in Krishna and

54 Shivkalin forts are the forts in the Shivaji’s (King of Maratha Kingdom inMaharashtra) tennure.

55 Haveli is the mansion or small palace of Prime Minister of kingdom.

Data Analysis


Koyana river basin and rest one third is dry terrain of which large area comes in

Deccan plateau.

5. Satara district grows many rare varieties of fruits (Ranmeva /Dongarimeva56) such

as Mulberry, Rasberry, Blueberry, Blackberry, Jumbo plums. It is also well-known

for Strawberry. Satara is known for its local sweets Kandi Pedha 57 , and

Mahbaleshwars jams and jelly sweets, which are very popular.

6. Kas and Koyna plateau of Satara District have been recognized and has place in

World Heritage site by UNESCO.

7. Temperature- Temperature-Max.-37.5 DegC., Min.-11.6 Deg. C. Rainfall- 2643

mm (Average) Satara has moderate temperature. It does not hinder tourists to visit

throughout the year.

8. More frequency of Non-stop Bus services to metro towns Mumbai, Pune and

Kolhapur.

9. Satara’s Natraj Mandir is only a 2nd Temple of its kind.

10. Oldest and biggest tree of India is located in Mhasve.

11. Worth seeing locations of Satara as Wai, Mahabaleshwar, Panchgani, Rahimatpur

and Satara attracts for cinema shooting.

12. Satara is known for rich historical background so with its ruins and its remnant.

13. Analysis of tourist services and amenities (refer Table No. 5.1.1) infer that

twenty-four services out of 33 are of high importance for the tourist and they are

highly satisfied with them. It means these are the strengths of Satara to develop as

a tourist destination. These tourist services and amenities are viz. ‘promptness of

ticketing window of the monument/tourist attraction’, ‘telephone/mobile

services’, and ‘behaviour of service personnel at wayside restaurants and dhabas’

and like.

Weaknesses:

1. The location Koyna Dam and surrounding are earthquake prone area

2. Sensitive zone like Koyna dam and surrounding will restrict tourist flow for

security purpose.

56 Dongrimeva term made up of two words dongri (hill) and Meva (Sweet), the berriesthat are avilable in the hilly region.57 Kandipedha, is a local sweets made up of milk solids and sugar.

Data Analysis


3. Lack of co-ordination between different departments and Absence of one

important ‘S’, ‘Sahyog’ of Tourism Policy 2006.

4. Inconvenient and less frequency of rail facility and only airstrip is available at

Karad, which is most of the time non-operational so Satara is inefficient to raise

tourist flow of outside states and countries.

5. Satara tourist season is depends on mainly good rainfall at destination like Kas

Flora, Thoseghar waterfall, Koyna Lake, hill stations like Mahableshwar and

Panchgani which depends on favourable climatic conditions.

6. Condition of city roads and roads that leads to potential tourist destinations are

narrow and in bad conditions.

7. Analysis of tourist services and amenities (Please refer the table No. 5.10.11)

focuses on tourist perception on 33 services and amenities in Satara. ‘Condition of

city roads’, ‘traffic management’, ‘public utilities at tourist attraction’ , ‘parking

facility at the tourist attraction’, general cleanliness at troust attraction and area

around’, ‘quality of roads’ , ‘condition of traffic and transport signages’ and

‘condition of signages within the tourist attraction’ are the services and amenities

which lie in 4th quadrant which reflects high importance and low satisfaction

level.

Opportunities:

1. Tourist flow is increasing at Satara. Narration is as follows

Tourist Arrival is in between July 2009 to June 2010 and the destinations are covered

like Mahabaleshwar, Panchgani, Shri Bhavani museum, Thoseghar,Kas Lake,

Ajinkya Fort, Sajjangad, Koyna lake.

Tourist Arrival

Following table shows tourist Arrival in between July 2009 to June 2010 and the

destinations are covered like Mahabaleshwar, Panchgani, Shri Bhavani museum,

Thoseghar, Kas Lake, Ajinkya Fort, Sajjangad, Koyna Lake.

Data Analysis


Table 4.2.8.1Tourist Arrival in Satara

(Numbers are individual tourists)

Sr.Type ofTourist

TotalActual figure

given

1. Foreign 4776 47772. Domestic 1550981 15509833. Total 1555757 1555760

Source: Incredible India, “Tourism Survey for State of Maharashtra”, Final Report,Ministry of Tourism (Market Research Division), Government of Indiahttp://www.tourism.gov.in/writereaddata/CMSPagePicture/file/marketresearch/statisticalsurveys/Maharashtra.pdf, dated 10/12/2011 at 4:05 PM

Tourist Arrival at Kas

Following table depicts the tourist arrival during 2008-9 to 2011-12 at Kas.

Table 4.2.8.2Tourist Arrival at Kas


Source: Figures obtained from Deputy Conservator of Forest office, Satara

Above table 4.2.8.1 and 4.2.8.2 shows, the figures of tourist arrival are significant.

The increase in number of tourist is also significant as far as Kas is concerned. At

other places also there found significant increase in tourist arrival.

Sr. Year visitedDomesticvisitors

Foreignvisitors

Total No.of visitors

% change overprevious year

1. 2008-09 8972 - 8972 02. 2009-10 49347 - 49347 81.823. 2010-11 129927 43 129970 62.034. 2011-12 350000 - 350000 62.87

Data Analysis


Table 4.2.8. 3Tourist Arrival in Satara at different locations


Sr.Year

Thoseghar Aundh Pratapgarh PanchganiMahabales

hwarKoyna

TouristArrival(Estimated)

% ofGrowthoverpreviousyear



Tourist

Arrival

(Estimate

d)



%ofGrowthoverprevious

year



year



year

1.

1999

-20

00

1323

2 0

2.

2000

-20

01

1032

574

0

1343

674

0

6369

1

79.2

2

3.

2001

-20

02

500-

600 0

6895

44

-49.

75

8766

45

-53.

27

8641

4

26.3

0

4.

2002

-20

03

750-

800

25

3560

1

0

7945

64

13.2

2

901,

110

2.71

9691

4

10.8

3

5.

2003

-20

04

000-

1100

27.2

7

9022

0

60.5

4

7779

87

-2.1

3

9312

10

3.23

1141

50

15.1

0

6.

2004

-20

05

1300

15.3

8

6908

3

-30.

60

8459

08

8.03

9838

00

5.35

1173

20

2.70

7.

2005

-20

06

800-

2000 35

3429

8

-10

1.42

7139

87

-18.

48

9010

18

-9.1

9

1268

51

7.51

8.

2006

-20

07

3300

-35

00

42.8

6

4997

9

31.3

8

8126

54

12.1

4

9231

00

2.39

1316

89

3.67

9.

2007

-20

08

5000

-60

00

41.6

7

4531

0

-10.

30

9093

21

10.6

3

1127

960

18.1

6

1389

14

5.20

Data Analysis


Source: Bhavani Museum office, Aundh, Forest Satara Taluka Office, Near S.T.Stand,Satara, Mahabaleshwar Forest Office, Pratapsinh Uddyan, Pratapgarh, NagarpalikaPanchgani, Nagarpalika Mahabaleshwar, Neharu Garden, Koyna PWD officeNA: Not availableNote: Tourist arrival was 43800 at Sajjangarh during July 2010 to June 2011. It isobserved that Tourist flow was doubled in 2012.

The above figures reveal that tourist flow is increasing to see the gorgeous nature of

Satara. It is increasing towards nature tourism like Kas, Thoseghar, and Koyna. Satara

has been gifted with beautiful nature, which can attract large number of tourist the

nation within and foreign countries.

2. UNESCO has recognized Kas and Koyna as World Nature Heritage Destinations.

The destinations would receive funds to conservation. This is likely to attract

foreign tourists UNSECO officials repeatedly.

3. Emerging trend of Agro Tourism where tourist can share farming life since

Satara’s cultivable land area is 799.4 thousand hectares, Village Tourism where

tourist can experience village life since there are 1727 villages in Satara, Rural

Tourism where tourist can share rural culture and traditions like Bagad at

Bawadhan, bullock-cart race in dry terrain of Mhasawad and surroundings, 1542

Sq Km forest area gives tourists scope for Eco Tourism and Heritage tourism

where tourist can enjoy historical sites while Satara has rich history of Shivaji

10.

2008

-20

09

8000

-85

00

29.4

1

3470

9

-30.

54

1144

190

0.53

1343

603

16.0

5

1268

18

-9.5

4

11.

2009

-20

10

1200

0-13

000

34.6

2

8877

8

0

5064

5

31.4

7

1262

700

9.39

1467

702

8.46

1277

29

0.71

12.

2010

-20

1117

00 0-18

00 027

.78

8098 8 -

9.61

871 23

29 0 -11

7.4

513

7865

5

8.41

1576

465

6.90

1442 50

11.4

5

13.

2011

-20

12

2500

0-27

000

33.3

3

8247

4

1.80

178

3295

5

29.3

3

NA

NA

1623

765 2.91

1159

99

-24.

35

Data Analysis


Maharaj and their descendants. Many social activist and saints were also part of

this beautiful land.

4. Bio Diversity Act passed to protect and Conserve the Nature and Wild Life. The

Bio Diversity Act provides provisions for regulated access to biological resources

by bonafide end-users for various purposes including scientific research,

commercial activities, and sustainable use of non-timber forest produce. The Act

is implemented through three functional bodies’ viz., NBA at the national level,

State Biodiversity Boards (SBBs) in different states, and Biodiversity

Management Committees (BMCs) at the level of local community (Panchayat).

The Act, according to Section 21 and Rule 20 of the Biodiversity Rules, insists

upon including appropriate benefit sharing provisions in the access agreement and

mutually agreed terms related to access and transfer of biological resources or

knowledge occurring in or obtained from India for commercial use, bio-survey,

bio-utilization or any other monetary purposes.

5. It has observed that trend of rural tourism where art and craft is indispensable.

Handicraft industries as Kale Tal-Karad is known for Stone carving, and entire

Man taluka is known for Sheppard’s local bedding (Jen).

6. Two Best museums Shivaji at Satara Headquarter and Aundh. Aundh can be the

best museum housed rare painting and sculptures of well-known artist from

worldwide. Shivaji museum is having large collection from Maratha Empire.

7. Many upcoming destinations like Kas-Lake, Kas Flora, and Thoseghar Waterfall,

Sajjangarh, Gondawale, Pusegaon, Chaphal, Koyna Lake, Ozarde waterfall,

Agashiv Caves, Aundh Museum, and Shivaji Museum etc.

Threats:

1. It observed that political desire is absent for the improvement and development of

Satara.

2. It is observed by researcher while encountering the discussion with bureaucrats of

the concerned department that legal threat to implement the tourism plan in

potential area which is under control of Archeological department/forest

Department (Thoseghar/Agashiv)

Data Analysis


3. Researcher observed that there is a lack of coordination between Tourism,

Archaeological, Forest, Irrigation, and Administrative department concerned with

Mayni bird Sanctuary.

4. Active Environmentalist in Satara District.58

5. UNESCO, Large Area lying in World Heritage Nature site and Tiger

Conservation project will hinder the infrastructural development. 59 (Wildlife

Protection Act 1972) Environment (Protection) Act 1986, a professional body

which will be responsible for the protection and sustainable development of the

Western Ghats).

58Wednesday, October 06, 2010 AT 12:00 AM (IST)Tags: environment, kas pathar, satara, western maharashtra, Tuesday,September 07, 2010 AT 12:31 AM (IST)Tags: kas pathar, satara, western maharashtra

59 http://articles.timesofindia.indiatimes.com/2012-03-27/pune/31244228_1_sandeep-shrotri-kas-plateau, accessed on 28 May 2012,http://articles.timesofindia.indiatimes.com/2011-07-14/pune/29772623_1_kas-plateau-illegal-constructions, 15 July 2011.

Data Analysis


Section IX

4.2.9 Analysis of Tourist Services and Amenities:

In the previous section of data analysis the satisfaction and importance towards tourist

services and amenities has been assessed. In this section, the same analysis is

extended to every destination and the section concludes with perceptual gap

comprehensive of all stakeholders. The perceptual gap between importance and

Satisfaction level is analyzed with the help of 33 tourist services and amenities60 and

the similar sequence kept throughout the analysis. In the graph, only serial numbers of

these services and amenities are used. Since the data is collected using five-point

scale, the graph is demarked at midpoint 3 at both the axis. Wherever necessities the

serial number of services and amenities are given in the bracket after mention of

services for easy reference to the graph.

Infrastructural Gap at Koyna

The perceptual satisfaction and importance of respondents towards infrastructure

facilities are presented with the help of mean score, ranks, and standard deviation

(S.D).

Table 4.2.9.1Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Koyna

(n=37)

Sr Tourist Services and AmenitiesSatisfaction Importance

Mean Rank S.D. Mean Rank S.D.1. Air Connectivity Status 1.35 33 0.48 2.65 33 1.032. Rail Connectivity Status 1.65 32 0.48 2.78 32 1.033. Quality of the Roads 3.16 19 0.55 4.24 8 0.434. Quality of Way Side Amenities Available

on This Road3.41 14 0.55 4.00 18 0.58

5. Public Conveniences AlongRoads/Streets

3.38 15 0.55 3.92 25 0.55

6. Sewage and Drainage System 3.16 19 0.50 3.92 27 0.557. Garbage Disposal 3.19 18 0.40 3.86 28 0.54

60 ‘Infrastructure Gaps in Tourism Sector at Five Tourist Destinations in India Based onPerception of Tourists’, report of Government of India, Ministry of Tourism, June 2010,accessed on 14 October, 2010, 11:09pm.

Data Analysis


8. Condition of City Roads 2.73 27 0.87 4.00 18 0.539. Drinking Water Supply 3.70 6 0.62 3.97 22 0.5510. Condition of Street Lighting 3.27 16 0.73 3.92 25 0.6411. Traffic Management 2.59 28 1.04 4.41 6 0.5012. Condition of Traffic or Transport Signage 2.92 23 0.76 4.46 4 0.5113. Availability of Commercial

Transportations3.58 10 0.55 4.14 13 0.59

14. Behaviour of the Drivers of CommercialTransportations

3.61 9 0.50 4.11 15 0.61

15. Availability of Authorized TourOperators

3.25 17 0.45 3.51 31 0.65

16. Availability of Hotels 3.62 8 0.64 4.16 11 0.5517. Behaviour of Service Staff at the Hotel 3.52 13 0.51 4.00 18 0.4818. Tariff Structure of the Hotel Rooms 3.15 21 0.37 3.97 23 0.4219. Hygiene at Wayside Restaurants and

Dhabas3.00 22 0.71 3.95 24 0.40

20. Availability of Petrol Pump 2.51 30 0.73 4.00 18 0.3321. Behaviour of Service Personnel at

Wayside Restaurants and Dhabas3.56 12 0.50 4.03 17 0.29

22. Levels of Road Taxes on Vehicles(TaxRates)

3.65 7 0.63 4.16 11 0.50

23. Administration of the Road Taxes 3.57 11 0.77 4.14 13 0.5424. Public Utilities at the Tourist Attraction 2.30 31 1.08 4.49 2 0.5125. General Cleanliness Tourist Attraction

and Area Around it2.84 24 0.76 4.43 5 0.50

26. Condition of Signage Within the TouristAttraction

2.76 26 1.14 4.54 1 0.51

27. Parking Facility at the Tourist Attraction 2.57 29 1.39 4.49 2 0.6128. Availability of Trained Tourist Guides 2.78 25 0.97 3.57 30 1.0729. Behaviour of the Guides at the Tourist

Attraction4.33 1 0.58 3.62 29 0.95

30. Conservation of Heritage Sites 3.73 4 0.56 4.19 10 0.6231. Promptness at the Ticketing Window of

the Monument/Tourist Attraction3.92 2 0.65 4.35 7 0.68

32. Power Supply Situation 3.83 3 0.51 4.05 16 0.5733. Telephone/Mobile Services 3.73 4 0.77 4.22 9 0.53

Rank Correlation Coefficient 0.394Significant(2-tailed) 0.023*Correlation is significant at the 0.05 level (2-tailed).

Source: Field Data

Data Analysis


Graph: 1.

Table 4.2.9.1 reveals the mean score of satisfaction and importance of tourist services

amenities in Koyna. Tourists are satisfied with twenty-two tourist services and

amenities since the mean score is higher than 3 (quadrant Ist in the graph). The

dissatisfaction lies with these eleven tourist services and facilities, which are

important in nature, as the mean score is less than 3. Tourists are strongly satisfied

with ‘behaviour of the guide at tourist attraction’, which receives first rank, 2nd rank to

the ‘promptness of ticketing window of the Monument/Tourist attraction’, 3rd rank to

the ‘power supply’ and 4th rank each to ‘telephone and mobile services’ and

‘conservation of heritage site’. However, tourists are strongly dissatisfied with the

‘air’(1) and ‘rail(2) connectivity as ranks are thirty three and thirty two but these

services are marked as less important, availability of petrol pump receives thirty rank

and public utilities 31 rank.

Thirty-one tourist services and amenities are important to the tourist at the

Data Analysis


destination as their mean score is more than 3 but two are not important since the

mean score is less than 3. Services and amenities like ‘condition of signage within the

tourist attraction’ receives 1st rank, 2nd rank to ‘parking facility at the tourist

attraction’ and ‘public utilities at the tourist attraction’ each and 4th rank to ‘condition

of traffic and transport signage’ are most important. On the contrary, least important

are ‘air connectivity’ (1), ‘rail connectivity’ (2) that receives 33 and 32 ranks,

availability of tour operator receives 31 rank and 30 rank to the availability of trained

tourist guide.

To probe into the depth of analysis researcher has calculated Spearman’s rank

correlation coefficient of satisfaction and importance of tourist services and facilities.

The score is 0.394, which is significant at 0.05 levels (2-tailed).

For better understanding, the 33 variables are plotted on a graph of importance and

satisfaction scale with the median value 3, the graph has divided into 4 quadrants. 1st

quadrant shows high satisfaction and high importance level, 2nd shows high

satisfaction and low importance, 3rd shows low satisfaction and low importance and

4th quadrant shows low satisfaction and high importance of the tourist services and

amenities. In the first quadrant, 20 variables are in a sound position to depict the

highest satisfaction and highest importance. Among them tourist were most satisfied

about the ‘behaviour of guide’ but not in a proportionate importance. ‘Quality of

road,’ ‘availability of commercial transportation’, ‘administration of road taxes,’

‘quality of wayside amenities’, and ‘garbage disposal services and amenities’ did not

find much gap in their satisfaction and importance level. However, ‘promptness at the

ticket window’ and ‘power supply situation’ the gap is very meager. In the second

quadrant, there is no single variable. Third quadrant shows two variables i.e. ‘air’ and

‘rail’ connectivity. It means these two services do not demand the attention. Fourth

quadrant depicts 10 variables viz. Public utilities, parking facilities, traffic

management, condition of signage within tourist attraction, General cleanliness,

availability of petrol pump, condition of city roads, hygiene at wayside restaurant,

Dhabas and availability of trained tourist guide which highlights highest gap in

satisfaction and importance level.

Quadrant 4 is important to focus since these parameters are very important and

carries dissatisfaction in the opinion of sample tourists. Variable number 24, 26

Data Analysis


and 27 viz. ‘public utilities at tourist attraction,’ ‘condition of signage within the

tourist attraction’ and ‘parking facility at the tourist attraction’ need to be addressed

Infrastructural Gap at Mahabaleshwar


facilities are presented with the help of mean score, ranks and standard deviation

(S.D).

Table 4.2.9.2Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Mahabaleshwar

(n=30)

Sr.

Tourist Services and Amenities

Satisfaction Importance

Mean

Rank

S.D.Mea

n

Rank

S.D.

1. Air Connectivity Status 1.60 32 0.50 2.90 31 1.322. Rail Connectivity Status 1.80 31 0.71 2.97 30 1.353. Quality of the Roads 3.13 23 0.90 4.43 10 0.734. Quality of Way Side Amenities

Available on This Road3.23 21 1.14 4.27 23 0.78


2.77 25 0.86 4.40 12 0.72

6. Sewage and Drainage System 3.63 11 0.67 4.20 24 0.557. Garbage Disposal 3.80 8 0.48 4.17 26 0.388. Condition of City Roads 3.30 20 0.65 4.30 19 0.539. Drinking Water Supply 3.63 11 0.89 4.50 8 0.6810. Condition of Street Lighting 3.37 18 1.07 4.40 12 0.6211. Traffic Management 3.50 14 0.94 4.33 18 0.6612. Condition of Traffic or Transport

Signage3.37 18 1.00 4.30 19 0.53

13. Availability of CommercialTransportations

4.30 1 0.53 4.67 4 0.55

14. Behaviour of the Drivers of CommercialTransportations

3.80 8 0.66 4.37 15 0.56


2.67 27 0.87 2.07 32 1.01

16. Availability of Hotels 4.27 2 0.64 4.83 1 0.3817. Behaviour of Service Staff at the Hotel 3.97 5 0.32 4.43 10 0.5018. Tariff Structure of the Hotel Rooms 2.73 26 0.83 4.50 8 0.5119. Hygiene at Wayside Restaurants and

Dhabas3.47 17 0.57 4.57 6 0.50

Data Analysis





1.83 30 0.59 4.07 27 0.83

23. Administration of the Road Taxes 2.23 29 0.90 4.30 19 0.5324. Public Utilities at the Tourist Attraction 2.93 24 1.05 4.57 6 0.5025. General Cleanliness Tourist Attraction

and Area Around it3.73 10 0.45 4.30 19 0.70

26. Condition of Signage Within the TouristAttraction

3.50 14 0.86 4.20 24 0.71

27. Parking Facility at the Tourist Attraction 3.50 14 0.86 4.37 15 0.6128. Availability of Trained Tourist Guides 3.63 11 0.49 4.37 15 0.7229. Behaviour of the Guides at the Tourist

Attraction3.17 22 0.41 3.97 29 0.49

30. Conservation of Heritage Sites 4.03 4 0.61 4.73 3 0.4531. Promptness at the Ticketing Window of

the Monument/Tourist Attraction* * * * * *


Rank Correlation Coefficient .588**

Significant(2-tailed) .000*Correlation is significant at the 0.01 level (2-tailed).

Source: Field Data*As there were no ticketing window so no responses.

Graph: 2.

Data Analysis


Table 4.2.9.2 reveals that tourists are satisfied with twenty-four tourist services and

amenities at Mahabaleshwar since their mean score is more than 3(quadrant Ist in the

graph) whereas dissatisfied with nine tourist service and amenities since the mean

score is less than 3.

Tourist are highly satisfied with the ‘availability of commercial transportation’,

‘availability of hotels’, ‘power supply’ and ‘conservation of heritage sites’ since they

receive first, second, third and fourth ranks respectively. Tourists are strongly

dissatisfied with the ‘air’(1) and ‘rail’(2) connectivity, ‘level of road taxes’ and

‘administration of the road taxes,’ ‘promptness in ticket window’ as they received

32th , 31st , 30th and 29th ranks respectively.

Tourist services as air (1), rail (2) and tour operator (15) are not important to the

tourists who have visited the destination as their mean score is less than 3. But

remaining thirty services tourist felt important since the mean score is more than 3.

‘Telephone/mobile’ services receives 1st rank, 2nd to ‘availability of hotels’, 3rd rank to

‘conservation of heritage site’ and 4th rank to ‘availability of commercial

transportation’ which are the most important services and amenities to the tourist.

However, ‘availability of authorized tour operator’ receives 32th rank, ‘air’ and ‘rail’

connectivity receives 31st and 30th ranks respectively and 29th rank to ‘behaviour of

guide at the tourist attraction’ are least important at Mahabaleshwar.

Spearman’s rank correlation coefficient of satisfaction and importance of tourist

services and facilities at Mahabaleshwar is 0.588, which is the significant at 0.01

levels (2-tailed). This signifies uniformity into opinions towards satisfaction and

importance.

In the first quadrant twenty-three variables shows high importance as well the high

satisfaction level. Out of this availability of hotels, availability of commercial

transportation, conservation of site, telephone and mobile service, power supply

shows highest gap. Tourist facilities, other services are the strengths of

Mahabaleshwar. No single variables lie in second quadrant. Three variables lie in the

third quadrant i.e. promptness of ticket window, availability of authorized tour

operator which shows the low importance and low satisfaction. Whereas ‘air’ and

‘rail’ connectivity is on the boundary of importance and satisfaction level. This infers

that ‘air’ and ‘rail’ connectivity is important at Mahabaleshwar. Eight variables lie in

Data Analysis


the fourth quadrant, which shows the highest importance and lowest satisfaction level.

‘Taxes and permits’, ‘petrol pump’ and ‘tariff structure of hotel,’ ‘public convenience

along the road,’ ‘quality of roads’ and ‘public utilities at tourist attraction’ tourist

facilities and amenities shows gap in their importance and satisfaction level.

Quadrant 4 is important to focus since these parameters are most important and

carries more dissatisfaction in the opinion of sample tourists. Variable number 23, 20

and 18 viz. administration of road taxes, availability of petrol pump and tariff

structure of hotel rooms in Mahabaleshwar need to be address.

Infrastructural Gap at Panchgani



(S.D).

Table 4.2.9.3Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Panchgani

(n=35)

Sr.

Tourist Services and AmenitiesSatisfaction Importance

Mean Rank S.D. Mean Rank S.D.1. Air Connectivity Status 1.29 32 0.62 3.31 31 1.212. Rail Connectivity Status 2.14 31 0.77 3.51 30 1.253. Quality of the Roads 3.71 11 0.46 4.54 12 0.514. Quality of Way Side Amenities



3.37 22 0.69 4.37 20 0.60


Signage3.34 23 0.94 4.63 8 0.49


3.77 7 0.65 4.46 16 0.51

14. Behaviour of the Drivers ofCommercial Transportations

3.88 3 0.59 4.54 12 0.51


3.40 21 0.89 2.29 32 1.30

Data Analysis


16. Availability of Hotels 3.74 10 0.82 4.71 3 0.4617. Behaviour of Service Staff at the

Hotel3.85 5 0.66 4.17 26 0.38

18. Tariff Structure of the Hotel Rooms 2.91 27 1.01 4.17 26 0.3819. Hygiene at Wayside Restaurants and

Dhabas3.66 14 0.80 4.37 20 0.49




2.66 29 1.08 4.17 26 0.71

23. Administration of the Road Taxes 2.69 28 1.11 4.20 25 0.5324. Public Utilities at the Tourist

Attraction2.66 9 0.84 4.46 16 0.51

25. General Cleanliness TouristAttraction and Area Around it

3.51 18 0.74 4.54 12 0.51

26. Condition of Signage Within theTourist Attraction

3.63 16 0.81 4.63 8 0.49

27. Parking Facility at the TouristAttraction

3.20 24 0.76 4.46 16 0.51

28. Availability of Trained TouristGuides

3.57 17 0.65 4.29 22 0.67

29. Behaviour of the Guides at theTourist Attraction

3.20 24 0.58 4.23 24 0.60

30. Conservation of Heritage Sites 3.68 13 0.48 4.43 19 0.5031. Promptness at the Ticketing Window

of the Monument/Tourist Attraction* * * * * *




Source: Field Data

*As there were no ticketing window so no responses.

Data Analysis


Graph 3.

Table 4.2.9.3 depicts the tourist are satisfied with twenty-seven tourist services as the

mean score is more than three (quadrant Ist in the graph) and dissatisfied with six as

score is less than 3. Tourists are strongly satisfied with mainly ‘telephone/mobile

services’(33) whose rank is 1st, 2nd to power supply(32), 3rd to ‘behaviour of the

drivers of commercial transportation’(14) and 4th rank to ‘quality of wayside

amenities available on this road’(4). However, tourists are strongly dissatisfied mainly

with the ‘air’ and ‘rail’ connectivity whose ranks are 32 and 31 respectively. Services

like ‘level of road taxes on vehicles’ (22) and ‘public utilities at the tourist attraction’

(24) receive 29 ranks each.

‘Availability of authorized tour operator’(15) tourists felt unimportant as the mean is

less than 3 and remaining thirty-two amenities are important at Panchgani which

mean score is more than 3. Out of that 1st rank receives to ‘telephone/mobile

Data Analysis


services’, 2nd rank to ‘drinking water supply’(9), 3rd rank each to ‘condition of street

light’(10) and availability of hotels which reflects the highest importance level.

However, ‘availability of authorized tour operator’ receives rank 32 and 31st to ‘air

connectivity’ and 30th to ' rail’ and 29th rank to ‘behaviour of service personnel at

wayside restaurant and Dhabas’ (21).

Satisfaction and importance of tourist services and amenities Spearman’s rank

correlation coefficient score is 0.672. That is significant at the 0.01 levels (2-tailed).

This signifies uniformity into opinions of sample tourists’ satisfaction and importance

hence, quadrant number one is found to be heavy.

Twenty-two variables are positioned on the 1st quadrant. Among these ‘traffic and

transport management facilities’, ‘parking facility’, ‘availability of petrol pump,’

‘general cleanliness’ and ‘quality of road facilities’ shows highest gap whereas other

facilities having least gap. Single variable viz. availability of authorized tour operator

is on the second quadrant showing high satisfaction and least importance.

‘Promptness of ticket window’ is positioned in the third quadrant. Thus, this facility is

not essential at Panchgani. Seven variables viz. ‘air connectivity’, ‘rail connectivity’,

‘level of road taxes’ and ‘its administration’, ‘Public utilities at the tourist attraction’,

‘tariff structure of hotel rooms’(18) and ‘petrol pump’ positioned in the 4th quadrant

which shows the highest gap in their satisfaction and importance level. Thus, this area

demands the attention for tourism development as tourists are more dissatisfied with

services and these facilities shows high importance to them.

Thus, quadrant 4 is important to focus since these parameters are most important and

carries low satisfaction in the opinion of sample tourists. Variable numbers 22, 23 and

24 viz. ‘levels of road taxes on vehicles’, ‘administration of road taxes’ (23) and

‘public utilities at tourist attraction’ in Panchgani need to be addressed.

Data Analysis


Infrastructural Gap at Wai



(S.D).

Table 4.2.9.4Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Wai

(n=37)

Sr. Tourist Services and AmenitiesSatisfaction Importance




2.95 15 1.05 4.11 22 0.97


Signage2.68 19 1.20 4.22 17 0.82


3.14 12 0.79 4.08 24 0.55


2.57 21 0.85 4.13 21 0.72


1.69 30 1.03 4.07 25 0.96


Hotel3.30 11 0.87 4.07 25 0.69


Dhabas3.42 3 0.90 4.19 18 0.52




2.32 26 0.71 3.57 30 0.83

23. Administration of the Road Taxes 2.65 20 1.01 3.78 28 0.89

Data Analysis


24. Public Utilities at the TouristAttraction

2.22 27 1.13 4.24 14 0.76


2.54 22 1.04 4.46 5 0.73


2.49 23 1.33 4.43 7 0.55


2.81 17 0.94 4.24 14 0.72


1.64 31 0.70 3.70 29 1.33


2.33 25 1.53 4.19 19 0.70

30. Conservation of Heritage Sites 3.30 10 1.15 4.46 5 0.7331. Promptness at the Ticketing

Window of the Monument/TouristAttraction

* * * * * *




Source: Field Data*As there were no ticketing window so no responses.

Graph 4

Data Analysis


Table 4.2.9.4 inferred that tourists are satisfied with fourteen tourist services as their

mean score is more than 3(quadrant Ist in the graph) and dissatisfied with nineteen

which mean score is less than 3 in Wai. ‘Telephone/mobile’ services receives 1st rank,

‘behaviour of service personnel at wayside restaurants and dhabas’ 2nd rank, 3rd rank

to ‘hygiene of wayside restaurant and dhabas’(19) and 4 rank to ‘availability of

hotels’(16) and ‘condition of street lighting’(10) each where tourist are strongly

satisfied. On the other hand, ‘air connectivity’, ‘availability of trained tourist guide’

(28) receives 32 and 31 rank respectively whereas ‘availability of authorized tour

operator’ receives 30th and 29th rank to ‘rail connectivity’ which reflect strong

dissatisfaction.

Only ‘air’ and ‘rail’ connectivity these two-tourist facilities tourists felt unimportant

as their mean score is less than 3 and remaining twenty-one are important because the

mean score is more than 3. Out of them ‘telephone/mobile services’, ‘drinking water

supply’, ‘condition of city roads’ and ‘quality of roads’ are most important as the

ranks are 1st four respectively. ‘Air connectivity’ and ‘rail connectivity’, ‘availability

of road taxes on vehicles’ and ‘availability of trained tourist guide’ status are least

important as the ranks are last four ie 32 to 29th respectively.

The Spearman rank correlation score is 0.673, which is significant at the 0.01 level (2-

tailed). This signifies uniformity into the opinion of tourist about satisfaction and

importance of tourist services and amenities at Wai.

1st quadrant shows eleven variables that reveal high satisfaction and high importance

towards tourist services and amenities. Second quadrant is empty, no single variable

found in this quadrant. Third quadrant having three variables viz. ‘promptness of

ticket window’ and ‘air’ and ‘rail’ connectivity, which are least, satisfied as well least

important to the tourist. Fourth quadrant having 19 variables that highlights its high

importance and low satisfaction level. The services viz. levels of road taxes on

vehicles, administration of road taxes, availability of trained tourist guide, behaviour

of the guide at the tourist attraction, condition of traffic and transport signage,

availability of authorized tour operators, sewage and drainage system, public utilities

at the tourist attraction, general cleanliness tourist attraction and area around it,

condition of signage within tourist attraction, parking facility at the tourist attraction,

Data Analysis


garbage disposal, behaviour of driver of commercial transportation, air connectivity,

availability of commercial transportation, traffic management, public convenience

along roads/streets, behaviour of service personnel at wayside restaurants and Dhabas

and drinking water supply shows tourists more dissatisfaction and high importance. It

means the Wai is still undeveloped for tourism. It demands more tourist facility and

services, which are lacking and are most important to the tourist who visited to the

Wai.

Therefore, quadrant 4 is important to focus since these parameters are most important

and carries dissatisfaction in the opinion of sample tourists. Variable number 6, 24, 26

and 25 viz. sewage and drainage system, public utilities at tourist attraction, condition

of signage within tourist attraction and general cleanliness of tourist attraction and

area around it in Wai need to be address.

Infrastructural Gap at Pratapgarh



(S.D).

Table 4.2.9.5Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Pratapgarh

(n=30)

Sr.


Mean

Rank

S.D.Mean

Rank

S.D.




3.00 27 1.13 4.50 8 0.82

6. Sewage and Drainage System 3.13 23 0.73 4.20 24 0.617. Garbage Disposal 3.00 27 0.98 4.17 25 0.758. Condition of City Roads 3.13 23 0.68 4.27 20 0.649. Drinking Water Supply 3.10 25 0.84 4.43 12 0.5010. Condition of Street Lighting 3.54 17 0.52 3.73 30 0.9411. Traffic Management 3.33 21 0.84 4.33 17 0.48

Data Analysis


12. Condition of Traffic orTransport Signage

3.63 14 0.89 4.43 12 0.50


4.10 3 0.61 4.37 15 0.67


4.23 2 0.68 4.27 20 0.91


2.83 29 0.98 * * *


Hotel3.70 12 0.67 4.43 12 0.57

18. Tariff Structure of the HotelRooms

3.09 26 1.04 4.33 17 0.48

19. Hygiene at Wayside Restaurantsand Dhabas

3.50 18 0.68 4.30 19 0.53

20. Availability of Petrol Pump 1.07 32 0.26 4.27 20 0.5821. Behaviour of Service Personnel

at Wayside Restaurants andDhabas

3.63 14 0.72 4.37 15 0.56


3.19 22 0.81 3.95 29 0.67

23. Administration of the RoadTaxes

3.40 19 0.75 4.05 28 0.60


2.57 30 0.97 4.57 6 0.57


3.70 12 0.65 4.60 4 0.67


4.03 5 0.89 4.70 2 0.47


3.73 11 0.64 4.60 4 0.50


3.77 10 0.86 4.47 11 0.68


4.10 4 0.70 4.50 8 0.51


Window of theMonument/Tourist Attraction

4.30 1 0.70 4.23 23 0.63




Source: Field Data* There was no response on importance of tour operator.

Data Analysis


Graph 5

Table 4.2.9.5 reveals that tourist who visited to Pratapgarh are satisfied with twenty-

eight tourist services because the mean score is more than 3 (quadrant Ist in the graph)

and dissatisfied with the five services because the mean score is less than 3. Among

these ‘promptness at the ticketing window of the monuments/tourist attraction’,

‘behaviour of driver of commercial transportations’, ‘availability of commercial

transportation’ and ‘behaviour of guide at tourist attraction’ shows strong satisfaction

level as their ranks are among first four respectively. However, the ‘air connectivity’,

‘availability of petrol pump’, ‘rail connectivity’ and ‘public utilities at the tourist

attraction’ status depicts strong dissatisfaction since the ranks are last between 33 to

30th respectively.

The destination demands importance towards all thirty-three tourist services and

amenities because their mean score is more than three. Out of that ‘telephone /mobile

services’, ‘condition of signage within the tourist attraction’, ‘conservation of heritage

sites’ and ‘parking facility at tourist attraction’ shows high importance by tourists as

the ranks are among first four respectively. Whereas ‘air’ and ‘rail’ connectivity,

Data Analysis


‘condition of street light’ and ‘levels of road taxes’ status shows least important as

the ranks are last and are between 32 to 29 respectively.

The calculation of Spearman’s rank correlation coefficient of satisfaction and

importance of tourist facilities and services is 0.583, which is significant at the 0.01

level (2-tailed). It shows that there is uniformity into the opinion of satisfaction and

importance of tourist services and amenities

Twenty-six variables found in the first quadrant. It means most of the important

tourist services and amenities are available to the tourist at the destination as well they

are satisfied with them. This is an encouraging clue in the tourism development.

‘Parking facility’, ‘condition of signage’ (26) and ‘telephone and mobile’ tourist

services shows highest gap in tourists ‘satisfaction and importance level. No single

variable found in second quadrant. Only one variable i.e. ‘availability of authorized

tour operator’ is found in the third quadrant. However, its importance level is on very

low. Six variables are found in the fourth quadrant. The variables as ‘air’ and ‘rail’

connectivity whose gap is very meager although other services like ‘petrol pump’,

‘public utilities at the tourist attraction’ , ‘garbage disposal’ and ‘drinking water

supply’ shows highest gap between tourist’s satisfaction and importance level. This

quadrant needs to focus for the development of tourism sector at Pratapgarh.


carries low satisfaction in the opinion of sample tourists. Variable number 20 and 24

viz. ‘availability of petrol pump’ and ‘public utilities at tourist attraction’ in

Pratapgarh needs to be address.

Data Analysis


Infrastructural Gap at Sajjangarh



(S.D).

Table 4.2.9.6Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Sajjangarh

(n=30)





2.83 22 1.29 4.47 18 0.57


Signage3.23 19 1.17 4.53 15 0.51


3.57 10 1.07 4.53 16 0.82


3.87 3 0.63 4.23 27 0.57


2.22 28 1.64 4.75 7 0.45


Hotel3.30 16 1.42 4.40 21 0.52


3.67 8 1.22 4.56 14 0.53


2.40 26 1.30 4.20 28 0.41




3.25 18 1.04 4.67 10 0.50


Data Analysis



3.70 7 0.88 4.77 5 0.43


3.77 6 0.82 4.90 1 0.31


3.83 4 0.99 4.77 5 0.43


2.83 22 0.99 4.87 3 0.35


* * * 4.47 18 0.68


* * * 4.47 18 0.51



* * * * * *



Significant(2-tailed) .000**. Correlation is significant at the 0.01 level (2-tailed).

Source: Field Data*As there were no facilities so there was no response from sample tourists.Graph 6

Data Analysis


Table 4.2.9.6 inferred that twenty-three variables’ satisfaction level mean score is

more than three (quadrant Ist in the graph). It shows tourists are satisfied about

twenty-three services, which are available at Sajjangarh. Remaining ten variables

mean score is less than three that means their dissatisfaction.

As 1st rank to ‘telephone/mobile services’, 2nd to ‘behaviour of service personnel at

way side restaurants and dhabas’, 3rd to ‘behaviour of driver of commercial

transportations’ , 4th rank each to ‘condition of signage within the tourist attraction’

and ‘conservation of heritage site’ that shows tourists’ have high satisfaction level. As

rank thirty to ‘air connectivity’, 29 to ‘rail connectivity’, 28 to ‘authorized tour

operators’ and 27 to ‘availability of hotels’ this shows strong dissatisfaction. Yet,

these services are not at all available at the destination.

Thirty tourist services are important to the tourists who visited to the destination as

their mean score is more than 3. Remaining three mean score is less than 3 which

shows they are not important to the tourist. ‘Conservation of heritage site’, ‘General

Cleanliness of tourist attraction’ has 1st rank each; ‘parking facility at the tourist

attraction’ carries 3rd rank and 4th rank the ‘quality of roads’ this shows high

importance level. Whereas ‘air,’ ‘rail’ connectivity, ‘availability of hotels’ and ‘petrol

pump’ shows least importance at the tourist as their ranks are thirty-two to twenty-

nine respectively.

The Spearman’s rank correlation Coefficient is 0.597 that is significant at the 0.01

level (2-tailed). This depicts that there is uniformity into the opinion of satisfaction

and importance of tourist services and amenities.

The first quadrant shows nineteen variables where tourists have high satisfaction level

and high importance. Among them ‘parking facility’, ‘condition of traffic and

transport signage’, ‘levels of road taxes on vehicles’, ‘general cleanliness’ and

‘quality of roads’ where tourist having satisfaction but compared to its importance

level it is average. No single variable found in second quadrant. In addition, third

quadrant depicts four variables, out of them promptness at ticket window received

least satisfaction and least importance since this services is neither available nor

essential. ‘Air’ and ‘rail’ connectivity and ‘availability of hotels’ like services also lie

in this quadrant but quiet closer to the average importance level. Fourth quadrant

shows ten variables, which reflect the high importance level of tourist services and

Data Analysis


amenities and lower satisfaction level of tourist. Out of them ‘availability of trained

guide’ and ‘behaviour of guide’ like facilities shows highest gap. The ‘hygiene at

wayside restaurants and dhabas’, ‘condition of city roads’ and ‘drinking water supply’

like facilities shows average gap between satisfaction and importance. It observed that

‘guide facility’ is not at all available at destination so the question of guide behaviour

does not arise.

Therefore, quadrant 4 is important to focus since these parameters are most important

and carries dissatisfaction in the opinion of sample tourists. Variable number 28

‘availability of tourist guide ‘lies in four quadrant since these facilities are not

available at all in Sajjangarh so question of variable number 29 i.e. behaviour of guide

is out of question. Variable numbers 15 and 8 as ‘availability of authorized tour

operator’ and ‘condition of city roads’ need to be address.

Infrastructural Gap at Aundh



(S.D).

Table 4.2.9.7Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Aundh

(n=30)

Sr.

Tourist Services andAmenities

Satisfaction Importance

MeanRank

S.D. Mean Rank S.D.

1. Air Connectivity Status 1.38 31 0.49 2.47 32 0.902. Rail Connectivity Status 2.00 30 0.00 2.47 32 0.903. Quality of the Roads 3.53 18 0.73 4.40 17 0.504. Quality of Way Side

Amenities Available on ThisRoad

3.13 19 0.63 4.47 15 0.51


2.93 24 0.94 4.33 20 0.48

6. Sewage and Drainage System 3.00 20 0.00 4.23 22 0.437. Garbage Disposal 4.00 9 0.00 4.54 14 0.518. Condition of City Roads 2.75 27 0.68 4.35 19 0.499. Drinking Water Supply 3.00 20 0.00 4.62 12 0.5010. Condition of Street Lighting 3.00 20 0.00 4.15 25 0.3711. Traffic Management 4.00 9 0.00 4.81 8 0.40

Data Analysis


12. Condition of Traffic orTransport Signage

2.91 25 0.60 4.69 11 0.47


2.74 28 0.75 4.21 23 0.41


4.00 9 0.00 3.17 30 0.38

15. Availability of AuthorizedTour Operators

3.00 20 0.00 3.00 31 0.00

16. Availability of Hotels 2.80 26 0.79 3.58 29 0.7217. Behaviour of Service Staff at

the Hotel4.00 9 0.00 4.17 24 0.56


4.00 9 0.00 4.46 16 0.51

19. Hygiene at WaysideRestaurants and Dhabas

2.71 29 0.62 4.79 10 0.41

20. Availability of Petrol Pump 4.00 9 0.00 4.29 21 0.4621. Behaviour of Service

Personnel at WaysideRestaurants and Dhabas

4.33 5 0.48 4.38 18 0.49


3.63 17 0.50 3.83 27 0.38

23. Administration of the RoadTaxes

3.75 16 0.45 3.67 28 0.48


4.40 3 0.50 4.93 1 0.25


4.33 5 0.48 4.93 1 0.25

26. Condition of Signage Withinthe Tourist Attraction

4.60 1 0.50 4.93 1 0.25


4.53 2 0.51 4.93 1 0.25


* * * 4.93 1 0.25


* * * 4.07 26 0.25


Window of theMonument/Tourist Attraction

4.40 3 0.50 4.80 9 0.41




Source: Field Data*As there were no facilities so, there were no responses.

Data Analysis


Graph 7

Table 4.2.9.7 draws the inferences that tourists who visited to Aundh are satisfied

with the twenty-five tourist services which are available at the destination as the mean

score is more than 3(quadrant Ist in the graph). However, dissatisfied with the eight

services since the mean score is less than 3. Tourist shows strong satisfaction towards

the services like ‘condition of signage within the tourist attraction’ that receives 1st

rank, 2nd to ‘parking facility at the tourist attraction’ (27) and 3rd each to ‘public

utilities at the tourist attraction’ and ‘promptness at the ticket window’. ‘Air’ and

‘rail’ connectivity, ‘hygiene of wayside restaurant and dhabas’ and ‘availability of

commercial transportation’ services shows strong dissatisfaction as the ranks are

thrity-one and twenty-eight respectively.

Thirty-one tourist services and amenities are important at the Aundh destination as the

mean score is more than 3. ‘Air’ and ‘rail’ connectivity like services tourist felt least

important which is closer to the average but not average since the mean score is less

Data Analysis


than 3. Among all thirty-three tourist services the priority has been given to the

‘public utilities at the tourist attraction’, ‘general cleanliness’, ‘condition of signage

within tourist attraction’ and ‘availability of trained tourist guides’ , ‘conservation of

site’ and ‘telephone and mobile services’ for their importance as they received 1st rank

each. On the contrary 32 rank each to ‘air’ and ‘rail’ connectivity and 31 rank

receives to ‘availability of authorized tour operator’ and 30 rank to ‘behaviour of the

drivers of commercial transportation’ which inferred that these services carries least

importance.

Spearman’s rank correlation coefficient between satisfaction and importance level of

tourist facilities and services is 0.563, which is significant at the 0.01 level (2-tailed).

This shows that there is uniformity into the opinion of satisfaction and importance of

tourist services and amenities.

First quadrant highlights about twenty-five variables, which show higher satisfaction

and higher importance. Among them, one variable viz. ‘availability of authorized tour

operator’ is on border which shows average common mean score 3. ‘Drinking water’,

‘sewage and drainage system’(6), ‘condition of street light’ facilities lay on the

average (median) line average satisfaction but more importance so still it demands

attention for improvement. Second quadrant is empty, so no tourist services are

showing their higher satisfaction and least importance. In the third quadrant ‘air’ and

‘rail’ connectivity, the two variables appeared which shows least importance and least

satisfaction. However, in the fourth quadrant six variables have appeared. Out of them

four variables viz. ‘availability of commercial transportation’, ‘condition of city

roads’, ‘hygiene at wayside restaurants and dhabas’ and ‘condition of traffic and

transport signage showing highest gap in satisfaction and importance level.


carries dissatisfaction in the opinion of sample tourists. Trained tourist guide is not

available so the behaviour of guide is out of question as the variable number 28 and

29 lies in quadrant IV. Variable numbers 19 and 12 viz. ‘hygiene at wayside

restaurant and Dhabas’ and ‘condition of traffic and transport signage’ need to be

address.

Data Analysis


Infrastructural Gap at Ajinkyatara



(S.D).

Table 4.2.9.8Perceptual Gap between Importance and Satisfaction of Tourist towards touristServices and Amenities at Ajinkyatara

(n=34)

Sr. Tourist Services and AmenitiesSatisfaction Importance

MeanRank

S.D. MeanRank

S.D.




2.41 29 1.42 3.76 25 0.75


Signage3.25 15 0.77 4.12 17 0.78


3.53 11 0.52 4.21 12 0.70


3.71 4 0.73 4.15 16 0.80


3.58 9 0.51 3.00 32 1.34


Hotel3.69 6 0.48 4.08 20 0.76


Dhabas3.60 8 0.52 4.27 11 0.47




2.86 22 0.95 3.55 28 1.04


Data Analysis



2.42 28 1.24 4.18 14 0.73


2.73 25 1.03 4.41 6 0.62


3.15 17 1.28 4.35 7 0.70


3.24 16 1.39 4.47 3 0.51


* * * 4.00 21 0.61


* * * 3.71 26 0.77



* * * * * *


Rank Correlation Coefficient .358*

Significant(2-tailed) .041*. Correlation is significant at the 0.05 level (2-tailed).

Source: Field Data*As there were no facilities, so there was no response.

Graph 8

Data Analysis


Table 4.2.9.8 highlights satisfaction and importance level of tourist facilities and

services at Ajinkytara. Tourists are satisfied with twenty-four services since the mean

score is more than three (quadrant Ist in the graph) whereas dissatisfied with nine

services. Tourist are strongly satisfied with the services like ‘telephone/mobile

services’, ‘availability of hotels’, ‘availability of petrol pump’ and ‘behaviour of

driver of commercial transportation’ as they received first to fourth rank. They are

strongly dissatisfied with ‘air connectivity’, ‘public convenience along roads/streets’,

‘public utilities at tourist attraction’ and ‘rail connectivity’ status where they received

thirty to twenty-seven rank respectively.

All tourist services are important and essential at the tourist destination as their mean

score is more than 3. Services like ‘power supply situation’ receives 1st rank , 2nd to

‘telephone/mobile services’, 3rd each to ‘parking facility’, ‘drinking water supply’

and ‘quality of roads’ that carries high importance level as their ranks are 1st to 4th

respectively. Some services like ‘availability of authorized tour operators’, ‘air

connectivity’, ‘sewage and drainage system’ and ‘quality of way side amenities

available on this road carries least importance with tourists point of view as their

ranks are thirty-two, thirty-one, thirty and twenty-nine respectively.

Spearman’s rank correlation coefficient is 0.358, which is significant at the 0.05 level

(2-tailed). It shows the uniformity into the opinion of Satisfaction and importance of

tourist services and amenities.

Twenty-four variables appeared in the first quadrant. Out of them one variable i.e.

‘availability of authorized tour operator’ is more towards the average importance and

higher satisfaction whereas ‘sewage and drainage system’, ‘quality of way side

amenities’, ‘garbage disposal’(7), ‘conservation of heritage site’(30) are on the

average side of satisfaction. No single variable appeared in second and third

quadrant. Nine variables appeared in the fourth quadrant. Out of them ‘air

connectivity’, ‘levels of road taxes’ shows least gap but the other facilities like ‘public

convenience along roads/streets’, ‘rail connectivity’, ‘public utilities at the tourist

attraction’, ‘condition of city roads’, ‘quality of roads’, ‘condition of street light’

reflects highest gap between the satisfaction and importance level of tourist because

tourist’s satisfaction level is far behind the importance of services.

Thus, quadrant 4 is important to focus since these parameters are most important and

Data Analysis


carries high dissatisfaction in the opinion of sample tourists. Variable number 24, 8, 3

and 25 viz. ‘Public utilities at tourist attraction’, ‘condition of city roads’, ‘quality of

roads’ and ‘general cleanliness at tourist attraction and area around it’(25) in

Ajinkyatara need to be address.

Infrastructural Gap at Kas



(S.D).

Table 4.2.9.9Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Kas

(n=30)





3.13 20 0.94 4.24 13 0.51


Signage3.70 5 0.84 4.40 8 0.50


3.59 9 0.50 4.10 20 0.40


3.72 4 0.70 4.10 20 0.48


3.30 15 0.47 3.67 30 0.84

16. Availability of Hotels 3.57 10 0.73 4.20 14 0.41

Data Analysis


17. Behaviour of Service Staff at theHotel

3.67 7 0.55 4.17 18 0.38


Dhabas3.40 13 0.67 3.93 28 0.25




2.70 25 1.06 3.97 27 0.18


Attraction1.97 28 1.33 4.67 1 0.48


3.33 14 0.92 4.47 4 0.57


3.17 18 0.87 4.20 14 0.48


2.00 27 1.20 4.50 3 0.51


1.09 31 0.30 3.87 29 0.97


* * * * 31 0.93



* * * 4.20 14 0.41


Rank Correlation Coefficient .190Significant(2-tailed) .290Correlation is not significant at the 0.05 level (2-tailed).

Source: Field Data*As there were no facilities, so there was no respons.

Data Analysis


Graph 9

Table 4.2.9.9 shows that tourists are satisfied with twenty-three facilities as the mean

score is more than 3(quadrant Ist in the graph) and dissatisfied with ten tourist

facilities and services since the mean is less than 3. Among these facilities, tourists are

strongly satisfied with the ‘telephone/mobile services’, ‘power supply’ (32),

‘availability of petrol pump’, ‘behaviour of driver of commercial transportation’ as

they received first four ranks respectively. However tourist who visited to the

destination are strongly dissatisfied with the services like ‘availability of trained

tourist guide’, ‘air connectivity’, ‘condition of city roads’ and ‘public utilities at the

tourist attraction’ as they received from 31 to 28 rank respectively.

The tourist who visited to the destination they think all the thirty-three facilities are

important at Kas as their mean score is more than 3. But they think the facilities like

‘public utilities at the tourist attraction’, ‘telephone and mobile services’, ‘parking

facility at the tourist attraction’ and ‘general cleanliness’ as well as ‘conservation of

heritage sites’ are the most important tourist services of Kas as they received 1st four

Data Analysis


ranks respectively. However, the least important services are ‘air connectivity’, ‘rail

connectivity’ and ‘behaviour of the guides’ and ‘availability of authorized tour

operators’ as they got thirty-three to thirty ranks respectively.

The Spearman’ rank correlation Coefficient between rank of satisfaction and rank of

importance is 0.190, which is not significant at a 0.05 level of (2-tailed). This shows

that there is no uniformity into the opinion of satisfaction and importance of tourist

services and amenities.

Nineteen variables appeared in first quadrant, which reflect high satisfaction and high

importance. Out of them three variables are on average importance side and higher

satisfaction viz. ‘tariff structure of the hotel rooms’(18), ‘administration of the road

taxes’(23) and ‘availability of petrol pump’. The services like ‘quality of way side

amenities available on this road’, ‘public convenience along roads/streets,’ ‘general

cleanliness,’ ‘condition of signage within the tourist attraction’ and ‘traffic

management’ are close towards the average satisfaction and higher importance level.

‘Power supply’ and ‘telephone/mobile’ services both appeared on higher side of

satisfaction and importance level. Two variables appeared in second quadrant, which

shows high satisfaction and low importance. They are ‘availability of authorized tour

operators’ and ‘hygiene at wayside restaurants and dhabas’. Five variables appeared

in 3rd quadrant which reflects low importance and low satisfaction. They are ‘air’ and

‘rail’ connectivity, ‘availability of trained tourist guide’ and their behaviour, but

‘levels of road taxes on vehicles’ is near to average of both satisfaction and

importance level. Seven variables appeared in the fourth quadrant that shows their

high importance and low satisfaction. Among this, one variable viz. ‘promptness of

ticketing window’ is at zero level of satisfaction as this service is not at all available at

Kas. ‘Garbage disposal’, ‘sewage and drainage system’ and ‘quality of roads’ are

close to the average level of satisfaction whereas the ‘condition of city roads’, ‘public

utilities at the tourist attraction’ and ‘parking facility at the tourist attraction’ like

facilities reflects higher gap i.e. more dissatisfaction and high importance. These

facilities are needed to be developed.

So it reveals that quadrant 4 is important to focus since these parameters are most

important and carries dissatisfaction in the opinion of sample tourists. Variable

number 8, 27 and 24 viz. ‘Conditions of city roads’, ‘parking facility at the tourist

Data Analysis


attraction’, ‘public utilities at the tourist attraction’ need to be address. ‘Ticketing

window facility’ is not available at all in Kas so the variable 31 lies in four quadrant

where satisfaction for this facility is zero level.

Infrastructural Gap at Thoseghar



(S.D).

Table 4.2.9.10Perceptual Gap between Importance and Satisfaction of Tourist towards Touristservices and Amenities at Thoseghar

(n=33)


Mean Rank S.D. Mean Rank SD1. Air Connectivity Status 1.47 31 0.62 2.64 32 1.172. Rail Connectivity Status 2.24 24 0.66 2.88 31 1.173. Quality of the Roads 2.21 25 1.05 4.33 13 0.484. Quality of Way Side Amenities



3.03 15 0.53 4.12 23 0.33


Signage2.18 6 0.73 4.76 7 0.44


2.64 19 0.68 4.42 11 0.50


3.70 7 0.47 4.25 18 0.44


3.29 12 0.46 3.19 30 1.33

16. Availability of Hotels 3.77 3 0.43 4.31 14 0.6417. Behaviour of Service Staff at the Hotel 3.76 4 0.60 4.12 23 0.33

Data Analysis



Dhabas2.58 20 0.76 4.18 22 0.39

20. Availability of Petrol Pump 3.85 1 0.36 4.06 26 0.35

21. Behaviour of Service Personnel atWayside Restaurants and Dhabas

3.76 5 0.44 4.21 20 0.48


2.58 21 0.61 3.97 28 0.30

23. Administration of the Road Taxes 2.55 22 0.67 3.94 29 0.3524. Public Utilities at the Tourist Attraction

1.45 32 0.83 4.91 4 0.29

25. General Cleanliness Tourist Attractionand Area Around it

2.12 27 0.55 4.94 1 0.24


2.73 17 0.94 4.82 6 0.39


1.48 30 0.94 4.94 1 0.24

28. Availability of Trained Tourist Guides 2.71 18 0.64 4.58 10 0.7929. Behaviour of the Guides at the Tourist

Attraction3.64 8 0.56 4.39 12 0.79


of the Monument/Tourist Attraction* * * * * *


Rank Correlation Coefficient -.044Significant(2-tailed) .808Correlation is not significant at the 0.05 level (2-tailed).

Source: Filed Data*As there were no facilities, so there were no responses.

Data Analysis


Graph 10

Table 4.2.9.10 depicts sixteen variables which show the satisfaction as their mean

score is more than 3(quadrant Ist in the graph) whereas remaining seventeen variables

reflecting dissatisfaction as their mean score is less than 3. Tourist are strongly

satisfied with the services like ‘conservation of heritage sites’, ‘availability of petrol

pump’, ‘ availability of hotels’, ‘behaviour of service staff at the hotel’ as the ranks 1st

, 2nd 3rd and 4th respectively. However, tourist are strongly dissatisfied with ‘public

utilities at the tourist attraction’, ‘air connectivity’, ‘parking facility’ and ‘traffic

management’ as they received 32th , 31st , 30th and 29th ranks respectively.

Tourists think that thirty-one services are important at Thoseghar as their mean score

is more than 3 whereas two facilities viz. ‘air’ and ‘rail’ connectivity are not

important as their mean score is less than 3. ‘Parking facility at the tourist attraction’,

‘conservation of heritage sites’, ‘general cleanliness’, ‘telephone mobile’ like services

and ‘public utilities at the tourist attraction’, tourist think most important as their

Data Analysis


ranks 1st to 4th. But ‘air’ and ‘rail’ connectivity and ‘availability of authorized tour

operators’ and ‘administration of road taxes’ are least important in tourist point of

view because the ranks are 32, 31st , 30th and 29th respectively.

The Spearman’s rank correlation coefficient is -0.044, which is insignificant at the

0.05 level of (2-tailed). It reveals that there is no uniformity into the opinion of

sample tourist about satisfaction and importance of tourist services and amenities.

Sixteen variables are positioned in the 1st quadrant that reflects high importance and

high satisfaction level at the destination. ‘Public convenience along roads/streets’(5),

‘sewage and drainage system’, ‘garbage disposal’ i.e. ‘civic administration’ like

facility have average satisfaction but high importance so gap is more. On the other

hand, ‘conservation of heritage’ and ‘power supply’ carries high level of importance

and satisfaction. ‘Availability of authorized tour operators’ like service is near to the

average of importance level. Remaining services and amenities carried noticeable gap

in their importance and satisfaction. Second quadrant is empty. Third quadrant shows

one variable i.e. ‘promptness at the ticketing window’ that is less important as well

less satisfaction level according to the tourist perception. Seventeen variables are

found in the fourth quadrant, which shows high importance and low satisfaction. Out

of them two variables ‘air’ and ‘rail’ connectivity are close to the lower satisfaction

and lower importance somehow few tourist may demand this service at Thoseghar.

Facilities like ‘condition of city road’, ‘traffic management’, ‘public utilities at the

tourist attraction’, ‘parking facility’, ‘general cleanliness at the tourist attraction and

area around it’, ‘condition of traffic signage’ showing noticeable gap on negative side

between satisfaction and importance so needed to be developed or it is emergency to

be developed as a tourist destination.

From the table it can be concluded that quadrant 4 is important to focus since these

parameters are most important and carries more dissatisfaction in the opinion of

sample tourists. Variable number 8, 11, 24, 27, 25 and 12 viz. ‘Condition of city

roads’, ‘traffic management’, ‘public utilities at tourist attraction’, ‘parking facility at

the tourist attraction’, ‘general cleanliness at the tourist attraction’ and ‘condition of

traffic and transport signage’ need to be attend.

Data Analysis


Infrasturctural Gap at Satara District as a Whole



(S.D).

Table 4.2.9.11Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Satara District as a Whole.

(n=326)

Sr.





3.02 23 0.96 4.23 18 0.66


Signage3.10 21 1.02 4.47 7 0.58


3.52 10 0.83 4.32 14 0.59


3.75 6 0.71 4.16 26 0.69


2.99 24 0.87 3.14 31 1.24


Hotel3.67 7 0.74 4.20 23 0.54


Dhabas3.16 18 0.97 4.26 16 0.52




2.78 30 0.94 3.97 30 0.64

Data Analysis



Attraction2.65 31 1.25 4.59 4 0.55


3.25 15 0.97 4.60 2 0.57


3.36 13 1.25 4.57 6 0.55


2.95 27 1.24 4.58 5 0.56


2.98 26 1.10 4.21 20 0.91


3.53 9 0.75 4.09 28 0.77


of the Monument/Tourist Attraction4.19 1 0.65 4.39 12 0.59




Source: Field Data

Graph 11

Data Analysis


Table 4.2.9.11 shows satisfaction level of tourist who visited to Satara as they are

satisfied with the twenty three variables as the mean score is more than 3(quadrant Ist

in the graph). On the contrary tourist are dissatisfied with the ten variables while their

mean score is less than3. Tourists are strongly satisfied with the facilities like

‘promptness of ticketing window of the monument/tourist attraction’,

‘telephone/mobile services’, ‘conservation of heritage sites’, and ‘behaviour of

service personnel at wayside restaurants and dhabas’ as they received rank first to

fourth respectively. But the tourist are strongly dissatisfied with the tourist amenities

like ‘air’, ‘rail’ connectivity, ‘public utilities at tourist attraction’ and ‘levels of road

taxes on vehicles’ as they have thirty-three to thirty ranks respectively.

In tourist point of view except two all facilities and amenities are important to the

tourist at Satara since their mean score is more than 3. Only two facilities viz. ‘air’

and ‘rail’ carries least importance in tourist point of view as their mean score is less

than 3. Among them ‘telephone/mobile services’, ‘general cleanliness at the tourist

attraction’, ‘conservation of heritage site and area around it’, ‘public utilities at the

tourist attraction’ as they received rank first, second, third and fourth respectively.

According to the tourist, services and amenities like ‘air’ and ‘rail’ connectivity,

‘availability of authorized tour operators’ and ‘levels of road taxes on vehicles’

carrying least importance since the ranks are 33, 32, 31 and 30 respectively.

Spearman rank correlation coefficient is 0.662, which is significant at the 0.01 level

(2-tailed). This reveals that there is uniformity into the opinion of tourist of

satisfaction and importance.

1st quadrant highlights twenty four variables which show high importance as well as

high satisfaction level. Most of the variables viz. ‘quality of roads’, ‘condition of

traffic and transport signage’, ‘hygiene at wayside restaurant and dhabas’,

‘administration of road taxes’, ‘general cleanliness’ and ‘condition of signage within

the tourist attraction’ are close to the average satisfaction level but carries high

importance level so need to be attend in the tourism development. One variable i.e.

availability of authorized tour operator is positioned in the second quadrant but very

close towards the average importance and average satisfaction. Two variables as ‘air’

and ‘rail’ connectivity lie in the third quadrant carrying least importance and low

satisfaction so it can be neglected. However, the most important is fourth quadrant

Data Analysis


which reflects high importance and low satisfaction having six variables all are near

to the average of satisfaction but has highest importance level. These are ‘public

utilities at the tourist attraction’, ‘traffic management’, and ‘condition of traffic and

transport signage,’ ‘condition of city roads’, quality of roads’, ‘parking facility’,

‘general cleanliness at tourist attraction and area around ’ and ‘condition of signages

within tourist attraction’. Thus, these services and amenities demand more attention

for the development of Satara as a tourist destination because it shows high

dissatisfaction but high importance of services.


carries dissatisfaction in the opinion of sample tourists. Variable number 8, 11 and 24

,27, 25, 3, 12, 26 viz. ‘Condition of city roads’, ‘traffic management’, ‘public utilities

at tourist attraction’ , ‘parking facility at the tourist attraction’, general cleanliness at

troust attraction and area around’, ‘quality of roads’ , ‘condition of traffic and

transport signages’ and ‘condition of signages within the tourist attraction’ in Satara

need to be address.

Infrastructural Gap in Hoteliers Point of View



(S.D).

Table 4.2.9.12Perceptual Gap between Importance and Satisfaction of Hoteliers towards TouristServices and Amenities at Satara District as a Whole

(n=40)





3.13 22 1.18 4.33 11 0.47

6. Sewage and Drainage System 3.00 24 1.13 4.43 3 0.507. Garbage Disposal 3.10 23 1.12 4.43 3 0.508. Condition of City Roads 2.90 25 1.13 4.48 2 0.519. Drinking Water Supply 3.67 12 0.77 4.43 3 0.50

Data Analysis

Shivaji University, Kolhapur 280Source: Field Data

10. Condition of Street Lighting 3.40 16 1.01 4.15 26 0.4311. Traffic Management 2.90 25 1.30 4.25 19 0.4912. Condition of Traffic or Transport

Signage3.73 11 0.82 4.28 17 0.45


4.13 2 0.52 4.30 16 0.56


4.13 2 0.40 4.35 10 0.48


3.58 13 0.75 4.05 29 0.45


Hotel3.83 8 0.90 4.33 11 0.47


3.38 18 0.78 4.21 24 0.52


4.03 4 0.80 4.40 6 0.50




3.14 21 0.72 3.94 31 0.47


Attraction2.24 31 1.15 4.33 11 0.47


2.85 28 1.00 4.33 11 0.47


3.43 15 0.75 4.25 19 0.44


2.63 30 1.19 4.38 8 0.49


3.46 14 1.02 4.23 23 0.58


3.94 7 0.61 4.24 22 0.61



4.00 6 0.55 4.11 28 0.52

32. Power Supply Situation 3.78 9 0.77 4.33 11 0.4733. Telephone/Mobile Services 4.43 1 0.55 4.58 1 0.50Rank Correlation Coefficient .311Significant(2-tailed) .078Correlation is not significant at the 0.05 level (2-tailed).

Data Analysis


Graph 12

Table 4.2.9.12 reveals that Hoteliers are satisfied with twenty-four tourist services and

amenities seeing that the mean score is more than 3(quadrant Ist in the graph).

Whereas dissatisfied with nine services as the mean score is less than 3. Hoteliers are

strongly satisfied with the ‘telephone/mobile services’, ‘availability of commercial

transportation’ and ‘behaviour of the drivers of commercial transportation’,

‘availability of hotels’ and ‘hygiene at wayside restaurants and dhabas’ because ranks

are 1st, 2nd, 3rd and 4th respectively. However, they are strongly dissatisfied with the

‘air’ and ‘rail’ connectivity, ‘public utilities at the tourist attraction’ and ‘parking

facility’ whose ranks are thirty-three to thirty respectively.

According to hoteliers, all thirty-three tourist services and amenities are important at

the destination since the mean score is 3. But the most important services are

‘telephone and mobile services’ i.e. communication that receives 1st rank, 2nd to

‘condition of city roads’ and 3rd rank each to ‘drinking water supply’, ‘garbage

Data Analysis


disposal’ and ‘sewage and drainage system’ i.e. civic administration. The least

important services are ‘air’ and ‘rail’ connectivity, ‘levels of road taxes’ and

‘administration of the road taxes’ whose ranks are 33 to 30 respectively.

Spearman’s rank correlation coefficient is 0.311, which is not significant at 0.05

levels (2-tailed). This refers that there is no uniformity into the opinion of satisfaction

and importance.

Twenty-three variables appeared in the 1st quadrant which shows the highest

satisfaction and highest importance level of tourist services and amenities in hoteliers’

point of view. Only one service i.e. ‘telephone and mobile services’ is in highest

position as well ‘administration of road taxes’ is very close to the average importance

level. The services like ‘garbage disposal’, ‘public convenience along roads/streets’,

and ‘quality of wayside amenities available on this road’ and ‘availability of pertol

pump’ are closer to the average satisfaction and carries high importance level. Other

variables appeared on highest side of satisfaction rather than its importance. Level of

road taxes on vehicle lie in the 2nd quadrant, which reflects high satisfaction and lower

importance, but the importance level is close to the average importance. ‘Air’ and

‘rail’ connectivity services are positioned in the third quadrant, which shows the low

satisfaction and low importance level. Eight variables appeared in the fourth

quardrant, which is more important because of their high importance and lower

satisfaction level. They are ‘public utilities at the tourist attraction’, ‘general

cleanliness at tourist attraction and area surround it’, ‘parking facility at the tourist

attraction’, ‘conservation of heritage sites’, ‘traffic management’, ‘sewage and

drainage system’, ‘quality of roads’, ‘condition of city roads’. A ‘public utility at the

tourist attraction’ is the priority in the development of tourist destination in Satara.

Condition of city roads, sewage and drainage system, quality of roads and traffic

management are nearer to the average satisfaction level so with little stretch it can be

improved to the extent of tourist satisfaction.

It concludes that quadrant four is important to focus since these parameters are most


number 24, 25 and 27 viz. ‘Public utilities a tourist attraction’, ‘general cleanliness’

and ‘parking facility at the tourist attraction’ need to be attended to.

Data Analysis


Infrastructural Gap inTour Operators Point of View



(S.D).

Table 4.2.9.13Perceptual Gap between Importance and Satisfaction of Tour Operators towardsTourist Services and Amenities at Satara District as a Whole

(n=10)

Sr. Tourist Service and AmenitiesSatisfaction Importance

Mean Rank S.D. Mean Rank S.D.




2.60 22 1.35 4.2 20 0.63


Signage3.00 11 1.15 4.5 5 0.53


3.90 2 0.74 4.2 20 0.42


3.80 3 0.79 4.5 5 0.53


3.40 10 0.97 4 29 0.82


Hotel3.60 6 0.70 4.2 20 0.42


Dhabas3.44 8 0.88 4.3 11 0.48




2.67 21 1.32 4.3 11 0.67


Attraction2.10 32 0.88 4.5 5 0.71

Data Analysis



2.50 24 0.97 4.3 11 0.67


2.60 22 0.97 4.2 20 0.63


2.50 24 0.97 4.3 11 0.67


2.40 27 1.35 4.3 11 0.48


3.00 11 1.22 4.2 20 0.44


of the Monument/Tourist Attraction3.00 11 0.87 3.9 30 0.74

32. Power Supply Situation 2.80 18 1.03 4.4 10 0.733. Telephone/Mobile Services 3.80 3 1.23 4.8 1 0.42Rank Correlation Coefficient .642**


Source: Field Data

Graph 13

Data Analysis


Table 4.2.9.13 reveals that Tour operators are satisfied with the fourteen tourist

services and amenities which are available at Satara since their mean score is more

than 3(quadrant Ist in the graph). However, they are dissatisfied with the nineteen

services and amenities as the mean score is less than 3. Tour operators are strongly

satisfied with services that are ‘availability of hotels’, ‘availability of commercial

transportation’, ‘behaviour of drivers of commercial transportation’ and ‘telephone

and mobile services’ whose ranks are one, two and three respectively. However,

strong dissatisfaction with the ‘air connectivity’, ‘public utilities at tourist attraction’,

‘sewage and drainage system’, ‘traffic management’, ‘condition of city roads’, ‘public

utilities at tourist attraction’, ‘condition of city roads’ and ‘traffic management’ as

their ranks are thirty-three to twenty-nine respectively.

All the tourist services and amenities are important except ‘air connectivity’ as the

mean score is more than 3. ‘Drinking water supply,’ ‘Telephone and mobile’ services

receive 1st rank each, and 3rd rank each to ‘condition of city roads’ and ‘quality of

roads’ which are most important. But ‘air connectivity’, ‘rail connectivity,’ ‘traffic

management’ and ‘promptness of ticketing window’ finds least importance since the

ranks are thirty three to twenty respectively.

Spearman’s rank correlation coefficient is 0.311, which is not insignificant at 0.05

levels (2-tailed). This signifies that there is no uniformity into the opinion of

satisfaction and importance.

The first quadrant is reflecting the highest importance as well highest satisfaction

levels of which fourteen variables are positioned. Out of them four variables viz.

‘promptness of ticketing window’, ‘behaviour of guide at tourist attraction’,

‘condition of traffic’, ‘transport signage’ and ‘quality of roads’ are on the border of

satisfaction and very close to the highest importance level. Second quadrant is empty;

it means there is no single variable carrying low importance and highest satisfaction.

‘Air connectivity’ finds only in third quadrant, which reflects low satisfaction and low

importance. Sixteen variables found in fourth quadrant viz. rail connectivity, traffic

management, sewage and drainage system, public utilities at the tourist attraction,

parking facility at the tourist attraction, availability of trained tourist guide, general

cleanliness at tourist attraction and area around it, condition signage within tourist

attraction, levels of road taxes on vehicles, quality of roads, condition of traffic or

Data Analysis


transport signage, quality of wayside amenities available on this road, administration

of road taxes, condition of street light, drinking water supply, behaviour of guide at

tourist attraction, promptness of ticket window and power supply situation which

depicts highest importance level and lower satisfaction level. Among these services

‘public convenience along roads/streets’, ‘general cleanliness of tourist attraction and

area around it’, ‘parking facility’, ‘conservation of heritage sites’, ‘availability of

trained tourist guide’, ‘drinking water supply’, ‘traffic management’, ‘sewage and

drainage system’, ‘public utilities at tourist attraction’ and ‘condition of city roads’

are needed to be developed as these services reveals high importance to the tourist and

however, more dissatisfaction towards the services.

It concludes that Quadrant 4 is important to focus since these parameters are most


number 6, 24, 8, 30 and 7 viz. ‘Sewage and drainage system’, ‘public utilities at

tourist attraction’, ‘condition of city roads’, ‘conservation of heritage site’ and

‘garbage disposal’ need to be address.

Infrastructural Gap According to All Stakeholders


facilities are presented with the help of mean score.

Table 4.2.9.14Perceptual Gap between Importance and Satisfaction of Stakeholders towards TouristServices and Amenities at Satara District as a Whole

Sr

Stakeholders’ Perception

Tourist Service and Amenities

Satisfaction Mean Importance Mean

Tourist

Hoteliers

Touroperator

Tourist

Hoteliers

Touroperator

1. 2. 3. 4. 5. 6. 7.1. Air Connectivity Status 1.29 1.17 1.71 2.83 3.18 2.62. Rail Connectivity Status 1.96 2.20 2.90 3.10 3.53 3.13. Quality of the Roads 3.17 2.90 3.00 4.45 4.40 4.64. Quality of Way Side Amenities

Available on This Road3.30 3.40 2.80 4.29 4.25 4.2


3.02 3.13 2.60 4.23 4.33 4.2

6. Sewage and Drainage System 3.11 3.00 2.11 4.20 4.43 4.3

Data Analysis


7. Garbage Disposal 3.16 3.10 2.30 4.21 4.43 4.38. Condition of City Roads 2.79 2.90 2.20 4.39 4.48 4.69. Drinking Water Supply 3.43 3.67 2.80 4.44 4.43 4.810. Condition of Street Lighting 3.40 3.40 2.90 4.24 4.15 4.211. Traffic Management 2.92 2.90 2.20 4.42 4.25 3.912. Condition of Traffic or Transport

Signage3.10 3.73 3.00 4.47 4.28 4.5


3.52 4.13 3.90 4.32 4.30 4.2


3.75 4.13 3.80 4.16 4.35 4.5


2.99 3.58 3.40 3.14 4.05 4

16. Availability of Hotels 3.55 4.03 4.00 4.14 4.38 4.517. Behaviour of Service Staff at the

Hotel3.67 3.83 3.60 4.20 4.33 4.2


3.12 3.38 3.50 4.16 4.21 4.2


3.16 4.03 3.44 4.26 4.40 4.3

20. Availability of Petrol Pump 3.09 3.25 3.70 4.20 4.28 4.321. Behaviour of Service Personnel at

Wayside Restaurants and Dhabas3.76 3.75 3.44 4.21 4.15 4.2

22. Levels of Road TaxesonVehicles(Tax Rates)

2.78 3.14 2.67 3.97 3.94 4.3

23. Administration of the Road Taxes 2.99 3.36 2.89 4.04 4.00 4.324. Public Utilities at the Tourist

Attraction2.65 2.24 2.10 4.59 4.33 4.5


3.25 2.85 2.50 4.60 4.33 4.3


3.36 3.43 2.60 4.57 4.25 4.2


2.95 2.63 2.50 4.58 4.38 4.3


2.98 3.46 2.40 4.21 4.23 4.3


3.53 3.94 3.00 4.09 4.24 4.2

30. Conservation of Heritage Sites 3.76 2.76 2.50 4.60 4.20 4.531. Promptness at the Ticketing


4.19 4.00 3.00 4.39 4.11 3.9

32. Power Supply Situation 3.75 3.78 2.80 4.44 4.33 4.433. Telephone/Mobile Services 3.93 4.43 3.80 4.72 4.58 4.8Source: Field Data

Data Analysis


Graph 14

Low Importance High

Table 4.2.9.14 reveals the opinion of tourist, hotelier and tour operator on 33 tourist

services and amenities at Satara. For Air (1) and rail (2) connectivity. Tourist, hotelier

and tour operators are dissatisfied with services and tourist and tour operator do not

feel its importance level for tourism development but hoteliers said it is important for

tourism development. It shows there is a difference of opinion among the

stakeholders.

For Road Connectivity (3, 4), Tourist and tour operators are satisfied with quality of

roads (3) as the mean score is more than 3 but hoteliers are not as their mean score is

less than 3 and tourist and hoteliers are satisfied with quality of way side amenities

available on this road (4) since the mean score is more than 3 but the tour operators

Data Analysis


are not as the mean score is less than 3. All stakeholders feel road connectivity is most

important in Satara for tourism development.

For Civic Administration (5 to 10) tourist and hoteliers are satisfied with Public

Conveniences along Roads/Streets (5), Sewage and Drainage System (6) and Garbage

Disposal since the mean score is more than 3 but tour operators are not as the mean

score is less than 3. For condition of city roads (8) all carries similar opinion that

dissatisfaction as the mean score is less than 3. For Drinking water supply(9) and

condition of street lighting(10) tourist and hoteliers are satisfied as the mean score is

more than 3 but hotelier is dissatisfied for the same as the mean score is less than 3.

However all carries similar opinion on the most importance of civic administration for

tourism development is Satara since the mean score is more than 4.

For Traffic and Transport Services (11 to 14) all stakeholders are dissatisfied with

traffic management (11) since the mean score is less than 3 but satisfied with

condition of traffic and transport signage(12), availability of commercial

transportation(13) and behaviour of drivers of commercial transportations(14) as the

mean score is more than 3. According to them traffic and transport services are most

important in Satara tourism development.

For Tourist Facilities (15 to 21) Tourist are dissatisfied with the availability of

authorized tour operators (15) as the mean score is less than 3 whereas the hoteliers

and tour operators are satisfied for the same since the mean score is more than 3. All

stakeholders are satisfied with availability of hotels (16), Behaviour of Service Staff

at the Hotel (17), Tariff Structure of the Hotel Rooms (18), Hygiene at Wayside

Restaurants and Dhabas (19), Availability of Petrol Pump (20) and Behaviour of

Service Personnel at Wayside Restaurants and Dhabas (21) since the mean score is

more than 3. According to stakeholders, tourist facilities are most important for

tourism development at Satara since the mean score is more than 4.

For Taxes/ Permits (22 and 23), Tourist and tour operators are dissatisfied as the mean

score is less than 3 and hoteliers are satisfied since the means score is more than 3.

According to Stakeholders taxes and permits is most important as the mean score is

more than 3.

For Maintenance and Management of Tourist Attraction (24 to 31) All stakeholders

are satisfied with behaviour of the guide at the tourist attraction (29) and promptness

Data Analysis


at the ticketing window of the monument/tourist attraction(31) since the mean score is

more than 3. They are dissatisfied with the public utilities at the tourist attraction (24),

parking facility at the tourist attraction (27) as the mean score is less than 3. Tourist

are satisfied with general cleanliness of tourist attraction and area around it (25) as the

mean score is more than 3 but hoteliers and tour operators are not as the mean score is

less than 3. Tourist and hoteliers are satisfied with the condition of signage within the

tourist attraction (26) since the mean score is more than 3 but tour operators are not as

the mean score is less than 3. Tourist and Tour operators are not satisfied with

availability of trained tourist guide (28) as the mean score is less than 3 but hoteliers

are satisfied for the same as the mean score is more than 3. Tourist are satisfied with

the conservation of heritage sites(30) since the mean score is more than 3 but hoteliers

and tour operators are not as the mean score is less than 3. According to all

stakeholders, maintenance and Management of Tourist attraction services and

amenities are most important at Satara since the mean score is more than 4.

For Other Services (32 and 33) Tourist, hoteliers, and tour oprators are satisfied on

telephone and mobile services (33) as the mean score is more than 3. Tourist and

hoteliers are satisfied with power supply since the mean score is more than 3 but the

tour operators are not as the mean score is less than 3. According to stakeholders

power supply and telephone services are most important for tourism development at

Satara.

It concludes that all are dissatisfied with air(1) and rail(2) connectivity, condition of

city roads(8), traffic management(11), public utilities at the tourist attraction(24),

parking facilities(27). Thus, need to be address for the tourism development at Satara.

It shows the weakness of Satara on infrastructural base.

All are satisfied with condition of traffic and transport signage(12), availability of

commercial transportation (13), behaviour of driver of commercial transportations

(14), availability of hotels(16), behaviour of service staff at the hotels(17), tariff

structure of the hotel rooms (18), hygiene of wayside restaurant and Dhabas(19),

availability of petrol pump (20), behaviour of service personnel at wayside restaurants

and Dhabas(21), behaviour of the guide at the tourist attraction(29), promptness at the

ticketing window of the monument/tourist attraction(31), power supply (32) and

Data Analysis


telephone and mobile services(33). It shows the strengths of Satara on infrastructure

base.

There are differences of opinion among the perception of tourist and service provider

i.e. hoteliers and tour operators on some of the tourist services and amenities. As the

tourists are dissatisfied with the availability of tour operators (15), level of road taxes

(22) and administration of the road taxes (23), availability of trained tourist guide (28)

but service providers do not carry similar opinion. According to tourist, hoteliers and

tour operators, all these tourist services and amenities are most important except air

service, which is not important to the tourist whereas it is important to the hoteliers.

X-axis represents the importance level and y-axis represents the satisfaction level. 3 is

the median value divide the graph into 4 quadrants. Ist quadrant depicts high

importance and high satisfaction where 13 variables in a sound position. IInd quadrant

depicts low importance and high satisfaction where no single variable found. In IIIrd,

quadrant depicts one variable that shows less importance and less satisfaction i.e. air

connectivity. However, in IVth quadrant 19 variables that shows high importance but

least satisfaction with slight difference of opinion among the stakeholders on

perception of tourist services and amenities.

Factor Analysis:

The responses towards tourist amenities on five-point scale were taken from tourist.

Thirty-three tourist amenities were executed. Researcher with view to find out

commonalities into preferences factor analysis has been applied.

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .784

Bartlett's Test ofSphericity

Approx. Chi-Square 5.85

df 528

Sig. .000

Data Analysis


The KMO and Bartlett’s measure comes to 0.784, which shows data adequacy to go

for factor analysis.

Total Variance Explained

Component

Initial Eigen valuesExtraction Sums ofSquared Loadings

Rotation Sums of SquaredLoadings

Total% of

VarianceCumulat

ive %Total

% ofVariance

Cumulative %

Total% of

VarianceCumulat

ive %

1 7.129 21.604 21.604 7.129 21.604 21.604 4.728 14.327 14.327

2 3.938 11.933 33.536 3.938 11.933 33.536 3.291 9.972 24.299

3 2.523 7.644 41.181 2.523 7.644 41.181 3.132 9.491 33.790

4 2.208 6.692 47.872 2.208 6.692 47.872 2.702 8.189 41.979

5 1.702 5.158 53.031 1.702 5.158 53.031 2.029 6.149 48.129

6 1.606 4.867 57.898 1.606 4.867 57.898 1.995 6.046 54.174

7 1.389 4.209 62.106 1.389 4.209 62.106 1.765 5.349 59.523

8 1.243 3.766 65.872 1.243 3.766 65.872 1.680 5.092 64.615

9 1.021 3.093 68.965 1.021 3.093 68.965 1.436 4.350 68.965

Extraction Method: Principal Component Analysis.

The responses of 326 samples were executed with the help of factor analysis. Nine

factors have been extracted using principal component methods, which explain

68.96% of variance.

The rotated component matrix has been work out to find out the nine factors and thevariables belongs to every factor.

Rotated Component MatrixComponent

TouristServicesCode

1 2 3 4 5 6 7 8 9

C7I .842 .046 .157 -.019 .028 .152 .091 -.006 -.034C6I .799 .055 .149 -.055 -.008 .135 .074 -.023 -.036C9I .795 .194 -.032 -.094 .069 .037 .044 .146 -.006C11I .780 .157 .074 .159 .019 -.082 .017 -.118 -.051C8I .746 .238 .000 .051 -.037 .117 -.113 .257 .162C12I .660 .274 .079 .298 .006 -.065 -.104 -.074 .090C10I .656 .187 .042 -.057 .037 .019 -.160 .320 .376C19I .261 .806 .280 .009 -.161 .010 .100 .091 -.028

Data Analysis


C20I .304 .774 .151 -.016 -.037 -.032 -.059 .191 .105C21I .236 .749 .088 .058 -.197 .026 .078 -.035 .006C13I .510 .518 .184 -.021 -.035 .053 .086 -.097 .039C14I .245 .518 .125 .160 .224 .148 -.137 -.228 .191C23I .166 .092 .883 -.121 -.105 -.024 -.016 .033 .032C22I .176 .090 .875 -.029 -.130 -.068 -.029 .006 .016

C18I-

.004.479 .634 -.001 .285 -.014 -.020 .048 -.092

C17I .004 .470 .611 -.015 .293 .066 -.091 .075 -.049C16I .173 .357 .559 -.166 .245 -.006 -.122 .054 .260C25I .060 -.004 -.055 .767 -.085 .139 .085 .117 .043C24I .017 .129 -.001 .744 -.079 .169 -.006 .099 -.046C27I .085 -.140 -.097 .725 .003 -.038 244 091 -.173

C26I-

.027.067 -.061 .653 -.097 .173 .173 -.070 .029

C1I .045 -.156 .038 -.119 .880 -.003 .106 .022 -.081C2I .021 -.011 .020 -.129 .860 .121 .082 .026 068C4I .133 .008 .141 .208 -.056 .816 -.049 -.070 -.009C5I .115 -.027 -.040 .130 .166 .714 .124 .051 -.179C3I .006 .102 -.198 127 .037 .704 .004 .119 .228C29I .064 .050 -.092 .094 .078 -.021 .831 -.035 .039

C28I-

.085.042 -.009 .294 .137 .069 .653 .076 .058

C30I .048 -.100 -.034 .295 -.045 .063 .474 .224 -.344C32I 085 -.033 .141 .053 .040 -.121 .069 .774 .088C33I .044 .118 -.052 .226 .022 .279 .048 .729 -.038

C31I-

.161-.027 .100 191 .144 -.097 -.247 -.247 -.706

C15I .001 .094 .399 .155 .174 -.124 -.296 -.208 .603

Extraction Method: Principal Component Analysis.Rotation Method: Varimax with Kaiser Normalization.a. Rotation converged in 18 iterations.

From above rotated component matrix, following factors has been derived.

Researcher has proposed the labels to the factors, which are mention at the title.

Data Analysis


Table 4.2.9.15Factor Civic Infra of tourist samples

Factor I- Factor Civic Infra

Component Tourist Services and AmenitiesFactor

LoadingC7I Garbage Disposal 0.842C6I Sewage and Drainage System 0.799C9I Drinking Water Supply 0.795C11I Traffic Management 0.780C8I Condition of City Roads 0.746C12I Condition of Traffic or Transport Signage 0.660C10I Condition of Street Lighting 0.656

Civic infra is the factor extracted from the 7 variables.

Table 4.2.9.16Factor Tourist Infra of tourist samples

Tourist infra is the factor extracted from five variables.

Table 4.2.9.17Factor Accommodation and Taxes of tourist samples

Factor Accommodation and Taxes extracted from five variables.

Factor II- Factor Tourist Infra


LoadingC19I Hygiene at Wayside Restaurants and Dhabas 0.806C20I Availability of Petrol Pump 0.774

C21IBehaviour of Service Personnel at WaysideRestaurants and Dhabas

0.749

C13I Availability of Commercial Transportations 0.518

C14IBehaviour of the Drivers of CommercialTransportations

0.518

Factor III- Factor Accommodation and Taxes


LoadingC23I Levels of Road Taxes on Vehicles(Tax Rates) 0.883C22I Administration of the Road Taxes 0.875C18I Availability of Hotels 0.634C17I Behaviour of Service Staff at the Hotel .0611C16I Tariff Structure of the Hotel Rooms 0.559

Data Analysis


Table 4.2.9.18Factor Maintenance and Management of Tourist Attraction of tourist samples

Factor Maintenance and Management of Tourist Attraction is extracted from 4variables.

Table 4.2.9.19Factor Transportation Facility of tourist samples

Factor Transportation Facility is extracted from 2 variables.

Table 4.2.9.20

Factor Road Infra of tourist samples

Factor road infra is extracted from three variables.

Factor IV- Factor Maintenance and Management of Tourist Attraction

Component Tourist Services and AmenitiesLoadingFactor

C25I Public Utilities at the Tourist Attraction 0.767

C24IGeneral Cleanliness Tourist Attraction andArea Around it

0.774

C27ICondition of Signage Within the TouristAttraction

0.725

C26I Parking Facility at the Tourist Attraction 0.653

Factor V- Factor Transportation Facility


C1I Air Connectivity Status 0.880C2I Rail Connectivity Status 0.860

Factor VI- Factor Road InfraComponent Tourist Services and Amenities Loading Factor

C4I Quality of the Roads 0.816

C5IQuality of Way Side Amenities Availableon This Road

0.714

C3I Public Conveniences Along Roads/Streets 0.704

Data Analysis


Table 4.2.9.21Factor Conservation and Guidance of tourist samples

Factor Conservation and Guidance is extracted from 3 variables.

Table 4.2.9.22Factor Essential Services of tourist samples

Factor Essential Services is extracted from 2 variables.

Table 4.2.9.23Factor Peripheral Services of tourist samples

Factor Peripheral Services is extracted from two variables.

Researcher has referred the report of Government of India, Tourism Ministry

marketing research department to develop structure as per the need of study the

structure is mentioned in detailed in research methodology chapter. In the said scale,

the structure used 33 variables to measure the tourist perception on importance of

tourist services and amenities at destination. Researcher has analyzed the data

collected with the help of said scale using factor analysis as above and extracted nine

Factor VII-Conservation and GuidanceComponent Tourist Services and Amenities Loading Factor

C29IAvailability of Trained TouristGuides

0.831

C28IBehaviour of the Guides at theTourist Attraction

0.653

C30I Conservation of Heritage Sites 0.474

Factor VIII-Essential Services


C32I Power Supply Situation 0.774C33I Telephone/Mobile Services 0.729

Factor IX-Peripheral ServicesComponent

Tourist Services and AmenitiesLoadingFactor

C31IPromptness at the Ticketing Window of theMonument/Tourist Attraction

0.706

C15I Availability of Authorized Tour Operators 0.603

Data Analysis


factors with the labels ‘civic infra’, ‘tourist infra’, ‘accommodation and taxes’,’

maintenance and management of tourist attraction’, ‘transportation facility’, ‘road

infra’, ‘conservation and guidance’, ‘essential service’ and ‘peripheral service’.

Comparing both scale it has found that in earlier structure contains 33 variables under

9 heads viz. Air facility, Road facility, Road Connectivity, Civic Administration,

Traffic and Transport Management, Tourist Facilities, Taxes/Permits, Maintenance,

Management of tourist Attraction and Other Services. After factor analysis nine

factors are extracted some of the variables has shifted their place from one group to

another group e.g. In the first loaded factor there are 7 variables, one variable of civic

administration missed and 2 variables of traffic and transport management added into

factor I. In the IInd loaded factor 5 variables are grouped out of these 3variables are

from tourist facilities and 2 from traffic and transport management. In the 3rd loaded

factor 5 variables are grouped, out of these 2 are from taxes/permits category and 3

from tourist facilities. In IVth loaded factor 4 variables are grouped all are from

maintenance and management of tourist attraction titled. In V loaded factor 2

variables are grouped and they are from separate identity of air facility and rail

facility. In VI loaded factor3 variable are grouped out of these 2 from road

connectivity and one from public convenience along roads/streets titled. In VII loaded

factor 3 variables are grouped all from maintenance and management of tourist

attraction titled. In VIII loaded factor 2 variables are grouped they are from other

service titled. In IX loaded factor 2 variables are grouped out of these one belong to

tourist facility and one from maintenance and management of tourist attraction titled.

Thus some of the variables remained in the groups and some of have shifted their

place. Researcher has renamed as per their nature of services to suffice the purpose of

study.

Data Analysis


Section X

4.2.10 Exploration of Destination:

Tourist visits only known famous places in Satara. There are number of destinations

worth seeing in Satara. Researcher observed majority of stakeholders like hoteliers,

tour operators, and government officials are not aware of many worth seeing

destinations. There is scope to explore few of them to develop and promote Satara as

a versatile tourist destination.

4.2.10.1 Vajrai Destination:

1. Name of Destination- Vajrai Waterfall, a place very close to Kas Lake yet

remained unnoticed by tourists. A beautiful destination, which is worth seen in

rainy season.

2. Reach- 31 Km away from Satara and Just 6 Km from Kas Lake.

3. Attractions to See

a. Waterfallb. Uramodi dams Backflowc. Misty and foggy environmentd. Mountain Ranges with valliese. Beautiful Naturef. Dense Forestg. Ideal for Trekkingh. Ideal Village Tourismi. Existence of Wild Animals like Bison, Bear and Leopard.j. Good location for Summer Campk. Mahakali and Vajrai Goddess Templel. Sunrise Pointm. Sunset pointn. Calm and Quiet location and free from pollution, Healthy Natural

Environment.o. A mine of Ayurvedic medicinal herbal plants.

4. Places of Tourist interest in vicinity

a. Kas Lake(from Vajrai 8 Km.)b. Kas Flora( from Vajrai 10 Km.)c. Bamnoli ( from Vajrai 18 Km)d. Tapola (from Vajrai 60 Km. but from Bamnoli ½ hour boating to Tapola)

Data Analysis


5. Rout Map-

6. Existing Tourism Services and Facilities

a. Road Connectivity- Road Connectivity is good; quality of road is also

good.

b. Civic Amenities- Drinking water supply

c. Traffic and Transport Facilities- thinly populated, very few i.e. 40-50

families are living. No traffic flow, less transport options.

d. Tourist Facilities- Opportunity to test local food.

e. Maintenance and Management of tourist Attractions- thinly populated and

more dense forest so less chance for garbage disposal or automatically

maintained clean, parking facility is available, trained guide can be made

available, behavior is excellent, local community has conserved the nature

since the local people are going to act as a guide there.

f. Other Services- Power supply, telephone and mobile services are good

7. Required Facilities to explore as a tourist destination

a. Quality of wayside amenities, Public convenience along road.

b. Civic Amenities- Sawage and drainage system, garbage disposal, condition

of street light.

c. Traffic and transport Facilities- traffic signage, commercial transportation

d. Tourist Facilities- hotels, petrol pump and restaurant and Dhaba

e. Maintenance and Management of tourist Attractions- public toilets.

Bamnoli Kas Plateau12km Kas Lake

1km 2km . 22km

Kas

6km.

Vajari

Sataraa

Data Analysis


8. How to Promote

Vajrai Waterfall, a good opportunity for tourist to visit this location who comes for

Kas Lake or Kas Flora. Accommodation facility needs to develop in the form of

Dharmshala and youth Hostels. This kind of destination can be boon to tourists who

likes to be away from busy metro life, nature lover, lonely and isolated environment,

people who are fond of adventure. Sustainable, village and Nature Tourism can be

possible. Vajrai is a good destination in rainy and winter season.

4.2.10.2 Parli Destination:

1. Name of Destination- Parli Temple

2. Reach- 10 Km away from Satara and in basement of Sajjangarh and

Uramodi Dam

3. Attractions to Seea. Mountain Rangesb. Beautiful Naturec. Ideal for Village Tourismd. The temple is a small model of Khajurao sculpturee. The temple is oldest Hemandpati Templef. A unique Shivling with five faces carved on it.g. A panoramic view of Urmodi Damh. Sunrise Pointi. Sunset pointj. Calm and Quiet location and free from pollution, Healthy Natural

Environment.

4. Rout Map

Parli Bogda(Tunnel)

1km 6km 3km.

Sajjangarh

2km

Satara

Data Analysis


5. Nearby Other Places to Visit

a. Sajjangarhb. Kelwali and Sandwali Waterfallc. Urmodi Damd. Thoseghare. Chalkewadi Wind Project

6. Existing Tourism Services and Facilities

a. Road Connectivity- Road Connectivity is good; quality of road is also good.

Quality of wayside amenities are good, Public convenience along road is also

excellent.

b. Civic Amenities- Drinking water supply is good. Sewage and drainage

system garbage disposal; condition of street light is available.

c. Traffic and Transport Facilities- thinly populated, tourist are unaware about

the destination so no tourist traffic flow as of date good commercial

transportation facilities existed.

d. Tourist Facilities- Restaurants are available, presentably catering local needs.

e. Maintenance and Management of tourist Attractions- Maintained Cleanliness,

parking facility is available.

f. Other Services- Power supply, telephone and mobile services are existed.

7. Required Facilities to explore as a tourist destination

a. Civic Amenities- Traffic and transport Facilities- traffic signage,

b. Tourist Facilities- Accommodation, hotels, petrol pump.

c. Maintenance and Management of tourist Attractions- public toilets and guide

facility.

8. How to Promote

A Parli a good destination to see the stone carving, Oldest Hemandpati temple,neglected by local community and government, a good heritage site presenting asmall model of Khajurao sculpture. There is a good view of Sajjangarh. Thedestination Parli is on the way of Sajjangarh and Thoseghar hence tourist can bediverted and make arrangement of budgeted accommodation i.e. Bed and Breakfast, agood site for Water Park, accessibility towards two waterfall destination i.e. Kelwaliand Sandwali which are also known for trekking.

Data Analysis


Section XI

4.2.11 Hypotheses Testing:

Introduction: This part discuss on the testing of hypotheses that was set in the research

proposal. There are 3 hypotheses tested with testing tools like independent sample ‘t’

test, one sample ‘t’ test, spearman’s rank correlation etc. This part was calculated with

the help of SPSS and results presented with their respective calculations for detailed

references.

This last section of analysis deals with hypotheses testing. Study put forth three

hypotheses to test as follows.

1. Lack of promotion of tourism destinations hinders development of tourism

sector in Satara district.

2. Availability of infrastructural facilities and tourism development are

correlated.

3. Government proposes planning to develop the places of tourist interest but the

gap exists in planning and implementation, which deals to failure in attracting

tourists.

Hypothesis 1:Lack of promotion of tourism destinations hinders development of tourism sector inSatara District.

For this hypothesis researcher has used data of (refer tourist schedule’ section I, sub

section ‘E’ in annexure I) perceptions of tourists about promotion of tourism with

three statements. The data are presented in four sections as first section contains total

tourist response, second section deals with destination wise tourist response, third

section contains hoteliers’ response, and fourth section is of tour operators’ response.

One sample‘t’ test is used with median value 3. The scale used to assess sample

respondent is five point scale with a mid value is three. The hypotheses is tested

across three stakeholders i.e. tourist, hoteliers and tour operators. The independent

testing of hypothesis has also done on tourist’s opinions destination-wise.

1. Total Tourist Opinion on Promotion2. Destination wise Tourist Opinion3. Hoteliers Opinion4. Tour Operators Opinion

Data Analysis


1. Total Tourist Opinion:

Following table presents descriptive statistics related with these three statements.

Sample Tourist Opinion on Promotion.

Table 4.2.11.1Tourists Descriptive Statistics


Sr.Perception about promotionof Tourism

N MeanStd.

DeviationStd. Error

Mean1. Advertisement play

important role in tourism326 4.08 .72 .04

2. Felt need of promotionalactivities

326 4.20 .74 .04

3. Lack of advertisementrestrict tourismdevelopment

326 4.02 .89 .05

Source: Compiled by Researcher

Sample opines that advertisement plays important role in tourism visa- visa the better

need of promotional activities. Samples highly argue with that lack of advertisement

restrict tourism development since the mean score is above four. All these statements

mean score is above 4 with little S.D states less variations in opinion.

Following table shows the one sample ‘t’ test of three statements.

Table 4.2.11.2Hypothesis Test of Sample Tourist Opinion on Promotion

One-Sample Test

SrPerception about promotion

of Tourism

Test Value = 3

t df

Sig.(2-tailed)

MeanDifference

95%Confidence

Interval of theDifference

Lower Upper1. Advertisement play

important role in tourism26.79 325 .000 1.07 .99 1.15


29.23 325 .000 1.19 1.11 1.27


20.64 325 .000 1.01 .92 1.11


Data Analysis


The‘t’ score for statement first, second and third are 26.79, 29.23 and

20.64respectively, with a ‘P’ value 0.00, the test is significant. It is inferred that

promotion is important and promotion is absent in Satara. Hence, the null hypothesis

is rejected. The alternative hypothesis i.e. lack of promotion of tourism destination

hinders the development of tourism sector in Satara district, is accepted.

2. Destination wise Tourist Response:

Researcher has tested the hypothesis with the samples visited destination-wise. In an

effort to find out opinions of different Strata of samples visited to variety of tourist

destinations. It is believed that the respective destinations are visited by different

strata of tourists having distinct characteristics. The testing of hypothesis destinations

wise is as follows


Sample Tourist Opinion on Promotion at Aundh

Table 4.2.11.3Tourists Descriptive Statistics at Aundh

One-Sample StatisticsSr. Perception about promotion

of TourismN Mean

Std.Deviation

Std. ErrorMean

1. Advertisement playimportant role in tourism

30 4.00 .00a .00


30 3.87 .63 .11


30 4.00 .74 .14

a. t cannot be computed because the standard deviation is 0.Source: Compiled by Researcher

Sample preaches with less confidence that there is need of promotional activities as

the mean score of this statement is less than 4 but more than 3. But samples argue

more with advertisement play important role and lack of advertisement restrict

tourism development since the mean score is four as these two statements mean is

above 4 with little S.D.

Data Analysis


Following table shows the one sample‘t’ test of three statements.

Table 4.2.11.4Hypothesis Test of Sample Tourist Opinion on Promotion at Aundh

One-Sample Test

Sr.Perception aboutpromotion of Tourism

Test Value = 3

t df

Sig.(2-tailed)

MeanDifference

95% ConfidenceInterval of the

DifferenceLower Upper


7.54 29 .00 .86 .63 1.10


7.37 29 .00 1.00 .72 1.28


The ‘t’ score for statement second and third are 7.54 and 7.37 respectively, with a ‘P’value 0.00, the test is significant. It is inferred that promotion is important andpromotion lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e.lack of promotion of tourism destination hinders the development of tourism sector inSatara district, especially opinions of tourist at Aundh is accepted.

Tourist Descriptive Statistics at Panchgani


Table 4.2.11.5Sample Tourist Opinion on Promotion at Panchgani


Sr. Perception about promotion of Tourism N MeanStd.Deviation

Std.ErrorMean

1. Advertisement play important role intourism

35 3.94 .68 .12

2. Felt need of promotional activities 35 4.03 .66 .113. Lack of advertisement restrict tourism

development35 3.97 .82 .14


Sample discourse that advertisement plays important role in tourism, lack ofadvertisement restrict tourism development since the mean score is less than four butmore than three. Samples highly argue with need of promotional activities since themean score is 4.03. First and third statements mean is less than four and that to ofsecond statement is above four with little S.D.

Data Analysis



Table 4.2.11.6Hypothesis Test of Panchgani Sample Tourist Opinion on Promotion

One-Sample Test

Sr.Perception about

promotion of Tourism

Test Value = 3

t dfSig. (2-tailed)

MeanDifferenc

e



1. Advertisement playimportant role intourism

8.16 34 .00 .94 .71 1.18

2. Felt need ofpromotional activities

9.17 34 .00 1.03 .80 1.26

3. Lack ofadvertisementrestrict tourismdevelopment

6.99 34 .00 .97 .69 1.25


The ‘t’ score for statement first, second and third are 8.16, 9.17 and 6.99 respectively

with a ‘P’ value 0.00, the test is significant. It is inferred that promotion is essential

and it lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack

of promotion of tourism destination hinders the development of tourism sector in

Satara district, especially opinions of tourist at Panchgani is accepted.

Tourist Descriptive Statistics at Pratapgarh


Table 4.2.11.7Sample Tourist Opinion on Promotion at Pratapgarh


Sr.Perception about

promotion of TourismN Mean S.D.

Std. ErrorMean


30 4.17 .53 .10


30 4.13 .57 .10

3. Lack of advertisementrestrict tourism development

30 3.93 .83 .15


Sample orate that lack of advertisement restrict tourism development as the mean

score is 3.93 which is less than 4 but more than 3. However, Samples very much

Data Analysis


favour with 1st two statements that advertisement play important role in tourism and

need of promotional activities since the mean score is 4.17 and 4.13 respectively. Two

statements mean score is above 4 with little S.D and one statement is below 4 but

more than3.


Table 4.2.11.8Hypothesis Test of Pratapgarh Sample Tourist Opinion on Promotion

One-Sample Test

Sr.Perception aboutpromotion ofTourism

Test Value = 3

t dfSig.(2-

tailed)

MeanDifference



1. Advertisementplay important rolein tourism

12.04 29 .00 1.17 .97 1.36

2. Felt need ofpromotionalactivities

10.86 29 .00 1.13 .92 1.35

3. Lack ofadvertisementrestrict tourismdevelopment

6.17 29 .00 .93 .62 1.24


The ‘t’ score for statement first, second and third are 12.04, 10.86 and 6.17

respectively with a ‘P’ value 0.00, the test is significant. It is inferred that promotion

is indispensable and it absent in Satara. Hence, the null hypothesis is rejected. The

hypothesis i.e. lack of promotion of tourism destination hinders the development of

tourism sector in Satara district, especially opinions of tourists at Pratapgarh is

accepted.

Data Analysis


Tourist Descriptive Statistics at Sajjangarh


Table 4.2.11.9Sample Tourist Opinion on Promotion at Sajjangarh


Sr.Perception about promotion of

TourismN Mean

Std.Deviation

Std.ErrorMean


30 3.97 1.15 .21

2. Felt need of promotional activities 30 3.97 1.03 .183. Lack of advertisement restrict tourism

development30 3.70 1.26 .23


Sample opines that advertisement plays important role in tourism there is need of

promotional activities and lack of advertisement restrict tourism development.

Samples have belief on advertisement play important role in tourism and need of

promotional activities since the mean score is 3.97, which is very close to four. All

these statements mean score is above three with little S.D.

Data Analysis



Table 4.2.11.10Hypothesis Test of Sajjangarh Sample Tourist Opinion on Promotion

One-Sample Test


Test Value = 3

t dfSig.(2-

tailed)

MeanDifference




4.57 29 .000 .97 .53 1.40

2. Felt need ofpromotionalactivities

5.12 29 .000 .97 .58 1.35

3. Lack ofadvertisement restricttourism development

3.03 29 .005 .70 .23 1.17


The‘t’ score of above three statements are 4.57, 5.12 and 3.03 respectively with a ‘P’

value 0.00, the test is significant. It proves that promotion is crucial and that lacks in

Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of promotion

of tourism destination hinders the development of tourism sector in Satara district,

especially opinions of tourist at Sajjangarh is accepted.

Tourist Descriptive Statistics at Wai


Table 4.2.11.11Sample Tourist Opinion on Promotion at Wai


Sr.Perception about promotion

of TourismN Mean

Std.Deviation

Std. ErrorMean

1. Advertisement play importantrole in tourism

37 4.22 .85 .14


37 4.54 .65 .11

3. Lack of advertisement restricttourism development

37 3.94 1.18 .19


Data Analysis


Sample discourses that lack of advertisement restrict tourism development. However,

Samples highly believes that advertisement play important role in tourism and need of

promotional activities while the mean score is 4.54. First two statements mean score

is above 4 and last is less than 4 with little S.D.


Table 4.2.11.12Hypothesis Test of Wai Sample Tourist Opinion on Promotion

One-Sample Test

Sr.Perception about


Test Value = 3

t dfSig.(2-

tailed)

MeanDifference




8.66 36 .000 1.21 .93 1.50


14.43

36 .000 1.54 1.32 1.76


4.89 36 .000 .94 .55 1.34


The ‘t’ score for statement first, second and third are 8.66, 14.42 and 4.48 respectively

with a ‘P’ value 0.00, the test is significant. It is inferred that promotion is essential

and it lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack

of promotion of tourism destination hinders the development of tourism sector in

Satara district, especially opinions of tourist at Wai is accepted.

Data Analysis


Tourist Descritive Statastics at Mahabaleshwar


Table 4.2.11.13Sample Tourist Opinion on Promotion at Mahabaleshwar


Sr. Perception about promotion of Tourism N Mean S.D.Std. Error

Mean1. Advertisement play important role in

tourism30 3.80 .84 .15




Sample orate that advertisement plays important role in tourism, tourist felt there is

better need of promotional activities and lack of advertisement restrict tourism

development . Samples argue with need of promotional activities since the mean score

is 3.90. All these statements mean is more than 3 with little S.D.


Table 4.2.11.14Hypothesis Test of Mahabaleshwar Sample Tourist Opinion on Promotion

One-Sample Test


Test Value = 3

t dfSig.(2-tailed)

MeanDifference



5.17 29 .000 .80 .48 1.12


5.83 29 .000 .90 .58 1.22


4.49 29 .000 .76 .42 1.12


The ‘t’ score above three statements are 5.17, 5.83 and 4.49 respectively with a ‘P’

value 0.00, the test is significant. It is proves that promotion is important and it lacks

in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of

Data Analysis


promotion of tourism destination hinders the development of tourism sector in Satara

district, especially opinions of tourist at Mahabaleshwar is accepted.

Tourist Descriptive Statastics at Koyna


Table 4.2.11.15Sample Tourist Opinion on Promotion at Koyna



TourismN Mean S.D.

Std. ErrorMean

1. Advertisement play important rolein tourism

37 4.16 .55 .091

2. Felt need of promotional activities 37 4.27 .56 .0923. Lack of advertisement restrict

tourism development37 4.16 .65 .106


Sample preaches on all above statements that advertisement play important role in

tourism and lack of advertisement restrict tourism development and highly argues

with need of promotional activities since the mean score is more than four. All these

statements mean is above 4 with little S.D.


Table 4.2.11.16Hypothesis Test of Koyna Sample Tourist Opinion on Promotion

One-Sample Test

SrPerception aboutpromotion of Tourism

Test Value = 3

t df

Sig.(2-

tailed)

MeanDifference




12.77 36 .000 1.16 .98 1.35


13.79 36 .000 1.27 1.08 1.46


10.94 36 .000 1.16 .95 1.38


Data Analysis



respectively with a ‘P’ value 0.00, the test is significant. It clears that promotion is

essential and promotion lacks in Satara. Hence, the null hypothesis is rejected. The


tourism sector in Satara district, especially opinions of tourist at Koyna is accepted.

Tourist Descritive Statastics at Thoseghar


Table 4.2.11.17Sample Tourist Opinion on Promotion at Thoseghar


Sr.Perception about promotion ofTourism

N Mean S.D.Std. ErrorMean


33 4.39 .66 .11




Sample opine that advertisement plays important role in tourism, tourist felt there is

better need of promotional activities and lack of advertisement restrict tourism

development. Samples highly argue with that lack of advertisement restrict tourism

development since the mean score is four. All these statements mean is above 4 with

little S.D.

Data Analysis



Table 4.2.11.18Hypothesis Test of Thoseghar Sample Tourist Opinion on Promotion

One-Sample Test

Sr.Perception about


Test Value = 3

t dfSig.(2-

tailed)

MeanDifference




12.15 32 .000 1.39 1.16 1.63


14.07 32 .000 1.51 1.29 1.73


11.86 32 .000 1.33 1.10 1.56



respectively with a ‘P’ value 0.00, the test is significant. It is inferred that promotion

is essential and it lacks in Satara. Hence, the null hypothesis is rejected. The


tourism sector in Satara district, especially opinions of tourist at Thoseghar is

accepted.

Data Analysis


Tourist Descriptive Statastics at Kas


Table 4.2.11.19Sample Tourist Opinion on Promotion at Kas


SrPerception about promotion ofTourism


1. Advertisement play important rolein tourism

30 4.13 .73 .13

2. Felt need of promotional activities 30 4.13 .63 .113. Lack of advertisement restrict

tourism development30 3.87 .63 .11


Sample orate that lack of advertisement restrict tourism development as the mean

score is above 3. Samples highly argue with that advertisement plays important role in

tourism and need of promotional activities, as the mean score is 4.13. First two

statements mean is 4 with little S.D.


Table 4.2.11.20Hypothesis Test of Kas Sample Tourist Opinion on Promotion

One-Sample Test


Test Value = 3

t dfSig.(2-

tailed)

Mean

Difference


Difference

Lower Upper


8.50 29 .000 1.13 .86 1.40


9.87 29 .000 1.13 .90 1.37


7.54 29 .000 .87 .63 1.10


The‘t’ score of above three statements are 8.50, 9.87 and 7.54 respectively with a ‘P’

value 0.00, the test is significant. It is evident that promotion is important and it lacks

Data Analysis


in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of


district, especially opinions of tourist at Kas is accepted.

Tourist Descriptive Statastics at AjinkyataraFollowing table presents descriptive statistics related with these three statements.Table 4.2.11.21Sample Tourist Opinion on Promotion at Ajinkyatara


Sr.Perception about promotionof Tourism



34 3.94 .60 .10


34 4.47 .79 .13


34 4.41 .82 .14


Samples discourse that advertisement plays important role in tourism, better need ofpromotional activities and lack of advertisement restricts tourism development.Samples highly argue with need of promotional activities and lack of advertisementrestricts tourism development since the mean score is 4.47 and 4.41 respectively.Second and third statements mean score is above 4 with little S.D.

Following table shows the one sample‘t’ test of three statements.Table 4.2.11.22Hypothesis Test of Ajinkyatara Sample Tourist Opinion on Promotion

One-Sample Test


Tourism

Test Value = 3

t dfSig. (2-tailed)

MeanDifference




9.15 33 .00 .94 .73 1.15


10.89 33 .00 1.47 1.19 1.74


10.03 33 .00 1.41 1.12 1.70


Data Analysis


The ‘t’ score of above three statements are 9.15, 10.89 and 10.03 respectively with a

‘P’ value 0.00, the test is significant. It is proves that promotion is important and it is

lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of


district, especially opinions of tourist at Ajinkyatara is accepted.

The hypothesis is tested using sample opinions of Hoteliers

3 Hoteliers Opinion:


Table 4.2.11.23Sample Hoteliers’ Opinion on Promotion


Sr. Perception about promotion of Tourism N Mean S.D.Std.ErrorMean

1. Advertisement play important role in tourism 40 4.02 .70 .112. Felt need of promotional activities 40 4.27 .85 .133. Lack of advertisement restrict tourism



Sample hoteliers orate that advertisement plays important role in tourism and there is

key need of promotional activities. But samples quite reluctant with statement that

lack of advertisement restrict tourism development as mean score is less than 4. But

highly argue with advertisement play important role in tourism and need of

promotional activities as the mean score is 4.27. First two statements mean score is

above 4 with little S.D.

Data Analysis



Table 4.2.11.24Hypothesis Test of Sample Hoteliers’ Opinion on Promotion

One-Sample Test

Sr.

Perception aboutpromotion of Tourism

Test Value = 3

T df

Sig.(2-tailed)

MeanDifference



9.29 39 .00 1.02 .80 1.25


9.52 39 .00 1.27 1.00 1.54


8.87 39 .00 .95 .73 1.17

The‘t’ score for statement first, second and third are 9.29, 9.52 and 8.87 respectively

with a ‘P’ value 0.00, the test is significant. It is evident that promotion is vital which

lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of


district as opined by hoteliers.

The hypothesis is tested using sample opinions of Tour operators

4. Tour Operators’ Opinion:


Table 4.2.11.25Sample Tour Operators’ Opinion on Promotion

Sr.One-Sample StatisticsPerception about promotion ofTourism

N MeanStd.Deviation

Std. ErrorMean


10 4.40 .51 .16


10 4.80 .42 .13


10 4.30 .94 .30


Data Analysis


Sample tour operators opine that advertisement plays important role in tourism, tour

operators felt there is better need of promotional activities and lack of advertisement

restrict tourism development. Samples highly argue with need of promotion activities

since the mean score is 4.80. All these statements mean score is above 4 with little

S.D.


Table 4.2.11.26Hypothesis Test of Sample Tour Operators’ Opinion on Promotion

Sr.

One-Sample Test

Perception aboutpromotion of Tourism

Test Value = 3

Tdf

Sig.(2-tailed)

MeanDifference



8.57 9 .000 1.40 1.03 1.77


13.50 9 .000 1.80 1.50 2.10


4.33 9 .002 1.30 .62 1.98


The‘t’ score for statement first, second and third are 8.57, 13.50 and 4.33 respectively.

It with a ‘P’ value 0.00, and 0.002 the test is significant. It is evident that promotion is

fundamental which lacks in Satara. Hence, the null hypothesis is rejected. The


tourism sector in Satara district, as opined by tour operators.

To conclude on hypothesis number 1, the null hypothesis is rejected and the

alternative hypothesis i.e. lack of promotion of tourist in Satara district is accepted.

Data Analysis


Hypothesis 2:

Second hypothesis set to test for the study is Availability of infrastructural facilitiesand tourism development is correlated.

For this hypothesis researcher has used Karl Pearson Correlation between averages of

satisfaction index towards infrastructural facilities with tourist arrival of recent year

2010-2011.

Following table depicts the destination wise tourists’ average satisfaction level and

previous year 2010-11 tourist arrival figures.

Table 4.2.11.27Average Satisfaction and Tourist Arrival at Satara

Sr. DestinationsAverageSatisfaction

Previous YearArrival#

1. Mahabaleshwar 3.31 16237652. Panchgani 3.38 13786553. Wai 2.83 *4. Pratapgarh 3.35 329555. Aundh 3.56 824746. Koyna 3.12 1159997. Sajjangarh 3.22 3000008. Thoseghar 2.82 270009. Kas 3.12 35000010. Ajinkya Tara 3.20 *Source: Compiled by Researcher# previous year refers to year 2011-12* Figures are not available

Table 4.2.11.27 presents the tourists average satisfaction level with 33 tourism

services and amenities and tourist arrival figure in respective destinations in Satara.

Tourist average satisfaction level is average that signifies the tourists are not strongly

satisfied with the available infrastructure. The tourist arrival figures are not also

similar as it starts from 27000 to 1623765 in a previous year. The highest tourist

arrival at Mahabaleshwar and followed by Panchgani but satisfaction level is average

as the mean score is less than 4.

Data Analysis


Following table presents the descriptive statistics of availability of infrastructuralfacilities of tourism development.

Table 4.2.11.28Descriptive Statistics of Tourism Development

Sr.Descriptive Statistics

Pariculars Mean S.D. N1. Average Satisfaction 3.23 .22 82. Previous year arrival 4.90 639199.68 8


The total average samples tourist satisfaction mean score is lesser than 4 but tourist

previous year arrival mean score is more than 4 and more deviation finds in tourist

arrival in different destination. Therefore, it can infer that arrival and satisfaction does

not have any relation.

The following table depicts the Pearson correlation of aveage satisfaction mean with

previous year arrival mean.

Table 4.2.11.29Hypothesis Testing of Average Satisfaction and Previous Year Arrival with PearsonCorrelation

Sr.Correlations

AverageSatisfaction

Previous yeararrival

1. AverageSatisfaction

PearsonCorrelation

1 .28

Sig. (2-tailed) .49N 8 8

2. Previous yeararrival

PearsonCorrelation

.28 1

Sig. (2-tailed) .49N 8 8


The above table shows Pearson correlation 0.28, with ‘P’ value 0.49, which is not

significant at 0.05 levels (2-tailed). Hence, it is inferred that there is no correlation

between average tourist satisfaction levels with tourist arrival figure of previous year.

Therefore, this test proves that availability of infrastructure facilities and tourism

Data Analysis


development are not correlated. Thus, the null hypothesis is accepted that

availability of infrastructure and tourism development is not correlated.

For this hypothesis researcher has also tested ‘Karl Pearson Correlation’ between

spending on infrastructural development and tourist arrival at respective tourist

destinations in Satara District since1999-2000 to 2010-11.

Following table presents the total amount of spending on infrastructure and tourist

arrival for 1999-2000 to 2010-2011.

Table 4.2.11.30Total Spending On Infrastructural Development with Tourist Arrival

Sr.Name ofDestination

Total spent on infrafor last 10 yearsAmount(in lakhs)

Last 10 yearstourist arrival

1. Mahabaleshwar 278.35 140000522. Panchgani * 103620843. Wai 13.86 *4. Pratapgarh 9.73 4660905. Aundh 74.72 2522406. Koyna 7.44 14039717. Sajjangarh 26.85 3000008. Thoseghar 39.8 818009. Kas 237.45 53828910. Ajinkya Tara * *

Source: Compiled by Researcher*figures not available

Table 4.2.11.30 reveals amount spent on infrastructure is neither uniform at various

destinations of Satara and nor tourist arrival. The highest tourist arrival are at

Mahabaleshwar (140000052) and Panchgani (10362084) compared to other

destinations of Satara. Expenditure on tourism development is equally higher at

Mahabaleshwar compared to other destinations. However, for Panchgani the

expenditure did not occurred through ‘C’ category tourism expenses at district level as

in the other destinations. Since the majority of properties are private and local

government, bear the expenses at local level, in the case of Panchgani.

Data Analysis


Following table presents the details of total spending for infrastructure of and their

tourist arrival since 1999-2000 to 2010-11.

Table 4.2.11.31Descriptive Statistics since 1999-2000 to 2010-11

Sr.Descriptive Statistics

Particulars Mean S.D. N1. Total Spending for Infrastructure of

1999-2000 to 2010-1196.33 113.24 7

2. Tourist Arrival 2.43 5.11 7Source: Compiled by Researcher

Above table, infer that two variables total spending and tourist arrival mean is not

matching the difference between means is very large with large standard deviation.

Following table shows pearon correlations between total spending for infrastructure

of with total tourist arrival from 1999-2000 to 2010-11.

Table 4.2.11.32Hypothesis Testing with Pearson Correlation


The above test figures shows that Pearson correlation is 0.70, with ‘P’ value 0.81,

which is not significant at 0.05 levels (2-tailed). Thus, there is no correlation between

total spending at destination with previous tourist arrival figure. Hence, it is inferred

that null hypothesis is accepted as availability of infrastructure facilities and tourism

developments are not correlated.

Sr.

Correlations

Particulars

TotalSpending

forInfrastruct

ure ofLast years

TouristArrival

1. Total Spending forInfrastructure ofLast years

Pearson Correlation 1 .70Sig. (2-tailed) .081N 7 7

2.Tourist Arrival

Pearson Correlation .70 1Sig. (2-tailed) .08N 7 7

Data Analysis


To probe into the depth the hypothesis is tested destination-wise by using Karl

Pearson Correlation between spending on infrastructural development and tourist

arrival as follows.

The data are amount spend on infrastructural development year wise to the respective

destination and tourist arrival at that year was available with few destinations.

Researcher tested the data using Pearson Correlation to check its relation. The data in

desired form was available at destination, Thoseghar, Koyna and only one-year data

was available of fort Pratapgarh.

Following table shows the amount spent on infrastructural development at Thoseghar

and the tourist arrival figure of the destination.

Table 4.2.11.33Amount Spent and Tourist Arrival at Thoseghar

Sr. YearAmount Spent(inlakhs)

Tourist Arrival (innos.)

1. 1999-2000 5.08 6002. 2008-2009 5 85003. 2010-2011 12 18000


Table 4.2.11.33 reveals that higher amount is spent during 2010-11 compared to

previous year 1999-2000 Rs. 5.08 and Rs. 5 lakhs during 2008-9. The tourist arrival

figure is also grown by 9500 during 2010-11.

Data Analysis


Following table shows the descriptive statistics of average amount spent and tourist

arrival at Thoseghar.

Table 4.2.11.34Descriptive Statistics of Thoseghar


From table it is infer that there is mean difference between amount spent and tourist

arrival at Thoseghar with larger standard deviation.

To test the hypothesis researcher has used Pearson correlation method for amounts

spent on infrastructural development and tourist arrival at Thoseghar.

Following table presents the Pearson correlation test to check the significant relation

between infrastructural development and tourism development.

Table 4.2.11.35Hypothesis Testing of Infrastructural Development and Tourism at Thoseghar

Sr. CorrelationsParticulars Amount Spent Tourist Arrival

1. AmountSpent

Pearson Correlation 1 .89Sig. (2-tailed) .31N 3 3

2. TouristArrival

Pearson Correlation .89 1Sig. (2-tailed) .31N 3 3


The Pearson correlation is 0.89 at 0.05 levels (2-tailed), with ‘P’ value 0.31 the test is

not significant. Therefore, there is no correlation between average satisfaction levels

of tourist with previous tourist arrival figure at Thoseghar. Thus, null hypothesis is

accepted i.e. infrastructural and tourism is not correlated.

Descriptive StatisticsSr. Funds Mean Std. Deviation N1. Amount Spent 7.36 4.019 32. Tourist Arrival 9033.33 8712.252 3

Data Analysis


Following table shows, the amount spent on infrastructural development at Koyna andthe tourist arrival figure of the destination.

Table 4.2.11.36Amount Spent and Tourist Arrival at Koyna

Sr. YearAmount spent(inLakhs)

Tourist( in Nos)

1. 2007-2008 7.41 138914

2. 2008-2009 3 126818


Table 4.2.11.36 reveals that higher amount (Rs.7.41 lakhs) was spend at Koyna in

2007-8 as compared to Rs. 3 lakhs during 2008-9 and tourist arrival figure was more

by 12096 compared to 2008-9.

Following table shows the descriptive statistics of average amount spent and tourist

arrival at Koyna.

Table 4.2.11.37Descriptive Statistics of Koyna

Sr. Descriptive StatisticsParticulars Mean Std. Deviation N

1. Amount Spent 5.20 3.12 22. Tourist Arrival 1.33 8553.16 2


Table 4.2.11.37 depicts that amount spent of infrastructural development at Koyna is

higher i.e. 5.20 than tourist arrival mean 1.33 with more S.D.

Data Analysis


Following table presents the Pearson correlation test to check the significant relation

between infrastructural development and tourism development.

Table 4.2.11.38Hypothesis Testing of Infrastructural Development and Tourism at Koyna

Sr.Correlations

ParicularsAmountSpent

TouristArrival

1. Amount Spent PearsonCorrelation

1 1.000**

Sig. (2-tailed) .N 2 2

2. Tourist Arrival PearsonCorrelation

1.000** 1

Sig. (2-tailed) .N 2 2

**. Correlation is significant at the 0.01 level (2-tailed).Source: Compiled by Researcher

The Pearson correlation is 1.00, with ‘P’ value 0.00, which is significant at 0.01 levels

(2-tailed). Thus, it proves that there is positive correlation between availability of

infrastructure facilities and tourism development. So the null hypothesis is rejected.

Hypothesis, Infrastructural development, and tourism are correlated.

Following table shows the amount spent on infrastructural development at Pratapgarh

and the tourist arrival figure of the destination.

Table 4.2.11.39Amount Spent and Tourist Arrival at Pratapgarh

Sr. YearAmount Spent(inlakhs)

TouristArrival(in Nos)

1. 2008-2009 9.73 34709


Only single one-year tourism expenditure and tourist arrival present at Pratapgarh. So

it cannot be compared for calculation.

Data Analysis


Hypothesis 3:

The third hypothesis put to test was Government proposes planning to develop theplaces of tourist interest but the gap exists in planning and implementation, whichdeals to failure in attracting tourists.For this hypothesis researcher has tested the gap between amount sanctioned for thedevelopment of a tourist destination and the amount actually spent.The funds for tourism development have allocated to basic infrastructuraldevelopment and tourist infrastructural development in Satara district. The fundsbudgeted and actual spending are compared by using independent sample ‘t’ test.Following table reveals the funds spending on basic and tourist infrastructure inSatara during 1999-2010.

Table 4.2.11.40Amount Budgeted and Amount Spent on basic infrastructure and tourist infrastructuresince 1999-2010

(Figures in Rs. Lakhs)

Sr.

Basic and Tourist Infrastructure Amountbudgeted

AmountspentBasic Infrastructure

1. Construction of Road (wp)* 200.65 151.682. Drinking Water 5 53. Footpath or Pathway, Stair Case, Railing, Fixing

Paving Block, Entrance, Fencing (Wp)*122.8 103.91

4. Repair And Maintenance (wp)* 84.66 50.155. Surrounding Development, Landscaping or

Survey5.74 5.5

6. Toilets And Bathrooms (wp)* 16.99 16.4Total 435.84 332.64

Tourist Infrastructure10. Arrangement of SPV Solar System 3.25 2.9511. Canteen , Tiffin Shade 6.42 6.4212. Construction of Hall or Multipurpose Hall,

Entertainment Hall/Waiting Room (wp)*19.79 19.77

13. Construction of Smarak 13.7 12.7314. Garden For Children(wp)* 14.59 015. Office 8.21 8.2116. Parking Place 9.91 9.9117. Provision of Other Facility 5 2.0718. Rest House (wp)* 50 41.18

Total 130.87 103.24Grand Total 566.71 435.88

Source: (District Planning Department, Satara, translated and compiled byresearcher)*(wp) - work is progress

Data Analysis


Following table, preach the mean and standard deviation of budgeted amount and

amount spent for basic and tourist infrastructure in Satara.

Table 4.2.11.41Group Statistics of Amount Budgeted and Amount Spent

Group Statistics

Sr. Particulars Gap N Mean S.D.Std. Error

Mean1. Amount budgeted 1 15 37.78 56.68 14.632. Amount Spent 2 15 29.06 43.46 11.22


Table 4.2.11.41 discourse the mean of budgeted amount and amount spent on basicand tourist infrastructure. Amount budgeted is higher than amount spent since themean score is 37.78 and 29.06 respectively with more S.D.

Following table discourse about the independent sample‘t’ test of amount budgetedand actual amount spent on infrastructure in Satara.

Table 4.2.11.42Hypothesis Test with Independent Sample ‘t’ Test


The test is insignificant at 95% confidence interval with 28 df the t statistics is 0.47,with ‘P’ value 0.42 that is not significant at 0.05 level. The gap between amountsanctioned and the amount spent is negligible. Hence the null hypothesis is acceptedand the alternative hypothesis i.e. Government proposes planning to developmentthe places of tourist interest but the gap exists in planning and implementation thatdeals to failure in attracting tourists has rejected.

Independent Samples TestLevene's Test forEquality of Variances

t-test for Equality of Means

FSig

.t df

sig.(2-

tailed)

MeanDifference

Std.ErrorDifference



AmountbudgetedandactualSpent

Equalvariancesassumed

.68 .42 .48 28 .640 8.72 18.44 -29.05 46.50

Equalvariancesnotassumed

.4726.23

.640 8.72 18.44 -29.17 46.61

Data Analysis


Section: XII

4.2.12 Cluster Analysis:

Data of Entire Tourist Samples.

The data of entire samples run through cluster analysis using hierarchical method tofind out number of clusters.

Table 4.2.12.1Case Processing Summary entire data for cluster.

Cases

Valid Missing Total

N Percent N Percent N Percent

326 100.0 0 .0 326 100.0

a. Squared Euclidean Distance used

b. Average Linkage (Between Groups)

Table 4.2.12.2Agglomeration Schedule

Stage

Cluster Combined

Coefficients

Stage Cluster FirstAppears

Next StageCluster 1 Cluster 2 Cluster 1 Cluster 2

313 1 31 3.277 299 294 319

314 3 14 3.312 308 0 322

315 17 30 3.494 306 304 317

316 4 10 3.909 302 312 320

317 5 17 4.338 310 315 324

318 2 8 4.979 305 311 321

319 1 135 5.159 313 276 321

320 4 26 8.115 316 309 323

321 1 2 8.350 319 318 324

322 3 22 9.098 314 272 323

323 3 4 13.940 322 320 325

324 1 5 14.222 321 317 325

325 1 3 65.685 324 323 0

From above agglomeration table, it is evident that three or six clusters can be

extracted from the data. Since the gap between cluster seven and six is major and that

Data Analysis


to between cluster 4 and 3 is major. Since the sample size is sufficient to devise six

clusters hence, the six-cluster alternative has been run through software.

The cluster analysis is used using K-means cluster. The results are as follows:

Convergence achieved in three iterations.

Table 4.2.12.3Final Cluster Centers Entire Data

Sr.Demographic Variables

Cluster

1 2 3 4 5 6

1 Gender 1 2 1 1 1 1

2 Age 5 6 3 4 4 3

3 Occupation 12 1 3 6 9 12

Above table shows final cluster centers of six clusters per variable. The narration of

each cluster is as follows:

Cluster One consists of male belongs to 45-55 age group and occupied as officer

executive middle and semi category.

Cluster Two – female belongs to 55 and above age group performing unskilled jobs.

Cluster Three - male belongs to 25-35 age group and occupation as petty traders.

Cluster Four- male belongs to 35-45 and occupation as industrialist with 1-9

employees.

Cluster Five- male belongs to 35-45 and occupation as clerical and salesmen.

Cluster Six- male belongs to 25-35 age group and occupation as Officer Executive’s

middle/semi.

Table 4.2.12.4Distances between Final Cluster Centers Entire Data

Cluster 1 2 3 4 5 6

1 10.355 8.787 6.026 2.959 2.229

2 10.355 3.064 4.657 7.893 11.480

3 8.787 3.064 2.802 5.944 9.422

4 6.026 4.657 2.802 3.306 6.891

5 2.959 7.893 5.944 3.306 3.596

6 2.229 11.480 9.422 6.891 3.596

Data Analysis


Above table shows the distance between final cluster centers. The distance seems to

be significant. The distance between cluster 4 and 3, 5 and 1 and 6 and 1 has

proximity. Other clusters are at sufficient distance.

Table 4.2.12.5ANOVA for cluster entire data

Sr. Variable Cluster Error

F Sig.Mean Square df Mean Square df

1 Gender .869 5 .175 320 4.964 .000

2 Age group 52.240 5 .507 320 103.114 .000

3 Occupation 692.296 5 .681 320 1.016E3 .000

Above table depicts that F statistics is significant with all variables shows that there is

significant difference into the samples belongs to different clusters with respect to

variables used.

Table 4.2.12.6Number of Cases in each Cluster for entire data

Sr.ClusterNumber

Cases incluster

Percentage

1 1 83.000 25.46

2 2 12.000 3.68

3 3 27.000 8.28

4 4 22.000 6.75

5 5 87.000 26.69

6 6 95.000 29.14

Total 326.000 100

Above table shows, the numbers of cases fall in every cluster. Cluster number sixth is

the biggest carries 29.14% of total samples followed by cluster 5 carries 26.69% of

samples. Cluster number one carries 25.46 % of samples the smallest cluster is

number 2 carries 3.68 % of samples followed by cluster number 4 carries 6.75% of

samples.

Data Analysis


Destination wise Cluster Analysis

Cluster analysis has been attempted for the tourist destinations independently to find

out segments destination wise.

Table 4.2.12.7Case Processing Summary Destinationwise

Destinationcode

Cases

Valid Missing Total

N Percent N Percent N Percent

1 30 100.0 0 .0 30 100.0

2 35 100.0 0 .0 35 100.0

3 37 100.0 0 .0 37 100.0

4 30 100.0 0 .0 30 100.0

5 30 100.0 0 .0 30 100.0

6 37 100.0 0 .0 37 100.0

7 30 100.0 0 .0 30 100.0

8 33 100.0 0 .0 33 100.0

9 30 100.0 0 .0 30 100.0

10 34 100.0 0 .0 34 100.0

a. Squared Euclidean Distance used

b. Average Linkage (Between Groups)

Above table depicts case summary of every destination. The entire samples were

process for cluster analysis. The minimum number of samples of 30 found at

destination Mahabaleshwar, Pratapgarh, Aundh, Sajjangarh and Kas. The maximum

numbers of samples found with destination Wai, Koyna Panchgani and Thoseghar.

The samples are processed through hierarchical cluster to find out number of clusters

the agglomeration schedule is as follows:

Data Analysis


Table 4.2.12.8Agglomeration Schedule DestinationWise

Destination StageCluster Combined

CoefficientsStage Cluster First

Appears NextStage

Cluster 1 Cluster 2 Cluster 1 Cluster 2

Mah

abal

esw

ar

1 15 29 .000 0 0 7

18 5 28 2.000 0 0 20

19 3 14 2.400 14 0 25

20 5 17 3.000 18 10 28

21 4 10 3.500 13 0 24

22 1 2 3.583 17 15 23

23 1 16 6.100 22 0 26

24 4 26 6.833 21 11 27

25 3 22 9.000 19 0 27

26 1 8 9.727 23 6 28

27 3 4 13.857 25 24 29

28 1 5 15.143 26 20 29

29 1 3 70.759 28 27 0

Pan

chag

ani

1 46 63 .000 0 0 14

27 36 40 1.667 24 20 30

28 34 38 2.350 22 21 31

29 32 61 3.500 23 0 33

30 36 45 4.208 27 26 32

31 31 34 4.472 18 28 32

32 31 36 7.021 31 30 33

33 31 32 16.100 32 29 34

34 31 33 53.690 33 25 0

Wai

1 94 102 .000 0 0 17

29 67 73 2.000 9 0 30

30 67 74 4.000 29 22 33

31 66 80 4.500 28 26 33

32 69 72 6.200 18 23 34

33 66 67 9.143 31 30 35

34 68 69 9.411 25 32 36

35 66 70 23.846 33 6 36

36 66 68 46.506 35 34 0

Pra

tapg

arh

1 105 131 .000 0 0 16

22 105 111 2.810 16 18 28

23 103 125 4.250 21 0 25

Data Analysis


24 106 116 4.500 17 19 26

25 103 114 5.760 23 20 27

26 106 110 9.000 24 13 29

27 103 104 11.200 25 0 28

28 103 105 15.845 27 22 29

29 103 106 42.630 28 26 0

Aun

dh

1 159 162 .000 0 0 14

22 133 134 1.500 21 20 26

23 139 143 2.375 16 13 24

24 137 139 3.500 18 23 25

25 135 137 5.300 19 24 26

26 133 135 9.667 22 25 27

27 133 136 14.812 26 15 29

28 138 142 26.500 17 14 29

29 133 138 96.100 27 28 0

Koy

ana

1 196 197 .000 0 0 2

29 166 173 2.000 0 0 30

30 166 171 3.000 29 0 34

31 165 179 3.400 26 0 33

32 163 164 4.000 27 28 35

33 165 169 6.500 31 25 35

34 166 186 9.167 30 19 36

35 163 165 10.825 32 33 36

36 163 166 51.012 35 34 0

Saj

jang

arh

1 228 229 .000 0 0 2

19 223 224 2.000 0 0 22

20 204 205 2.167 11 14 21

21 201 204 3.200 16 20 23

22 217 223 3.500 12 19 24

23 201 222 6.312 21 10 26

24 200 217 7.556 18 22 28

25 212 214 8.000 0 0 27

26 201 211 8.750 23 13 28

27 203 212 9.000 17 25 29

28 200 201 18.132 24 26 29

29 200 203 73.632 28 27 0

Tho seg

har 1 261 262 .000 0 0 2

25 244 246 1.500 22 0 29

Data Analysis


26 238 256 2.000 14 0 29

27 233 248 2.000 18 0 32

28 230 253 2.182 24 7 30

29 238 244 2.556 26 25 30

30 230 238 4.048 28 29 31

31 230 241 6.826 30 23 32

32 230 233 8.456 31 27 0

Kas

1 266 292 .000 0 0 20

20 266 267 1.500 1 13 24

21 263 269 1.667 11 19 23

22 271 282 2.150 15 14 25

23 263 265 2.429 21 8 28

24 264 266 3.250 18 20 26

25 271 277 3.278 22 12 27

26 264 268 5.333 24 17 27

27 264 271 6.261 26 25 28

28 263 264 12.521 23 27 29

29 263 275 51.966 28 0 0

Aji

nkya

tara

1 321 326 .000 0 0 20

27 294 310 2.100 25 22 30

28 295 297 2.500 24 0 32

29 293 298 2.861 21 26 30

30 293 294 4.143 29 27 31

31 293 300 10.210 30 23 32

32 293 295 14.167 31 28 33

33 293 296 67.364 32 0 0

From above agglomeration table, it is evident that from destination code

1(Mahabaleshwar) 6 to 7 clusters can be extracted from the data. Whereas destination

code 2(Panchgani) 2 clusers, destination code 3(Wai) 4 clusters, destination code

4(Pratapgarh) 4 clusters, destination code 5(Aundh) 3 clusters, destination code 6

(Koyna) 4 clusters, destination code 7(Sajjangarh) 4 clusters, destination code 8

(Thoseghar) 3 clusters, destination code 9 (Kas) clusters 2, destination code 10

(Ajinkyatara) 3 clusters extracted from the data

The cluster analysis used by using K-means cluster. The results are as follows:

Data Analysis


Destination Mahabaleshwar

Table 4.2.12.9Final Cluster Centers for Mahabaleshwar

Sr. Variable Cluster

1 2 3 4 5 6 7

1 Gender 2 1 1 1 1 2 1

2 Age group 6 4 3 6 4 2 4

3 Occupation 1 5 2 4 9 13 12

Above table shows final cluster centers of seven clusters per variable.

Cluster One- consists of female belongs to 55 & above age group and occupied as

unskilled.

Cluster Two – male belongs to 35-45 age group and occupied industrialist and

businessmen.

Cluster Three – male belongs to 25-35 age group and occupation skilled workers.

Cluster Four- male belongs to 55 & above and occupation as shop owners.

Cluster Five- male belongs to 45-55 and occupation as clerical and salesmen.

Cluster Six- female belongs to 15-25 age group and occupation as housewife.

Cluster Seven- male belongs to 35-45 age group and occupation as officer/executive

middle/semi.

Table 4.2.12. 10Distances between Final Cluster Centers for Mahabaleshwar

Cluster 1 2 3 4 5 6 7

1 4.738 2.915 3.640 8.073 12.649 10.790

2 4.738 3.189 2.386 3.880 8.233 6.564

3 2.915 3.189 3.775 7.051 11.277 9.746

4 3.640 2.386 3.775 4.717 9.447 7.334

5 8.073 3.880 7.051 4.717 4.743 2.748

6 12.649 8.233 11.277 9.447 4.743 2.662

7 10.790 6.564 9.746 7.334 2.748 2.662

Above table shows the distance between final cluster centers. The distance seems to

be significant. The distance between cluster 4 and 3 has proximity.

Data Analysis


Table 4.2.12. 11ANOVA for Mahabalwshwar



1 Gender .533 6 .094 23 5.662 .001

2 Age Group 4.439 6 .558 23 7.955 .000

3 Occupation 86.580 6 .452 23 191.679 .000

Above table depicts that ‘F’ statistics is significant with all variables shows that there

is significant difference into the samples belongs to different clusters with respect to

variables used.

Table 4.2.12.12Number of Cases in each Cluster at Mahabalwshwar

Sr.ClusterNumber

Cases incluster

Percentage

1 1 1 3.332 2 3 10.003 3 6 20.004 4 2 6.675 5 6 20.006 6 3 10.007 7 9 30.00

Total 30 100

Above table shows, the number of cases falls in every cluster. Cluster number seventh

is the biggest carries 30 % of total samples followed by cluster 3 and 5 each carries

20% of samples. Smallest cluster is number 1 carries 3.33 % of samples.

Destination Panchgani

Table 4.2.12.13Final Cluster Centers for Panchagani


1 2

1 Gender 1 1

2 Age group 4 4

3 Occupation 12 6

Data Analysis


Above table shows final cluster centers of two clusters per variable.

Cluster One- consist of male belongs to 35-45 age group and occupied as officer

/executive middle/semi.

Cluster Two – male belongs to 35-45 age group and occupied industrialist and

businessmen with 1-9 employees.

Table 4.2.12. 14Distances between Final Cluster Centers for Panchagani

Cluster 1 2

1 5.994

2 5.994

Above table shows the distance between final cluster centers.

Table 4.2.12. 15ANOVA for Panchagani



1 Gender .643 1 .209 33 3.075 .089

2 Age group .560 1 .759 33 .738 .396

3 Occupation 255.431 1 2.228 33 114.621 .000

Above table depicts that ‘F’ statistics is significant with only one variable and not

with other two variables and shows that there is significant difference into the samples

belongs to different clusters with respect to occupation and not with gender and age.

Table 4.2.12.16Number of Cases in each Cluster at Panchagani

Sr. ClusterNumber

Cases incluster

Percentage

1 1 25 71.43

2 2 10 28.57

Total 35 100

Above table shows, the number of cases falls in every cluster. Cluster number first is

the biggest carries 71.43 % of total samples. Smallest cluster is number 2 carries

28.57 % of samples.

Data Analysis


Destination Wai

Table 4.2.12.17Final Cluster Centers for Wai


1 2 3 4

1 Gender 1 1 1 1

2 Age group 4 4 3 5

3 Occupation 7 4 12 10

Above table shows final cluster centers of four clusters per variable.

Cluster One- consist of male belongs to 35-45 age group and occupied as

industrialist/businessmen with 10+ employees.

Cluster Two – male belongs to 35-45 age group and occupied shop owners.

Cluster Three- male belongs to 25-35 age group and officer/executive middle/semi.

Cluster Four –male belongs to 45-55 age group and supervisory level occupation.

Table 4.2.12.18Distances between Final Cluster Centers for Wai

Cluster 1 2 3 4

1 3.452 5.478 3.540

2 3.452 8.893 6.906

3 5.478 8.893 2.831

4 3.540 6.906 2.831

Above table shows the distance between final cluster centers.Table 4.2.12.19ANOVA for Wai



1 Gender .228 3 .151 33 1.504 .232

2 Age group 6.272 3 .730 33 8.586 .000

3 Occupation 135.120 3 .779 33 173.350 .000

Above table depicts that ‘F’ statistics is significant with age group and occupation

variable and not with gender since the convenient sampling technique. It shows that

Data Analysis


there is significant difference into the samples belongs to different clusters with

respect to age group and occupation and not with gender.

Table 4.2.12.20Number of Cases in each Cluster at Wai

Sr. ClusterNumber

Cases incluster

Percentage

1 1 9 24.322 2 6 16.223 3 16 43.244 4 6 16.22

Total 37 100

Above table shows, the number of cases falls in every cluster. Cluster number three is

the biggest carries 43.24 % of total samples.

Destination Pratapgarh

Table 4.2.12.21Final Cluster Centers for Pratapgarh


1 2 3 4

1 Gender 1 1 1 1

2 Age group 3 4 3 4



Cluster One- consist of male belongs to 25-35 age group and occupied as petty

traders.

Cluster Two – male belongs to 35-45 age group and occupied officer/executive

middle/semi.

Cluster Three- male belongs to 25-35 age group and self employed professionals.

Cluster Four –male belongs to 35-45 age group and industrialist with 1 to 9

employees.

Data Analysis


Table 4.2.12.22Distances between Final Cluster Centers for Pratapgarh

Cluster 1 2 3 4

1 9.142 5.510 2.693

2 9.142 3.642 6.628

3 5.510 3.642 3.073

4 2.693 6.628 3.073

Above table shows the distance between final cluster centers. Distance is seems to be

identical.

Table 4.2.12.23ANOVA for Pratapgarh



1 Gender .233 3 .077 26 3.033 .047

2 Age group .933 3 .718 26 1.300 .296

3 Occupation 100.993 3 .726 26 139.013 .000

Above table depicts that ‘F’ statistics is not significant with age group and gender

variable and only significant with occupation since the convenient sampling

technique. It shows that there is significant difference into the samples belongs to

different clusters with respect to d occupation and not with gender and age group.

Table 4.2.12.24Number of Cases in each Cluster at Pratapgarh

Sr. ClusterNumber

Cases incluster

Percentage

1 1 5 16.672 2 9 30.003 3 12 40.004 4 4 13.33

Total 30 100.00

Above table shows the number of cases falls in every cluster. Cluster number three is

the biggest carries 40 % of total samples.

Data Analysis


Destination Aundh

Table 4.2.12.25Final Cluster Centers for Aundh


1 2 3

1 Gender 1 2 2

2 Age group 4 4 6

3 Occupation 12 8 1

Above table shows final cluster centers of three clusters per variable.

Cluster One consists of male belongs to 35-45 age group and occupied as

officer/executive.

Cluster Two – female belongs to 35-45 age group and self-employed professionals.

Cluster Three- female belongs to 55 & above age group and unskilled.

Table 4.2.12.26Distances between Final Cluster Centers for Aundh

Cluster 1 2 3

1 3.542 11.190

2 3.542 7.653

3 11.190 7.653

Above table shows distance between each cluster with final cluster. The distance is

identical.

Table 4.2.12.27ANOVA for Aundh



1 Gender .555 2 .235 27 2.356 .114

2 Age group 10.333 2 1.407 27 7.342 .003

3 Occupation 308.733 2 .963 27 320.608 .000

Above table depicts that ‘F’ statistics is significant with age group and occupation

variable and not significant with gender since the convenient sampling technique. It

shows that there is significant difference into the samples belongs to different clusters

with respect to age group and occupation.

Data Analysis


Table 4.2.12.28Number of Cases in each Cluster at Aundh

Sr. ClusterNumber

Cases incluster

Percentage

1 1 14 46.662 2 8 26.673 3 8 26.67

Total 30 100.00

Above table shows, the number of cases falls in every cluster. Cluster number one is

the biggest carries 40.66 % of total samples.

Destination KoynaTable 4.2.12.29Final Cluster Centers for Koyna


1 2 3 4

1 Gender 1 1 1 1

2 Age group 2 3 4 4



Cluster One -consist of male belongs to 15-25 age group and occupied as student.

Cluster Two – male belongs to 25-35 age group and clerical/salesmen.

Cluster Three- male belongs to 35-45 age group and officer/executives.

Cluster Four- male belongs to 35-45 age group and shop owner.

Table 4.2.12.30Distances between Final Cluster Centers for Koyna

Cluster 1 2 3 4

1 3.947 2.138 9.153

2 3.947 2.299 5.235

3 2.138 2.299 7.459

4 9.153 5.235 7.459

Above table shows distance between each cluster with final cluster.

Data Analysis


Table 4.2.12.31ANOVA for Koyna



1 Gender .140 3 .118 33 1.187 .330

2 Age group 3.411 3 .381 33 8.948 .000

3 Occupation 88.381 3 .640 33 138.048 .000Above table depicts that ‘F’ statistics is significant with age group and occupation

variable and not significant with gender since the convenient sampling technique. It

shows that there is significant difference into the samples belongs to different clusters

with respect to age group and occupation.

Table 4.2.12.32Number of Cases in each Cluster at Koyna

Sr ClusterNumber

Cases incluster

Percentage

1 1 6 16.222 2 15 40.543 3 11 29.734 4 5 13.51

Total 37 100.00Above table shows, the number of cases falls in every cluster. Cluster number 2 is the

biggest carries 40.66 % of total samples.

Destination Sajjangarh

Table 4.2.12.33Final Cluster Centers for Sajjangarh


1 2 3 4

1 Gender 1 1 2 1

2 Age group 4 2 5 4



Cluster One - consists of male belongs to 35-45 age group and occupied as

clerical/salesmen.

Data Analysis


Cluster Two – male belongs to 15-25 age group and officer/executive middle/semi.

Cluster Three- consists female belongs to 45-55 age group with officer/executive

middle/semi.

Cluster Four- belongs to male and the age group 35-45 with petty traders’ occupation.

Table 4.2.12.34Distances between Final Cluster Centers for Sajjangarh

Cluster 1 2 3 4

1 4.102 3.614 5.764

2 4.102 2.418 9.760

3 3.614 2.418 9.257

4 5.764 9.760 9.257

Above depicts distance between each cluster with final cluster centers.

Table 4.2.12.35ANOVA for Sajjangarh



1 Gender .561 3 .192 26 2.926 .053

2 Age group 7.325 3 .955 26 7.671 .001

3 Occupation 116.243 3 .874 26 132.928 .000

Above table shows that ‘F’ statistics is significant with age group and occupation

variable and not significant with gender. It shows that there is significant difference

into the samples belongs to different clusters with respect to age group and

occupation.

Table 4.2.12.36Number of Cases in each Cluster at Sajjangarh

Sr. ClusterNumber

Cases incluster

Percentage

1 1 9 30.002 2 7 23.333 3 9 30.004 4 5 16.67

Total 30 100.00

Above table depicts that cluster one and three carries highest samples with 30% each

of total samples. Smallest cluster is 4 which carries 16.67% of samples.

Data Analysis


Destination Thoseghar

Table 4.2.12.37Final Cluster Centers for Thoseghar


1 2 3

1 Gender 1 1 1

2 Age group 3 2 4

3 Occupation 10 13 12


Cluster One- consist of male belongs to 25-35 age group and occupied as supervisory

level.

Cluster Two – male belongs to 15-25 age group and students.

Cluster Three- male belong to35-45age group with officer/executive middle/semi.

Table 4.2.12.38Distances between Final Cluster Centers for Thoseghar

Cluster 1 2 3

1 2.753 1.963

2 2.753 2.616

3 1.963 2.616

Above table depicts that distance between each cluster with final cluster centre.

Table 4.2.12.39ANOVA for Thoseghar



1 Gender .079 2 .112 30 .706 .502

2 Age group 10.594 2 .312 30 33.966 .000

3 Occupation 18.007 2 .377 30 47.724 .000



into the samples belongs to different clusters with respect to age group and

occupation.

Data Analysis


Table 4.2.12.40Number of Cases in each Cluster at Thoseghar

Sr ClusterNumber

Cases incluster

Percentage

1 1 18 48.652 2 7 18.923 3 8 21.62

Total 37 100.00Above table depicts that cluster one carries highest percentage of membership i.e.

48.65% of total samples. In addition, cluster 2 carries lowest i.e. 18.92%.

Destination Kas

Table 4.2.12.41Final Cluster Centers for Kas


1 2

1 Gender 1 1

2 Age group 4 4

3 Occupation 8 11

Above table shows final cluster centers of two clusters per variable.

Cluster One -consists of male belongs to 35-45 age group and occupied as self-

employed professionals.

Cluster Two – male belongs to 35-45 age group and occupied as officer/executive

juniors.

Table 4.2.12.42Distances between Final Cluster Centers for Kas

Cluster 1 2

1 3.529

2 3.529

Above table depicts the distance between final clusters with corresponding cluster.

Data Analysis


Table 4.2.12.43ANOVA for Kas



1 Gender .050 1 .223 28 .224 .640

2 Age group .022 1 .605 28 .037 .849

3 Occupation 89.606 1 1.596 28 56.136 .000

Above table shows that ‘F’ statistics is significant with occupation variable and not

significant with gender and age group. It shows that there is significant difference into

the samples belongs to different clusters with respect to occupation and not gender

and age group.

Table 4.2.12.44Number of Cases in each Cluster at Kas

Sr ClusterNumber

Cases incluster

Percentage

1 1 12 402 2 18 60

Total 30 100

Above table depicts that cluster second carries higher sample cases i.e. 60% whereas

cluster one carries only 40%.

Destination Ajinkyatara

Table 4.2.12.45Final Cluster Centers for Ajinkyatara


1 2 3

1 Gender 1 1 1

2 Age group 2 3 5

3 Occupation 13 4 11


Cluster One -consist of male belongs to 15-25 age group students.

Cluster Two – male belongs to 25-35 age group and occupied as shop owners.

Data Analysis


Table 4.2.12. 46Distances between Final Cluster Centers for Ajinkyatara

Cluster 1 2 3

1 9.064 3.023

2 9.064 7.654

3 3.023 7.654

Above table shows distance between each cluster with final cluster centre.

Table 4.2.12.47ANOVA for Ajinkyatara



1 Gender .112 2 .220 31 .508 .607

2 Age group 24.040 2 .628 31 38.261 .000

3 Occupation 38.660 2 .895 31 43.204 .000



into the samples belongs to different clusters with respect to age group and occupation

and not with gender.

Table 4.2.12.48Number of Cases in each Cluster at Ajinkyatara

Sr. ClusterNumber

Cases incluster

Percentage

1 1 10 29.412 2 1 2.943 3 23 67.65

Total 34 100

Above table clears that cluster three carries highest membership samples i.e. 67.65%

and smallest cluster is two who carries 2.94% of membership cases.

Data Analysis


Following table shows the cluster of highest sample tourist in each destination.

Table 4.2.12.49Summary of Destinationwise Major Cluster

Sr.Name of

Destination

Numberof

clusters

Demographic Background

GenderAge

groupOccupation

1 Mahabaleshwar 7 1(male) 4(35-45)12(Officer/Executive

Middle/Semi

2 Panchghani 2 1(male) 4(35-45)12(Officer/Executive

Middle/Semi

3 Wai 4 1(male) 3(25-35)12(Officer/Executive

Middle/Semi

4 Pratapgarh 4 1(male) 3(25-35)8(Self Employed

professionals)

5 Aundh 3 1(male) 4(35-45)12(Officer/Executive

Middle/Semi6 Koyna 4 1(male) 3(25-35) 9( Clerical/Salesmen)

7 Sajjangarh 41 & 2

(male&female)

4/5(35-45)/(45-

55)

9/12(Officer/ExecutiveMiddle/Semi

8 Thoseghar 3 1(male) 3(25-35) 10(Supervisory level)9 Kas 2 1(male) 4(35-45) 11(Officer/Executive/Junior)10 Ajinkyatar 3 1(male) 5(45-55) 11(Officer/Executive/Junior)

The clusters derived from entire samples have used further to assess samples opinions

cluster wise on tourism product that attract tourists in Satara district. Respondents’

opinion on tourism products have assessed on five-point scale that 1 for not at all

attracts, 2 for not attracts, 3 for neither attracts nor distracts, 4 for attracts and 5 for

highly attracts. Each tourism product analyzed independently with entire cluster group

i.e. 6 and presented in following table.

Product Perception on Tourism Product Attraction

The total samples processed with 15-tourism products viz. Adventure, Flora, Fauna,

Waterfall, Ghats, Hill stations, Lake/Reservoir, Scenery/Beauty, Valleys, Pilgrimage,

Temples, Museum, Historical Monuments, Forts, and Windmills. The summery of

case processing is as follows.

Data Analysis


Table 4.2.12.50Analysis of Tourism Product Attraction

Sr.Name of Tourism

Products

CasesValid Missing Total

N Percent N Percent N1 Adventure 200 61.3% 126 38.7% 3262 Flora 226 69.3% 100 30.7% 3263 Fauna 193 59.2% 133 40.8% 3264 Waterfall 243 74.5% 83 25.5% 3265 Ghats 241 73.9% 85 26.1% 3266 Hill Stations 319 97.9% 7 2.1% 3267 Lake/ Reservoir 271 83.1% 55 16.9% 3268 Scenery/Beauty 283 86.8% 43 13.2% 3269 Valleys 252 77.3% 74 22.7% 32610 Pilgrimage 214 65.6% 112 34.4% 32611 Temples 230 70.6% 96 29.4% 32612 Museum 198 60.7% 128 39.3% 32613 Historical Monuments 224 68.7% 102 31.3% 32614 Forts 255 78.2% 71 21.8% 32615 Windmills 193 59.2% 133 40.8% 326

The entire samples have taken for study; have not marked their opinion towards all 15tourism products since the opinions taken on perceptions of sample tourist. Hence, themissing frequency found in above table. The maximum opinions i.e. 97.9% havefound for Hill stations and least i.e. 59.2% for Fauna and Windmills.

Adventure Tourism Product

Following table shows opinion of total samples on attraction of adventure tourism inrespective cluster in Satara district.

Table 4.2.12.51Attraction of Adventure Tourism Product

Sr. OpinionClusters

Total1 2 3 4 5 6

f % f % f % f % f % f %1 Not at all attracts 1 2.22 0 0.00 1 9.49 1 7.69 0 0.00 0 0.00 32 Not attracts 1 2.22 1 10.00 0 0.00 1 7.69 4 6.90 2 3.17 93 Neither attracts

nor distracts19 42.22 8 80.00 2 18.18 7 53.85 27 46.55 18 28.57 81

4 Attracts 22 48.89 1 10.00 8 72.33 2 15.38 21 36.21 30 47.62 845 Highly attracts 2 4.44 0 0.00 0 0.00 2 15.38 6 10.34 13 20.63 23

Total 45 100 10 100 11 100 13 100 58 100 63 100 200Source: Field Data

Data Analysis


Table 4.2.12.51 depict that ‘Adventure’ of Satara attracts cluster 3rd as it carries

highest i.e.72.33% and of having demographic profile as ‘male’ of ‘25-35’ age group

which belongs to ‘petty traders’ as an occupation. Followed by cluster 6th this carries

68.25% consist male of similar age group differ in occupation as ‘officer executive’s

middle/semi’. However second cluster has least percentage i.e. 10% which attract

‘Adventure’ of Satara who are female of age group ‘55 and above’ and belonging to

‘unskilled jobs’ (housewife). Young male tourist of age group ‘25-35’ are more

attracted to ‘Adventure’ of Satara.

Flora Tourism Product

Following table shows opinion of total samples on attraction of Flora in respective

cluster in Satara district.

Table 4.2.12.52Attraction of Flora Tourism Product

Sr OpinionClusters

Total1 2 3 4 5 6f % f %f % f % f % f %

1 Not attracts 1 1.64 1 10 1 8.33 0 0 2 3.13 4 5.97 92 Neither

attracts nordistracts

11 18.03 8 80 2 16.67 4 33.33 16 25.00 8 11.94 49

3 Attracts 38 62.30 0 0 8 66.67 6 50.00 37 57.81 49 73.13 1384 Highly

attracts11 18.03 1 10 1 8.33 2 16.67 9 14.06 6 8.96 30

Total 61 100 10 100 12 100 12 100 64 100 67 100 226

Table 4.2.12.52 shows that ‘flora’ of Satara attracts almost all clusters since the

highest percentage i.e. more than 70% samples carries in all clusters. However, the

distinct cluster second shows least percentage i.e. 10% since they are ‘female’ belongs

to ‘55 and above’ age group of ‘unskilled job’. It infers that ‘Flora’ of Satara attracts

all tourists but ‘female’ belongs to ‘55 and above’ age group of ‘unskilled job’ did not

attract.

Data Analysis


Fauna Tourism Product

Following table shows opinion of total samples on attraction of Fauna in respective


Table 4.2.12.53Attraction of Fauna Tourism Product

Sr. Opinion

Clusters

Total1 2 3 4 5 6

f % f % f % f % f % f %1 Not at all attracts 1 2.33 0 0 0 0 0 0 0 0 0 0 12 Not attracts 0 0.00 1 10 1 10 1 8.33 1 1.72 3 5 73 Neither attracts

nor distracts13 30.23 9 90 1 10 5 41.67 20 34.48 18 30 66

4 Attracts 24 55.81 0 0 6 60 3 25.00 30 51.72 27 45 905 Highly attracts 5 11.63 0 0 2 20 3 25.00 7 12.07 12 20 29

Total 43 100 10 100 10 100 12 100 58 100 60 100 193

Table 4.2.12.53 shows that ‘fauna’ of Satara highly attracts third clusters followed by

first, fifth and sixth respectively but not to second cluster. It also shows that cluster 4

carries only 50% samples who perceive the ‘fauna’ attracts them and they are ‘males’

of age group ‘35-45’ and having occupation as ‘industrialist with 1-9 employees’.

The cluster 3rd shows higher attraction it is ‘male’ of age group ‘25-35’ belong to

‘petty traders’ as an occupation. Moreover, cluster number 2nd is distinct of ‘female’

of ‘55 and above’ age group of ‘unskilled job’. It concludes that Fauna highly attracts

‘petty traders’ of ‘25-35’ age group ‘male’ category followed by ‘officer/ executive

middle/semi’ and ‘clerical & salesmen ‘.

Data Analysis


Waterfall Tourism Product

Following table shows opinion of total samples on attraction of ‘Waterfall’ inrespective cluster in Satara district.

Table 4.2.12.54Attraction of Waterfall Tourism Product

Sr. OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not attracts 0 0 0 0 0 0 0 0 1 1.49 1 1.30 22 Neither

attracts nordistracts

11 17.46 9 90 1 8.33 2 14.29 12 17.91 3 3.90 38

3 Attracts 41 65.08 1 10 8 66.67 7 50.00 40 59.70 44 57.14 1414 Highly

attracts11 17.46 0 0 3 25.00 5 35.71 14 20.90 29 37.66 62

Total 63 100 10 100 12 100 14 100 67 100 77 100 243

Table 4.2.12.54 shows that ‘Waterfall’ of Satara highly attracts all clusters as thepercentage is above 70% except cluster number 2nd of which only 10% tourist’waterfall’ attracts. It infers that ‘waterfall’ of Satara attracts all tourists but ‘female’ of‘55 and above’ age group performing ‘unskilled job’ is exception to it.

Ghats Tourism Product

Following table shows opinion of respective cluster in Satara district in respect to

‘Ghats’ attraction by tourist samples.

Table 4.2.12.55Attraction of Ghats Tourism Product

Sr. OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts 0 0 0 0 0 0 0 0 1 1.41 0 0 12 Not attracts 1 2 0 0 1 6.67 1 6.25 1 1.41 1 1.28 53 Neither attracts

nor distracts21 42 8 72.73 3 20.00 3 18.75 19 26.76 17 21.79 71

4 Attracts 21 42 1 9.09 7 46.67 6 37.5 38 53.52 38 48.72 1115 Highly attracts 7 14 2 18.18 4 26.67 6 37.5 12 16.90 22 28.21 53

Total 50 100 11 100 15 100 16 100 71 100 78 100 241

Table 4.2.12.55 shows that ‘Ghats’ of Satara attracts to clusters viz. 6,5,4,3 and 1, but

among them cluster one it attracts comparatively less since the percentage of this

cluster one is 56 and rest of cluster percentage is above 70%. However, cluster

Data Analysis


number 2nd carries less percentage i.e. 27.27 since the cluster unique. It infers that

‘Ghats’ of Satara attracts young category of ‘male’ tourists irrespective of their

occupation.

Hill Stations Tourism Product

Following table shows opinion of total samples on attraction of ‘Hill stations’ in

respective cluster in Satara district.

Table 4.2.12.56Attraction of ‘Hill stations’ Tourism Product

Sr OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts 0 0 0 0 0 0 0 0 0 0 1 1.09 12 Not attracts 1 1.23 0 0 1 3.70 1 4.55 2 2.33 0 0.00 53 Neither attracts

nor distracts8 9.88 9 81.82 3 11.11 0 0.00 7 8.14 5 5.43 32


Total 81 100 11 100 27 100 22 100 86 100 92 100 319

Table 4.2.12.56 shows that except cluster 2nd ‘Hill stations’ of Satara highly attract all

clusters. It infers that ‘Hill stations’ of Satara attracts ‘male’ ‘young’ and ‘mid aged’

tourists irrespective of their occupation.

Lake/Reservoir Tourism Product

Following table shows opinion of total samples on attraction of ‘Lake/Reservoir’ in


Table 4.2.12.57Attraction of Lake/Reservoir Tourism Product

Sr OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts 0 0 0 0 0 0 0 0 0 0 2 2.44 22 Not attracts 1 1.43 1 9.09 3 18.75 1 5.56 1 1.35 2 2.44 93 Neither attracts

nor distracts16 22.86 8 72.73 4 25 5 27.78 11 14.86 16 19.51 60


Total 70 100 11 100 16 100 18 100 74 100 82 100 271

Data Analysis


Table 4.2.12.57 shows that Lake/Reservoir of Satara attracts more to clusters viz.

6,5,4,3 and 1, but among them cluster three attracts comparatively less since the

percentage of cluster three is 56.25% and rest of cluster percentage is above 60%, the

difference is hardly few percentage it may be because of its occupation ‘Petty traders’.

However, cluster number 2nd carries less percentage i.e. 18.18. It infers that

‘Lake/Reservoir’ of Satara attracts ‘male’ of all age group and its occupation matters

to some extent to perceive the attractiveness of ‘Lake/Reservoir’.

Scenery/Beauty Tourism Product

Following table shows opinion of total samples on attraction of ‘Scenery/Beauty’ in


Table 4.2.12.58Attraction of Scenery/Beauty Tourism Product

Sr. OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not attracts 1 1.39 0 0 1 5.88 1 5.56 1 1.27 0 0 42 Neither attracts nor

distracts12 16.67 9 81.82 3 17.65 2 11.11 12 15.19 7 8.14 45


Total 72 100 11 100 17 100 18 100 79 100 86 100 283

Table 4.2.12.58 shows that ‘Scenery/ beauty’ of Satara highly attracts to all clusters

since percentage is 75% and above except cluster number 2. It infers that

‘Scenery/beauty’ of Satara attracts ‘male’ tourists of all age group and occupational

category.

Data Analysis


Valleys Tourism Product

Following table shows opinion of total samples on attraction of ‘Valleys’ in respective


Table 4.2.12.59Attraction of Valleys Tourism Product

Sr OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts 0 0 1 10 1 6.25 0 0 0 0 4 4.82 62 Not attracts 1 1.85 0 0 1 6.25 1 5.56 1 1.41 6 7.23 103 Neither attracts nor

distracts18 33.33 8 80 2 12.5 9 50.00 18 25.35 21 25.30 76

4 Attracts 31 57.41 1 10 9 56.25 5 27.78 42 59.15 41 49.40 1295 Highly attracts 4 7.41 0 0 3 18.75 3 16.67 10 14.08 11 13.25 31

Total 54 100 10 100 16 100 18 100 71 100 83 100 252

Table 4.2.12.59 shows that ‘Valleys’ of Satara attracts more to clusters 1st, 3rd, 5th, and

6th since percentage is nearly 60%. However, cluster number 4th shows less

percentage towards attraction of ‘valleys’ and second cluster carries 10%, which is

very meager. The noticeable difference in 4th cluster due to its occupation and in 2nd

cluster as it is identical group of ‘female’ ‘housewife’ of age group ‘55 and above’. It

infers that valleys of Satara attract salaried male tourists.

Pilgrimage Tourism ProductFollowing table shows opinion of total samples on attraction of ‘Pilgrimage’ in


Table 4.2.12.60Attraction of Pilgrimage Tourism Product

Sr OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts 1 2 1 10 1 7.14 1 5.88 1 1.69 5 7.81 102 Not attracts 0 0 0 0 1 7.14 0 0.00 1 1.69 3 4.69 53 Neither attracts nor

distracts7 14 0 0 4 28.57 2 11.76 21 35.59 12 18.75 46

4 Attracts 29 58 1 10 6 42.86 11 64.71 19 32.20 34 53.13 1005 Highly attracts 13 26 8 80 2 14.29 3 17.65 17 28.81 10 15.63 53

Total 50 100 10 100 14 100 17 100 59 100 64 100 214

Table 4.2.12.60 shows that Pilgrimage of Satara highly attracts cluster 2nd, whichshows 90% of sample tourist followed by rest of the group. It infers that ‘pilgrimage’

Data Analysis


of Satara attracts all category of tourist irrespective of their gender, age group, andoccupation but highly attracts ‘female’ of age group ‘55 and above’ ‘unskilled job’ asan occupation.

Temples Tourism ProductFollowing table shows opinion of total samples on attraction of Temple in respectivecluster in Satara district.

Table 4.2.12.61Attraction of Temples Tourism Product

Sr. OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts 1 1.89 0 0 1 7.14 1 7.14 1 1.52 0 0 42 Not attracts 0 0.00 0 0 0 0.00 0 0.00 1 1.52 1 1.41 23 Neither attracts nor

distracts11 20.75 0 0 3 21.43 3 21.43 25 37.88 10 14.08 52


Total 53 100 12 100 14 100 14 100 66 100 71 100 230

Table 4.2.12.61 shows that temples of Satara highly attracts to cluster 2nd, whichshows 100% of sample tourist followed by rest of the group which carries more than65%. It infers that Satara temples attracts all category of tourist irrespective of theirgender, age group, and occupation but highly attracts ‘female’ of age group ‘55 andabove’ having ‘unskilled job’ as an occupation.

Museum Tourism ProductFollowing table shows opinion of total samples on attraction of ‘Museum’ inrespective cluster in Satara district.

Table 4.2.12.62Attraction of Museum Tourism Product

Sr. OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts1 2.17 1 10 1 8.33 1 7.69 1 1.79 3 4.92 82 Not attracts 0 0.00 0 0 1 8.33 1 7.69 3 5.36 5 8.20 103 Neither attracts

nor distracts13 28.26 8 80 3 25.00 3 23.08 29 51.79 14 22.95 70


Total 46 100 10 100 12 100 13 100 56 100 61 100 198

Data Analysis


Table 4.2.12.62 shows that Museum of Satara highly attracts to cluster 1st, 4th and 3rd

which shows more than 60% of sample tourist but cluster 5th , which shows less i.e.

41.07% of sample tourist followed by cluster 2nd. It infers that Satara museum attracts

male category of tourist but difference was notice at occupation level so the ‘male’ of

all age group except ‘clerical and salesmen’ attracts towards museum.

Historical monuments Tourism Product

Following table shows opinion of total samples on attraction of Historical monuments

in respective cluster in Satara district.

Table 4.2.12.63Attraction of Historical monuments Tourism Product

Sr. OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts 1 1.96 0 0 1 5.56 1 7.14 1 1.56 1 1.52 52 Not attracts 1 1.96 0 0 0 0.00 1 7.14 4 6.25 3 4.55 93 Neither attracts nor

distracts18 35.29 9 81.82 3 16.67 3 21.43 28 43.75 15 22.73 76


Total 51 100 11 100 18 100 14 100 64 100 66 100 224

Table 4.2.12.63 shows that ‘Historical Monuments’ of Satara highly attracts to cluster

1st, 3rd 4th and 6th which shows more than 60% of sample tourist but cluster 5th ,

which shows less i.e. 48.44% of sample tourist followed by cluster 2nd 18.18%. It

infers that Satara ‘museum’ attracts male category of tourist but difference notices at

occupation level and gender so the male of all age group except ‘clerical and

salesmen’ attracts historical monuments of Satara as 5th cluster belongs to ‘clerical

and sales person’ occupational category and 2nd cluster carries only female.

Data Analysis


Forts Tourism Product

Following table shows opinion of total samples on attraction of ‘Forts’ in respective


Table 4.2.12.64Attraction of Forts Tourism Product

Sr. OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts 1 1.45 0 0 1 5.56 1 6.25 1 1.49 0 0 42 Not attracts 0 0.00 0 0 0 0.00 0 0 2 2.99 0 0 23 Neither attracts

nor distracts14 20.29 8 72.73 1 5.56 2 12.5 25 37.31 5 6.76 55

4 Attracts 43 62.32 1 9.09 12 66.67 5 31.25 25 37.31 44 59.46 1305 Highly attracts 11 15.94 2 18.18 4 22.22 8 50 14 20.90 25 33.78 64

Total 69 100 11 100 18 100 16 100 67 100 74 100 255

Table 4.2.12.64 shows that Forts of Satara highly attracts to cluster 1st, 3rd 4th, 6th and

5th of which cluster 5th carries comparatively less percentages i.e 58.21 and rest of

cluster carries high percentages i.e. above 75% . However, cluster second shows

27.27 % of sample tourist who attracts ‘forts’ of Satara. The difference noticed as

second cluster uniqueness due to its gender and fifth cluster occupation ‘clerical and

salesmen’ occupational category. It infers that Satara ‘fort’ attracts all male

irrespective of his age group category except ‘clerical and salesmen’ as an occupation.

Windmills Tourism Product

Following table shows opinion of total samples on attraction of Windmill in


Table 4.2.12.65Attraction of Windmills Tourism Product

Sr. OpinionClusters

Total1 2 3 4 5 6f % f % f % f % f % f %

1 Not at all attracts 1 2.33 1 10 1 9.09 1 8.33 2 3.70 8 12.70 142 Not attracts 4 9.30 0 0 1 9.09 0 0.00 2 3.70 3 4.76 103 Neither attracts nor

distracts24 55.81 8 80 3 27.27 4 33.33 31 57.41 22 34.92 92


Total 43 100 10 100 11 100 12 100 54 100 63 100 193

Data Analysis


Table 4.2.12.65 shows that ‘Windmill’ of Satara attracts more to cluster 4th and 3rd of

which the percentage is 58.33 and 54.55 respectively. Rest of cluster carries less than

50% of samples. Thus, it infers that ‘windmill’ attracts more to young male belong to

‘25-45’ age group having occupation as a ‘petty traders’ and/or’ industrialist with 1-9

employees’.

Conclusion:

The chapter discusses data, which is analyzed from desired perspectives. The analysis

involves macro analysis and wherever it is required, it did. The data is analyzed by

using relevant statistical tools. To keep data at minimal quantity and used of

inferential statistics. Since, the topic deals with tourism where qualitative observations

are very important to note. Hence, wherever it is a need to explain quantitative data

with the help of researchers own observations and experience the effort has been

made of such discussion to make analysis lucid and interesting to read. The findings

and discussions of earlier researches have taken out into next chapter. The chapter

also discusses suggestions followed by findings.

chapter 4 data analysis -...

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